Memories That Matter: How We Remember Important Things [1 ed.] 0367144387, 9780367144388

Citation preview

Memories That Matter What makes some experiences more memorable than others? How can you better remember specific information later? Memories That Matter addresses these questions and more. The book is divided into three main parts, with each one focusing on a different aspect of memory. After the introductory first part, Part II discusses everyday uses of memory and why we remember, establishing a foundation for how memory is structured and stored in the brain. Part III dives into what makes us remember. Emotional and rewarding experiences are both more memorable than mundane experiences but are often studied using different approaches. Self-relevance and objects we can interact with are remembered better than less relevant information. The author explores these motivation-related influences on memory and considers whether a common mechanism underlies them all. Part IV changes the focus, discussing how we sometimes want to remember specific information that does not automatically capture our attention. The book considers evidence-based learning strategies and memory strategies, whilst also exploring real-world applications, with discussion of professions that accomplish amazing memory feats daily. The book concludes with a reflection on how the role of memory is changing as our world makes information increasingly accessible, particularly with the ever-expanding influence of the internet. Drawing from a variety of literatures and perspectives, this important book will be relevant for all students of memory from psychology, cognitive neuroscience, and related health backgrounds.

Christopher R. Madan is an Assistant Professor in the School of Psychology at the University of Nottingham.

Memories That Matter How We Remember Important Things Christopher R. Madan

Cover image: © GettyImages/stock_colors First published 2023 by Routledge 4 Park Square, Milton Park, Abingdon, Oxon OX14 4RN and by Routledge 605 Third Avenue, New York, NY 10017 Routledge is an imprint of the Taylor & Francis Group, an informa business © 2023 Christopher R. Madan The right of Christopher R. Madan to be identified as author of this work has been asserted in accordance with sections 77 and 78 of the Copyright, Designs and Patents Act 1988. All rights reserved. No part of this book may be reprinted or reproduced or utilised in any form or by any electronic, mechanical, or other means, now known or hereafter invented, including photocopying and recording, or in any information storage or retrieval system, without permission in writing from the publishers. Trademark notice: Product or corporate names may be trademarks or registered trademarks, and are used only for identification and explanation without intent to infringe. British Library Cataloguing-in-Publication Data A catalogue record for this book is available from the British Library ISBN: 9780367144388 (hbk) ISBN: 9780367144401 (pbk) ISBN: 9780429032028 (ebk) DOI: 10.4324/9780429032028 Designed and typeset in Latin Modern Roman by Christopher R. Madan. Publisher’s notice: This book has been prepared from camera-ready copy provided by the author.

I write because I must.

Acknowledgements

To anyone and everyone who has written a paper that I have read, spoken to me at a conference, cited one of my papers, or emailed me about my research— thank you. All of you have contributed to my development as a researcher and given me the confidence and inspiration to start writing this book—and to persist and follow through. Starting a big project is relatively easy. Finishing it, persisting when there are so many other priorities in life and in knowing whether it is worth the effort, that’s difficult. This book has been over a decade in the making, beginning as I puzzled over the evolutionary function of memory during my PhD studies and driven ever forward as I sought an understanding of how my various research projects fit together coherently. Of course, it progressed through ebbs and flows. I moved countries several times. Relationships have started and ended. There was a pandemic. This book has been both an on-going commitment and a guiding light. My views, as presented here, have been strongly influenced by discussions I have had with my former supervisors and mentors (ordered by when we began to work together): Jeremy Caplan, Esther Fujiwara, Anthony Singhal, Marcia Spetch, Elliot Ludvig, Alinda Friedman, Tobias Sommer, and Elizabeth Kensinger. Thank you all for believing in me and spending countless hours mentoring me. The support from each of you has made a world of difference to how I have developed as a researcher. In particular, I will be forever thankful for training and opportunities that Jeremy provided. I started working with him as an undergraduate student, having not even taken the introductory psychology course yet. Having worked with him for many years as a trainee, this experience was essential in me being able to develop into an independent researcher. I have been closely collaborating with Daniela Palombo, and the insightful discussions we’ve had, have helped shape how I understand memory. More importantly though, having a caring friend with so similar interests, also at the same career stage, has been so very appreciated. I have also had the pleasure of supervising several PhD students in my own research group. Our individual and lab group discussions have played a formative role in the development of this book: Layla Akacem, Yashoda Gopi, Ruo-Chong Zhang, Nick Simonsen, and Antti Lattula. I would similarly like to acknowledge three of Daniela’s students that I have had the opportunity to work closely with, Victoria Wardell, Chantelle Cocquyt, and Omran Safi.

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Acknowledgements

Since moving to Nottingham, I have had the joy of working with Myron Tsikandilakis, now a close friend and probably the wisest person I know. I would like to thank my supportive friends and colleagues who have also influenced how I think about memory, in particular (alphabetically): Holly Bowen, Norman Brown, Liz Coulthard, Howard Eichenbaum, Angela Gutchess, Muireann Irish, JeYoung Jung, Sarah Kark, Joshua Koen, John Ksander, Eric Legge, Nikolai Malykhin, Ian McDonough, Alice Mason, Brendan O’Connor, Daniela Palombo, Jeff Pisklak, Megan Sumeracki, Myron Tsikandilakis, Gonzalo Urcelay, Thomas Van Hoof, and Bo Wang. This book also benefitted from insightful discussions with colleagues: Kate Bailey, Laura Blackie, Peter Chapman, Michelle Chan, Yvonne Chen, Rob Dineen, Mark Haselgrove, Stan Hrybouski, Hanna Isotalus, Daniel Jolley, Sieun Lee, Yang Liu, Dan Lurie, Donald Lyall, Angie Makri, Stephanie McDonald, Nick Myers, Jean-François Nankoo, Enoch Ng, Brian O’Shea, Rakesh Patel, Jon Pierce, Mayank Rehani, Andrew Reid, Marije ter Wal, Michael Tobia, and Mimma Veniero. Thank you all for sharing your views, experiences, and time with me. All of that said, any mistakes or misinterpretations of the literature are mine and mine alone. I would further like to thank the staff at Routledge for their support with the publishing process. This book has taken many years to take shape and the encouragement and support in getting this to the end was invaluable. I am deeply indebted to the library staff at Boston College, who were critical in scanning many chapters and articles that were printed decades ago and otherwise assisting in my innumerable inter-library loan requests. I would like to thank the designers at The Noun Project, these icons were essential for designing the reminder cues that became a strength of this book. Finally, I am also grateful to the Overleaf staff, who helped me debug LaTeX issues on more occasions than I can count. This book is part of the Memory 2030 Initiative, which has three overarching goals: first, to redefine our understanding of memory systems in the context of recent scientific progress; second, to highlight the pivotal role of memory in everyday life, especially in areas including learning, decision making, and personal development; and third, to investigate how cuttingedge technologies can be harnessed to maintain and enhance our memory and cognitive capacities.

Author biography

Dr Christopher R. Madan is an Assistant Professor in the School of Psychology at the University of Nottingham (UK). He studies what makes some experiences more memorable than others and how this can manifest in future behaviour, such as decision making. He asks these questions using a combination of cognitive psychology, neuroimaging, and computational modelling approaches. Dr Madan has received a 2021 Early Career Award from the Psychonomic Society and a 2017 Rising Star Award from the Association for Psychological Science. He is a Fellow of the Psychonomic Society and AdvanceHE and has been elected to the membership of the Memory Disorders Research Society and the Experimental Psychological Society. To date, he has published over 150 peer-reviewed articles. Dr Madan completed his PhD in Psychology at the University of Alberta (Canada), having worked extensively with Drs Jeremy Caplan, Marcia Spetch, Anthony Singhal, Esther Fujiwara, and Alinda Friedman. During his PhD, he also held a visiting scientist position in the Department of Systems Neuroscience at the University Medical Center Hamburg-Eppendorf (Germany), under the supervision of Dr Tobias Sommer. Prior to his faculty position, Dr Madan was a post-doctoral research fellow with Dr Elizabeth Kensinger at Boston College (USA). Through each of these positions, Dr Madan increasingly broadened his skills and background across a variety of topics, including cognitive psychology, neuroimaging, and computational modelling, but also spanning behavioural economics, comparative psychology, and the neurobiology of aging—all of which are domains that he continues to actively conduct research within. Having always expressed a need to write, in grade school, Dr Madan wrote short stories for fun and would bring them to class; in middle school, he wrote website programming tutorials (CSS, JavaScript, PHP) in his spare time. Later on, concurrent with his PhD studies, Dr Madan published the book An Introduction to MATLAB for Behavioral Researchers (Sage, 2014), which was later translated into Chinese (DUFEP, 2017). In parallel with writing this book, he interviewed academics and non-academics about their post-PhD career journeys, recently published as Academia and the World Beyond, Vol. 1: Navigating Life after a PhD (Springer, 2022) and Academia and the World Beyond, Vol. 2: A PhD Is Not a Commitment to Academia (Springer, 2024). More books yet are in preparation, see https://engra.me/books.

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Dr Madan has become well established in the field for his approach of examining how memory relates to other aspects of cognition. He organised a symposium on “Motivated Memory” at the 2016 meeting of the Psychonomic Society as well as a symposium on the same topic for the 2018 American Psychological Association (APA) Convention. Moreover, he has spoken about these ideas in symposia at several other conferences, including several meetings of the Psychonomic Society (2020–2023), 2019 Aspects of Neuroscience conference, 2021 meeting of the Society for Applied Research in Memory & Cognition (SARMAC), the 2023 meetings of the Spanish Society for Comparative Psychology (SEPC) and British Association for Cognitive Neuroscience (BACN), and 2024 meeting of the European Workshop on Cognitive Neuropsychology (EWCN). Over the last years, Dr Madan has given dozens of invited talks around the world on his research and the broader vision presented here. This diversity in audiences—spanning cognitive psychology, comparative psychology, applied psychology, cognitive neuroscience, and neuropsychology—demonstrate the breadth of literatures and perspectives being integrated in his work. He also has organised/co-organised special issues on motivated memory in Cognition and Collabra: Psychology. Dr Madan has been a strong proponent of open science and behavioural methods, most recently demonstrated through his roles at Psychological Science, Behavioral Research Methods, and the Journal of Open Source Software. He particularly advocates for sharing of stimuli for memory research to aid in transparent reporting, but even moreso for sharing and recognition of software contributions. Sharing code across research labs underline his commitment to advancing not just the knowledge in his field, but also the methodologies and tools used to acquire that knowledge. This shift would additionally improve computational reproducibility and support a more collaborative research community.

Contents

List of figures

xv

List of tables

xix

Preface

xxi

About this book

xxiii

Reminder cues

xxvii

I Introduction

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1 Pondering the past and fantasising about 1.1 Why study memory? . . . . . . . . . . . 1.2 Memory is special . . . . . . . . . . . . . 1.3 Memory as a recording . . . . . . . . . . 1.4 Memory is a reconstruction . . . . . . . . 1.5 Memory is the basis of imagination . . .

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II Fundamentals

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2 Considering the functional purpose 2.1 Memory for everyday events . . . 2.2 Story narratives . . . . . . . . . . 2.3 Truths and lies . . . . . . . . . . . 2.4 Verbatim recall . . . . . . . . . . . 2.5 Availability . . . . . . . . . . . . .

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3 Structure and organisation 3.1 Taxonomy of memory . . . . . 3.2 Memory strength and precision 3.3 Associations and order . . . . 3.4 Memory capacity . . . . . . . 3.5 Broader memory principles . .

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5 Neurobiological architecture 5.1 Memory is distributed, yet modular 5.2 Cortical specialisation . . . . . . . . 5.3 Medial temporal lobe . . . . . . . . 5.4 Role of the hippocampus . . . . . . 5.5 Progression of Alzheimer’s disease .

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127 127 133 139 143 148

4 Individual variability 4.1 Aging . . . . . . . . . . . . . . . 4.2 Variability in memory ability . . 4.3 Ability to imagine: Phantasia . . 4.4 Memory abilities at the extremes 4.5 Patient H.M. . . . . . . . . . . .

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III Motivation

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6 Memories of emotions past 6.1 Flashbulb memories . . . . . . . . . . . 6.2 Emotional experiences . . . . . . . . . . 6.3 Confounds and considerations . . . . . 6.4 Memory is multifaceted . . . . . . . . . 6.5 Good is not merely the opposite of bad

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157 159 162 176 181 191

7 Remembering the wins 7.1 Experimental procedures . . . . . . . . . 7.2 Choices and lingering biases . . . . . . . 7.3 Decisions from experience . . . . . . . . . 7.4 Variations in procedures . . . . . . . . . 7.5 Individual differences in reward sensitivity

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199 200 208 210 217 225

8 Making it personal 8.1 Autobiographical memory . . . . 8.2 Lifespan distribution of memories 8.3 Self narratives and identity . . . 8.4 Self-reference effect . . . . . . . 8.5 Egocentric bias . . . . . . . . . .

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231 231 236 241 248 253

9 Moving to remember 9.1 Enactment . . . . . . . . . . . . . . . 9.2 Semantic properties of motoric stimuli 9.3 Neurobiology . . . . . . . . . . . . . . 9.4 The treachery . . . . . . . . . . . . . 9.5 Drawing . . . . . . . . . . . . . . . .

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263 264 267 273 278 282

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Contents

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10 A domain-general influence of motivation 10.1 Considering a common motivational process 10.2 Neurobiology of motivational domains . . . 10.3 A generalised view of availability . . . . . . 10.4 Animacy effects . . . . . . . . . . . . . . . 10.5 Adaptive memory . . . . . . . . . . . . . .

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IV Deliberate strategies

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11 Strategies for deliberate memorisation 11.1 Repetition, repetition . . . . . . . . . . . 11.2 Content-specific mnemonics . . . . . . . . 11.3 Scaffold mnemonics . . . . . . . . . . . . 11.4 Understanding and information relevance 11.5 Gamification . . . . . . . . . . . . . . . .

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323 326 334 337 345 349

12 Memory expertise across domains 12.1 Structured knowledge . . . . . . 12.2 Perceptual identification . . . . 12.3 Schematic frameworks . . . . . . 12.4 Verbatim recall . . . . . . . . . . 12.5 Memory champions . . . . . . .

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13 Extended mind, expanded memory 13.1 Daily external aids . . . . . . . . . . . 13.2 Veridical recordings, but also highlight 13.3 Remembering how instead of what . . 13.4 Memory in a digital society . . . . . . 13.5 Fictional future technologies . . . . .

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V Conclusion 14 Final thoughts 14.1 Memory systems and taxonomy 14.2 Neurobiology of cognition . . . . 14.3 Technological innovations . . . . 14.4 Assumptions and generalisations 14.5 Here be dragons . . . . . . . . .

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445 446 450 455 458 460

Quiz answers

467

References

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Index

635

List of figures

1.1 1.2 1.3

Example icons associated with ‘memory’ and ‘reminder.’ . . Parnassus by Anton Raphael Mengs (c. 1761). . . . . . . . . Example of boundary extension and contraction. . . . . . .

5 7 22

2.1 2.2 2.3 2.4

Imagery of the Ampelmännchen. . . . . . . . . . . . . . . Selecting juice from a store display. . . . . . . . . . . . . . Memory for the Starbucks logo from the signs.com study. . Pill organiser with multiple compartments for each day. .

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32 33 37 47

3.1 3.2 3.3 3.4 3.5 3.6 3.7 3.8 3.9 3.10 3.11

Taxonomy of memory systems. . . . . . . . . . . . . . . An example of episodic vs. semantic memory. . . . . . . Example of a portion of semantic network. . . . . . . . . Semantic network of general knowledge concepts. . . . . Example icons representing real-world objects. . . . . . . Memory strength in an item-recognition paradigm. . . . Mnemonic similarity task design. . . . . . . . . . . . . . Typical serial position curve for a free recall task. . . . . Recall from a free recall task across varying list lengths. Topic trajectories for BBC Sherlock episode. . . . . . . . Jenkins’ tetrahedral model of memory experiments. . . .

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58 59 60 61 62 69 75 85 86 90 93

4.1 4.2 4.3

Age-related differences in memory performance. . . . . . . . Individual brain structure gradually changes longitudinally. Ventral view of patient H.M.’s post-mortem brain. . . . . . .

102 104 121

5.1 5.2 5.3 5.4 5.5 5.6 5.7 5.8 5.9 5.10 5.11 5.12

Procedure for subsequent memory and retrieval success. . . Example of a brain from a structural MRI. . . . . . . . . . . Ventral regions associated with domain-specific processing. . Example stimuli used in fMRI localiser tasks. . . . . . . . . Brain activations related to memory over different time scales. Circuitry of the medial temporal lobe. . . . . . . . . . . . . Results of fMRI study examining memory strength. . . . . . Illustration of the hippocampus as a seahorse in the brain. . Anatomy of hippocampal subfields. . . . . . . . . . . . . . . Comparative neuroanatomy of hippocampal brain volumes. Illustration of Braak staging of tau accumulation. . . . . . . Alzheimer’s disease biomarker severity progression. . . . . .

130 134 135 136 137 139 142 144 145 147 148 150

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List of figures 6.1 6.2

Examples of emotional stimuli. . . . . . . . . . . . . . . . . When they look back. . . . . . . . . . . . . . . . . . . . . .

166 188

7.1 7.2 7.3 7.4

Two prominent reward-memory study procedures. . Overview of decision-from-experience study. . . . . Reward salience relationship. . . . . . . . . . . . . Approach-avoidance tendencies for different stimuli.

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201 213 214 219

8.1 8.2 8.3 8.4 8.5

Hypothetical recalled events by decade for an 80-year-old. Major life events for Forrest Gump and Luke Skywalker. . Song popularity across different ages. . . . . . . . . . . . . Photo of a cola bottle with ‘Chris’ on it. . . . . . . . . . . Illustration of the uncinate fasciculus tract. . . . . . . . .

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237 239 246 251 252

9.1 9.2 9.3 9.4 9.5 9.6 9.7

Two pyramids common in the learning literature. . . . . Object words and different semantic properties. . . . . . Illustration of the notion of microvalence. . . . . . . . . . Multiple objects map to a single word. . . . . . . . . . . Typical and atypical object interactions. . . . . . . . . . The Treachery of Images by René Magritte (c. 1929). . . Continuum of experimental control to ecological validity.

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267 268 270 270 277 278 279

10.1 10.2 10.3 10.4 10.5 10.6 10.7

SIMON framework. . . . . . . . . . . . . . . . . . . . . . . . SIMON framework applied to conditioned place preference. Brain maps for each motivation factor. . . . . . . . . . . . . Images of the locus coeruleus. . . . . . . . . . . . . . . . . . Frames from the Heider and Simmel (1944) animation. . . . Frames from “Horse in Motion.” . . . . . . . . . . . . . . . . Examples of food pictures and relevant characteristics. . . .

293 294 297 300 306 307 315

11.1 11.2 11.3 11.4 11.5 11.6 11.7 11.8

Eye movement data when viewing a scene. . . . . . . . . . . Example of study scheduling. . . . . . . . . . . . . . . . . . Simulated memory recall with weekly spaced practice. . . . Curve of the relationship between confidence and experience. Cranial nerves and their function. . . . . . . . . . . . . . . . Imagery used for remembering events from the gospel. . . . Typical items used in the peg mnemonic. . . . . . . . . . . . Apartment floorplan and 35 enumerated distinct loci. . . . .

325 326 327 333 335 338 339 341

12.1 12.2 12.3 12.4 12.5 12.6 12.7

Procedures used for expertise knowledge elicitation. . . Internal structure of keyboards and lock key cylinders. Examples of stimuli requiring perceptual expertise. . . Wine aroma wheel. . . . . . . . . . . . . . . . . . . . . The beginning moves of a game of chess. . . . . . . . . A word in a foreign script. . . . . . . . . . . . . . . . . Initial optimised pattern for Pac-Man. . . . . . . . . .

358 361 367 373 376 379 387

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List of figures

xvii

13.1 13.2 13.3 13.4 13.5 13.6

BikeAround equipment setup. . . . . . . . . . . . . . . Screenshots from a selection of DOS games. . . . . . . Facebook reminders. . . . . . . . . . . . . . . . . . . . Example health messages from Cameron et al. (2013). Fake composite photo of Albert Einstein. . . . . . . . . Postcard of the year 2000, as imagined in 1910 . . . . .

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410 420 422 427 429 432

14.1 14.2

Rodent navigating a virtual environment. . . . . . . . . . . Screenshots from “Cliffwood Village” virtual environment. .

456 456

List of tables

4.1

Example questions for subjective memory complaints. . . . .

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Phenomenological ratings of emotional memories. . . . . . .

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7.1

Top 15 most interesting trivia questions. . . . . . . . . . . .

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Love life script events and associated ages. . . . . . . . . . . Thinking About Life Experiences (TALE) scale. . . . . . . .

238 243

12.1 12.2

Knowledge in Diverse Domains (KIDD) 12-item test. . . . . Overview of the Major system. . . . . . . . . . . . . . . . .

389 396

13.1

Twenty often used security questions . . . . . . . . . . . . .

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Preface

The field of psychology, and the topic of memory, is intrinsically connected with countless other fields of science, and facets of daily life itself. At my undergraduate institution, the University of Alberta, the Psychology department is part of both the Faculty of Arts and the Faculty of Science. This is not a singular ‘Faculty of Arts and Science,’ but instead two distinct faculties, with Psychology being the only department at the university a member of two faculties. Specific classes are associated with only one of the faculties: subfields such as cultural psychology and social psychology are associated with Arts; biological psychology classes are associated with Science; and cognitive psychology classes are a bit of a mix. As I ventured out and learned about other universities, I saw that the Psychology departments elsewhere can vary, for instance, ‘Faculty of Social Science,’ ‘Faculty of the Humanities,’ and ‘Faculty of Medicine and Health.’ While this shows that organisational structures between universities can vary, it also highlights how Psychology as a department can be grouped with other departments in a variety of ways. As a further anecdote, when exploring books on memory, I found that even books with the same Library of Congress classification code (BF371) were held in different university libraries—corresponding to science, medicine, humanities, and education. Though books can be requested between library branches, there is a lot to be learned and appreciated from the lost art of browsing the stacks of a university library. Taking a more formal approach, a scientometric analysis of citation patterns, Boyack et al. (2005) revealed that along with established fields of science including medicine, chemistry, physics, mathematics, earth sciences, and social sciences, psychology is a hub science—a finding further brought to light by the late John Cacioppo (2007, 2013). This book views memory as a microcosm of the interconnected nature of psychology as a discipline, with connections to neuroscience, education, gerontology, zoology, and behavioural economics—among other fields. I started making notes on a functional approach to memory over a decade ago—only to later discover much had already been thought about from this approach in the 1980s. This book developed over many years, but was finished during the COVID-19 pandemic. Focusing on completing the book helped me cope with the stresses of this time, but I hope it also brings some joy to you, the reader. A book is only useful for communicating to a reader and I sincerely hope the interesting findings from decades—and centuries—past and integration across many literatures are able to provide something for everyone.

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About this book

I have divided the memory literature into three distinct approaches, though these are not mutually exclusive: fundamentals of memory, motivated memory, and strategic memory. This view is carried through to the organisation of this book, with each approach comprising one section of the book. This book presents highlights for each featured topic, showcasing findings and theories that are of interest and together form a coherent narrative. There are, of course, countless other studies that merit further reading—in some ways, this book is more of a painting of the landscape of the memory literature, rather than a verbatim photo of the scene. The book is based on a mixture of three perspectives on learning: • Cognitivism—learning is an internal process in which information is received, processed, and retrieved when necessary (e.g., James, 1890; Moore, 1939; Neisser, 1967; Atkinson & Shiffrin, 1968). • Behaviourism—learning is a change in observable behaviour caused by external stimuli in the environment (e.g., Thorndike, 1898b; Watson, 1913; Skinner, 1938; Abramson & Levin, 2021). • Constructivism—our understanding of the world is constructed through experiences and interactions with our environment (e.g., Bartlett, 1932; Piaget, 1954; Neisser, 1976; Rumelhart & Ortony, 1977; Vygotsky, 1978). These used to be considered distinct and contradictory ideologies, but we have now reached a stage where they can be integrated (e.g., Rozeboom, 1958; Ertmer & Newby, 1993; Petri & Mishkin, 1994; Mahadevan et al., 2002; Watrin & Darwich, 2012; Urcelay & Alfei, 2022). Even beyond these three major perspectives, other views have been proposed in the literature and have a guiding hand in how we study memory (Grant, 1932; Herrmann & Searleman, 1992; Bates, 2023). The first approach—fundamentals—is the primary focus of most memory texts. However, the emphasis of this book is the functional utility of memory. Some experiences are inherently more memorable due to their perceived importance and salience: motivated memory. Other times experiences are deliberately and effortfully etched into memory: strategic memory. These two approaches are topics I have written perspective pieces on previously, rethinking the definition and role of episodic memory (Madan, 2020a, 2023a), discussing how motivational processes can influence memory and cognition broadly (Madan, 2013, 2017b; Palombo & Madan, 2015; Murty et al., 2020), xxiii

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and how strategies can deliberately enhance memory (Madan, 2014a, 2023b; Weinstein et al., 2018; Van Hoof et al., 2021a, 2021b, 2022). The emphasis of this book is on episodic memory function, and to a lesser degree, semantic memory. While I have done studies investigating sensory memory (Nankoo et al., 2012, 2015a, 2015b), this book is centred on the experiences that persist and become memorable. Subsection headings are intended as focused discussions as part of the preceding numbered section. Each chapter ends with visual reminder cues to serve as a study aid and prompt memories of topics discussed, a multiplechoice quiz, thought questions to prompt consideration and discussions beyond the presented material, along with suggestions for further reading. It is no secret that psychology has had a replication crisis, though cognitive psychology findings have generally held (Open Science Collaboration, 2015; Wilson & Wixted, 2018; Camerer et al., 2018; O’Grady, 2021). Nonetheless, where possible, meta-analyses and replication attempts are highlighted. Metaanalysis effect sizes are reported as weighted Cohen’s d or Hedge’s g, as available. Moreover, findings discussed here are ‘biased’ in that I am not comprehensively reporting all findings on, for instance, emotion effects on memory, but am choosing which results to discuss partly based on my own beliefs of what is reputable. While this book primarily builds on a foundation of cognitive psychology and neuroscience, it integrates concepts from other subdisciplines, including biological psychology, neuropsychology, personality and individual differences, and social psychology.

Chapter structure The first approach is the fundamentals. To study memory, we must first understand how it is generally organised (Chapter 3), factors that affect individual ability (Chapter 4), and the neurobiology that supports it (Chapter 5). Given this book’s emphasis, these are preceded by an in-depth discussion on the functional purpose of memory (Chapters 1 and 2). The second approach and primary emphasis is motivated memory. Some events and information is inherently more salient, relative to more mundane information, and is better remembered. In particular, information associated with emotion (Chapter 6) or rewards (Chapter 7) is remembered well, though this is not specific to just these two domains. Memory for information related to one’s self is also remembered better than less relevant information (Chapter 8); memory is also enhanced for objects and actions (Chapter 9). Commonalities between different types of motivation that can influence memory are also examined, with the notion of a domain-general enhancement of memory being explored (Chapter 10). The third approach is strategic memory. When information is desired to be remembered well, but may not be more intrinsically interesting, memory strategies can be used. Memory strategies can be ways of internally organising or learning information that facilitates later memory recall (Chapter 11).

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In some hobbies and professions, remembering a wealth of information is important (Chapter 12). The use of notes, devices, and the internet has also affected how we remember information—or remember how to access information (Chapter 13). This book has a different structure than typical textbooks on ‘Human Memory,’ which often have chapters for each memory system and later chapters on topics such as ‘Eyewitness Memory’ and ‘Aging.’ Instead, I focus on episodic memory and factors that make experiences memorable. Nonetheless, I include a sufficiently comprehensive view to ensure a solid foundation and broad scope, while also making the material engaging and, hopefully, memorable.

Advice for instructors This book is intended for a senior undergraduate or graduate course, but should also be a useful reference text for faculty-level researchers. The book should serve equally well as a core reading for a lecture-based course or as the prompt for seminar discussions. Depending on the structure of the course, some of Chapters 1–5 could be used as assigned as background, though Chapter 1 or 2 may be worth discussing directly in class. Chapters 6–13 are intended to be discussed one chapter per week. If there are too many topics for the available weeks, the instructor should select a subset or allow students to choose which chapters are covered. Apart from Chapter 10 (domain-general motivation), chapters are relatively independent. To supplement the book content, online resources are available at https://engra.me/books/memoriesthatmatter/resources/. These are primarily videos that align with topics discussed in the book. As online links are ephemeral, I decided a companion website where I can update and replace them would be preferable to including them in the book directly.

Bibliometrics Managing the references for this book has been a challenge unto itself— there are 3,593 references throughout the entire book. Seven references were published before 0 AD (Hesoid, Plato, Aristotle, and Cicero); two were published before 1000 AD (Pliny the Elder and St. Augustine). 13 references were published between 1000 and 1799; 47 references in the 1800s, then 379 were published between 1900 and 1979. For each of the following four decades (1980s, 1990s, 2000s, 2010s), there were 235, 360, 700, and 1275 references, respectively. The remaining 575 references were published since 2020. Of the 3142 journal articles, they were published across 889 journals, with between 1 and 97 articles per journal referenced; 32 journals had at least 20 articles cited from them. The list of journals and their respective citation counts are shown on the following page.

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Rank 1 2 3 4 5

6

Journal Memory & Cognition Proceedings of the National Academy of Sciences of the USA Memory Psychological Science Journal of Memory and Language (combined with Journal of Verbal Learning and Verbal Behavior)

Citations 97 65 63 57 53

7 8 = 10

Journal of Experimental Psychology: Learning, Memory, and Cognition NeuroImage Applied Cognitive Psychology Journal of Neuroscience Science

51 50 48 48 47

11 12 13 14 15

Trends in Cognitive Sciences Psychonomic Bulletin & Review Psychological Review Journal of Personality and Social Psychology Neuropsychologia

46 42 41 39 37

16 17 18 = 20

Journal of Experimental Psychology: General Quarterly Journal of Experimental Psychology Journal of Experimental Psychology Behavior Research Methods Psychological Bulletin

36 35 33 33 32

21 = 23 = 25

Nature PLOS ONE Journal of Cognitive Neuroscience Neuron Frontiers in Psychology

30 30 29 29 24

27 28 29 30 = =

Hippocampus Cognition Cognition and Emotion Cerebral Cortex Cortex Nature Neuroscience

23 22 21 20 20 20

Reminder cues

Each section through all 14 chapters is represented by one of the following icons. These icons are also presented at the end of each section and chapter. Reviewing these icons is intended to serve as a reminder of all 65 sections across these chapters.

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Part I

Introduction

Chapter 1 Pondering the past and fantasising about the future

Imagine, then, for the sake of argument, that our minds contain a block of wax, which in this or that individual may be larger or smaller, and composed of wax that is comparatively pure or muddy, and harder in some, softer in others, and sometimes of just the right consistency. Let us call it the gift of the Muses’ mother, Memory, and say that whenever we wish to remember something we see or hear or conceive in our own minds, we hold this wax under the perceptions of ideas and imprint them on it as we might stamp the impression of a seal ring. Whatever is so imprinted we remember and know so long as the image remains; whatever is rubbed out or has not succeeded in leaving an impression we have forgotten and do not know. — Plato (368 BC)

Memory, a cornerstone of our cognition, is a topic that invites curiosity and exploration from psychologists, neuroscientists, philosophers, and historians alike. Memory is more than a system for recalling facts or experiences; it is an integral part of our identity, shaping our actions, decisions, and our anticipations for the future. It is not a simple storage system; it is a complex, dynamic process that is constantly being updated and revised. Our memories influence and are influenced by an abundance of factors, from emotions and actions to circumstances and prior experiences. The study of memory, therefore, opens up a fascinating world of insights into our minds and daily lives. It is not just about understanding how we remember things, but the foundation for how we think, perceive, and construct our reality. In the first chapter, we will begin to delve into the intricacies of memory, and I hope the journey is as enlightening as it is intriguing. Memory offers a deeper understanding of a process so integral to our lives, yet so often

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taken for granted. This will be a journey into the core of human cognition, exploring a process that is as complex as it is fascinating.

1.1 Why study memory? Our memory system is designed to enable us to remember experiences that are meaningful, emotional, surprising, or repeated—these are the memories that matter. We often recall experiences and information that have at least one of these features, rather than those that are mundane and routine. In this book we will discuss what makes some experiences more memorable than others and some strategies and methods for deliberately remembering information. These are the memories that matter. This book assumes the reader has some background in cognitive psychology, but otherwise should be suitable for anyone with an interest in memory, from undergraduate to researcher. Most memory books focus on the structure and organisation of memory, the cognitive neuroscience of memory, or specific aspects of memory—such as emotional memory or learning strategies. Instead, this book takes a fresh approach by providing an overview of a variety of factors that relate to durable memories, and aims to be of interest to many. Many attribute Neisser (1967) as the first book on “Cognitive Psychology” (e.g., Gardner, 1985; Ashcraft & Radvansky, 2014; Baddeley, 2023). While this remains an excellent book decades later, Moore (1939) earns the title of being the first book entitled Cognitive Psychology. This 636-page text provides a prescient vision for cognitive psychology across a variety of domains, including consciousness, perception, reasoning, philosophy of mind, and memory. Revisiting early texts can show us how far we have come as a field, but it is also humbling to see what was already understood and which ideas were before their time. Knapp (1985) and Surprenant and Neath (1997) provide further context on Moore’s book and why it did not receive sufficient attention. MIN RE

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To truly appreciate the role of memory within cognitive psychology, we must first appreciate—or at least acknowledge—the role of memory within a broader context. Memory is integral to our daily lives, but also the development of culture and technology. “Memory” as a term is used in many fields, not just psychology. These can range from computer science to

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world history—Figure 1.1 provides an overview of the pictorial representations associated with memory. While these fields are quite varied, they also each provide insights into how we understand the term ‘memory’ in society and our everyday lives. Memory is both the storage of factual information and personal experiences. Memory is our remembrance of past events—our own, those related to our identity, or those around us more generally (e.g., Remembrance Day, ‘in memoriam’), as well as the deliberate outcome of successful studying. Having established the importance of studying memory, let’s delve into the unique aspects that make memory a special domain within cognitive psychology.

FIGURE 1.1: Example icons associated with ‘memory’ and ‘reminder.’ In a book about memory from 1920, Richards begins with a reflection: We are told all these things are imprinted upon our brain, and that is why we can recall them so readily. Well now what puzzles me is, how is it possible to find room enough in our brain to register or imprint all the phenomena of our past life, the thousand, aye tens of thousands of incidents and images we have seen, as in my own experience of 85 years existence. How do you account for the existence of memory? How is it possible to memorize things that have happened in the multitudinous events and scenes of a long life? We are conscious of these thousand and one things of course, but what is it that enables us to record and remember them, the primal root that underlies the whole business? (pp. 7–8)

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This passage was from a letter that Richards sent to an unnamed professor. Here is the response: I am in receipt of your letter of Jan. 18th asking certain questions about the problem of Memory. I am surely at a loss what literature to suggest in order that you may find any adequate answer to your question as to what is the primal cause as a root of our memory processes. Psychology nowadays, like other natural sciences, has pretty much ceased to speculate on ultimate causes and as in physics for instance, confines itself to a gathering of facts, their classification and an attempt to discover uniform laws. In this phase of the matter, there is of course you know a wealth of literature, but I know of nothing that would enable us to specify any more ultimate cause for memory than the change undergone in the course of our lives by the nervous system. As for the possibility of having recorded in such relatively small compass, the thousand of facts over which our memory has command, I do not feel the seriousness of the problem. As you may know the nervous system is made up of microscopic elemental units called neurons, of which you know there are probably some ten thousand million or more, how these neurons are interconnected by mere contact, that since each neuron has many processes projecting from it one can see that there are millions and millions of possible connections that may be established between different neuron systems. (pp. 8–9) 100 years have passed since Richards’s request, and we can do better now. Memories That Matter is motivated by this same curiosity and will answer some of these questions—among others.

1.2 Memory is special Memory is quite unique, as a domain within cognitive psychology and in its representation in society—from mythologies to modern daily life. Attention, language, decision making—all of these are important, both in their own right and in relation to memory, but none of these concepts were represented by their own designated god. Mnemosyne is the goddess of memory in Greek mythology—one of the 12 Titans, coming into existence even before the gods of Mount Olympus (Hesoid, 700 BC, p. 7). The etymology of ‘Mnemosyne’ is shared with ‘mnemonic,’ both derived from ‘mneme.’ Famous paintings of Mnemosyne have been made, in particular Parnassus, a painting by Anton Raphael Mengs (c. 1761; see Figure 1.2), and a depiction of the goddess herself by Dante Gabriel Rossetti (c. 1880). Mnemosyne is also mother of the nine Muses, being one of Zeus’ wives prior to Hera, who are also depicted in

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FIGURE 1.2: Parnassus by Anton Raphael Mengs (c. 1761). Apollo is shown in the centre, with Mnemosyne immediately to the right and leaning on a pedestal, surrounded by the nine Muses. Credit: State Hermitage Museum. Parnassus, along with Apollo featured in the centre. (Note, this is a different painting than The Parnassus, Raphael [Raffaello Sanzio da Urbino], who also made a painting of the same name that adorns the Vatican [c. 1511]. Raphael’s painting features Apollo and the nine Muses, but does not include Mnemosyne.) Not only did the ancient Greeks have Mnemosyne—there is also Lethe, goddess of forgetfulness. MIN RE

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Some other mythologies also had gods that directly oversaw the domain of memory. For instance, Mímir is the patron of memory in Norse mythology, with the name thought to be derived from “to think, recall, reflect, worry over” (Lincoln, 1982, p. 27). Of course, other mythologies also have deities that oversee memory or knowledge, but often have a broader domain than only memory, such as the Aztec god Quetzalcoatl, Hindu goddess Saraswati, Sumerian god Enki, and the Japanese Buddhist goddess Benzaiten. Likely intended to convey the impermanence of memory itself, gods of memory are often also associated with water—as is the case for all of the aforementioned gods. This aligns well with the famous adage made by Greek philosopher Heraclitus: “No man ever steps in the same river twice, for it’s not the same

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river and he’s not the same man.” (see McCabe, 2015). And, more recently, also with Marcel Proust, a French writer, “Remembrance of things past is not necessarily the remembrance of things as they were.” (Proust, 1913). As a further example, the malleability and fluidity of memory are aptly embodied in Salvador Dalí’s acclaimed painting, The Persistence of Memory (1931). The well-known depiction of melting clocks offers a vivid allegorical representation of our subjectivity in perceiving memory. Facets of memory have also been highlighted in literature over the ages—including William Shakespeare, Charles Dickens, and Kazuo Ishiguro (Camden, 1939; Weaver, 1956; Maguire, 2002; Teo, 2014; James, 2016). These works have explored topics such as the perseveration of memories, mental time-travel, and mourning. The myriad ways in which memory is used in literature further serve to emphasise its role in shaping our understanding of reality and the self. These authors, among others, have used memory as a narrative device to investigate the interplay between the past, the present, and the future (Bell, 2003; Groes, 2016; Gudmundsdottir, 2017; Grmusa & Oklopcic, 2022). Shakespeare used memory to establish a continuity of self and motivate dramatic moments; Dickens used it to develop complex character narratives. Ishiguro, in novels like The Remains of the Day and Never Let Me Go, elegantly explored the topic of memory and regret, revealing how our memories can be selectively edited or completely erased over time, often to shield us from uncomfortable truths (Teo, 2014). By exploring the persistence of memories and the concept of mental time-travel, these works underscore the importance of memory in the formation of identity. These narratives thus serve to demonstrate that memory is not merely a record of the past but a complex and dynamic process that continuously influences our perception of the present and expectations for the future (James, 2016). Memory further is the basis of how we represent the past, “remembered, conventionalised, and mythologised” (Fussell, 1975, p. ix). This aligns with the well-known and timeless adage—history is written by the victors (also see Deyermond, 2009). Relatedly—“those who cannot remember the past are condemned to repeat it” (Santayana, 1905, Vol. 1, Ch. 12). This also relates to the unfortunate case of why books are sometimes banned, or even burned (Brockmeier, 2002). For a contemporary initiative to counter banned media, see Section 13.4 on p. 417. In other instances, knowledge can be lost for centuries, such as Greek fire (Groller, 1981), Damascus steel (Verhoeven et al., 1998), and Roman concrete (Seymour et al., 2023). The role of memory in how we understand previous generations cannot be underestimated (Nora, 1989; Olick & Robbins, 1998; Ricoeur, 2004; Assmann, 2008; Cubitt, 2019)— it is just a different form of memory than we usually think of in psychology. Memory—as we consider it in psychology—is also a relevant topic in legal circles—from the limits of eyewitness memory (Simmonsen, 2011; West & Meterko, 2016; Graves, 2019), terms of a contract (Merrill, 1936), timing of jury instructions (Goldberg, 1981), to even the legality of copyrighting memory strategies (U.S. Circuit Court, 1898; Hamlin, 1904; Schlattman, 1951).

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Having explored the unique status of memory in society, let’s delve into the rich vocabulary that has developed to describe memory and its processes.

Memory vocabulary More contemporaneously, memory is unique in having such a rich vocabulary of related terms. Referring to memory as a storage, memories can be accessed or retrieved. However, more memory-specific terms can be used, such as ‘remembered,’ ‘recognised,’ or ‘recollected.’ For instance, “To the best of my recollection, I have never seen her before.” Someone or something else can prompt your memory, serving as a reminder. Failure to remember is labelled with a whole other term, ‘forgetting,’ but the memories may instead be unavailable in relation to a state or context, due to suppression. Incorrect memories may be “made up” or confabulated. We can reminisce about the past. Thinking back to past experiences could be associated with a positive framing, nostalgia, or a negative frame, if labelled as ‘rumination.’ Some terms have a more complex relationship with memory, relating to thinking back to past events and alternate outcomes (i.e., counterfactual). These include ‘regret,’ ‘relief,’ and ‘melancholy.’ Moreover, these are all distinct from other terms related to how memories are formed, such as ‘encoding’ or ‘studying.’ Sometimes the to-be-remembered information is referred to as ‘memorandum,’ though a related term is seldom used in the cognitive psychology literature, ‘memorial.’ Indeed, a rich, yet nontechnical, set of vocabulary is specifically relevant to how we discuss the role of memory in our daily lives. The concept of memory truly is ever present, we are always surrounded by reminders. Statutory holidays include “Remembrance Day” and “Memorial Day.” A common adage in life is to “forgive and forget.” Memory is also special in being a game—alternatively known as Concentration, Matching Pairs, or Pelmanism—that has been played since at least the early 1800s. Here a deck of cards is laid out in a grid, face down, and two or more players take turns flipping over a pair of cards and seeing if they match. If they match, the player removes the card from the grid and earns a point and goes again. If the pair of cards do not match, the two cards are flipped back to face down and the next player takes their turn. Decks can also be used in educational settings, such as half having a picture and the other half having words in a foreign language—or having trivia questions and answers. Standard 52-card decks can also be used, where cards of the same value and colour are considered a match, such as a nine of hearts with a nine of diamonds. Velleman and Warrington (2013) derived the expected number of moves for a game of memory, finding that optimally a game takes an average of 1.6× the number of card pairs.

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Memory analogies To help grasp the intricate workings of memory, researchers and scholars have often used comparisons, drawing analogies between memory and everyday objects and processes. Many analogies have been used to discuss how memory works—likening it to a wax tablet (Plato, 368 BC; Thorndike, 1898b; Small, 1997), a net or sieve (Miller, 1956), or a recording (Penfield, 1958; Beckett, 1958; Posner & Warren, 1972; but see Milner, 1977). The most pervasive analogy is that memories are stored as encapsulated experiences of some sort that can be accessed through an index, library, or storehouse system (Locke, 1690; James, 1890; Brown & McNeill, 1966; Loftus, 1977; Loftus & Loftus, 1980; Koriat & Goldsmith, 1996). The Pixar movie Inside Out (2015) brings this analogy to life to show memory encoding, storage, and retrieval. Each of these analogies has value, but all of them are only caricatures of how memory functions. For example, memory being likened to a wax tablet to emphasise its ability to store information; a net, highlighting its filtering mechanism. Colloquial expressions like “having a memory like a goldfish” or “having a memory like an elephant” reflect popular perceptions of individual differences in memory abilities. These analogies not only provide vivid imagery but also help us understand how we use memory to store and retrieve information, filters out relevant details, and exhibits inter-individual variations. Roediger (1979, 1980b) provided a thoughtful discussion of these analogies, as well as some that are more creative, such as likening memory to a cow’s stomach (St. Augustine, 399; Hintzman, 1974; Tsushima, 2008), a tuning fork (Ratcliff, 1978), an acid bath (Posner & Konick, 1966), or even a garbage can (Landauer, 1975)—each highlighting a unique property of memory. Most analogies describe how characteristics of memories are stored or retrieved. While I am almost inclined to leave you to wonder and maybe seek out the original articles to understand the intended relevance of each of these objects in characterising memory, we are just beginning our journey. As you may know, cows have multiple stomachs. Like a cow, the human mind ingests experiences and knowledge. These initial experiences are somewhat akin to the food that a cow initially swallows. Later, the food is brought back to the mouth for further chewing—now referred to as ‘cud.’ Because of this digestion process, cows are considered a ‘ruminant’ animal. In St. Augustine’s (399) view, our mind also ‘ruminates’ on our experiences— later our mind brings it back for further processing. This process of ‘chewing the cud’ of thought is likened to the act of remembering. By remembering, and ruminating, we achieve a deeper understanding and extract more from our past experiences, much like the cow extracts more nutrients through the act of cud-chewing. St. Augustine’s comparison of memory to a cow’s stomach illustrates the on-going process of experiencing and remembering, which also changes the form of the initial experience further. Hintzman (1974) delves deeper, exploring how this intellectual ‘ruminant’ process reflects the intricate processes of memory (also see Mourant, 1979; Grove, 2021). While delving into

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this analogy, I learned that the digestion process of a ruminant animal and the cognitive process of rumination share the same root word. Ratcliff (1978) was particularly focused on memory retrieval and suggested that memory search shares features with how a tuning fork evokes resonating vibrations in matched tuning forks. Some more recent, and more enjoyable, analogies have also been proposed since Roediger’s comprehensive summary. In a children’s book, Brosgol (2021) describes a child that is determined to hold onto the memories of her happy experiences. She does this by placing objects, people, or even experiences she wants to remember inside jars. The idea is that by capturing and preserving these memories in jars, she can keep them from fading away or changing over time. The concept serves as a metaphor for the desire to hold onto special moments and the fear of losing those memories. As the story unfolds, the child learns that while it’s natural to want to preserve good memories, it’s also important to let go and make room for new experiences and memories to form. One of my favorites has been provided by Lansdale and Baguley (2008): Suppose, earlier in his or her career, a pirate has buried several separate chests of treasure on a long beach. Returning some years later, the pirate, forgetting exactly where the chests are buried, carries out a geophysical survey of a sufficiently long stretch of beach to be sure of including the chests. The survey identifies many possible signals of variable strength that could be treasure chests or that could be odd bits of buried flotsam and jetsam. Unfortunately, there will only be one chance to dig a hole and get away before attracting unwanted attention. What is the chance of digging up a chest as opposed to an old bucket? (p. 865) In contrast to the analogies discussed thus far, the acid-bath analogy is an account of forgetting during a retention interval (Posner & Konick, 1966). In this case, details of the memory are eaten away over time, leaving only a gist representation to remain. The garbage-can analogy (Landauer, 1975), rather, provides some insight into the structure, and limits, of memory: The order will be more like that of the detritus in a garbage can than the entries in a dictionary. A garbage can is neither selforganizing nor structured, yet one finds coffee grounds and orange peels near each other, things used long ago on the bottom, and so forth. It is this sense of order being imposed only by historical order of entry that is implied by calling this a random storage model. (p. 502) Memory can provide organisation and use cues to retrieve previously indexed information, and replay past experiences. While memory lays at the

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centre of all of these perspectives, none of them are individually sufficient. One of the most pervasive analogies about memory is the idea of memory as a recording. Let’s delve into this concept and its implications.

1.3 Memory as a recording Consider the following statement: “Human memory works like a video camera, accurately recording the events we see and hear so that we can review and inspect them later.” Based on your current knowledge, do you agree or disagree? What do you think the general public thinks? MIN RE

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In 2011, Simons and Chabris conducted a telephone survey of the US population with over 1,800 respondents. They asked for responses, strongly disagree to strongly agree, as well as ‘don’t know,’ to 16 statements about psychology. In a separate sample, they also surveyed 73 attendees at a major experimental psychology conference, and further selected the ‘experts’ that had reported at least ten years of memory research experience. We will be focusing on the statement “human memory works like a video camera…” that was stated at the beginning of this section. For the general public, responses were very distributed: 24% strongly agreed, 39% mostly agreed, 23% mostly disagreed, 11% strongly disagreed, and 3% didn’t know. That is, 63% either strongly or mostly agreed with the statement. After adjusting for sampling biases (relative to census data), this dropped, but still remained at 53%. The conference attendees and expert subsample had a very different view however. Here 97% and 94% strongly disagreed, respectively, with the remainder instead mostly disagreeing. To replicate the findings, Simons and Chabris (2012) conducted a study with the same overall methodology but recruited nearly 1,000 participants online from Amazon Mechanical Turk. After again weighting the data based on census data, 47% strongly or mostly agreed with the statement. These were not the first studies to examine this ‘recorder’ myth. In a comprehensive book of psychology myths, Lilienfeld et al. (2010) discuss this at length (also see Jarrett, 2014). Similar questionnaires have since been done with non-experts (e.g., undergraduate students, teachers) and observed similar views (Magnussen et al., 2006; Bornstein, 2017; Papadatou-Pastou et al., 2017). Brewin et al. (2019) probed this further, examining statements about more specific beliefs about memory (e.g., completeness, accuracy,

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permanence) providing some more specific insights, though the general results were consistent. Practising psychologists and judges do not know more about eyewitness memory than lay people (Magnussen & Melinder, 2012). Neisser (1985a) provides a brief reflection on the curiosity that people so readily accept the recorder fallacy. Clearly most have a different view of memory than the academics who study it. There is no limit to sources that suggest that memory can be replayed like a video. A popular book on visualisation, Seeing with the Mind’s Eye by Samuels and Samuels (1975), begins its preface with the statement: “The human mind is a slide projector with an infinite number of slides stored in its library, an instant retrieval system and an endlessly cross-referenced subject catalog.” Turning to more empirical evidence, in foundational research, William Penfield stimulated regions of patients’ brains when conducting brain surgery. In addition to mapping sensory and motor regions, Penfield’s brain stimulation work has been used as evidence that previous experiences, memories, can be replayed verbatim—like a recording. Specifically, Penfield (1952) electrically stimulated brain regions in patients suffering from focal epilepsy, sometimes eliciting conscious experiences (also see Penfield & Perot, 1963). These instances were described as corresponding to memories or flashbacks. However, further consideration has indicated that these experiences are more consistent with reconstructions than recollections (Neisser, 1967; Loftus & Loftus, 1980; Curot et al., 2017; Nitsch & Stahnisch, 2018). Neisser (2008) highlights the issue best: these metaphors compare memory to some permanent medium of storage: written documents, photographic film, magnetic tape. Such a comparison seems harmless enough, but once the metaphor is in play we tend to endow memory itself with properties that only the medium really has: permanence, detail, incorruptibility. (p. 81) Memory is mired with countless biases and distortions, far from being a veridical recording of experiences that can be readily played back. Contrary to the belief that human memory works like a video recorder, accurately recording events for later review, memory is a reconstructive process influenced by biases and distortions. This key tenet challenges the notion of memory as a veridical recording and highlights the presence of innumerable biases that lead to preferential recall of certain experiences. However, these may not be as heterogeneous as they initially appear; I will suggest that there are patterns across subfields of research that reappear in more specific circumstances—perhaps with shared underlying phenomena. Additionally, there are instances where we intentionally desire to remember mundane information, such as shopping lists or chess-board arrangements, in order to preserve specific details that might otherwise fade away. Here we approach memory with a different goal: how to make specific information persist when it otherwise may fall away.

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1.4 Memory is a reconstruction When two people experience an event together, their individual memories of the event often differ. Discussions about the event can lead to information exchange and adoption, blurring the boundaries of individual recollections (Sutton et al., 2010; Hirst & Echterhoff, 2012; Jalbert et al., 2021). However, real-world demonstrations of this are likely to show even more variation from the veridical experience. Consider a married couple that is in counselling or having a divorce. If asked about a recent argument involving their partner, they both could recount a plausible, and likely relatively accurate, narrative of the argument. However, these narratives, and their respective memories for the details of this argument, will differ—each of them remembers some details more saliently than others, based on how they felt about the events and were coloured by past experiences (Bradbury & Fincham, 1990; Halford et al., 2002; Philippe et al., 2013; Harris et al., 2014). Each individual will have autobiographical memories of their interactions, but these reconstructions of past events will not be identical recordings. Beyond these limitations of remembering, memory retrieval has other properties—such as re-interpreting past events based on subsequent experiences Over time, there can also be age-related differences in how we re-evaluate the emotionality of our past experiences (Kennedy et al., 2004; Ready et al., 2007; Ford et al., 2018). Autobiographical memories are reconstructions rather than verbatim recordings, influenced by emotional responses and personal biases. To illustrate this concept, let’s delve into a real-world example.

John Dean’s memory as a case study Real-world examples can often offer invaluable insights into memory and cognition, providing perspectives that complement and sometimes surpass findings from controlled laboratory studies. One such compelling case study is John Dean’s memory during the Watergate scandal, which provides a unique opportunity to compare recollections with verifiable recordings, shedding light on the reconstructive nature of memory. In 1973, the US was in the middle of the Watergate scandal—John Dean, former counsel to President Nixon— was one of the central individuals to testify. Dean’s testimony was extensive, opening with a 245-page statement. Of particular relevance, when Dean first testified he was sometimes referred to as ‘the human tape recorder’ due to his level of detail. Dean (1973) himself was more modest, stating “my mind is not a tape recorder” (p. 1373) and “I would say I have an ability to recall, not specific words necessarily, but certainly the tenor of a conversation and the gist of a conversation” (p. 1434). However, the subsequent discovery of recorded conversations related to the events allowed for a comparison between Dean’s recollections and the verbatim truth.

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Neisser (1981) treated this situation as a case study to examine how Dean’s memory and testimony compared to the recorded transcripts, revealing fascinating insights into the reconstructive nature of memory. Dean’s testimony made him appear more central to the events than he actually was in the recordings—providing evidence of the egocentric bias (see Section 8.5 on p. 253). Dean recalled many details, but they often were only the ‘gist’ of what was said, rather than verbatim. Moreover, some phrases and instances occurred on multiple occasions, resulting in multiple events becoming intermixed in memory. The details testified were definitely rehearsed, further leading his testimony to be reconstructed rather than a verbatim record. Interestingly, it is also noted that Dean seems to have developed his own variation of the famously effective memory strategy ‘the method of loci,’ which we will discuss in detail in Section 11.3 on p. 340. The memory errors made by John Dean and others in public statements, provide insight into how memory functions (Edwards & Potter, 1992; Belli et al., 1997; Greenberg, 2004; Kaposi, 2011). To follow the tenet that memory is not like a recorder, memory is reconstructive. This juxtaposes well with recent findings demonstrating parallels between remembering the past and imagining the future. Hebb (1949, pp. 46–47) and Neisser (1967, pp. 114–116, 285–286) have presented this understanding of memory more clearly than many current researchers, describing the process of remembering as being similar to a palaeontologist reconstructing a dinosaur. Reconstructing dinosaur structures has been an on-going challenge over the centuries—from initially considering them to be large humans, misidentifying a thumb as a horn, and often confusing a different species for different developmental stages of a singular species (Plot & Burghers, 1677; Taquet & Russell, 1998; Norell, 2019). Moreover, in the decades since this analogy was proposed, it has become even more apt than either of them could have known, as evidence is increasingly accumulating suggesting that some dinosaurs were feathered (Chen et al., 1998; Turner et al., 2007; Xing et al., 2016; Pan et al., 2019)—further highlighting the fact that reconstructing the past is associated with reinterpretations of sometimes questionable veracity.

The War of the Ghosts Bartlett (1932) observed clear evidence that memory is reconstructive. In this study, Bartlett asked students to read a North American folk tale, The War of the Ghosts. This story was intentionally chosen because it was from a different culture than the students, included unfamiliar vocabulary, and elicited vivid visual imagery. Participants were given sufficient time to read the story twice and were then asked to reproduce it after a 15-minute delay, and again at a later opportunity that varied across participants. Participants were not aware of the goal of the study, that they would be asked to reproduce it at a later time. The text of this story is reproduced here:

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The War of the Ghosts One night two young men from Egulac went down to the river to hunt seals and while they were there it became foggy and calm. Then they heard war-cries, and they thought: “Maybe this is a war-party”. They escaped to the shore, and hid behind a log. Now canoes came up, and they heard the noise of paddles, and saw one canoe coming up to them. There were five men in the canoe, and they said: “What do you think? We wish to take you along. We are going up the river to make war on the people.” One of the young men said,“I have no arrows.” “Arrows are in the canoe,” they said. “I will not go along. I might be killed. My relatives do not know where I have gone. But you,” he said, turning to the other, “may go with them.” So one of the young men went, but the other returned home. And the warriors went on up the river to a town on the other side of Kalama. The people came down to the water and they began to fight, and many were killed. But presently the young man heard one of the warriors say, “Quick, let us go home: that Indian has been hit.” Now he thought: “Oh, they are ghosts.” He did not feel sick, but they said he had been shot. So the canoes went back to Egulac and the young man went ashore to his house and made a fire. And he told everybody and said: “Behold I accompanied the ghosts, and we went to fight. Many of our fellows were killed, and many of those who attacked us were killed. They said I was hit, and I did not feel sick.” He told it all, and then he became quiet. When the sun rose he fell down. Something black came out of his mouth. His face became contorted. The people jumped up and cried. He was dead. (p. 65)

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In the original report, Bartlett (1932) provides examples of participants’ reproductions. Critically, these reproductions are not identical to the original but have been transformed in specific ways—they are shorter, use more words the participant is familiar with, and are more coherent of a story. Some participants were asked to reproduce it several times, with longer intervals, as opportunity arose. In one instance a participant was unexpectedly met again after six-and-a-half years and voluntarily reproduced the story, but in a written, bulleted form. The participant was quite satisfied with his recollection, though some details had incidentally been replaced with beliefs more in-line with the participant. Another participant was run into again ten years after the initial study. She had correct memory for many details, but had lost much of the story. MIN RE

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All of these cases, described in much more detail in Bartlett (1932) than I have summarised here, suggest that memory for the story is reconstructed from central details—far from being recalled verbatim even when tested just the next day. These findings have since been later replicated by Bergman and Roediger (1999) using a six-month delay. However, this concept of memory as a reconstruction, while seemingly not discussed before Neisser and Bartlett, had actually been acknowledged even earlier, though in a different literature.

The forgotten history of memory reconstruction While experimental studies have become more rigorous as we increasingly are able to articulate and rule out potential confounds, the use of naturalistic demonstrations cannot be understated in highlighting the relevance of these behavioural phenomena to real life, to situations that matter. The fallacies of memory—acknowledging the limitations and reconstructive nature—had been done earlier, in an essay itself called “The fallacies of memory” (Cobbe, 1867). Frances Power Cobbe, a 19th-century femninist philosopher, eloquently described the reconstructive nature of memory as well as any contemporary academic could. Though her work has not been acknowledged within the psychology literature and has largely been lost to time, there has been some recent appreciation of her work (Taylor, 2000; Stone, 2022). In “The fallacies of memory,” she wrote:

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Memories that matter We remember, not the things themselves, but the first recollection of them, and then the second and the third, always the latest recollection of them. A proof that this is so may be found by anybody who will carefully study the processes of his own mind, after he has once detailed at length, in words, any scene he has previously witnessed. He will find himself constantly going over precisely what he has narrated, and no more. […] We find, indeed, in our minds something which we call a remembrance, and which appertains in truth to the faculty of memory; but it reproduces, not the event it assumes to record, but that idea of it which, after twenty modifying repetitions, has left for the moment the uppermost trace in our minds. (Cobbe, 1867, pp. 104–105)

Cobbe’s words, written over a century and a half ago, resonate with the modern understanding of memory as a reconstructive process. She intuitively grasped what cognitive science has since confirmed: our memories are not static imprints but dynamic reconstructions. This perspective, while not discussed in psychology until decades later, has deep roots in our intellectual history. Cobbe’s insight underscores the fact that our understanding of memory, though refined and expanded by modern research, is not entirely new. It also serves as a reminder that the human fascination with memory, its mechanisms, and its quirks, is as old as our capacity for reflection. As an aside, it is unfortunate that the work of yesteryear is often lost to time. It may be unlikely for a young academic to come across a forgotten gem like this from 1867, but digital preservation efforts have made this work easily retrievable now. It is old enough to be easier to access than contemporary papers with their copyright restrictions. Many complain about the fast pace of current publications and difficulty in finding time to stay current, but really we need to know what has been done before to truly make meaningful advances in human understanding, not only narrow in our reading to see the seductive images of brain-imaging papers. I hope that you—the reader—are already aligned with this view, but prescient perspectives such as those from Cobbe make me pause and lament the limitations in what we knew then, and what we still have yet to understand. This historical perspective, however, provides a unique lens through which we can explore another fundamental aspect of memory: its role in imagination.

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1.5 Memory is the basis of imagination It is easy to find patterns in the past, but perhaps it is no ‘accident’ that the nine Muses are daughters of Mnemosyne. Many converging lines of evidence have emerged, connecting memory and imagination. Here is a brief excerpt from the beginning of J. R. R. Tolkien’s The Hobbit (1937): [The hole] had a perfectly round door like a porthole, painted green, with a shiny yellow brass knob in the exact middle. The door opened on to a tube-shaped hall like a tunnel: a very comfortable tunnel without smoke, with paneled walls, and floors tiled and carpeted, provided with polished chairs, and lots and lots of pegs for hats and coats—the hobbit was fond of visitors. (p. 1) Can you see the scene in your mind? Some people are unable to conjure mental visual imagery, otherwise known as aphantasia (more on this in Section 4.3, beginning from p. 108). Imagining this detailed scene relies heavily on semantic memory, to interpret these words into images, but also to fill in the details unsaid, based on what would be typical features (i.e., schematic knowledge). For instance, are the panelled walls made of wood? The wood must then also have a shade of how dark or light it is, and a texture. Memory is the basis of imagination, but imagination includes more specific aspects, such as scene construction (McGilvary, 1933; Furlong, 1948; Hebb, 1968; Schacter et al., 2008, 2012). Korsakoff (1889, 1996) noted that amnesic patients also exhibited more general impairments: This is why, after conversing at length with one of the patients, his initially striking perceptiveness and presence of mind seem somewhat deficient. We realize that: (1) the patient reasons by making use of old material, accumulated during a long period of time. Recent impressions have almost no role in his reasoning; (2) even with this old material, the patient makes only routine combinations and repeats phrases learned long ago; (3) the circle of ideas in which the patient’s intelligence moves becomes very restricted, and even this narrow frame, he always makes the same connections. (Korsakoff, 1996, p. 7) Building on this information, memory researchers found that similar cognitive and neurobiological processes were involved in remembering the past as imagining the future (Suddendorf & Corballis, 2007; Hassabis & Maguire, 2009; Addis & Schacter, 2012; Gilmore et al., 2016; Comrie et al., 2022). Given that episodic memory was already understood to be a reconstructive process, this may not seem too surprising. Indeed, memories of past experiences may even be necessary for imagining plausible future events, with past experiences

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being recombined to form a coherent future scenario. Future events likely also fit with learned schemas—if given the prompt, “imagine a trip to a beach in the summer,” there are certain objects and events you would expect to be present in the narrative response. This approach of asking for descriptions of personally relevant future events has come to be called episodic future thinking (Atance & O’Neill, 2001). In some ways, the connection between memory and mental time-travel is particularly apt here. Mental time-travel can occur in two directions—into the past is remembering, but into the future is imagination (Spreng & Levine, 2006; Botzung et al., 2008; Arnold et al., 2011; Schacter et al., 2012). Naturally one can remember only those things which have been encountered in the past. Conceptual objects, according to the foregoing account, consist of single items or groups of items which have been abstracted from past experience. Likewise imaginary objects and events are novel combinations of familiar items of previous experience. Let one imagine a tree as situated on the shore of a lake. Both lake and tree may be familiar items of experience, and hence their spatial combination constitutes the only novel feature of the imaginary object. The validity of the contention is quite apparent in such chimerical objects as a mermaid, a cat with horns, and a dog with wings. All inventions and products of creative thought are regarded as new combinations of the older materials of knowledge. Without prior perception, thought is impossible (Carr, 1925, p. 167) Surprising—to me at least—similar views have been held by philosophers for hundreds of years previous: Hobbes (1651): So that imagination and memory are but one thing, which for diverse considerations hath diverse names. Much memory, or memory of many things, is called experience. Again, imagination being only of those things which have been formerly perceived by sense, either all at once, or by parts at several times; the former (which is the imagining the whole object, as it was presented to the sense) is simple imagination, as when one imagineth a man, or horse, which he hath seen before. (In other words—you can only imagine things you first have memories of, both of which rely on perception first.) (pp. 5–6)

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Hume (1739): We find by experience, that when any impression has been present with the mind, it again makes its appearance there as an idea; and this may do after two different ways: either when in its new appearance it retains a considerable degree of its first vivacity, and is somewhat intermediate betwixt an impression and an idea; or when it entirely loses that vivacity, and is a perfect idea. The faculty, by which we repeat our impressions in the first manner, is called memory, and the other the imagination. ’Tis evident at first sight, that the ideas of the memory are much more lively and strong than those of the imagination, and that the former faculty paints its object in more distinct colours than any which are employ’d by the latter. When we remember any past event, the idea of it flows in upon the mind in a forceable manner; whereas in the imagination the perception is faint and languid, and cannot without difficulty be preserv’d by the mind steddy and uniform for any considerable time. (pp. 8–9) Vico (1744): imagination is nothing other than the resurfacing of reminiscences (p. 295) Additionally, in interpreting St. Augustine (399), Mourant (1979) stated: although we obviously cannot have a memory of the future as we do of the past and the present, memory is basic to any anticipation we make of the future (p. 24) Memory and imagination have been intertwined throughout history, as even Norse mythology reflects. Depicted with two ravens, Munin and Hugin, which represent Memory and Thought respectively, the god Odin would send them out each day to gather information and return with knowledge (Orchard, 1997). This mythological depiction symbolises the connection between memory and the creative process of imagination. Cobbe (1872) also discusses a surprisingly analogous distinction between memory and thought, though does not include any explicit connection to Norse mythology. MIN RE

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FIGURE 1.3: Example of boundary extension and contraction. Adapted from Bainbridge and Baker (2020). Returning to contemporary times, beyond brain-imaging studies that had indicated the involvement of memory-related regions in imagery, convergent behavioural evidence has also been found. For decades it has been suggested that remembered scenes are distorted such that people ‘zoom’ out and extrapolate the scene, seeing more than was actually present—a phenomenon known as boundary extension (Intraub & Richardson, 1989; Gottesman & Intraub, 1999; Intraub & Dickinson, 2008). Despite the relatively consistent evidence for extension, a recent study has shown that boundary contraction is also common (Bainbridge & Baker, 2020), demonstrating that the effect is contingent upon the composition of the scene. Boundary extension occurs when the scene only has a few central objects. However, when several dispersed objects are present in the scene, boundary contraction occurs—as shown in Figure 1.3. This dynamic demonstrates the automatic access and application of our schema information. This information enables us to not only interpret the immediate scene but also to extrapolate beyond the given boundaries, even unintentionally. This extrapolation might be an essential part of our cognitive machinery, allowing us to create a coherent and continuous perception of our environment even when our visual field is limited. Together, the effect is then a sort of boundary normalisation. Furthermore, this process can be conceptualised as an interplay between memory and imagination. Our past experiences (memory) fuel our ability to predict or imagine what lies beyond the visible scene. On the other hand, boundary contraction might be seen as a cognitive adaptation, enabling us to focus and recall key elements in a complex scene more efficiently. In this view, memory and imagination are not discrete cognitive functions but part of a continuum that helps us navigate and make sense of our world. This research underscores the complexity and flexibility of our perceptual and cognitive systems, demonstrating that our perception of the world is a construct of both what we see and what we expect to see. An extension of the notion of memory being the basis of imagination is the case of confabulation. Conventionally, confabulation is a neuropsychological symptom of a disruption to episodic memory, where memories are distorted or fabricated, without any conscious intent to deceive (Berlyne, 1972; Dalla Barba, 1993; Dalla Barba et al., 1990, 1997, 1999; Berrios, 1998; Borsutzky et

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al., 2008). The phenomenon of confabulation can be seen as a byproduct of the brain’s inherent need to maintain a coherent narrative or self-identity. When faced with gaps in memory, the mind—in an attempt to maintain continuity— fills these gaps with fabricated information that aligns with the individual’s self-concept or expectations of the world. This is not deliberate and is not intended to deceive others, rather it is an unconscious effort to reconcile the discontinuity in one’s memory. However, if we were to consider the underlying process more broadly, it could be considered as an ad-hoc justification when memory cannot fill in the blank—an error of commission (Dalla Barba et al., 1997; Coltheart, 2017; Bergamaschi Ganapini, 2020; Stammers, 2020). This process is similar to the phenomenon of boundary extension, where our brain extrapolates beyond the given information available in the scene. In this way, confabulation could be considered as the use of semantic knowledge— particularly schemas—in a manner not too different than imagination, but also false memories (Johnson & Raye, 1998; Ciaramelli et al., 2006; Mason et al., 2022). Further, this unintentional and everyday confabulation shows that memory is influenced by our expectations and beliefs—memory is not a passive repository of information but an active, constructive process.

On the importance of memory I hope you are convinced that memory is special and worth thinking about more deeply. I have recently found my own view aligns well, though not as eloquently expressed, as one from nearly 150 years ago: Unless the mind possessed the power of treasuring up and recalling its past experiences, no knowledge of any kind could be acquired. If every sensation, thought, or emotion passed entirely from the mind the moment it ceased to be present, then it would be as if it had not been; and it could not be recognized or named should it happen to return. Such an one would not only be without knowledge,— without experience gathered from the past,—but without purpose, aim, or plan regarding the future, for these imply knowledge and require memory. Even voluntary motion, or motion for a purpose, could have no existence without memory, for memory is involved in every purpose. Not only the learning of the scholar, but the inspiration of the poet, the genius of the painter, the heroism of the warrior, all depend upon memory. Nay, even consciousness itself could have no existence without memory for every act of consciousness involves a change from a past state to a present, and did the past state vanish the moment it was past, there could be no consciousness of change. Memory, therefore, may be said to be involved in all conscious existence—a property of every conscious being! (Kay, 1888, pp. 2–3)

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End of chapter wrap-up Summary Memory, a cornerstone of our cognition, is more than a system for recalling facts or experiences; it is an integral part of our identity, shaping our actions, decisions, and our anticipations for the future. In this chapter we discussed the background topics to situate our understanding of memory. These included its importance in society and the rich vocabulary developed to describe its processes. While many analogies are used to understand memory, considering it as a recording is particularly pervasive, but also limited in relevance. Memory is not verbatim, but rather is reconstructive. This was highlighted using the case of John Dean’s memory during the Watergate scandal. The relationship between memory and imagination is also profound, with past experiences being recombined to form coherent future scenarios. Throughout the chapter, we see that memory is not a simple storage system but a dynamic process that is constantly being updated and revised. As we will continue to see, memory is not just about understanding how we remember things, but the foundation for how we think, perceive, and construct our reality.

Reminder cues

These pictures are intended to remind you of concepts discussed in the chapter. Can you remember what ideas correspond to each picture?

Quick quiz 1. As a language teacher, you understand the importance of memory in learning new vocabulary. Which of the following strategies would likely be the least effective in helping your students remember new words? (a) Ask students to list the new words along with their translations in their native language. (b) Encourage students to create a story with the new words, in which the words play a crucial role in the plot. (c) Have students write each new word in a sentence that relates to their recent experiences. (d) Use the new words in surprising but relevant contexts during class to catch the students’ attention.

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2. If we were to integrate the analogies of a treasure chest and a garbage can in describing memory, how might these work together? (a) Memories are like treasures, each one precious and unique, but over time, they get mixed up and lost among the ‘garbage’ of irrelevant details and newer memories. (b) Memories are treasured and carefully stored away, but as with a garbage can, the contents are not always easily differentiated or accurately retrieved, leading to false memories. (c) Each memory is a treasure, stored in a vast beach of our minds. However, like a garbage can, the order of these treasures is stored in a disorganised pile. (d) The treasure chest represents our precious, significant memories but they are hard to retrieve, like finding a specific item in a garbage can, which represents the unreliable nature of memory retrieval. 3. A friend who is studying for an exam tells you they wish their memory worked like a video camera so they could recall all the material verbatim. How could you respond based on your understanding from this section? (a) You agree with them, noting that human memory indeed works like a video camera. (b) You suggest they use mnemonic strategies or other memory aids, noting that memory is not a verbatim recording but rather a reconstruction that can be influenced by various factors. (c) You tell them that their wish is impossible because the human brain has a limited storage capacity. (d) You advise them to get more sleep, as sleep is known to improve memory recall. 4. Based on the analogy of a palaeontologist reconstructing a dinosaur, how might we expect a person’s memory of a recent vacation to change over time? (a) The memory will become more accurate and detailed, like a palaeontologist finding more fossils. (b) The memory will remain mostly unchanged, like a dinosaur skeleton in a museum. (c) The memory may be intermixed with elements of other experiences, like a palaeontologist attempting to reconstruct a dinosaur with fossils from multiple species. (d) The memory might become less detailed or altered, as the person reconstructs the event based on their current knowledge and feelings.

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Memories that matter 5. You’re asked to imagine your perfect birthday party. Which type of memory is primarily used to construct this mental image? (a) Episodic memory, as you’ll use memories of past birthday parties. (b) Semantic memory, as you’ll use general knowledge about what can occur at a birthday party. (c) Both episodic and semantic memory, as you’ll use personal memories and general knowledge to create a plausible scenario. (d) Neither episodic nor semantic memory, as this is a task of imagination.

The answer key for all end-of-chapter quizzes can be found immediately after the Conclusion chapter, beginning from page 467.

Thought questions ▶ Are you surprised that the general public agreed with the video camera statement? How does this myth affect society at large? ▶ What is your favourite analogy of how memory works? What features does it capture, and what are some limitations? ▶ Do you have memories that you remember vividly? Are you certain they are accurate? Was there someone else there that you can discuss the memory with? Or, better yet, if you kept a diary or journal, how does your recorded version compare with your memory? Thought questions are included at the end of each chapter. They are related to content discussed in the chapter, but are intended to make you think beyond what was presented here. There is no definitive correct answer; in some cases it would be helpful to find additional sources.

Online resources Online resources are available for each chapter: https://engra.me/books/ memoriesthatmatter/resources/. These resources are primarily videos related to the concepts discussed in each chapter, intended to help make lectures more engaging or be suggested as optional supporting resources. While these are provided for every chapter, I only note their availability here and on pages xxv and 465.

River of moments, Echo in our memory, Forever persist.

Part II

Fundamentals

Chapter 2 Considering the functional purpose

…literal recall is extraordinarily unimportant — Frederic C. Bartlett (1932)

Memory is a net; one finds it full of fish when he takes it from the brook; but a dozen miles of water have run through it without sticking. — Oliver Wendell Holmes (1858)

In the early days of psychology as an academic discipline, structuralism and functionalism emerged as two major schools of thought (Surprenant & Neath, 1997). Structuralism, primarily championed by Edward Titchener, a student of Wilhelm Wundt, aimed to understand the structure of the mind by dissecting mental processes into their most basic components. This approach was prominent in the late 19th and early 20th centuries, up until the 1930s (Titchener, 1898). Functionalism, advocated by William James and influenced by Charles Darwin’s theory of natural selection, focused on the purpose of mental processes, specifically how they contribute to adaptation to one’s environment (James, 1890; Angell, 1907; Carr, 1925; Bartlett, 1932). These initial schools of thought were eventually superseded by new psychological perspectives. By the 1920s and 1930s, behaviourism, led by figures like John Watson and B. F. Skinner, rose to prominence (Watson, 1913; Skinner, 1938). Behaviourism focused on observable behaviours, rejecting the introspective analysis of the mind characteristic of both structuralism and functionalism. By the mid-20th century, the cognitive revolution had begun, leading to the emergence of cognitivism. Championed by Ulric Neisser and Noam Chomsky, cognitivism redirected psychology’s focus back towards internal mental processes, such as thinking, memory, and problem solving, but with a more empirically rigorous approach than that of structuralism or 29

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functionalism (Moore, 1939; Neisser, 1967). Around the same time, another influential perspective known as constructivism emerged. Constructivism posits that learners actively construct knowledge and understanding through experiences and reflection. Influenced by the work of scholars such as Jean Piaget and Lev Vygotsky, constructivism emphasises the learner’s active role in the learning process, rejecting the idea that knowledge can be passively received (Piaget, 1954; Vygotsky, 1978). This perspective has significantly influenced fields like education and cognitive development, underscoring the importance of both individual and social processes in learning. Since the latter half of the 20th century and continuing to the present day, constructivism has been a dominant force in psychology. As we delve into the purpose of memory, it’s important to remember the historical context that has shaped our current understanding. Early on, periodic review papers were able to summarise the incremental sets of findings every few years (Robinson, 1924; McGeoch, 1928, 1930, 1934; Grant, 1932). However, this became less practical as the literature on memory continued to expand. Most discussions of memory’s fundamentals focus on the structure (i.e., taxonomy)—we can return to that later (i.e., Chapter 3). Here let’s begin with a more functionalist view: What is memory for? As discussed last chapter with the passages from Richards (1920), this question and approach is generally not the focus of memory research in experimental psychology. Even though this question may appear simplistic, unfortunately, it is still difficult to answer and can be interpreted in multiple ways. We could be asked about the evolutionary pressures that led to the development of memory (i.e, phylogeny), such as those that led to the development of multiple memory systems (Sherry & Schacter, 1987; Klein et al., 2002)—the notion that multiple brain systems underlie learning and memory in parallel, each optimised for a different type of learning. That is valuable and is especially useful when considering variations in memory function across species (Mayr, 1961; Tinbergen, 1963; Mayes, 1983; Oakley, 1983; Bruce, 1991; Conley, 2020). Another interpretation is to think of the function of memory more mechanistically, as a means to bridge between perception and action (Anderson, 1996; Glenberg, 1997). Alternatively yet relatedly, memory could be viewed as a way for us to consciously re-experience the past (Klein, 2015). Yet another view, is to consider the function of memory within a naturalistic or an ecological context, focusing on how memory is used in present-day society. Even then there is contention as to how a broader theory of memory would be developed (Neisser, 1978, 1985b; Bruce, 1985a, 1985b, 1989). Somewhat distinct from this is the goal of understanding how memory has developed for past real-world situations (Nilsson, 1979, 1987; Scribner & Beach, 1993; Nairne, 2005; Nairne & Pandeirada, 2008, 2010; Otgaar et al., 2023). These last two approaches are the closest to that emphasised in the current book—what memory has evolved for and how it is important to day-to-day life now—though some perspectives aligned other interpretations will also be intermixed.

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Neisser (1978) had said: “It is an example of a principle that is nearly as valid in 1978 as it was in 1878: If X is an interesting or socially significant aspect of memory, then psychologists have hardly ever studied X.” (p. 4). This increasing emphasis in the 1970s and 1980s on applied memory research had a direct relationship to the establishment of the journal Applied Cognitive Psychology in 1987. The function of memory is still very much a topic of debate (Mahr & Csibra, 2018; Sant’Anna & Michaelian, 2018; Schwartz, 2020; Boyle, 2019, 2022; Ménager et al., 2022). Unsurprisingly, this strong emphasis on understanding memory within everyday situations, rather than controlled experimental studies, was contentious at the time. In particular, a perspective article by Banaji and Crowder (1989) entitled “The bankruptcy of everyday memory,” created quite a stir at the time, eliciting over a dozen follow-up commentaries and further discussions (also see Koriat & Goldsmith, 1996). As this debate occurred thirty years ago, one might think researchers have since resolved this dispute, however, a nearly identical lamentation has only just been made of decisionmaking studies (Weiss & Shanteau, 2021). Here I focus on a holistic approach, drawing examples from both everyday, naturalistic studies of memory as well as experimental ones. Taken as a whole, and with a more developed literature to draw from than existed in the 70s or 80s, I find that there is a wealth of converging evidence for memory mechanisms and underlying principles. For our exploration, let’s begin with the day-to-day practicalities: How do we use memory in everyday life? How is memory interwoven into daily behaviours, even when not directly being assessed? Growing up, children—as students—are tested frequently in school exams and assignments. These are highly dependent on memory of subject content and sometimes also knowledge of algorithmic rules (e.g., mathematics), and performance could be aided by memory strategies (see Chapter 11), however let’s fast forward to adulthood. Here we will consider a simple task and some events that may occur along the way: walking from home to a nearby grocery store, purchasing a few items, and then returning home. What are some of the instances where memory will be relevant and what can prior research tell us about these everyday memory occurrences?

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2.1 Memory for everyday events You leave your house and walk for several blocks, inevitably you need to cross an intersection. What comes to mind when you see the picture shown in Figure 2.1A?

FIGURE 2.1: Imagery of the Ampelmännchen. (A) Ampelmännchen icon. (B) Photo of Ampelmännchen on a traffic light, with Karl Peglau. Credit: With the kind permission and support of AMPELMANN GmbH, www.ampelmann.de. Clearly it is a man wearing a hat. Based on the pose, and some additional context (see Figure 2.1B), you may think of a pedestrian traffic light. These are all true, but to some people, this same visual cue will lead to the retrieval of much more information. Traffic signals vary in different parts of the world, but, of course, you know where you are currently. Designed by Karl Peglau, a traffic psychologist, in the 1960s for use in Eastern Germany, these traffic light symbols were not as minimalist as they are in many other parts of the world. Instead, this traffic light man, or Ampelmännchen, was designed to be both likeable as well as functional (Duckenfield & Calhoun, 1997; Moran, 2004; Ampelmann GmbH, 2016). Today the iconic symbol is still used and is a popular souvenir item of Berlin and regions of Germany (e.g., as a keychain or printed on clothing), and has even been adopted in portions of formerly western Berlin (Milman, 2012; Pan, 2013; Ampelmann GmbH, 2016). While you may not be in Germany and facing as iconic a pedestrian traffic sign, other signs may cue rich semantic representations. For instance, depending on the time of year, you may see Christmas or Halloween decorations (Berger & Fitzsimons, 2008).

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You continue into the store and find the aisle where the juice is on display.

FIGURE 2.2: Selecting juice from a store display. (A) Photo of a grocery store shelf. (B) Original and redesigned Tropicana carton. Here you will see a near endless number of options for drinks—similar to the view shown in Figure 2.2A. Naturally you will look for something familiar, a brand you know. In 2009, Tropicana changed from its original design to a more modern design, as shown in Figure 2.2B. The original design featured the brand’s iconic image of an orange with a straw in it. In contrast, the redesign was less distinct from other brands and changed the relative emphasis on different aspects of the text—e.g., the “100% orange” became much more prominent. The change was not well received and sales dropped by 20%. About two months later the company announced a return to the original design (Young & Ciummo, 2009; Kirk & Berger, 2011).

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While those working at Tropicana likely had gotten bored with the original design, this is what customers were familiar with. Brand familiarity is important to memory and choice (Mantonakis et al., 2008; Samu & Krishnan, 2010). Moreover, cognitive, emotional, and conditioning processes need to be considered when evaluating a potential change to brand identity (Rothschild & Gaidis, 1981; Janiszewski & Warlop, 1993; van Osselaer & Janiszewski, 2001; Peterson et al., 2015). Campbell Soup Co.’s can design is similar, if not even more iconic. The familiar red-and-white label was first used in 1898, but was later refined by Andy Warhol in 1962 (Frye, 2015). Nonetheless, changes have been periodically evaluated (Eastlack & Rao, 1989; von Hahn, 2017). Many other companies have changed their logos over the years, some with reversions after public backlash—such as Gap (2010, one week to revert), Leeds United Football Club (2018, not even 24 hours), and Kraft foods (changed in 2009, reverted back in 2012). Other changes have persisted, such as Pepsi’s infamous 2008 rebranding. While the Pepsi logo retained some characteristics of the previous version, a 27-page design proposal later propagated throughout the internet that was quite—grandiose. Some speculated that the document was a hoax or part of a viral marketing campaign, but this does not appear to be the case—it was genuinely created to convince the Pepsi executives (Parekh, 2009). Both the Tropicana and Pepsi logo changes were developed by the same marketing company. After a decade and a half, Pepsi changed its logo again in 2023, now more similar to the variations from the 1960s to the 1990s, intended to capitalise on feelings of nostalgia. Original logos ideally need to be distinctive. Logo changes can be useful when a company changes priorities, but needs to be done with care to not carelessly discard its established brand identity familiarity. Some redesigns have been improvements—though still were unveiled to negative reception, including airbnb (changed in 2014), Duolingo (2013), Google (2015), Instagram (2016), and Slack (2019). You stop by the aisle where the kitchenware is located. Memory for brands can also relate to product expectations. For instance, for many decades Pyrex glass cookware has been known to be particularly resilient to temperature changes, unlike other types of glassware. However, in 1998 the company largely changed from using borosilicate glass—the resilient one—to a different type of glass, made from soda lime. This change had not been broadly publicised. As a result, many news reports in the 2000s covered the surprising breakage of Pyrex cookware. Complicating matters, some glassware items are still made of borosilicate, depending on where they were manufactured. So now these two types are currently manufactured despite their varying properties. The printing of the logo on the item is not indicative of the composition. One way to tell which type of glass a particular item is made from is by examining the edge of the glass; soda-lime glass will have a blueish-green hue, while borosilicate has no colour. The soda-lime glass

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is still good cookware, however it challenges our previous assumptions of how a Pyrex glassware item can be treated. You continue your shopping and reach the section of the store with the wine. Pleasant music draws you in and you decide to consider adding a bottle to your shopping basket. Even without your conscious attention, cues around you can influence your choices. North et al. (1997, 1999) examined how in-store music can influence wine purchases. Across two separate weeks, either French or German music was played in a supermarket. A set of four wines from each country was selected and matched for price and sweetness. Position on the shelf was also alternated within each week. If customers chose one of the eight an experimenter—posing as a customer—asked the customer follow-up questions. Of the 44 customers that consented to the questionnaire, only six responded “yes” to “Did the type of music playing influence your choice of wine?” More bottles of French wine were purchased in the week with French music playing, while more German bottles were bought when the German music was playing. This finding has been replicated and extended over the subsequent years (Wang & Spence, 2015; Reinoso Carvalho et al., 2016; Hsu & Chen, 2020). Additionally, being told that wine is more expensive leads to greater experiences of enjoyment (Plassmann et al., 2008; Schmidt et al., 2017; Werner et al., 2021). You complete your shopping and reach the checkout counter. You decide to pay with cash. In other cases, memory for everyday objects can be quite poor, especially for detailed information. Do you think you could reproduce the imagery and text shown on local currency? In the 1980s and 1990s, memory researchers in several countries examined people’s memory for details of local currency (Nickerson & Adams, 1979; Rubin & Kontis, 1983; Jones, 1990; Jones & Martin, 1997; Kikuno, 1991, 1993). Arguably, the text and specific picture details on coins are not relevant. In contrast, the details of a bicycle’s structure are all relevant to how it works. Lawson (2006) asked people to draw a bicycle—frame, pedals, chain, and wheels. A recognition version of the test was also conducted. Those with more cycling experience tended to make fewer errors, but errors were still quite common. Errors related to the chain were the most frequent. While coins and bicycles are common objects, it is possible that people do not look at them closely very often. In contrast, logos for popular brands are much more common and without as much nuanced detail.

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Memories that matter On the way home you pass a Starbucks coffee shop.

In 2017, signs.com conducted a study with the general public, where 156 adults (aged 20–70 years old, mean of 34; 50% women) in the US were asked to draw logos of ten popular brands. The brands examined were Apple, Adidas, Burger King, Domino’s, 7-11, Foot Locker, Starbucks, Walmart, Target, and IKEA. While this was not a peer-reviewed study, the methodology was nonetheless quite rigorous, with the experiment session taking approximately 30 minutes, including training to use the drawing software, drawing of the ten logos from memory, self-perceived ratings of accuracy (on a scale out of ten), and questions about engagement with the brand. All of the over 1,500 drawn logos were subsequently rated for accuracy by a panel of five design and marketing professionals, based on the drawn logos’ features, proportions, and colours. Figure 2.3A shows the Starbucks logo over the years; all 156 drawn reproductions of the logo from memory are shown in Figure 2.3B. From the scoring reported by the independent professionals, 6% of the participants produced near-perfect drawings, while 31% drew the older logo with the brand name in the logo; 55% of participants drew the mermaid in the logo, but did not include the tail; 45% instead forgot the crown. Of the ten logos, the Starbucks logo had the second lowest rating of selfperceived accuracy (Foot Locker was the lowest), but also had one of the lowest degrees of overconfidence (i.e., difference between self-perceived accuracy and professional-rated accuracy). Towards the other end of the range, the Apple logo had the second highest rating of self-perceived accuracy (Target was the highest), but demonstrated the greatest degree of overconfidence. Here 20% of participants produced near-perfect drawings. For 16% of the participants, the apple bite was missing; 22% had the bite on the wrong side. Other errors included 25% forgot the leaf and 31% drew a stalk (also see Blake et al., 2015; Prasad & Bainbridge, 2022; Whatley et al., 2023). A follow-up study was conducted examining memory for logos of 32 American football teams in the NFL (National Football League), drawn by 157 people (signs.com, 2018). You return home and before putting away your purchased items, glance at a few items left on your coffee table. You see a small Eiffel Tower snow globe, a postcard from a friend, and a small desk toy representing one of your favourite TV characters. These items, these fragments of your past, are more than mere objects. They are physical embodiments of your experiences, tangible pieces of your memory that you can hold in your hands. They are not just souvenirs, they are stories, each one a chapter in the book of your life. The Eiffel Tower snow globe, a memento from a trip to Paris, stirs up a flurry of memories with each shake. The postcard, a simple piece of cardstock, carries with it the warmth of a friend’s words and the memory of a shared bond. The desk

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FIGURE 2.3: Memory for the Starbucks logo from the signs.com (2017) study. (A) Changes to the Starbucks logo over the years. (B) Drawings of the logo from memory for all 156 participants, sorted by actual accuracy (organised with lowest accuracy in the top-left). Credit: signs.com (www.signs.com/ branded-in-memory/).

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toy, a miniature representation of your favourite TV character, is a testament to the hours spent immersed in a fictional world, a world that brought you joy, comfort, and perhaps even a sense of belonging. (NB. ‘souvenir’ in French means remembrance or recollection.) As a complementary anecdote, I bought a souvenir keychain from the city of the first conference I attended. I continued to do this for each conference I attended during my PhD studies, connecting them in order. This has since been a lovely way to reminisce about past conferences, my growth as a researcher, and the friends I have made along the way. Nostalgia, a longing for the past, is a powerful emotion (Hofer, 1688). It can be triggered by the smallest things—a scent, a song, a souvenir—transporting us back in time, reliving moments of joy or sadness (Holbrook, 1993; Holbrook & Schindler, 2003; Lasaleta et al., 2014; Chen et al., 2023). It is a testament to the power of memory, its ability to make us feel, to make us remember. MIN RE

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Returning to the academic literature, souvenirs are a physical accompaniment to experiential purchases—bridging the divide of experiential vs. material purchases (see Van Boven & Gilovich, 2003; Gilovich & Gallo, 2020)—a topic discussed at the end of this chapter. You can spend money on a movie or a vacation, with souvenirs being a commemorative soda cup, keychain, or stuffed toy (Gordon, 1986; Hwang et al., 2018; Sthapit, 2018; Puente-Díaz & Cavazos-Arroyo, 2022). An interviewed participant stated: “The thing that I consider when buying souvenirs is if it’s unique and something that I can only find in that particular place. I don’t prefer souvenirs that are mass-produced. I like something quite unique” (Sthapit, 2018, p. 130). Souvenirs can have important roles in representing our identity, past, and what is important to us (Riggins, 1994; Haldrup & Larsen, 2010; Haldrup, 2017). Moreover, Riggins (1994) suggests: domestic artifacts are more likely to serve as entry points for the telling of stories about the self and its personal relationships. All such content will be referred to as mapping, meaning by this that the self uses the displayed objects (gifts, heirlooms, photographs, etc.) as a way of plotting its social network, representing its cosmology and ideology, and projecting its history onto the world’s map, its spatial spread so to speak. This is indeed what objects are—dots on a map and connecting links which can be retraced in any direction. (p. 109)

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Before we end this adventure, let us do one more action. Among the various items, there lies a book you recently read. As you pick it up, you are immediately drawn into its world, the characters, the plot, the emotions all coming back to you. This, too, is memory at work. It allows us to immerse ourselves in narratives, to remember and understand them, to connect with them on a deeper level.

2.2 Story narratives Have you been reading any other books recently? If you were interrupted, or simply took a break, you likely have little difficulty resuming at a later time and getting back into the narrative. Beyond the role of memory in everyday life, memory is integral to our ability to maintain and understand narratives. Studies have shown that people remember stories in ‘chunks’ (Thorndyke, 1977; Black & Bower, 1979; Mandler, 1984; Goldman & Varnhagen, 1986). That is, stories are not remembered as sets of words or sentences, but rather as units of goal-oriented episodes. Chunking as a concept, however, is more general and is the basic unit of information being cognitively processed. This will be an idea revisited throughout this book. Moreover, chunks can often occur in a predictable sequence, like a script. Bower et al. (1979) provides an example of visiting a restaurant, where there are four overall ‘scenes’ to the event: entering, ordering, eating, and exiting. Each scene has several steps within it, effectively the chunks. For instance, ordering involves picking up the menu, looking at the menu, making a decision, signalling to the restaurant staff that you are ready to order, etc. While this example may not seem sufficiently relevant to a story narrative, it lays the groundwork for these more complex topics (Schank & Abelson, 1977; Owens et al., 1979; Whaley, 1981; Hudson & Nelson, 1983; Komeda et al., 2013). Being provided with concrete statements has been shown to be more useful in remembering story events than being provided with character names (Neisser & Hupcey, 1974). Many stories and movies follow a ‘hero’s journey,’ first proposed in 1949 (Campbell, 2008). Based on this model, stories include at least 12 stages, beginning with the ‘call to adventure,’ ‘refusal of the call,’ and ‘meeting the mentor.’ Each stage of the hero’s journey represents a ‘chunk’ within the narrative; this can also be thought of as a schema—a concept we will discuss throughout this book. Moreover, stories typically have one of six different emotional arcs, based on the general trajectory and fluctuations (Vonnegut, 1965, 1981; Reagan et al., 2016; Toubia et al., 2021; Konstantopoulos, 2023). Our ability to see parallels across narratives relies on memory, as does our ability to maintain an understanding of the on-going unfolding of events (Brom et al., 2007; Boyd et al., 2020; Yang et al., 2022). Even more nuanced, memory is necessary to understand the state of mind of what a character may not know, but has been shown to the reader.

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Long and Prat (2002) developed a knowledge test based on the TV show Star Trek. Here memory was assessed based on recognition of key facts, rather than a sequence of events. Other studies have examined knowledge related to Star Wars (Means & Voss, 1985) and Tolkien’s Lord of the Rings fictional world (Louwerse & Benesh, 2012), among other fictional works (Neisser & Hupcey, 1974; Wilbers et al., 2012; Brown & Shi, 2017; Troyer & Kutas, 2020; Yang et al., 2022). These studies nonetheless provided insight into how recognition memory can be tested based on semantic knowledge, and that this knowledge can be gradually acquired over tens to hundreds of hours without deliberate study. MIN RE

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Beyond having our own memories, we also learn the life stories of those close to us. For instance, those in a romantic relationship will have their own personal story as well as a version of their partner’s life story (Panattoni & Thomsen, 2018). Analyses comparing these two narratives may be useful in understanding how well the couple relate to each other (Bradbury & Fincham, 1990; Halford et al., 2002; Catal & Fitzgerald, 2004; Alea & Vick, 2010; Harris et al., 2014). Memories can, of course, also be shared in other social situations as well (Hirst & Echterhoff, 2012; Hirst & Manier, 2008; Brown et al., 2015; Jalbert et al., 2021). While narratives often rely on our memory to be understood and enjoyed, it’s also important to consider how memory relates to our judgement of truths and lies.

2.3 Truths and lies Most hope the justice system works on transparent and easily understood principles, those being “If you did a crime, you did the time. If you were innocent, you went free” (Brown, 1990, p. 2). However, this is not always the case—in some instances, coincidences, along with incorrect eyewitness testimony, have resulted in failures in the justice system. Such a travesty is exactly what Joyce Ann Brown experienced, spending nearly a decade in jail after a wrongful conviction that was made, at least in part, due to eyewitness testimony. Münsterberg, a pioneer in applied of psychology, said: “Justice would less often miscarry if all who are to weigh evidence were more conscious of the treachery of human memory” (1908, p. 44). From the other side, the perpetrators of a crime often have knowledge of the incident that an innocent individual would not. This premise lays that foundation for lie detection.

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Eyewitness memory Donald Thomson, a native of Australia, moved to Canada to work with Tulving and study memory (Tulving & Thomson, 1973). Later he returned to Australia and continued studying memory, and in particular, became interested in limitations of eyewitness memory. In an ironic twist of fate, Thomson was arrested in 1975 as a suspect in a rape case, owing to the victim’s precise description that matched him. However, Thomson had an irrefutable alibi; he was on live television at the time of the crime, discussing the fallibility of memory, along with a regional chief of police. The victim had seen the show during the incident and had misattributed Thomson’s involvement. Thomson was promptly released, though the true perpetrator was never arrested. In some cases, DNA evidence or fingerprints are not possible to find, such as in the case of a drive-by shooting. Eyewitness testimony may be all that’s available in cases such as this, and may be influenced by biased or coercive police interview practices. In the past, eyewitness training was a requirement and even then, established recommendations are not always followed—for instance, interrupting the witness or providing feedback after an identification can reinforce that choice as being correct (Wells & Olson, 2003; Douglass et al., 2010; Compo et al., 2012). After an incorrect identification is made, recanting it may not be truly possible as the motivations for doing so can be questioned. These are the circumstances of Franky Carrillo’s wrongful conviction for the 1991 murder of Donald Sarpy, only cleared after serving 20 years in prison (Graves, 2019). Other instances of incorrect eyewitness identification have also been examined in detail, often also revisited using DNA evidence (ThompsonCannino & Cotton, 2009; Murray, 2015; West & Meterko, 2016). Thankfully, witness interview practices have improved over the years (Fisher et al., 1989; Fisher & Geiselman, 1992; MacDonald et al., 2017; Dodier et al., 2021). MIN RE

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Yuille and Cutshall (1986) interviewed 13 real eyewitnesses to a violent shooting incident. Initial interviews with witnesses occurred shortly after the event by police, and again by researchers 4–5 months later. Overall, the witnesses were highly accurate in their accounts, with about 80% of details recalled correctly in both interviews. This high accuracy persisted over the months of delay, indicating that memory for salient events are more resilient to forgetting. Moreover, witnesses who were more directly involved in the incident recalled it with 93% accuracy compared to 75% for less involved witnesses. This suggests active involvement may improve real eyewitness memory. Less

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event-relevant information—like clothing colour and age/height estimates— were recalled less accurately, but descriptions of actions and objects were more accurate. Christianson and Hübinette (1993) interviewed 58 witnesses of 22 different bank robberies, including victims (bank tellers) and bystanders (employees and customers). The witnesses were interviewed 4–15 months after the robberies about their memory for details and their emotional reactions. Recall was compared to police reports to assess accuracy. Results were generally consistent with those reported by Yuille and Cutshall (1986). Work by Crombag et al. (1996) provides additional insight into memory for untimely events. In 1992, a cargo plane crashed into a residential building in Amsterdam. The incident was covered extensively in the news over several days, but no footage was recorded of the actual crash—though TV crews had arrived later and filmed the building ablaze being fought by firefighters. In the study, a sample of university students and staff answered a questionnaire about the incident ten months after it had happened. Here the critical question embedded in the questionnaire was “Did you see the television film of the moment the plane hit the apartment building?” with the only available responses as “yes” and “no.” If the participant answered “yes,” they were asked to answer a set of follow-up questions, including “After the plane hit the building, there was a fire. How long did it take for the fire to start?” Of the participants, 55% reported seeing the crash happen, and of those, 82% responded with an estimate of when the fire started. There was no recording of the crash, as it happened suddenly and no filming would have been possible (also see Greenberg, 2004, for a similar remembered impossibility). These findings were replicated in a second study reported in the same paper, which included additional questions about the crash. Results were consistent. Loftus and Palmer (1974) conducted a foundational study in demonstrating that memory interviews can be flawed if leading questions are used. In the first experiment, participants watched seven video clips of car accidents, each followed by a series of questions. Critically, five groups of participants were each provided with a different phrasing of a target question: “About how fast were the cars going when they hit each other?” was asked of one group. For the remaining four groups, “hit” was swapped with “contacted,” “bumped,” “collided,” or “smashed.” After this target question, participants were also asked to estimate speed of the cars in the collision. Based on the phrasing, participants estimated faster car speeds, ranging from 31.8 mph (contacted) to 40.5 mph (smashed). In a second experiment, an analogous design was used, but with only three groups—hit, smashed, and a control group with this question absent. This study included a second session one week later, with an additional series of questions. In this set was the critical question, “Did you see any broken glass?” at the scene of the accident. The video had no broken glass, but the researchers predicted that participants who were given the earlier phrasing with “smashed” would be more likely to falsely respond “yes” to this question; 32% of the participants in the smashed group did respond yes, compared to 14% in the hit group, and 12% in the control group. Furthermore,

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those who provided higher speed estimates (one week prior) were more likely to say they saw broken glass. This finding not only demonstrated that the wording of questions influences a person’s memory of an event, but also can create false memories. This research has had significant implications for legal systems, as it raises questions about the reliability of eyewitness testimony and the potential for leading questions to distort witnesses’ memories during investigations and trials. Later studies have further investigated how question phrasing may influence memory reports, though some studies have indicated that the effect does not always generalise depending on the specifics of the questions used (Loftus & Zanni, 1975; Read et al., 1978; Dodd & Bradshaw, 1980; McAllister et al., 1988; Goldschmied et al., 2017). While actual car accidents are quite memorable, not in the least because of how they affect life afterwards, near-accidents are quite readily forgotten (Chapman & Underwood, 2000). In this study, participants recorded information about near-accidents after each journey over the course of a year. Across the 80 participants (aged 17 to 30), over 400 near-accidents were recorded. Memory did scale with near-accident severity, such that a greater proportion of later recalls were for more dangerous near-accidents and where the participant was more at fault for the incident (also see Wagenaar, 1992). However, overall recalls were quite low. A limitation of this study was that participants only participated in the study at three intervals; at each point they were asked to recall events for the two weeks prior and then record each journey over the subsequent two weeks. As such, the recalled and recorded events correspond to different time periods and do not correspond to the same instances and frequencies when compared. However, this also rules out the possibility that recalled events were more likely to be recalled because they were previously recorded, as these were different events. There are a number of other critical eyewitness memory studies. Studies focused on ‘flashbulb memories,’ particularly emotional and salient experiences, are discussed in Section 6.1 (p. 159). In general, eyewitness memory studies have demonstrated that our memories are susceptible to distortions, particularly related to how questions are asked. (There are other sets of studies that have shown that false memories can be implanted—I am not going to delve into these studies here.) One of the most well known of these studies is the ‘lost-in-the-mall’ study by Loftus and Pickrell (1995). Participants in this study were asked to recall childhood memories based on brief descriptions provided by their family members. The researchers included four different events for each participant: three genuine events and one fabricated event—a story about the participant being lost in a shopping mall as a child and eventually being found by an elderly person who helped reunite them with their family. This study was inspired by an anecdote of an attempted kidnapping from Jean Piaget (Loftus & Ketcham, 1994; described here in Section 8.2 on p. 239). Loftus and Ketcham (1994) reflect on the experience of creating a false memory for the first time in a pilot study:

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Memories that matter I couldn’t believe what I had just witnessed. In five minutes, with a few suggestions and minor prods from her father, Jenny had accepted a false memory and embellished it with details of her own. She remembered being lost, she remembered looking all over for her father, and she remembered being scared. In less time than it took to cook a hard-boiled egg, we had created a false memory. (pp. 95–96)

Some of the participants falsely remembered the event, though it is difficult to know what experiences they may have been recalling details from; subsequent studies have replicated these findings (Hyman & Pentland, 1996; Murphy, Dawson, et al., 2023). This study has far-reaching legal implications and sparked an ethical debate (Coan, 1997; Crook & Dean, 1999; Loftus, 1999). The Innocence Project reports that eyewitness misidentification contributed to an overwhelming majority of wrongful convictions that have been overturned by post-conviction DNA testing. Between 1989 and 2020, of the 375 people who have been exonerated due to DNA evidence, incorrect identification by eyewitnesses was a factor in 69% of wrongful convictions (West & Meterko, 2016; Innocence Project, 2020). Thus, eyewitness misidentification has been the leading contributing cause of these wrongful convictions. This statistic underscores the potential for error in eyewitness memory and highlights the need for improved methods of eyewitness identification. The advent of DNA testing has provided a powerful tool to challenge wrongful convictions, but also the need for caution in the interpretation of eyewitness testimony. Wells et al. (2020) highlighted the potential for suggestive police procedures to influence eyewitness identifications, leading to misidentifications and wrongful convictions. This research has led to important reforms in law enforcement practices related to eyewitness identifications, including the use of double-blind lineups and sequential presentation of lineup members (Wells et al., 1998; Wells, 2006). However, current debates for further reform still continue (Berkowitz et al., 2022; Wixted & Mickes, 2022). Memories for individual episodic experiences are not the only extent to which memories can be false. Binjamin Wilkomirski published Fragments: Memories of a Wartime Childhood (1995), recounting his experiences as a child survivor of the Holocaust including time in concentration camps in Majdanek and Auschwitz. Wilkomirski describes the inhumane treatment of the prisoners, the heart-wrenching separations of families, and the constant fear of death. The book was widely praised and won several awards. However, as uncovered in 1998, the memoir was fabricated—Wilkomirski was elsewhere in Europe during the Holocaust. This revelation demonstrated that verification is needed for autobiographies that may influence the historical record. Some have suggested that Wilkomirski identified with Holocaust victims and internalised their experiences as a way to deal with his own genuine childhood adversities, but he was never in any concentration camps (Hasian, 2005; Sorensen, 2012; Vivian, 2017). Regardless, examining his

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fabricated autobiography can provide insight into how false recollections are made; for instance, there are differences in how details are described and how episodes are transitioned between (Maechler, 2001; Pennington, 2013). While this particular Holocaust survivor story was false, it was based on real stories. Verified autobiographies of those who have lived through the atrocities of the Holocaust do exist, such as Anne Frank’s diaries.

Lie detection Shifting our focus from attempting to reconstruct criminal and traumatic events from those that mean well, some studies have sought to test for memories that someone wants to hide from others—in particular, looking for physiological measures of a concealed information, more generally considered as lie detection. These types of tests have a long tradition in the psychology literature (Lykken, 1959, 1960, 1974); established experimental procedures for these studies include the Concealed Information Test, Guilty Knowledge Test, and Guilty Actions Test (Gamer, 2010; Meijer et al., 2010; Verschuere et al., 2011; Matsuda & Nittono, 2018). Here the examiner would ask a question that should only be known to the guilty individual (e.g., not been shared with the media), asking several statements with each being followed by three to five options. Skin conductance response would be monitored and the option with the highest fluctuation judged as the individual’s response. The man we’re looking for held up a loan office in Manhattan. If you’re the guilty party, you will recognise the name of that loan company. I’m going to name a few loan companies that have offices in the vicinity; you just sit there quietly and repeat the names after me as you hear them. Was it the Ideal Loan Company? …Was it the Continental Loan Company? …Was it the Guarantee Loan Company? …Was it the Friendly Loan Company? …Was it the Fidelity Loan Company? (Lykken, 1974, p. 726) A challenge in experimental studies has been to distinguish the individual guilty of committing a mock crime from an informed innocent who also possesses crime-related knowledge (Gamer, 2010). Critically, in both cases the individual has memories of privileged information. Matsuda and Nittono (2018) provide a comprehensive review of psychophysiological measures related to both recognition and concealment, including changes in heart rate, skin conductance, and brain activity (also see Section 6.2 on p. 167). During recognition, there is typically an increase in skin conductance response and heart rate, as well as increased activation of brain regions such as the amygdala and hippocampus, reflecting increased emotional arousal and memory-retrieval processes. During concealment, on the other hand, there may be a decrease in skin conductance response and heart rate, as well as changes in brain activity related to cognitive control processes. These responses are

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thought to reflect attempts by the individual to suppress or inhibit their physiological responses to crime-related information. While these physiological changes are true in aggregate, it is difficult to determine if an individual response is truthful or not. Though multiple lie-detection test approaches have been developed, they each do not have sufficiently high validity and can be misled by countermeasures (Lykken, 1981; Iacono & Lykken, 1997; Kotsoglou & Oswald, 2021). Fictional works have explored many hypothetical future technologies that could probe one’s memories; these are discussed in Section 13.5 from p. 432.

2.4 Verbatim recall Having discussed the fallibility of memory at length already, our memory system clearly is not well-suited to verbatim recall. While this is not necessary in much of day-to-day life, there are instances where verbatim recall is required. One clear instance of this is passwords. MIN RE

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Passwords are ‘odd’ in that they are self-generated strings of alphanumeric characters and symbols, or sometimes just numbers, that we need to store en masse along with a mapping of where they are applicable (Zviran & Haga, 1993). Everyone has a long list of passwords—separate ones for your email, bank, video streaming, and a dozen of other online services. Some of these passwords may expire and even have rules against re-using the password again within a set period. They are designed to be somewhat unwieldy, often now requiring the inclusion of symbols and perhaps not allowing dictionary words. Other items of memoranda may be more loosely considered as ‘passwords,’ but are shared across groups of people, such as the key-code for the lab space or department lunchroom. In such cases, as well as for some personal codes like the ones associated with your debit and credit cards, these are constrained to only a short sequence of numbers. Regardless of all of these instances, verbatim recall is necessary—being off by one character or transposing a character is not ‘close enough’ to allow passage, and sometimes too many consecutive incorrect attempts can temporarily lock you out of the desired service. We will discuss passwords further in Section 13.4 (p. 430)—including how to choose passwords that improve your mental health.

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A second example of verbatim recall, albeit sufficiently different, is medication adherence. Memory plays a crucial role in medication adherence, as patients must remember to take their prescribed medications at the appropriate times and dosages. Forgetting to take medication or not following the prescribed regimen can lead to reduced effectiveness, complications, or worsening of the condition being treated. Medication needs to be taken at specific times of day, with a set dosage, and sometimes varying over the week (e.g., once a week or every second day). When asked about adherence, memory biases influence patients’ responses, such that those adhering will overestimate the extent of their adherence, and those that did not follow the treatment plan will overestimate how little they followed (Lippman & Mackenzie, 1985; Coughlin, 1990; Tarrant et al., 1993). This applies to many forms of medical recommendations, including physical activity (Prince et al., 2008). This type of recall bias can have broader diagnostic implications, such that those observing side effects may be more motivated to think back to reasons why they may have occurred (e.g., interactions with other medication) than those without side effects (Raphael, 1987; Kjellsson et al., 2014). Simple memory aids such as the pill organiser shown in Figure 2.4 can be useful for improving medicine adherence (Boron et al., 2013; McDonald et al., 2019). Though these are often not considered when asking if a person is using memory aids, the sole purpose of this device is to remind a person to take their required medicine dosage. They do, nonetheless, still require the person to keep track of dosage specifics; for instance, one pill may need to be consumed 30 minutes before lunch and another may be advised to be

FIGURE 2.4: Pill organiser with multiple compartments for each day.

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taken with food. Asking patients to keep diaries of their medication use has been shown to improve adherence better than some alternative self-report measures (Garber et al., 2004; McDonald et al., 2019). By prioritising memory management in medication adherence, patients can ensure that they are taking full advantage of their prescribed treatment, leading to better health outcomes and overall well-being. In some cases, the medication is meant to treat memory difficulties (Cosentino et al., 2011) or medication side-effects include impairing memory function (Roth et al., 1984); these circumstances can be particularly problematic for medication adherence. In some instances, memory reports are based on reconstructions and are clearly not verbatim. As described by Brown and Sinclair (1999), many survey studies have found discrepancies between men’s and women’s selfreported number of lifetime sexual partners. Stemming from surveys of the general public, heterosexual men tend to estimate that they have 2–4 more partners than women, which should not occur if reports are accurate. One would expect these should be the same number for a given region. For lifetime estimates, men reported more partners than women, with men more likely to use rough approximation strategies and women more likely to enumerate partners. Critically, strategy type affected estimate size. No differences occurred for past-year estimates or strategies. These findings suggest the lifetime discrepancy arises from differences in estimation strategies used, not intentional bias to over- or under-exaggerate estimates. Brown et al. (2017) followed this work with larger and more representative samples and a more constrained survey design. This study replicated the prior findings that men used rough approximation more and women used enumeration more. These results demonstrate different memory strategies for how people reflect on their past experiences.

2.5 Availability In a typical text, are there more words that begin with the letter K, or that have K as their third letter? When Tversky and Kahneman (1973) asked this question, 69% responded that more words begin with the letter K. This was also repeated for four other letters (L, N, R, and V), and across all letters participants tended to respond that the specified letter occurred more often in the first position than in the third. However, based on a previous analysis of letter frequencies, all five of these letters were selected because they occurred more often in the third position. This result is known as availability bias (also see Kahneman & Tversky, 1972; Tversky & Kahneman, 1974). The explanation proposed is that more examples of K in the first position come to mind. An alternative mechanism was later proposed by Schwarz et al. (1991), that the key factor is the ease of retrieval that matters, not the number of examples. Admittedly, these two properties generally co-occur (Echterhoff

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& Hirst, 2006). While these examples of the availability heuristic are relatively contrived, it can be thought of as a much more general principle. For instance, Tversky and Kahneman (1973) suggest that “one may assess the divorce rate in a given community by recalling divorces among one’s acquaintances” (p. 208). In gambling-related studies, memory accessibility for recent and salient outcomes can also be considered extensions of the availability heuristic (Madan et al., 2014; Madan, Ludvig, & Spetch, 2019). In a similar vein, Goldstein and Gigerenzer (2002) proposed a recognition heuristic. In the original study, students in both the USA and Germany were presented with names of two cities, within the same country, and had to judge which city had a higher population. The US participants got more responses correct for the German city questions, whereas the German participants scored higher on the US questions. Participants tended to judge the city with the more recognised name as being more populated, and having less pre-existing knowledge about the city made it easier to make the judgements. Basehore and Anderson (2016) conducted a follow-up study using only fictitious cities, allowing the researchers to control for variations in prior knowledge or familiarity associated with real cities. Some fictitious cities were presented in a pre-exposure phase as well as a judgement phase, while other fictitious cities were only presented in the judgement phase. The results of the experiment showed that participants were more likely to select the city they recognised as having a larger population, replicating prior studies. Gigerenzer and Goldstein (2011) provide a detailed and comprehensive review of the studies conducted within ten years of the initial work. Work on the recognition heuristic has largely been developed independent of recognition memory. To resolve this, Erdfelder et al. (2011) modelled memory processes more directly and found that this approach had two major benefits. First, it helped explain contradictions in previous research results by accounting for both memory accuracy and response bias. Second, it also led to new, previously untested predictions. This work helped bridge the gap between the initial recognition heuristic work and established memory research by highlighting the importance of considering both factors when studying decision-making processes. Similarly, the estimation of event dates is affected by familiarity, as well as recency (Brown et al., 1985). Taken together, memory availability is an important cognitive bias that occurs often in everyday life. If some experiences are more easily retrieved from memory, then this bias in memory can influence subsequent decision making. This principle will be a focus throughout this book. Some factors can influence memory retrieval, such as the environmental context–like in the earlier example of background music influencing wine purchases (North et al., 1997, 1999). Here the music is priming memory related to the country to influence retrieval in a targeted way, but it nonetheless is related to how available the memories were. When voting in an election, people vote in variety of polling locations. Some locations for voting occurred in churches, schools, or community centers—ballots on policies and funding

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priorities can be biased by polling location (Berger et al., 2008; Rutchick, 2010; Pryor et al., 2014). Conceptually related environmental cues can also influence product evaluations and accessibility, such as orange-coloured chocolate being more retrievable at Halloween (Berger & Fitzsimons, 2008). Being reminded of past events and episodic future thinking can both make the perceived likelihood of specific future events seem more likely, similarly occurring through an availability-based mechanism (Carroll, 1978; Folkes, 1988; Morewedge et al., 2005; Lempert et al., 2017; Bulley et al., 2019). An availability bias should not be merely considered a ‘quirk’ of our cognition. For instance, it is well established that cognitive biases can influence medical diagnoses and diagnostic error has been identified as a leading cause of death (Makary & Daniel, 2016). In a thorough review of cases of diagnostic error, Graber et al. (2005) found that errors were often due to multiple contributions. One category of cognitive contributions to error was ‘faulty verification,’ which included several types of contributions where available information was considered sufficient. This framework has also been applied to thoroughly assess single case studies, again finding some of the most frequent cognitive contributions to diagnostic error as being related to availability bias (Melo et al., 2017; Schaller-Paule et al., 2021; Thompson et al., 2022). However, Mamede et al. (2020) demonstrated that engaging in a training activity of relevant topics, a week in advance, can attenuate the availability bias and improve diagnostic accuracy. This may seem minor, but could be the basis for a continuing professional development training where medical doctors are ‘reminded’ of different diagnoses, reducing variations in the availability of the diagnosis possibilities. This is one of several approaches being explored to reduce the influence of cognitive biases (Kulatunga-Moruzi et al., 2004; Coderre et al., 2010; Croskerry et al., 2013; Loncharich et al., 2023). The most common type of faulty verification is ‘premature closure’ (Graber et al., 2005). In essence, this is getting stuck on the initial diagnosis and not sufficiently considering other possibilities. Luria (1966) eloquently described the need for determining the underlying cause and not stopping just at the symptoms, based on a article by Goldstein (1925): The symptom cannot be regarded as an immediate expression of the damaged function: it has to be analysed, and only an analysis of the basic disturbance which has to be singled out can show its real essence; this basic disturbance can solve the riddle of the whole syndrome—and only when it becomes clear is the clinical analysis of the patient over. (Luria, 1966, p. 312) Turnbull (2023) provides an example of this, where as a trainee, he initially misdiagnosed the type of amnesia that a child was exhibiting. He provides a summary of his first session with the patient, subsequent discussion with his supervisor, and realisation of premature closure. He then reflects on how he and his supervisor assessed the patient in subsequent visits.

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Peaks and ends Of an experience with some duration and variation, people tend to make judgements about the experience based particularly on the points of maximal and final intensity. This phenomenon is known as the peak-end rule (Kahneman et al., 1993). Though there were earlier demonstrations, the most well-known example of this finding was presented by Redelmeier and Kahneman (1996). In this study, patients made both real-time and retrospective ratings of two minimally invasive medical procedures. As an example of one participant’s experience, they provided a pain rating on a 0–10 scale every 60 seconds while undergoing a colonoscopy, using a handheld device. An hour later, the participant was asked to judge “the total amount of pain experienced.” Attention was given to emphasise the difference between this scale, based on the entire experience, relative to the real-time reports that were intended to be in the moment. A group of lithotripsy patients was also included in the study and given the same instructions. (Lithotripsy is a non-invasive procedure to break down kidney stones using ultrasound waves.) These two medical procedures were chosen for the study because they have unambiguous start and end points. To rule out effects of making real-time evaluations on the retrospective judgement, some colonoscopy patients were not asked to make these evaluations; though a research assistant then observed the procedure and instead made these ratings every 60 seconds. Across all—nearly 300 patients—the medical procedures lasted an average of around 30 minutes, ranging from 4–67 minutes (both extreme durations corresponded to colonoscopy patients). Both peak pain and end pain correlated with the retrospective judgement, but when both were included in the model, the retrospective judgements were significantly better explained. Several other predictors were also additionally considered—such as initial pain, average pain, and duration—but these only minimally, and often not significantly, contributed to the model fit. MIN RE

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These results of Redelmeier and Kahneman (1996) provided strong evidence in support of the peak-end rule, though were only observational. In a subsequent study, an intervention was evaluated—the pain for the final minutes was made less intense by allowing the instrument to remain just barely within the body for up to three minutes prior to removal (Redelmeier et al., 2003). This would lengthen the duration of the procedure, but ideally lead to a less painful end to the procedure. Based on the peak-end rule, this

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should decrease later memories of how painful the procedure was. Nearly 700 participants agreed to participate in the experiment, and were equally likely to be assigned to receive standard care or this modified care. The intervention was successful in decreasing retrospective ratings of pain and also increased the likelihood that patients would be willing to agree to future follow-up procedures. Subsequent studies have demonstrated that the peak-end rule is more general with converging evidence being found in treadmill running intensity (Hutchinson et al., 2018) and childbirth labour pain (Chajut et al., 2014). Thankfully, the peak-end rule is not limited to experiences of pain or negative events. Studies have also found similar results in evaluations of enjoyment of food (Just et al., 2015; Quigley-McBride et al., 2018), gifts (Do et al., 2008), and vacations (Mitchell et al., 1997; Gärling, 2017; Kim & Kim, 2019). Converging evidence has also been shown in more typical experiments, such as involving retrospective evaluations of word lists that included negative words or pictures (Aldrovandi et al., 2015). Support was not found, however, in ‘simple’ positive experiences, such as receiving a gift (Mah & Bernstein, 2019). Demonstration of this effect can include findings of better memory for the end of an entertainment experience and the notion of ‘ending on a high note’ (Gutwin et al., 2016; Bestue et al., 2020). As a further example of using the peak-end rule as an intervention, the use of a nature-based virtual reality as an immediate follow-up to a medical procedure has been shown to reduce retrospective evaluations of pain (Tanja-Dijkstra et al., 2018).

Experiences, not things When spending on an indulgence—such as a gift or celebration—broadly, there are two categories: material purchases or experiences (such as an evening out or a vacation). Numerous studies have found that people are happier in relation to experiential purchases (‘doing’), than material ones (‘having’) (Van Boven & Gilovich, 2003; Gilovich & Gallo, 2020). One reason for this preference is that experiences often facilitate more social interaction, contribute to one’s identity, and generate lasting memories (Kasser & Sheldon, 2002; Caprariello & Reis, 2013; Tully et al., 2015; Garcia-Rada et al., 2023). Moreover, the anticipation leading up to the experience, the event itself, and the reminiscence afterward all contribute to a higher degree of satisfaction and overall happiness (Nicolao et al., 2009; Kumar et al., 2014, 2020; Kumar & Gilovich, 2016). However, this general trend does not apply to everyone equally. The choice between experiential and material purchases can be influenced by various factors such as personal preferences; for instance, individuals with a higher preference for novelty and adventure are more likely to derive happiness from experiences, while those who value stability and security may derive more happiness from material purchases (Tully et al., 2015). Furthermore, the perceived value of experiences and material purchases can change over

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time. Bhattacharjee and Mogilner (2014) found that as people age, they tend to place more value on experiences. This is attributed to the realisation that time is finite and the desire to create meaningful memories increases. This preference for experiences over material goods can be seen clearly in the context of engagement in concerts and other live events. Here research has indicated increased satisfaction and happiness derived from such experiences. Live events support one’s sense of self-identity and provide a platform for interpersonal connection, fostering a sense of belonging (Kasser & Sheldon, 2002; Van Boven & Gilovich, 2003; Carter & Gilovich, 2010; Caprariello & Reis, 2013). The memories created during these unique experiences are longlasting, extending beyond the enjoyment of the immediate experience. Indeed, reminding participants that experiences can provide lasting memories shifts their preferences further towards choosing experiences (Tully et al., 2015). Moreover, the anticipation of a pleasurable experience and the subsequent reminiscence elicit joy, a sentiment that extends the happiness derived from the experience itself (Nicolao et al., 2009). This cycle of anticipation and savouring is typically more pronounced with experiences than with material possessions (Kumar et al., 2014; Kumar & Gilovich, 2016). Some hotels have adopted memory-related slogans directly, such as advertising themselves as “Where moments make memories,” “Transforming Moments into Priceless Memories,” and “Life is a collection of moments; so here at _____, our wish is to make those moments unforgettable.” Not all experiences we pay for are as obvious as a concert or a vacation. An instance where experiences are implicitly bought is commute time. Living further from where you work is typically associated with cheaper housing expenses, but then requires more commuting time. Many studies have found that longer commute times are negatively associated with life satisfaction (Stutzer & Frey, 2008; Christian, 2012; Sandow, 2014). These studies find that people often underestimate the dissatisfaction and stress associated with long travel times. Longer commuting times can also limit opportunities for social interaction and leisure activities (Besser et al., 2008; Hilbrecht et al., 2014), integral elements for overall happiness and life satisfaction. Convergently, those that spend money on time-saving services, such as house cleaning and grocery delivery, report greater life satisfaction—even after controlling for a range of other covariates (Whillans et al., 2017). In a sense, spending money on experiences is spending money on forming memories. These memories can be shared with others and are formative for our identity, but after the event happens—the dinner out, the concert, or the vacation—memories are what persist.

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End of chapter wrap-up Summary Memory is intricately linked to our everyday lives—particularly in how prior knowledge shapes our real-time experiences. Our ability to follow story narratives is also heavily dependent on memory, as we remember the journeys of heroes. However, memory can also be quite fallible, a caveat to the use of eyewitness memory in legal cases and the potential for memory distortion through leading questions. We do sometimes need verbatim recall, such as when remembering passwords and taking medication. A key principle is that there are biases in the availability of our memories, and this can influence our decision-making processes. Our daily experiences are complex and nuanced, and memory is interwoven throughout.

Reminder cues

Quick quiz 1. What is the term for the basic unit of information being cognitively processed? (a) Chunk (b) Script (c) Cue (d) Schema 2. What is the significance of the ‘hero’s journey’ model in the context of memory for story narratives? (a) It suggests that stories should follow the hero’s journey to be memorable. (b) It is a model used to assess the cognitive ability of individuals. (c) It is a model that only applies to fictional narratives. (d) It provides a sequence for major events that can aid in memory.

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3. Suppose you are a detective interviewing a witness to a crime. Based on what you know about the reconstructive nature of memory and the influence of leading questions, which of the following approaches would be most appropriate? (a) Ask the witness to recall the event in reverse order to ensure accuracy. (b) Provide the witness with a detailed account of the crime and ask them to confirm it. (c) Ask the witness to recall the event in their own words without interruption. (d) Ask the witness what they think was the motivation for the crime. 4. Why is verbatim recall important in medication adherence? (a) Patients need to remember to take their medication at the right times and dosages. (b) Patients need to remember the names of their medications. (c) Patients need to remember the side effects of their medications. (d) Patients need to remember the cost of their medications. 5. How do memory availability findings relate to interventions aimed at reducing the perceived intensity of medical procedures? (a) Findings suggest that reducing the intensity at the beginning of the experience can lead to lower remembered pain. (b) Findings suggest that maintaining a constant intensity throughout the experience can lead to lower remembered pain. (c) Findings suggest that reducing the intensity at the peak and end of the experience can lead to lower remembered pain. (d) Findings suggest that increasing the intensity at the end of the experience can lead to lower perceived pain.

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Thought questions ▶ What is another example of an everyday memory study and its findings? ▶ What are some limitations of the everyday memory approach? ▶ Can you think of an instance where the peak-end rule manifested in your life?

Further reading ▶ Hirst, W., & Echterhoff, G. (2012). Remembering in conversations: The social sharing and reshaping of memories. Annual Review of Psychology, 63(1), 55–79. doi: 10.1146/annurev-psych-120710-100340 ▶ Crook, L. S., & McEwen, L. E. (2019). Deconstructing the lost in the mall study. Journal of Child Custody, 16(1), 7–19. doi: 10.1080/15379418.2019.1601603 ▶ Nilsson, L.-G., Mäntylä, T., & Sandberg, K. (1987). A functionalistic approach to memory: Theory and data. Scandinavian Journal of Psychology, 28(2–3), 173–188. doi: 10.1111/j.1467-9450.1987.tb00754.x

Chapter 3 Structure and organisation

What memory has in common with art is the knack for selection, the taste for detail. Complimentary though this observation may seem to art (that of prose in particular), to memory it should appear insulting. The insult, however, is well deserved. Memory contains precisely details, not the whole picture; highlights, if you will, not the entire show. The conviction that we are somehow remembering the whole thing in a blanket fashion, the very conviction that allows the species to go on with its life, is groundless. More than anything, memory resembles a library in alphabetical disorder, and with no collected works by anyone. — Joseph Brodsky (1986)

Before we really get into how we preferentially remember some information, we need to establish some background in how memory is organised. Here I will be divorcing the organisation and neurobiology of memory into separate chapters. For the most part this is an artificial distinction, with the two topics being closely intertwined.

3.1 Taxonomy of memory Memory is conceptualised as being composed of several distinct memory systems. A coarse division is working memory, which is limited to information that can be consciously kept in mind. Generally this system can only store a few seconds of information and any distraction that causes one to ‘lose their train of thought’ results in the content no longer being in working memory. Long-term memory refers to any longer time-scale, spanning from tens of seconds after an event occurs to days to decades later. In this book, we will principally focus on episodic memory and semantic memory, the two types of declarative memory—as shown in Figure 3.1, and 57

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from the broader taxonomy proposed by Squire and Zola-Morgan (1988). Declarative memory is the broad category of memory that encompasses information we can verbally ‘declare.’ Semantic memory is related to facts and decontextualised information that you just ‘know,’ without having explicit memory for when you learned it. Episodic memory is related to events and experiences—episodes that you can remember and replay in your mind. Remembering what you did yesterday or for your last birthday are heavily reliant on episodic memory. Knowing that a lion is a type of cat, being able to name a particular object as a guitar, and understanding that a spoon is more appropriate for stirring coffee than a pencil are all reliant on semantic memory. More succinctly—the two systems correspond to memory for knowledge and memory for events.

FIGURE 3.1: Taxonomy of memory systems. As shown in Figure 3.2, “Dog or not?” would be a test of semantic memory, “Did I see this dog in the last few days?” would be a test of episodic memory. This semantic memory test bears a resemblance to website CAPTCHA tests, where the user is asked to click on the motorcycles or traffic lights. However, these tests have begun to change as computer vision methods have improved. DER CU MIN E RE

To concisely introduce another key term, autobiographical memory is an orthogonal categorisation of declarative memory focused on a person’s own history and identity (discussed in more detail in Section 8.1 from p. 231), predating the development of episodic and semantic memory

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FIGURE 3.2: An example of episodic vs. semantic memory. system terms. Episodic memory is nearly always autobiographical—these are episodes of your own experiences after all—however, recalling details of a recently read novel or television series could be considered episodic, but not autobiographical. Semantic memory is often not autobiographical, but personal information such as where you grew up would be autobiographical details—particularly the sort of questions often used as security questions for your online accounts, as further discussed in Section 13.4 from p. 430 (particularly Table 13.1).

Defining semantic memory Semantic memory is our storage of facts and knowledge. Some facts you likely know are that Mercury is the planet closest to the sun, a dog is both a type of pet and a mammal, and that China was the first country to have a population of one billion. For each of these facts, you likely do not remember the experience of learning about them, but you know them to be true. Some facts might be known to some, but not as common, such as the riddle of the Sphinx, from Greek mythology: “Which creature has one voice and yet becomes four-footed and two-footed and three-footed?” This is viewed as the most famous riddle in history, so it is likely that many of you already know the answer, but do not remember when you were first told of it. For some of you, this might be your first time coming across this, so I will tell you the answer here—though likely years from now you will also forget this ‘episode.’ The response is: “Man—who crawls on all fours as a baby, then walks on two feet as an adult, and then uses a walking stick in old age.”

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FIGURE 3.3: Example of a portion of semantic network. In a general sense, semantic memory is the knowledge we develop over years. It is one of the purposes of formal education, such as how medical doctors learn the requisite clinical knowledge to diagnose and treat patients. Semantic memory is best thought of as a large network of associations between concepts (Quillian, 1966; Collins & Quillian, 1969), as illustrated in Figure 3.3. Concurrent to this work, several other groups of researchers also began developing other models of semantic memory based on associative networks (Kintsch, 1972; Anderson & Bower, 1973; Loftus, 1977). A variety of approaches have been developed to computationally model how related different concepts are, often through the generation of a high-dimensional ‘topic space’ based on text co-occurrences in large databases of text (Landauer & Dumais, 1997; Landauer et al., 1998; Blei et al., 2003; Ensor et al., 2021). A graphic, network representation of general semantic knowledge is shown in Figure 3.4, giving us a lens through which we can visualise how our knowledge and understanding of the world are organised, showing how different concepts are related. This network, based on WordNet (Miller, 1995), involves an expansive 1,705 categories, derived from over 118,000 word lexical-semantic (i.e., string—meaning) representations. The hierarchical categories of this network span all general knowledge domains, encompassing representations of objects and actions ranging from basic geometric shapes to complex events. Semantic knowledge is not flat; it has a structure, depth, and form that seeks to reflect the complexity of the world around us. This hierarchical network has been used in many studies of semantic knowledge.

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FIGURE 3.4: Semantic network of general knowledge concepts. What categories do you see in the icons shown in Figure 3.5A? All of these icons are the same size and have similar visual properties. The left half of the icons here represent inanimate objects, while the right half are animals. You may also notice that the upper half represent relatively large items, while the lower half are relatively small. This figure panel alone is insufficient to convey any of this information, but hopefully this quadrant arrangement of animacy and size is apparent now—this categorisation relies fully on semantic information. Figure 3.5B provides further sub-categories, can you identify them? Some are mammals and others birds; some domestic and others wild. Many other categories—not all mutually exclusive—can also be considered. Moreover, these are all likely pictures you have not seen before— nor are they photos similar to items you have seen previously. In our rapidly evolving digital age, certain icons have become anachronistic, yet they persist due to their entrenched symbolism and the role of semantic memory in our understanding of these symbols. Consider the floppy disk icon, often used to represent the ‘save’ function in many software applications. While the actual floppy disk is a relic of the past, its image has

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A

B

FIGURE 3.5: Example icons representing real-world objects. become universally recognised as a symbol for saving work. This is a testament to our semantic memory, which allows us to understand the meaning of the floppy disk icon without the need for recent interaction with an actual floppy disk. Similarly, the gear icon, used to denote ‘settings’ in many interfaces, and the landline telephone handset icon, often used to represent a call function, are other examples of how semantic memory works. Despite the obsolescence of gears in everyday objects and landline phones in our communication, our semantic memory allows us to recognise and understand what these icons represent. Some other technological depictions still relate to contemporary objects, but they are lessening in prominence. Three examples of this are the visual of a letter to represent email, file folders to represent computer folder organisations, and scissors for cutting information and temporarily storing it in computer memory. These icons serve as a testament to the lasting impact of these objects on our collective semantic memory, demonstrating how our knowledge and understanding of the world can persist and adapt, even as the objects themselves become obsolete. These icon examples also reflect the concept of ‘skeuomorphism,’ the principle where digital interface design elements correspond to real-world, physical counterparts.

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Defining episodic memory Endel Tulving has been the key researcher in defining the boundaries of episodic memory. Let’s review his definition for episodic memory and then work throughto understand it. The definition of episodic memory, as described in Tulving (2002): Episodic memory is a recently evolved, late-developing, and earlydeteriorating past-oriented memory system, more vulnerable than other memory systems to neuronal dysfunction, and probably unique to humans. It makes possible mental time travel through subjective time, from the present to the past, thus allowing one to re-experience, through autonoetic awareness, one’s own previous experiences. Its operations require, but go beyond, the semantic memory system. Retrieving information from episodic memory (remembering or conscious recollection) is contingent on the establishment of a special mental set, dubbed episodic “retrieval mode.” Episodic memory is subserved by a widely distributed network of cortical and subcortical brain regions that overlaps with but also extends beyond the networks subserving other memory systems. The essence of episodic memory lies in the conjunction of three concepts—self, autonoetic awareness, and subjectively sensed time. (p. 5) Tulving’s definition of episodic memory, as you have seen, is quite dense and packed with technical terms. Let us unpack it, phrase by phrase, to get a clearer understanding of what is being defined as episodic memory. Episodic memory is a recently evolved, late-developing, and earlydeteriorating past-oriented memory system, more vulnerable than other memory systems to neuronal dysfunction, and probably unique to humans. This first part of the definition tells us that episodic memory is a relatively new development in the grand scheme of evolution. It develops later in life compared to other memory systems and is also the first to deteriorate as we age. It is also more susceptible to damage from neurological disorders. Tulving suggests it is likely that only humans possess this type of memory. It makes possible mental time travel through subjective time, from the present to the past, thus allowing one to re-experience, through autonoetic awareness, one’s own previous experiences. Here, Tulving is saying that episodic memory allows us to mentally revisit past events; this is meant by mental time-travel. We can re-experience these events through what he calls autonoetic awareness, a conscious sense of self

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in time. As such, this phrase is inextricably linking episodic memory to being able to have conscious experiences. Its operations require, but go beyond, the semantic memory system. This phrase tells us that while episodic memory relies on semantic memory— our knowledge of facts and concepts—it also involves more than just semantic memory. It’s not just about knowing facts; it’s about remembering experiences. Retrieving information from episodic memory (remembering or conscious recollection) is contingent on the establishment of a special mental set, dubbed episodic “retrieval mode.” This part of the definition explains that to access episodic memories, we need to enter a specific mental state, which Tulving calls the episodic retrieval mode. Episodic memory is subserved by a widely distributed network of cortical and subcortical brain regions that overlaps with but also extends beyond the networks subserving other memory systems. This tells us that episodic memory involves a broad network of brain regions, some of which are also involved in other types of memory, but some of which are unique to episodic memory. The essence of episodic memory lies in the conjunction of three concepts—self, autonoetic awareness, and subjectively sensed time. Finally, Tulving sums up the essence of episodic memory as involving three key elements: a sense of self, autonoetic awareness (the conscious sense of self in time), and a subjective sense of time. In summary, episodic memory is our ability to remember specific events from our past, to mentally revisit them, and to place them in the context of our own personal timeline. It’s a complex system, involving many parts of the brain, and it’s likely unique to humans.

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Revising the definition of episodic memory Though Tulving’s (2002) definition is generally accepted and has developed over decades (Tulving, 1972, 1983a, 1985), it has its shortcomings. For instance, it requires conscious recollection, which can be problematic for memory research in non-human animals. As it is difficult to assess consciousness in other species, comparative psychology and behavioural neuroscience researchers have taken to describing results as ‘episodic-like’ memory across a large range of species, including non-human primates (Schwartz et al., 2002; Basile & Hampton, 2011), birds (Clayton & Dickinson, 1998; Skov-Rackette et al., 2006; González-Gómez et al., 2011), but also dogs (Fugazza et al., 2016, 2018, 2020; Lo & Roberts, 2020), horses (Hanggi & Ingersoll, 2009; Valenchon et al., 2013), dolphins (Mercado et al., 1999), cephalopods (Jozet-Alves et al., 2013; Billard et al., 2020; Schnell et al., 2021), rodents (Babb & Crystal, 2005; Davis et al., 2013; Panoz-Brown et al., 2016, 2018), and even insects (Pahl et al., 2007; Perry et al., 2017). Further demonstrating the complexity of memory in non-human animals, evidence of inter-generational knowledge transfer has been reported in pigeons (Sasaki & Biro, 2017) and elephants (McComb et al., 2001; Jesmer et al., 2018). This social communication of knowledge in animals can have real-world implications. To keep flocks of sheep within a particular area, one barrier used is a cattle grid—a grid of metal or wooden bars spaced out wider than an animal’s feet. In 1985, sheep found a way past this barrier—rolling (The Guardian, 1985; The Sunday Times, 1985). At the time this had never been observed before, and as reported in The Sunday Times (1985): “Naturally, the authorities are anxious to contain this flamboyant behaviour. They have taken steps to isolate the Welsh sheep so that they don’t go to market and boast their grid-rolling activities to other sheep.” The concern was that if other flocks learned this strategy as well, millions of pounds of infrastructure would become obsolete (The Guardian, 1985). However, several news reports over the years have observed other groups of sheep re-discovering this strategy (BBC, 2004; North Wales Live, 2007). Given that some studies have otherwise demonstrated the criteria of episodic memory, this definition could be considered overly anthropocentric; Madan (2020a) discusses these considerations in detail (also see Griffiths et al., 1999; Dere et al., 2006; Templer & Hampton, 2013; Allen & Fortin, 2013). More generally, an objective approach to evaluating cognitive abilities should be amicable to understanding non-human minds (Nagel, 1974; Allen & Bekoff, 1999; Godfrey-Smith, 2016). To quote Nagel (1974) directly: A Martian scientist with no understanding of visual perception could understand the rainbow, or lightning, or clouds as physical phenomena, though he would never be able to understand the human concepts of rainbow, lightning, or cloud, or the place these things occupy in our phenomenal world. The objective nature of the things picked out by these concepts could be apprehended by

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Decades ago, a term was proposed to specifically describe conscious recollection, “ecphory,” by Semon (1904, 1918) (also see Tulving, 1976, 1983a; Schacter et al., 1978; Schacter, 2001). By using ecphory more commonly, we can more precisely describe the presence or measurement of specific features of episodic memory. For instance, some experimental procedure may involve ecphory, such as an old/new recognition test, while other tests may not, such as lexical decision. This aligns particularly well with the distinction of direct vs. indirect memory tests, discussed later in this chapter. To provide a summary of the resolution determined in Madan (2020a), I proposed a revised definition of episodic memory: Episodic memory is the remembrance of one’s own previous experiences and can be done by both human and non-human animals. Episodic memory is supported by a distributed network of cortical and subcortical brain regions, but requires the involvement of the hippocampus—unlike other memory systems. Mental time travel, the re-experiencing or imagining of a sequence of events, is dependent on episodic memory. Familiarity may involve episodic memory but is not a type of episodic memory, as familiarity is also dependent on other memory processes. (p. 187) This is not to say that consciousness is not important, rather, understanding and measuring consciousness is a hard problem (Armstrong, 1898; Lashley, 1923; Sandberg et al., 2010; Dennett, 2018; Hunt et al., 2022)—it is even often described as ‘the hard problem’ (Chalmers, 1995). Over the centuries, many have proposed thought-provoking scenarios where the relationship between consciousness, memory, and self are difficult to interpret (Locke, 1690; Mitchell, 1866; Ryle, 1949; Parfit, 1984). I think it is unambiguous that some aspects of episodic memory are intertwined with consciousness (Madan, 2023a), as has been discussed in theoretical and philosophical frameworks (Franklin & Baars, 2010; Dokic, 2014; Hopkins, 2014; Klein, 2014, 2018; Boyle, 2020; Budson et al., 2022). As consciousness itself is not well understood (Yaron et al., 2022), requiring it as part of the definition of episodic memory then muddles our ability to study episodic memory. The intent here is to focus on what is necessary to distinguish episodic memory from other types of memory—for a more nuanced discussion, see Section 14.1 (p. 447).

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Common tests of episodic memory The most commonly used memory tests for assessing episodic memory are free recall and recognition. Free recall involves asking the participant to respond with all of the words they saw earlier in the experiment. Recognition typically involves presenting stimuli, either words or pictures, sequentially and asking for a judgement of ‘old’ or ‘new.’ Some stimuli would have been previously shown in the study, while others were not previously presented. Following from the signal-detection theory literature, a correct judgement of a presented stimulus, target, as ‘old’ is referred to as a hit; an incorrect response would be a miss. For stimuli not previously presented, lures, a correct judgement of ‘new’ is referred to as correct rejection; an incorrect response would be a false alarm. The principles underlying this approach are shown in Figure 3.6A–B. These procedures and their variations will be discussed in further detail as the chapter progresses. Though the term episodic memory is often attributed to Tulving (1972, 1983b), it was first proposed by Munsat (1967). The distinction between two memory systems had been a topic of interest for decades prior (James, 1890; Bergson, 1911; Schachtel, 1947; Ryle, 1949; Furlong, 1951; Lewis, 1979), though had not reached a sufficient level of clarity until the definitions proposed by Tulving (1972, 1986). All activities involve an interplay of different memory systems—episodic and semantic memory systems are never truly operating in isolation. Even with a task as simple as remembering a string of letters; it is easier to remember a word than an arbitrary string of letters, similarly a grammatical sentence is much more easily memorised than an unpredictable sequence of words. A cacophony of objects and lines becomes sensible once it is identified as a photo of a messy bedroom. This ability to group ‘items’ together and remember them as a single unit is known as chunking. Based on prior knowledge, more information can be stored within a single chunk. Related to this is the notion of schemas, which are the prior knowledge we are relying on—these are our templates of how things typically occur (Bartlett, 1932; Alba & Hasher, 1983; Mandler, 1984; Ghosh & Gilboa, 2014). For instance, if you often bake cakes, your grocery list might just include “cake stuff” as shorthand for listing out “eggs, flour, sugar, butter, cake mix.” Extending the idea of schemas slightly, they also may lead to different representations based on contextual information. If I ask you to imagine a chair, some object will come to mind. However, if I specified that this chair was in a kitchen or office setting, this object would likely differ in the material it is made of or if it has wheels or legs. Moreover, the first suggestion of a chair was likely to be one of these types of chairs—one you encounter more frequently—as opposed to other types of chairs, such as those you would expect to see in a barber shop or dentist’s office.

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3.2 Memory strength and precision Now that we have some definitions to work with, it is time to think more about how episodic memory works. The main content or pieces of information that we are studying are referred to as ‘items.’ These are often words or pictures, but more nuance can be relevant too, such as if a picture is showing a single object, a detailed scene, or an abstract shape. For now we will consider a visually presented word. As a researcher, how can we make some words more likely to be remembered than others, when presented one-at-a-time in a list? This conceptualisation of memory strength is directly considered as the continuum underlying signal-detection models of item-recognition (Norman & Wickelgren, 1965, 1969; Murdock & Dufty, 1972), as illustrated in Figure 3.6. While memory strength will vary randomly and due to item properties— e.g., for words, word frequency—it also can vary due to experimental factors. Briefly, word frequency is a measure of how often a word occurs in everyday language. The influences of content on memory will be discussed more later, but some readily apparent experimental factors that can influence memory strength are presentation time and repeated presentations. If some words are presented briefly, but other words are presented for longer durations, you would likely suspect that recognition performance would be better for the longer-duration items (Burtt, 1916; Fischer, 1966; Vilberg & Rugg, 2009; Ahmad et al., 2017). If some items are presented on multiple occasions and others are given only a single presentation, recognition is higher for the repeated presentations—though this often requires variations in encoding to emerge (Rowland & Franken, 1976; Murnane & Shiffrin, 1991; Malmberg et al., 2004; Starns & Ksander, 2016), otherwise there may be no benefits (Ratcliff et al., 1990; Yonelinas et al., 1992). Both of these examples highlight a very important point: information can only be remembered if it is first attended to. If some words are presented for longer or more often, they will be encoded into memory more than other words that were present briefly and less often. (Note, if the task is not sufficiently engaging, there are some violations of this ‘simple’ relationship, discussed as total-time invariance; see Cooper & Pantle, 1967; Zacks, 1969.) Recall tests are also sensitive to memory strength manipulations, with stronger items being more likely to be recalled—and recalled earlier (Jacoby et al., 1978; Cohen, 1988; Wixted et al., 1997). Memory strength will also decay as more time elapses since the information was studied (i.e., retention interval). Ebbinghaus (1885), a pioneering figure in experimental psychology, used himself as a subject in the study of memory, focusing on memorising lists of nonsense syllables. His primary findings revealed that forgetting occurs rapidly at first, but the rate of loss decreases over time—the forgetting curve. He also demonstrated that learning is more effective when study sessions are spaced out—the spacing effect (also see Section 11.1 from p. 326). Ebbinghaus’ work laid the groundwork for future research into the serial position effect and developed the savings method to measure retained memory over time. Despite being conducted with only one

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FIGURE 3.6: Illustration of memory strength in an item-recognition paradigm. (A) Studying items increasing memory strength and the respective item distributions (shown with the assumption of single process and equal variance). (B) In a simple old/new recognition task, based on a set response criterion/threshold, items are judged to be old or new. Correct judgements of old and new items are referred to as ‘hits’ and ‘correct rejections,’ respectively. Errors of judging a new item as ‘old’ is a ‘false alarm’; the reverse error is a ‘miss.’ (C) Example of correspondence of item distributions to six-point confidence rating.

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participant and other methodological idiosyncrasies, this work has held up to replication attempts (Dallenbach, 1913; Heller et al., 1991; Murre & Dros, 2015). Other researchers have also studied memory of themselves over even long intervals, using more naturalistic approaches—using real events recorded in diaries over years (Linton, 1982; Wagenaar, 1986). Meeter et al. (2005) examined memory for public events in a sample of over 14,000 participants over an interval of up to two years, and similarly examined forgetting curves. We will discuss these studies based on real-world events in Section 8.1 (p. 234). In a clever set of studies, Murphy, Witnauer, et al. (2022) investigated the specific interactions between presentation duration and repetition (also see Castiello et al., 2022). To provide a simplified view, consider that you were going to present a list of 15 words, once each, for 4000 ms per presentation. Here the study period would last for 60 seconds. In a separate condition, what if you presented 15 words, four times each, but only for 1000 ms at a time—this would still take 60 seconds, but would memory be better, worse, or no different? The findings from these studies suggest memory would be better with the increased presentations. Note, this example is a simplification of the procedures used in their studies. Instructional manipulations can also result in variations in memory strength, such as in the case of a directed-forgetting paradigm (Woodward & Bjork, 1971; Bjork & Woodward, 1973). In this procedure, item presentations are followed by an instructional cue that conveys that the participant should remember some items, but forget others, as a test of memory control. A similar procedure exists within the think—no-think procedure, where these instructional cues respectively denote thinking or not thinking about the justpresented item (Anderson & Green, 2001; Depue et al., 2006). Both of these procedures rely on intentional memory control. (For a discussion of the social consequences of not expressing memories, see Stone et al., 2012.) Recognition tests are not necessarily just based on a judgement of old vs. new, but could instead be made using multiple criterions to include degrees of confidence. This approach often relies on a six-point confidence rating (Wixted et al., 2010; Koen et al., 2017), as illustrated in Figure 3.6C. Note that the spacing between the criterions does not need to be consistent. Remember/know judgements rely on qualitative differences in memory strength that require more nuanced assumptions, with separate processes for recollection and familiarity, respectively. The findings of a well-designed brain-imaging study investigating memory strength (Smith et al., 2011) will be discussed in Section 5.3 (p. 141). One approach to emphasise the focus on episodic memory (true what– where–when memory that is less contaminated by familiarity-like processes), is to present stimuli multiple times such that the old and new stimuli are both recently presented. Though many researchers have used such a manipulation, I have seen it being used particularly effectively by Mayes et al. (2004) with a patient with selective hippocampal damage, Y.R.—a case we will discuss further in the next chapter. Similar proposals, to present stimuli repeatedly

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to make an experimental procedure more episodic dependant, have also been carefully adapted and developed for animal studies (Crystal, 2018, 2021). More recent perspectives on episodic memory are moving away from this subjective distinction (Madan, 2020a) and this is tangential to the main focus of this book, so this approach will generally not be discussed in detail, apart from the underlying principle that ‘remember’ responses denote better item-recognition memory than a ‘know’ response but also are intended to correspond to distinct memory processes. For a thoughtful discussions of this signal-detection theory approach to recognition memory, I recommend Yonelinas (2002) and Wixted (2007). One well-known limitation of remember/know studies is that different studies have used different instructions to explain to participants how to distinguish between these two types of responses. Williams and Lindsay (2019) examined past studies and showed that there have been a range of definitions used to describe what corresponds to a ‘know’ or ‘familiar’ response. Here the definitions were systematically compared and the definition used was found to affect results. However, findings indicated that remember/know subjective judgements are continuous, rather than corresponding to two distinct processes (also see Haaf et al., 2021). Next I quote the instructions from three prior studies to provide an indication of how they are typically presented, and how they vary. Gardiner and Java (1990): Often, when remembering a previous event or occurrence, we consciously recollect and become aware of aspects of the previous experience. At other times, we simply know that something has occurred before, but without being able consciously to recollect anything about its occurrence or what we experienced at the time. Thus in addition to your indicating your recognition of a word from the original study set, I would like you to write either the letter “R” after the encircled item, to show that you recollect the word consciously, or “K” if you feel you simply know that the word was in the previous study set. (p. 25) Rajaram (1993): If your recognition of the word is accompanied by a conscious recollection of its prior occurrence in the study list, then write “R.” “Remember” is the ability to become consciously aware again of some aspect or aspects of what happened or what was experienced at the time the word was presented (e.g., aspects of the physical appearance of the word, or of something that happened in the room, or of what you were thinking and doing at the time). In other words, the “remembered” word should bring back to mind a particular association, image, or something more personal from

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Dewhurst and Anderson (1999): A remember response is one in which you can consciously recollect the appearance of that item some 15 or 20 min ago as a discrete event in your past. You may recall details of the event, such as any thoughts, feelings,or memories you experienced when you saw the item, an association you formed with another item, or some aspect of the item’s physical appearance. A know response is one in which you recognise the item because it feels familiar in this context, but you cannot recall its actual occurrence in the earlier phase of the experiment. You recognise the item purely on the basis of a feeling of familiarity. (p. 667) Depending on our goals, we also engage in retrieval differently; this is referred to as ‘retrieval mode’ (Tulving, 1983b). (This concept was briefly mentioned in the 2002 quote earlier in the chapter.) This is typically a more sustained goal, such as responding on whether a list had relatively more old or new items, or instead made a semantic classification (e.g., size or category) (Rugg & Wilding, 2000). A more naturalistic example of this behaviour would be if you went in to a small, previously unvisited store to quickly buy a snack— having to find the appropriate section and preferred item—or instead had to find a friend within the store and tell them it is time to go. In either instance, the stimuli or situation is the same, but your behaviour in processing it differs based on your goals. Alternatively, recognition could be tested where two stimuli are presented simultaneously, with participants instructed to select the one that had been previously presented, rather than presenting a single item and asking the participant to respond ‘old’ or ‘new.’ This two-item procedure is referred to as two-alternative-forced-choice (2AFC) as opposed to a yes/no or old/new. The single-item (old/new) procedure is susceptible to issues of response bias, i.e., if the participant responds ‘old’ moreso for one experimental condition than another (such as in a study of emotionally negative and neutral pictures; see Section 6.3 from p. 179). In contrast, in a 2-AFC procedure, participants must choose one item or the

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other (e.g., “Which is the old item, left or right?”). Other considerations are also necessary when designing a study to assess recognition memory, but this is one key difference. A variation of this approach, such as 4- or 5-AFC, is also used in some studies (Kintsch, 1968; Norman & Wickelgren, 1969; Hacker & Ratcliff, 1979; Baddeley et al., 2016). This has a few advantages, some more obvious than others. First, the likelihood of choosing the correct item due to chance is now decreased from 50% to either 25% or 20%—for 4- or 5-AFC, respectively. This gives better sensitivity to measuring differences between conditions, as now the effective range for useful responses, and possibly the number of necessary trials and associated measurement precision, is enhanced. Second, the choice of lure items allows for some conditional analyses. For instance, perhaps some items are from the correct stimulus category or otherwise similar, whereas others are unrelated to the target item (Madan, Fujiwara, et al., 2017; Madan, Ng, & Singhal, 2018). I have also used 5-AFC recognition in a few studies for these reasons (Madan, Fujiwara, et al., 2017; Madan, Ng, & Singhal, 2018; Caplan, Sommer, et al., 2019; Palombo, Te, et al., 2021; Palombo, Elizur, et al., 2021). While typically old/new recognition studies have an equal number of old and new items (1:1), this is not always the case. When time is limited and there are several types of old items, some studies opt to have twice as many old to new (2:1) (Madan, Shafer, et al., 2017; Bowen et al., 2020). In other instances, researchers match the number of new items to each condition, e.g., 20 items from condition 1 (old), 20 items from condition 2 (old), and 20 new (Yonelinas & Jacoby, 1995; Khoe et al., 2000; Maratos et al., 2001; Gruber et al., 2014)—though typically the proportion of old and new stimuli is matched at the aggregate level. Some studies have varied the ratio of old and new items across blocks to examine brain activity associated with memory retrieval success (Rugg, Fletcher, et al., 1998; Herron et al., 2004). Depending on the circumstances, this could even be more extreme; Smith et al. (2011) had 5:1 ratio, as did Brezis et al. (2017). Smith et al. (2011) will be discussed in detail in Section 5.3 (p. 141). In some instances it can even be informative to have old/new judgements even when all items are old, as part of a multi-stage memory test where you first assess if the cue is recognised (Madan et al., 2020). The choice of old:new ratio is largely dependent on the specific requirements and constraints of the study, but the implications to scoring and response bias need to be considered. Continuous recognition is another procedure variation, where participants are presented with a continuous stream of items and are asked to indicate when they recognise an item as a repeat. In a way, this is a mix of an old/new recognition and go/no-go tasks. This method allows for the examination of memory over varying repetition lags (i.e., the number of intervening items between the first and second presentation of a repeated item). Early studies by Hockley (1982, 1984) laid the groundwork for this method, demonstrating its utility in studying recognition memory. Later studies followed up and examined further properties of the task (Berman et al., 1991; Larrabee,

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1992; Brady et al., 2008; Johnson et al., 2008). More recently, Allen et al. (2022) presented participants with 10,000 unique pictures while collecting high-resolution fMRI data across 40 scan sessions per participant—now shared as the Natural Scenes Dataset. This design allowed for testing recognition at a range of time-scales, from seconds to minutes (within session) to weeks, months, and nearly up to a year (across sessions). To summarise these results briefly, the adjusted hit rate within session was between 0.6 and 0.8, whereas from a month onwards to the near-year longest delay was relatively constant at 0.2. Finally, continuous recognition tasks have been adapted for use in the clinic, such as MemTrax. Critically, this test has been validated in relation to conventional standardised neuropsychological assessment (van der Hoek et al., 2019; Liu et al., 2021) and large normative samples (Ashford et al., 2022; Liu et al., 2023). The assessment takes only two minutes to administer and includes enough pictures to produce over 600 unique tests. Understanding memory strength is crucial in our exploration of memory; however, another equally important aspect to consider is memory quality.

Memory quality Several approaches have been used to examine the quality of memory. If the item was presented visually, it could be presented in a specific colour or location on the computer screen. If the item was a word presented verbally, the speaker’s voice could have been a man or a woman. In some studies, the researchers first ask for an old/new judgement, and ask for a second judgement after, related to these details—often described as source memory (Geiselman & Bellezza, 1976; McIntyre & Craik, 1987; Johnson et al., 1993). In these cases, the participant may correctly identify the item as old, but may or may not also correctly identify the source information. The procedure could, alternatively, use a single judgement for both sets of information, such as providing the options of: ‘presented left,’ ‘presented right,’ and ‘new.’ Another common approach often used, as mentioned previously, is to ask for a subjective judgement of remember, know, or new. Sometimes a ‘guess’ option is also provided. Alternatively, a set of continuous options related to memory confidence can be provided, such as: sure old, maybe old, maybe new, sure new. These remember/know and confidence judgement approaches align more with the notion of memory strength and the differentiation of recollection and familiarity processes. A more recent third option is to present some ‘similar’ options during the recognition test. Though a few other names have been used in the past, this procedure is now known as the mnemonic similarity task (MST) (see Stark et al., 2019, for a review). Participants would be asked to respond ‘same’ (i.e., old), ‘similar,’ or ‘new.’ An illustration of this procedure is shown in Figure 3.7. Similar items can also vary in the similarity to old items, varying the difficulty of the memory test (Stark et al., 2013; Hout et al., 2014; Frank et al., 2020). While the MST is usually conducted using a single-item test procedure, some

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have modified the test to function with a 2-AFC design with several critical trial types (Huffman & Stark, 2017), based on earlier work done to investigate memory precision with scenes (Friedman, 1979; Tulving, 1981). Though the MST is often done with pictures, at least a few studies have used it with word stimuli (Aust & Stahl, 2020).

Study

Test NEW SIMILAR SAME SIMILAR NEW

SAME

SIMILAR

NEW

FIGURE 3.7: Mnemonic similarity task design. Brady et al. (2008) examined both capacity and precision of memory. Participants were presented with 10 study blocks each with 300 object pictures shown over approximately 20 minutes. After each block there was a 5-minute break. Together there were 2,500 unique pictures shown, with 300 repeats. During the study block, repeated pictures occurred with lags between 0 and 1,023—participants were instructed to press spacebar when they see a repetition. Afterwards a test block was presented, involving 2-AFC judgements which varied in difficulty. One picture was old; the other was either unrelated, from the same object category (e.g., clock, mirror, cake), or the same object in a different state (e.g., an abacus with the beads in different configurations, a briefcase and papers in a different arrangement). Accuracy was high in all conditions, but varied with difficulty: 93% for unrelated lure items, 87% for lure items with different states (also see Cunningham et al.,

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2015). Performance with the study repetitions was also quite high—100% for the immediate repetitions and still remaining at 79% for the lag of 1,023. In a classroom study with an incidental recognition-memory test. Kintsch and Bates (1977) examined verbatim memory for three categories of statements: topic sentences, details, and extraneous remarks. After a two-day delay, students were able to distinguish verbatim statements from paraphrased ones, across all three categories. In a second experiment, a 5-day delay was used and recognition dropped markedly.

Levels of processing When studying memory, often participants are asked to intentionally remember the to-be-remembered items. However, in many other studies, information is learned incidentally. In these cases, words or pictures are presented, but the participant is unaware that there will be a subsequent memory test. The participant could be asked to make a judgement such as if a word has an odd or even number of letters, or if the word represents an animal. These are clearly different types of tasks, the first is quite superficial and does not require any processing of the meaning of the word, whereas the second requires the content to be processed semantically and evaluated. This difference in processing and later memory are the basis of the levelsof-processing approach (Craik & Lockhart, 1972; Lockhart & Craik, 1990). Task instructions can also interfere and prevent deeper processing from automatically occurring (Johnston & Jenkins, 1971; Madan & Singhal, 2012a). Common semantic orienting tasks include asking about category membership (“Is the word an animal name?” or “Does this picture represent something living?”) or about the size, for words that represent objects (“Will this fit in a shoebox?”). If words representing abstract concepts are included, a semantic orienting encoding task could be: “Is it abstract?” A shortcoming of the levels-of-processing approach itself is not sufficiently objective—you cannot quantitatively measure processing depth. This limitation, among others, was brought up shortly after the approach’s proposal by several prominent memory researchers (Nelson, 1977; Baddeley, 1978; Eysenck, 1978). Nonetheless, it is also worth acknowledging that Craik and Tulving (1975) followed the original 1972 paper with an exploration of the approach across ten experiments. The conditions and ranking of their depth may be open to debate, but this was nonetheless a useful and necessary proofof-principle empirical demonstration. It is without a doubt that the levels-of-processing approach has limitations, but it is a useful method and studies in several chapters of this book have used it as a foundation for evaluating motivation-related memory effects. Some following work has suggested that the approach can instead be thought of as the degree of semantic elaboration (Baddeley, 1982) and a focus on encoding procedures (Roediger, Gallo, & Geraci, 2002). Additionally, there is evidence of earlier proposals similar to the levels-of-processing approach, particularly

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by Zinchenko in the 1930s, and later reprinted in English (Zinchenko, 1983, 2008) (also see Meshcheryakov, 2008; Craik & Lockhart, 2008). For reflective overviews on the development of the approach, see Craik (2002, 2020).

Contextual reinstatement While the level of processing significantly impacts memory, the context in which information is learned and recalled also plays a crucial role. Memories are more retrievable when the test conditions are more similar to those during study, referred to as the encoding specificity principle (Thomson & Tulving, 1970) or environmental reinstatement effect (Carr, 1925). Recall depends upon environmental conditions. All experiences are revived in virtue of their direct or indirect association with some sensory stimulus. Any experience can be reinstated only in those environmental situations with which it is associated. Most experiences have some indirect association with every environmental situation and theoretically can be revived under any set of circumstances. Practically, however, an experience can be recalled most readily in those environmental situations with which it has the most direct, the strongest, and the most numerous associations. (Carr, 1925, p. 251) This means that if information is learned in room A, and some participants are tested in room A and others are tested in room B, those that were tested in same room would perform better (Abernethy, 1940; Smith, 1979). A better study would use a 2×2 design with some participants learning information in room B and then evaluating the memory as same vs. different room. Similar effects have also been demonstrated with background music, either being the same or different for the study and test sessions. Smith (1985) used three types of music as context (Mozart, Jazz, Quiet) and assigned participants across nine groups. Three groups corresponded to the same context for study and test (e.g., Mozart—Mozart); the remaining six groups had different contexts. Indeed, recall was better for the same context groups. A better design yet would be a within-subjects design where each person learns some information in each context. Godden and Baddeley (1975) used this within-subjects design; however, rather than merely using two indoor rooms, the participants here were trained scuba divers. Participants learned several lists of words—some on land and some underwater—with one experimental condition administered per day, separated by approximately 24 hours between sessions, and preceded by an initial practice session. When on land, participants were on a busy beach; when underwater, they were 20-feet below in cold open waters. The specific diving site locations changed between sessions, in relation to the summer expeditions of the diving club involved in the study. Lists were presented auditorily, with short pauses interleaved

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between word presentations to allow for intervals of breathing. Recall was done by writing on weighted formica boards with pencils, for both above and underwater tests. Memory was later tested in each context, with better recall when the study and test contexts were the same. (For additional anecdotes that led to the design and conduction of this study, see Chapter 6 of Baddeley, 2018. As discussed in that chapter, other scuba studies were also conducted even prior to this well-known work, such as a study of the relationship between time duration estimation and body temperature, Baddeley, 1966.) While this study is often used as an exemplar to demonstrate the influence of context, a follow-up study that used recognition rather than recall did not show any effect of context (Godden & Baddeley, 1980). MIN RE

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In a meta-analysis of 75 studies across 41 articles, Smith and Vela (2001) examined the generality of environmental context effects. The average effect size across studies had a Cohen’s d effect size of 0.28. More salient environmental changes included changing the experimenter along with the room; a longer retention interval, more than one day, was also associated with a stronger context effect. The test type, recall vs. recognition, was not found to meaningfully influence the effect size. Smith and Vela (2001, p. 213) remark that this null effect of test type is surprising, a sentiment recently echoed by Baddeley (2018, pp. 80–81). Murre (2021) recently reported a failure to replicate the Godden and Baddeley (1975) study; however, the study design differed in many ways. Whereas the original study was conducted over four days, the replication included all four conditions within a 1.5-hour period—as part of a TV show involving a celebrity. Murre (2021) states towards the end of his paper: “We have to admit that we were disappointed by our failure to replicate. […] we fully expected to obtain the same results” (p. 6). Thus, the expectation was that the original study would be replicated when being filmed; indeed, Murre has previously succeeded in replicating a foundational memory finding (Murre & Dros, 2015). Even though the TV show this replication was conducted in collaboration with is devoted to the investigation of scientific facts and fables, it can be challenged that there were too many methodological changes for this to be viewed as a direct replication. For instance, the presence of the celebrity likely caused a global context that could be even more salient than the water and land settings. In the publicly available peer-review reports, Baddeley (2020) commented on this study. For these reasons and others, he states: “I would not regard the attempted replication as close, robust or valid.

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I do however accept that the broad hypothesis that replication is important, but only if done appropriately” (p. 2). Noteably, a successful conceptual replication of Godden and Baddeley (1975) has been conducted previously (Martin & Aggleton, 1993). This principle of context reinstatement is not limited to environmental states and even applies to physiological states that can be otherwise detrimental to cognitive performance. Goodwin et al. (1969) asked participants to self-generate associates for cue words and were asked to recall their generated words in a second session, 24 hours later. Participants were randomly assigned to one of four groups, such that they were either sober or intoxicated for each of the experiment sessions. Those assigned to be intoxicated consumed between 8 and 10 ounces (250—300 mL) of 80-proof vodka, diluted with a soft drink. Blood alcohol content was measured to range between 0.08 to 0.14 g/dL and all participants showed signs of intoxication. Unsurprisingly, participants that were sober on both days had the best recall of the four conditions. However, those that were intoxicated on both days performed better than those that were intoxicated on day 1, but sober on day 2. These results have been extended to a variety of further manipulations, including the administration of an antihistamine (causing drowsiness; vs. placebo) (Carter & Cassaday, 1998) and virtual-reality contexts (underwater vs. Mars) (Shin et al., 2021). In the absence of access to the prior learning context, imagining the encoding context can be beneficial (Chu et al., 2003). Mood can also serve as a state-dependent context, as discussed further in Section 6.2 (p. 170). Contexts influence the availability of information. Contextual reinstatement highlights the importance of the environment in memory recall. However, memory isn’t always tested—or accessed—directly. Sometimes, we use indirect tests to assess memory processes. More generally, our understanding of the role of context in memory continues to develop (DuBrow et al., 2017; Stark et al., 2018).

Indirect tests Occasionally we can find ourselves in situations that are relatively context free, where recognition occurs incidentally and context retrieval becomes the goal. Mandler (1980) provides a poignant example of this process: Consider seeing a man on a bus whom you are sure that you have seen before; you “know” him in that sense. Such a recognition is usually followed by a search process asking, in effect, Where could I know him from? Who is he? The search process generates likely contexts (Do I know him from work; is he a movie star, a TV commentator, the milkman?). Eventually the search may end with the insight, That’s the butcher from the supermarket! (pp. 252–253) This has subsequently become known as the butcher-on-the-bus phenomenon.

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The opposite phenomenon can also occur, where a famous person’s identity is known, yet the surprisingness of the encounter causes people to discount the correct identification due to disbelief. Tony Hawk, a famous skateboarder, often shares stories of interactions online of people telling him that he “looks like Tony Hawk.” Most studies of memory assess either recognition or recall—both direct tests of memory. Memory processes can also be tested indirectly using other tasks, such as lexical decision, word-stem completion, or preference tasks. Lexical decision involves presenting a participant with a letter string, with response keys assigned with ‘word’ and ‘nonword.’ This task is quite straightforward and accuracy is near perfect, however, response time is a useful measure. If a task preceded the lexical decision task and words were repeated across tasks, response times will be faster for the previously shown (i.e., ‘old’) words relative to ‘new’ words. As will be further discussed over later chapters, response times are further facilitated by emotion and rewards. In this context, lexical decision serves as a measure of lexical accessibility and serves as an indirect test of memory. Some would describe recognition as a test of explicit memory and lexical decision as implicit memory. The point here is that considering these two tasks as direct and indirect tests of memory, respectively, is more appropriate. More generally, this serves as an example of the importance of considering the underlying assumptions and being precise about what the evidence actually shows—such as distinguishing between behavioural procedures and inferences about the underlying processes. (Kunst-Wilson & Zajonc, 1980; Johnson & Hasher, 1987; Jacoby & Hollingshead, 1990; Rugg, Mark, et al., 1998). While the majority of indirect memory tests necessitate an explicit response, such as a key press, this is not the sole behavioural response available. Eye tracking, for instance, can yield substantial insights into memory-related processes. This technique, which involves the recording of gaze direction or eye fixations, can provide indications of whether a stimulus is perceived as old or new (Hannula et al., 2010; Kafkas & Montaldi, 2011). The principle of novelty preference is particularly pertinent in this context. When presented with both an old and a new stimulus, the trajectory and duration of gaze can provide evidence of recognition (Ryan et al., 2000). In adult populations, the dynamics of fixation data, such as the gaze path, can offer rich information about memory processing and recognition (Kafkas & Montaldi, 2011; Damiano & Walther, 2019). However, substantial benefits of eye tracking emerges when conducting research with populations unable to provide explicit responses, such as pre-verbal children or non-human animals. In the case of pre-verbal children, eye tracking can offer valuable insights into their cognitive development and memory processes (Fantz, 1964; Rose et al., 2004; Righi et al., 2014). By observing their gaze direction and fixation duration, researchers can infer recognition or novelty detection. Similarly, eye tracking has proven invaluable in memory research involving non-human animals. Studies with non-human primates often use eye tracking as a response modality (Fantz,

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1956; Bernacchia et al., 2011; Meister & Buffalo, 2016). Relatedly, studies involving rodents often employ object recognition tasks, where the time spent exploring new vs. old objects can serve as an indicator of memory function (Dere et al., 2007). An interesting consideration here is if any test is effectively an indirect test of episodic memory, such as judgements of valence for previously presented stimuli (as discussed in Chapter 6) and decision making based on learned associations (Chapter 7). Are these truly based on episodic memory, or interactions with other memory systems? How does this influence our understanding of the division between episodic memory and other systems? Serving as an interesting foundation for these discussions, Stickgold et al. (2000) asked participants to play seven hours of Tetris over three days. Notably, five of these participants had amnesia due to bilateral medial temporal lobe damage. Though the amnesiacs did not remember playing the game in the prior sessions, their scores did improve gradually—albeit much more slowly than the non-amnesic participants. More interestingly, three of the five amnesic patients reported Tetris-like imagery from their dreams. For instance, one described: “I was just trying to figure out those shapes and how to get them aligned” (p. 353). Another patient described seeing “images that are turned on their side. I don’t know what they are from, I wish I could remember, but they are like blocks.” While there was no direct memory test, the report of a dream experience was intended to serve as an openended indirect test of memory, and provided evidence of memories of recent experiences in the amnesic patients.

3.3 Associations and order Memory is not limited to just recognition or recall of specific items, but can also be applied to information about how the item is related to other information. Associations are the simplest view of this, where items are conceptually related to other items. As an example, “Mark Twain”—the pen name for writer Samuel Clemens—is a river boating term meant to represent a water depth of two fathoms or 12 feet. A leadsman would call out “mark twain” to indicate that the water depth was a sufficient depth of two fathoms; Clemens took the name based on his past experiences as a riverboat pilot on the Mississippi River. Knowing this association demonstrates the power of memory and the importance of associations; now by knowing his pen name, you are able to also recall its origin and the contextual significance. Dating back to Aristotle (350 BC), some core principles of memory were understood (also see Burnham, 1888; Grant, 1932). These four laws are based on the relative associations between different items, and can be summarised as follows:

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(1) Law of Similarity: Items similar to each other are interconnected. For example, one might understand the function of memory by comparing it to a library. Just as a library organises and stores information for later retrieval, the memory system in our brain categorises, stores, and retrieves information when needed. (2) Law of Contrast: Opposite items can form associations. For example, in studying personality psychology, students might better understand the concept of extraversion by contrasting it with introversion. (3) Law of Contiguity: Items occurring close together in space or time tend to be associated. For example, if you always put on your running shoes before going for a run, over time, just the act of putting on your running shoes might trigger thoughts of running. (4) Law of Frequency: The more frequently two items co-occur, the stronger their association. For example, if you frequently eat a particular type of cake on your birthday, eating that same type of cake will remind you of previous birthday celebrations. In contemporary experimental studies, associations are often based on unrelated items, but this is primarily to ensure that participants are not aware of the associations before the experiment. Associations can also be between different types of items, such as an object and location. Within a larger context, items can also have an order—usually either spatially or temporally. These, again, can map onto semantic knowledge, such as knowing that the United Kingdom is east of North America, or the order of the alphabet. Continuing with the alphabet as an example, order can be relative, e.g., M is later in the alphabet than C, and W is one of the last letters. Absolute order in a sequence can also be tested, for instance, what is the 11th letter of the alphabet? (K.) A further example—that may not age well—is remembering the order of songs in an album. If you think back to a favourite music album, you may be able to not only hear the music in your mind, but also skip forward and hear the tracks in order, even without continuing through each song from beginning to end. With respect to episodic lists, an item could be relatively early in your shopping list, perhaps with the consideration that it’s kept near the entrance of the store. Caplan (2015) provides a thorough theoretical discussion on memory for associations and order within a common framework, as well as how they are commonly tested (also see Murdock, 1974).

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Memory tests When testing memory for associations there are generally two approaches: cued recall and associative recognition. Cued recall involves presenting one of the two associated items and the participant to respond with the other. The instruction here would be something similar to “recall the word that was previously shown with the one presented” (Calkins, 1894, 1896). Responses could be typed, said aloud, or handwritten on paper. Alternatively, associative recognition involves presenting a pair and asking the participant to respond “yes” or “no” if it matches what was presented during study (Underwood, 1974; Humphreys, 1976). Recognition typically involves ‘intact’ pairs—those that were studied, and ‘rearranged’ pairs—those include items that were studied, but not together. Rearranged pairs control for item recognition, as both have been seen during study, whereas a pair including new items would be easier to detect as not previously presented, not requiring associative memory. Rearranged pairs are typically randomly re-paired from those previously shown, but this can be varied systematically; Campbell et al. (2014) examined ‘near’ and ‘far’ rearranged pairs, based on their presentation order in study. Using the sequence of pairs shown in Figure 5.1 (p. 130), a rearranged pair of BIKE–COPE (near, lag 1) should have a higher false alarm rate than BIKE–ROCKET (far, lag 3), as the pairs contributing to the rearranged pair had been presented closer in time. Either of these approaches works well with both intentional or incidental associative learning. Specifically, participants may have been asked to deliberately remember that two words go together for a subsequent memory test. Or, the instruction may have been to provide a rating of how similar two words are, as an example of an incidental task. Which procedure is preferred usually relies on a variety of factors, including how many associations the participant is learning at a time, if the stimuli are words or pictures, and other goals of the study. Some associations can be easier to be remember than others, such as if they rely on pre-existing semantic knowledge, rather than being arbitrary items (Nott, 1975; des Rosiers & Ivison, 1988; Nelson et al., 2004). For instance, SALT–PEPPER is easier to remember than STOVE– FIELD. Some novel approaches to measure inter-individual creativity rely on similar principles of semantic knowledge structure, asking participants to generate a list of unrelated words (Beaty & Johnson, 2021; Olson et al., 2021). As an example, a list of highly unrelated words—that also correspond to ideas discussed across the chapters of this book—would be: WATER, SEAHORSE, CELEBRATION, GAMBLE, WRENCH, INTERLEAVED, PASSWORD. Semantic memory can also be assessed using cues. For instance, compare: “The boy played fetch with his ___.” and “The man drove home with his ___.” In either case, the sentence was followed by a picture—here, a dog (Piai et al., 2016). However, there is a stronger association in the first sentence than the second sentence, based on semantic knowledge. This degree of expectancy for the following word is known as cloze probability.

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Returning to episodic memory, two-stage tests are also useful in modulating the demands of the test; for instance, asking if the participant can recognise the cue before being given an association cued recall test (Madan et al., 2020) or providing a yes/no response on remembering the associate (akin to a cued recall test) before being given a 5-AFC associative recognition (Madan, Fujiwara, et al., 2017). The first approach here allows for disentangling different stages of an association-memory procedure, by testing for cue recognition and allowing for conditional analyses; only if the cue was recognised do we consider if they could remember the associated target. The second approach allows for a recall component (potentially making a test more hippocampal dependent) before providing potential recognition options. Again, analyses can be conducted based on whether the self-reported recall response was “yes” or “no,” allowing the researcher to distinguish stronger memories (e.g., if the participant responded “no” but then was able to choose the correct option when presented). Testing memory for order has even more options. As with associations, there is generally the choice of recall and recognition approaches. Participants could be asked to “recall all the words that you can from the previously presented list.” This instruction would be described as free recall as the participant is allowed to recall the words in any order (Kirkpatrick, 1894). Alternatively, the participant could be asked “do your best to recall the words in the order that they were presented.” This instruction is described as serial recall, as there was a request to maintain the order. These both allow many possible analyses to be conducted. The most basic measure would be to examine the overall proportion of words recalled, however, the recall probability for each list position—otherwise known as serial-position curve— could also be plotted, as in Figure 3.8. More nuanced analyses are also possible, such as the likelihood that the next recalled word is later in the list than the current recall (forward-transition probability), the likelihood of a recall at a given position relative to the current recall (lag-conditional recall probability, or lag-CRP), or analyses of temporal or semantic clustering (Kahana, 1996; Polyn et al., 2009; Caplan et al., 2015; Diamond & Levine, 2020). In terms of order-recognition measures, participants could be asked to do order reconstruction, where all of the items are available and need to be moved around into the correct sequence (Horowitz, 1961; Healy, 1974; Nairne, 1991). However, a more simple test would be to present two items to the participant at a time and ask them either “which was presented earlier” or “which was presented later,” a judgement of relative order (Sternberg, 1969; Muter, 1979; Hacker, 1980). Do consider that these instructions matter and do not produce identical behavioural results (Chan et al., 2009; Liu et al., 2014). This topic of how information is stored in memory and how to test it is an extensive one. While I will provide further information in the next sections, I strongly recommend Kahana (2012) Foundations of Human Memory to those who will be conducting their own experiments or otherwise would appreciate a more thorough understanding of memory structure and organisation.

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Serial position curve Even though people can remember items from a list, that does not mean they are all equally memorable—for many reasons. One factor that can influence item memorability is its position within a list. Consider if you were to present a list of 19 words to a participant one at a time and asked for a participant to recall as many words as they can, i.e., free recall. The overall pattern of results would look similar to Figure 3.8. The first three words would be relatively more likely to be recalled, known as a primacy effect. The last four to five words would also be preferentially remembered, known as a recency effect. These biases were first described by Nipher (1878) and Ebbinghaus (1885), and many times since (Thorndike, 1927; Crafts, 1932; Roediger, 1980a; Capitani et al., 1992).

FIGURE 3.8: Typical serial position curve for a free recall task. This analysis shows the probability of recall for each position that a word is presented. The first and last words are most likely to be recalled, known as the primacy and recency effects, respectively. The average recall for a 19-word list, across 28 lists, for 100 participants is shown in black. Serial position curves for the first ten participants are shown in light grey. Data from Lau et al. (2018). Murdock (1962) conducted a well-designed study where lists of different length were compared, producing the serial position curves shown in Figure 3.9. As is readily visible, the recency effect remains quite strong regardless of list length, whereas the recall probability for the intermediate

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items continuously decreases as the list length increases. However, if viewed as the number of items recalled (Figure 3.9C), rather than the recall probability, recall performance is relatively stable, varying only from 6 and 9 words. The number of words recalled can increase with longer lists, however. Naim et al. (2020) conducted a large-scale online study of free recall, with list lengths of 8, 16, 32, 64, 128, and 512 words—presented for 1.5 s/item. With list length 512, participants had an average recall of approximately 32 words.

FIGURE 3.9: Recall from a free recall task across varying list lengths. (A) Serial position curve showing probability of recall for each position for lists of 10, 15, 20, 30, and 40 word lists with presentation rates of either 2 s/item (white) or 1 s/item (grey), based on data from Murdock (1962). (B) Average recall probability across serial position, for each list length and presentation rate. (C) Same data instead plotted as number of items recalled.

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Primacy effects result from: (a) an increased ability to rehearse the first items, at the beginning they are the only items presented so far; and (b) they also represent a change in ‘context’ from before the list, where the participant was doing something else (Rundus, 1971). Recency effects result from: (a) having the least delay interval between presentation and test; and (b) being at the end—with no further items following them and before the context sufficiently changes over time (Postman & Phillips, 1965; Glanzer & Cunitz, 1966). Serial position curves for serial recall tend to have stronger primacy effects, as the recall is required to begin with the first items—and weaker recency effects as the recall of prior items increases the delay before they are reached (Jahnke, 1965). Including a short delay, even just ten seconds, between list presentation and free recall drastically decreases the magnitude of the recency effect (Glanzer & Cunitz, 1966; Ward et al., 2010). Recency effects tend to get stronger over successive lists, with evidence that it is a recall strategy that participants improve on with experience (Dallett, 1963; Hasher, 1973). This could be considered a ‘learning-to-learn’ effect associated with practice (also see Section 11.1 from p. 329). Serial position can also be examined for semantic memory information, such as for US presidents (Roediger & Crowder, 1976; Roediger & DeSoto, 2014) or Canadian prime ministers (Neath & Saint-Aubin, 2011), order of known media (e.g., song verses, Harry Potter book names, Pixar movie releases) (Maylor, 2002; Overstreet & Healy, 2011; Kelley et al., 2013; Overstreet et al., 2015), and general knowledge information (e.g., actor age, animal weight, US state area) (Kelley et al., 2015; Neath et al., 2016). Primacy effects are quite frequent in daily life, which is why forming a good first impression is important. This applies in many settings, from meeting a new person (Asch, 1946) to more specific circumstances, such as scientific article citation rates (Newman, 2009; Stevens & Duque, 2019; also see Carlson & Conard, 2011), job interviews (Carlson, 1971; London & Hakel, 1974; Shaheen, 2010), and jurors in a court trial (Weld & Roff, 1938; Lawson, 1968; Stone, 1969). Primacy has also been acknowledged to be important in decision-making studies (Denrell & March, 2001; Shteingart et al., 2013; Karmarkar et al., 2015). Evidence of recency effects in naturalistic situations is also strong, including daily news consumption (Xu, 2013) and gambling behaviour (Yu et al., 2008; Durand et al., 2021; Metz & Jog, 2023), among other situations (Lawson, 1968; McKenzie & Humphreys, 1991; Shaheen, 2010). It is generally known that a performance should ‘end on a high note’ or have a ‘grand finale’—applicable to social interactions, concerts, and fireworks displays. Recency effects are also convergent with the earlier described peakends rule (Section 2.5 from p. 51). Together, both primacy and recency are embedded in the advice of providing feedback to others based on a ‘sandwich model,’ where criticism is both preceded and followed by statements of praise. Other, more complex, analyses of retrieval dynamics also exist. For instance, given a specific word was the first recalled, what will be recalled next? Focusing on serial position, one could calculate the likelihood that the

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next word output will be the next word in the sequence or the previous word, i.e., those with lags of +1 or −1 respectively. This could also be done for any other possible transition. This analysis would be the lag conditional recall probability, or lag-CRP (Kahana, 1996). A measure of temporal clustering can be derived based on the overall pattern of recalling nearby items sequentially, rather than ‘randomly’ from the list (Polyn et al., 2009; Manning & Kahana, 2012; Dev et al., 2022). Alternatively, semantic features may lead to grouping of items that were not temporally nearby, such as recalling the animal words before the object words (Jenkins & Russell, 1952; Bousfield, 1953; Shuell, 1969; Polyn et al., 2005). MIN RE

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Naturalistic experiences and memory narratives Diamond and Levine (2020) provide an excellent example of a how memory for order can be examined in naturalistic experiences. In their study, participants followed an audio-guided tour of an entrance area of a hospital, including many paintings, sculptures, and other features—such as the gift shop. The guide highlighted specific items along the tour and determined the item viewing sequence, but the tour was partially self-paced as the participants had to press a button when they arrived at the next stop. The tour took 20–30 minutes to complete and featured 27 items. Two days later, participants were asked to recall their tour experience. Serial position curves tend to be relatively smooth, but this is after item order has been randomised and averaged across multiple lists and people. However, there are some instances where item order is not randomised and the serial positions have clearly visible ‘jagged’ contours, due to itemmemorability effects. This is evident in the results of Diamond and Levine (2020, Fig. 4), where one of the events with the highest recall rates, despite being an intermediate item (position 9 of 27), was an Andy Warhol painting. Moreover, some items were described in more detail than others and some were unambiguously less interesting—such as walking past the marketplace area. This is not intended as a critique of the study, but rather highlighting an important feature of a naturalistic example. In everyday experiences, item properties influence recall beyond the effects of order—whereas these effects are typically adjusted for in experimental studies.

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In an innovative study, Chen et al. (2017) asked participants to watch an episode of the BBC TV show Sherlock while in a magnetic resonance imaging (MRI) scanner (A Study in Pink, loosely based on A Study in Scarlet, the first appearance of Sherlock as a fictional character; Doyle, 1887). Participants were subsequently asked to verbally describe what they saw in as much detail as they could, while MRI data was again collected. In the original publication, complex analyses were done to compare patterns of brain activity between participants when watching the show and brain activity for watching with narrative recall. Near the beginning of the episode, there is a scene of a police press conference that lasts just over two minutes. The following is an excerpt corresponding to this scene, from a participant that recalled many events (Participant 13): At that point it switches to a news conference. And the woman you later [inaudible] is Sergeant Donovan, and then the man, the Private, Sergeant…Are at a news conference with lots of supporters and they’re answering questions about the murders, or well no the suicides. And she says yes there’s clearly a linkage between these now, there’s been three deaths where the same poison that’s been taken. And the court reporters, especially one woman, questions how can there be a link between suicides? Like basically skepticism, like suicides can’t be linked. And the seemingly incompetent Sergeant answers, well there’s the same poison, we’ve got our best people on it. And when he says there’s a link, like there are suicides, like everyone in the room, all their phones go off. And the screen shows a bunch of, the screen shows the words and they all show wrong. So they’ve clearly all gotten a text message that says wrong. And then he starts to says something else, like we’ve got our best people working on it, and I think he says, he gets a text message that says wrong as well. And then this woman asks, well so how can we protect ourselves? And he kind of flippantly responds to her, saying don’t commute suicide. And then Sergeant Donovan says [inaudible] clearly implying that this is a woman that we should answer with sincerity. And so the man says oh well take all precautions, we’re as safe as we thinks ourselves. And they all get a text that says wrong. And each of those the first texts, the woman had said if you’ve all received a text, please ignore it. She seems annoyed. And then the man gets a text that says, if you have any questions, you know where to find me, SH. And the pair walk out of the news room and the woman is frustrated, like we have to figure out how he does that, we have to make him stop. And the guy is like oh if I knew how he did it, I would stop it. (text from raw narrative data)

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For comparison, the following is an excerpt from the narrative recall from a participant who provided far less details (Participant 4): And that flashes to a news conference where there’s the chief inspector and there’s a bunch of reporters talking about, or asking questions about what happened. And each time they ask a question that the chief inspector responds to they get a text saying nope, or wrong. And then, finally after like the third time, the chief inspector gets a text saying you know where to find me, signed SH. Heusser et al. (2021) modelled the representation trajectory of sections of the narrative in ‘topic space’ and compared participants’ narrative recall to detailed annotations of the episode’s events, using the raw narrative data from Chen et al. (2017). As briefly described earlier, topic space is a computational approach for approximating the network structure of semantic knowledge. These trajectories are shown in Figure 3.10—participants who did well were able to retain nearly all of the key events and remember them in order. Participants who fared poorly had less events in their narrative and sometimes recalled them out of order. Conventional recall analyses were also conducted and reported, such as serial position curves and lag-CRP. Some other studies have additionally conducted analyses on the MRI data from Chen et al. (2017), highlighting the advantages of using naturalistic designs, rather than the more typical and constrained task designs (Kim, Weber, et al., 2020; Kumar et al., 2020; Lee Masson & Isik, 2021)—also see Section 14.1 (p. 448).

FIGURE 3.10: Topic trajectories for BBC Sherlock episode. (A) Original TV episode, based on annotated video. (B) Narratives for participants with relatively more or less events recalled. Adapted from Heusser et al. (2021).

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3.4 Memory capacity While memory studies generally use either words or pictures as stimuli, they are not equally remembered as items. Pictures are more memorable than words, known as the picture superiority effect (Burtt, 1916; Shepard, 1967; Paivio et al., 1968; Nelson et al., 1976; Dewhurst & Conway, 1994; Ally et al., 2009). Standing (1973) demonstrated that memory for pictures is incredibly vast, as participants were shown 10,000 pictures, each for just five seconds, and afterward their recognition memory was tested. The surprising result was that participants were able to remember an average of 6,600 pictures, with some being able to recall more than 8,000. This general finding has been corroborated by later work—often with more difficult test trials by using ‘similar’ lures (Vogt & Magnussen, 2007b; Konkle et al., 2010; Jenkins et al., 2018; Draschkow et al., 2019), including the work described earlier in this chapter by Brady et al. (2008). Examining memory for a specific category where we would expect people to have relatively precise and expansive memory, Jenkins et al. (2018) found that participants could remember around 5,000 faces. MIN RE

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The visual properties of pictures are also relevant, with better memory for larger pictures (Masarwa et al., 2022), even when the size manipulation is illusory, with the pictures presented centrally within an Ebbinghaus illusion (Jeong, 2023). Visual properties in mental imagery can also matter—after some practice, Luria’s S., Solomon Shereshevsky, found that making imagery larger, and more visible, improved his performance: I know that I have to be on guard if I’m not to overlook something. What I do now is to make my images larger. Take the word egg I told you about before. It was so easy to lose sight of it; now I make it a larger image, and when I lean it up against the wall of a building, I see to it that the place is lit up by having a street lamp nearby…I don’t put things in dark passageways any more…Much better if there’s some light around, it’s easier to spot then. (Luria, 1968, p. 41)

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It has long been understood that memory performance will be higher for recognition than recall (sometimes referred to as reproduction) (Kennedy, 1898). Recognition can be further divided into tests of identification or selection (Baldwin & Shaw, 1895). In identification, a single item is presented and the participant needs to identify if it was previously shown. In more modern terms, this would be yes/no, remember/know, or confidence-based old/new recognition test. Sometimes these involve multi-step tests, such as an old/new judgement followed by a confidence rating. In selection, more than one item is presented and the participant must select the previously seen item from an array (of at least two options). Some studies have examined memory in non-human animals and observed impressive capacity as well (Cook et al., 2005; Fagot & Cook, 2006). For instance, Kendrick et al. (2001) demonstrated that sheep can recognise 50 other sheep faces for at least two years—a retention interval of over 800 days! While humans can have difficulties identifying other animals, many animals have been able to remember and recognise individual humans (Sugita, 2008; Levey et al., 2009; Huber et al., 2013; Eatherington et al., 2020). Movie actors provide a surprising source of converging evidence. When filming a Western movie, Liam Neeson reported being confident that a horse on the movie set was one that he worked with in the past: “I’m saying this horse knew me, he actually remembered me from another western we made a while back…He whinnied when he saw me. And pawed the ground” (Zhou, 2018). Russell Crowe described working with horses and being remembered: “There’s a horse, George, who I gave the speech in the forest in Gladiator on, years later he was on the set of Robin Hood and we would have a chat every day. Same with the white horse, Rusty, in Robin Hood. We chatted again on Les Mis. Lifelong friends.” Animals are even better at recognising unique individuals in their own species—i.e., conspecifics and an own-species bias, as discussed in Section 8.5 (p. 256).

3.5 Broader memory principles This chapter was primarily a brief orientation to the memory systems, tests, and features. Now that we have a reasonable foundation, we can discuss some underlying principles that are critical in understanding the literature and what inferences we can make.

Limitations to study generalisability Memory studies vary in several dimensions. For instance, one study could use emotional and neutral pictures, while another study uses words that vary in self relevance. If the first example of the emotional study was conducted with healthy young adults, we may not expect consistent results in other groups of participants, such as older adults or young adults with depression. So far, these

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represent two dimensions, materials and participants, but other critical ones exist as well. Results may also vary based on whether learning was intentional or occurred incidentally through some other task, the orienting task, or if tested using old/new recognition or free recall, the critical task. Jenkins (1979) proposed a ‘tetrahedral model of memory experiments,’ suggesting that these four properties were critical for memory studies—with each of them representing a vertex of a tetrahedron, as illustrated in Figure 3.11. Based on this view, every memory study and its results are defined by interaction of its specific design parameters, and a change to any of these four parameters may be relevant to the generalisability of the findings. Zinchenko independently developed a similar proposal (Meshcheryakov, 2008); this view has been further explored by Roediger (2008) and Talarico (2022).

FIGURE 3.11: Jenkins’ tetrahedral model of memory experiments. As an example of the importance of these parameters, we should consider the word-frequency paradox. Word frequency is defined as how common a word is in language use and is typically measured by the frequency of occurrence in a large corpus of text (Kučera & Francis, 1967) or in popular media, such as through the subtitles of films and television shows (Brysbaert & New, 2009; van Heuven et al., 2014). Consider a study where a sample of young adults is presented with a list of words including those both high and low in word frequency and asked to intentionally remember the words. If memory is then tested using free recall, the participants will recall more high-frequency words than low-frequency words. However, if memory was instead tested using an old/new item-recognition procedure, we would instead observe better memory for the low-frequency words than the high-frequency words. This ‘paradox’ has been observed in many studies over the decades and is one of the classic findings in the memory literature (Hall, 1954; Gregg, 1976; Malmberg et al., 2004; de Zubicaray et al., 2005). A key difference between these two tests is that high-frequency words are easier to generate and output, as we do so more often than low-frequency words. For instance, they are likely easier to bring to mind and produce, even if considering only language activation models, rather

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than memory per se. In contrast, low-frequency words are encountered less often, so they stand out more so when they do occur—there is less confusion of “Did I last see this word in the experiment or elsewhere previously?” As such, low-frequency words are easier to recognise and identify as recently seen. In this example, only the critical task was varied, but changes to one or more other aspects of the tetrahedral model’s parameters would similarly require consideration to determine if an associated change in memory performance would occur.

Memory system interactions Experimental procedures are often designed to focus on a particular memory systems, but this is not always the case. Here we will be focusing on episodic memory, but semantic memory and conditioning processes sometimes overlap. The word-frequency paradox is one clear example of this; high- and lowfrequency words can be equally presented in the experiment, but still differ in their pre-experimental properties. If a list of words is presented and one word was in a different font size or colour, it would be more likely to be remembered (Hunt & Elliot, 1980; Karis et al., 1984; Parker et al., 2006). Alternatively, if the list consisted of a specific category of words, e.g., animal names, and one inanimate object, the object word would stand out. The ‘odd one out’ would also be better remembered if it was a list of objects with one animal name (Hunt & Mitchell, 1982; Strange et al., 2000). This principle is most commonly referred to as distinctiveness, or the von Restorff effect or oddball procedure (Karis et al., 1984; Fabiani et al., 1990; Huettel & McCarthy, 2004). In these instances, the ‘odd’ stimuli is distinct within the list itself. This effect is primarily attributed to von Restorff (1933) (also see Hunt, 1995; MacLeod, 2020). MIN RE

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The word-frequency case is different, however, this effect is due to a contrast in distinctiveness relative to semantic knowledge and daily life as a context. This also can occur when words are used in atypical contexts (Waddill & McDaniel, 1998). Schmidt (1991) proposed that this be referred to as ‘secondary distinctiveness.’ In contrast, the within-list distinctiveness effect is relative to the local context within the experiment or even specific list, and is labelled as ‘primary distinctiveness.’ While this may appear to be an overly arduous discussion of a technical point, it is a fundamental principle for much of this book. For instance, although studies of emotional memory often present

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emotional and neutral items equally often within the experiment, emotional experiences are far more infrequent than mundane ones in daily life. Another critical example of interactions between episodic and semantic memory systems is the Deese-Roediger-McDermott (DRM) paradigm (Deese, 1959; Roediger & McDermott, 1995). When presented with a list of semantically related words, people will falsely recall or recognise a predefined target word as also being presented. For example, read the following list: HOUND, PUPPY, BITE, MUTT, PET, BEWARE, BONE, TAIL, CAT, ANIMAL, PAW, POODLE, FLEA, BARK, LASSIE, VET. Was the word DOG present in the list? If this list was presented one-ata-time and done in an experimental setting, we would expect about 69% of readers to respond “yes” (Watson et al., 2003). The phenomenon was originally reported by Deese (1959) across 36 lists of 12 words each, followed by free recall, in a sample of 50 participants. For each list, there was a target word. While some lists were not successful, with the target word never falsely recalled (i.e., an intrusion), the lists with target words of SLEEP and NEEDLE fared much better, eliciting the target word as a response in 44% and 42% of participants, respectively. This work fell into relative obscurity for several decades, until Roediger and McDermott (1995) further developed the procedure and more directly connected it to the false-memory literature. Incidentally, Kirkpatrick (1894, p. 608) proposed a similar procedure many decades prior. In the years since, this procedure has become widely used and has been found to be highly replicable (Gallo, 2010). This procedure is designed to assess experimentally induced false memories, but more generally serves as a demonstration of semantic knowledge interfering with an episodic memory task. Conceptually, this phenomenon is explained as a spreading of activation throughout the semantic network, where concepts near episodically presented items are also ‘brought to mind’ to a lesser degree (Collins & Loftus, 1975). When this spreading activation occurs from several nearby items, the target concept is sufficiently activated that it feels remembered, even though it was not presented. More broadly, false memory is complicated—the DRM procedure and lostin-the-mall study (Section 2.3 from p. 43) are quite different. Patihis et al. (2018) and Bernstein et al. (2018) both conducted different false-memory tasks with the same participants and found that susceptibility to false memories in one task was unrelated to other tasks. As everyday behaviour, as well as many experiment-based observations, are best explained by interactions between memory systems, this is yet another critical tenet to bear in mind as we investigate memory further. This highlights the diversity of memory processes and underscores the importance of studying each memory system in its own right, as well as in relation to each other.

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End of chapter wrap-up Summary There are the two main types of long-term memory: semantic and episodic memory. Semantic memory is described as our memory for facts and general knowledge about the world, while episodic memory is our memory for specific events in our lives. Memories are not all the same, but can also vary in strength and quality. Some approaches used to assess these are the levelsof-processing framework and indirect tests of memory. Memory is not just about recalling specific items but also understanding how these items are related to other information. Some of these are highlighted in Aristotle’s four laws of association (similarity, contrast, contiguity, and frequency). Serial position effects are important in evaluating studies involving lists of items, as well as real-world phenomena. People can remember a surprising amount of items, particularly pictures. The tetrahedral model of memory experiments characterises the key dimensions to consider when reading a memory study, including materials used, participants involved, and the type of learning and testing procedures employed. Finally, considering how multiple memory systems interact can provide insights into many well-established findings.

Reminder cues

Quick quiz 1. You are watching a historical movie and recognise that the costumes and settings are accurate for the period it represents. This recognition primarily involves which type of memory? (a) Visual memory (b) Historical memory (c) Episodic memory (d) Semantic memory

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2. Consider a situation where you meet someone at a social event. You don’t remember their name, but you remember that they were wearing a red sweater and that you talked about a recent movie. According to the continuum model of recognition memory, how would you describe your memory strength for this encounter? (a) Very strong, as you remember specific details. (b) Very weak, as you can’t remember their name. (c) Somewhere in the middle of the continuum. (d) Not applicable, as the continuum model doesn’t apply to this situation. 3. Dr. Lin is interested in examining memory for order of events. She asks participants to recount the events of a popular movie in the order they occurred. According to the text, what type of memory test is this researcher employing? (a) Order reconstruction (b) Cued recall (c) Judgement of relative order (d) Serial recall 4. A researcher presents several items to a participant and then, later, asks them to pick out the items they’ve seen before from a larger set. Which term best describes this type of memory test? (a) Recall (b) Identification (c) Selection (d) Indirect

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Memories that matter 5. What is the difference between primary and secondary distinctiveness? (a) Primary distinctiveness refers to the effect of the word’s frequency on memory, while secondary distinctiveness refers to the effect of the word’s orthography on memory. (b) Primary distinctiveness refers to the distinctiveness of a word within the local context of an experiment or a specific list, while secondary distinctiveness refers to distinctiveness relative to semantic knowledge and daily life as a context. (c) Primary distinctiveness refers to the distinctiveness of a word in relation to other words in the same semantic category, while secondary distinctiveness refers to the distinctiveness of a word in relation to words in different semantic categories. (d) Primary distinctiveness refers to the distinctiveness of a word based on its visual features, while secondary distinctiveness refers to the distinctiveness of a word based on its semantic features.

Thought questions ▶ Remember/know and mnemonic similarity tasks are both approaches for assessing the detail of memories. What are relative benefits of either approach? ▶ What are some ways that different encoding tasks influence later memory? ▶ Are associations unidirectional or bidirectional? How could this be assessed?

Further reading ▶ Brady, T. F., Konkle, T., Alvarez, G. A., & Oliva, A. (2008). Visual long-term memory has a massive storage capacity for object details. Proceedings of the National Academy of Sciences USA, 105(38), 14325– 14329. doi: 10.1073/pnas.0803390105 ▶ Diamond, N. B., & Levine, B. (2020). Linking detail to temporal structure in naturalistic-event recall. Psychological Science, 31(12), 1557–1572. doi: 10.1177/0956797620958651 ▶ Tulving, E. (2002). Episodic memory: From mind to brain. Annual Review of Psychology, 53(1), 1–25. doi: 10.1146/annurev.psych.53.100901.135114

Chapter 4 Individual variability

The advantage of a bad memory is that, several times over, one enjoys the same good things for the first time. — Friedrich Wilhelm Nietzsche (1878)

Why is it that solitary confinement, without labor, is regarded as the severest form of imprisonment? It is because the lonely victim can find nothing to do but to remember. And this incessant remembering has often proved more than the mind could bear. — D. B. Coe (1849)

Within the typical population, a number of lifestyle and experiential factors have been related to individual variations in memory ability. Some of these are well acknowledged, like aging. Other factors are also relevant—education, social support, and exercise are associated with better memory ability (Hill et al., 1995; Ertel et al., 2008; Coutrot et al., 2018; Loprinzi et al., 2021). Sleep quality is also important for maintaining episodic memory. A recent metaanalysis of 54 studies examining associations between sleep characteristics, memory, and aging found that more time spent in the slow-wave sleep stage and less time spent awake after sleep onset to be better for later memory (Hokett et al., 2021). Loneliness and social isolation have been associated to lower memory performance in a meta-analysis (Kang & Oremus, 2023); other negative influences can include poor cardiovascular health, chronic stress, and childhood exposure to lead (Gross & Hen, 2004; Hanson et al., 2015; Cansino et al., 2018; Lee et al., 2022). Our memory ability is not a constant, not only due to slow changes such as aging, but across different instances. Some transient factors can also relate to inter-individual variability (Madan, 2014a). The use of memory strategies can explain some of this variance, discussed in detail in Chapter 11. The use of drugs, spanning daily habits—caffeine consumption—and medication not 99

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commonly known to have memory effects (Zhang & Madan, 2021; de Cates et al., 2021), and brain stimulation (Hamani et al., 2008; Suthana et al., 2012; Javadi et al., 2012; van der Plas et al., 2021) can also contribute to differences. Kahana et al. (2018) conducted a large-scale study of 79 participants each completing 23 experimental sessions. By having so many sessions, Kahana and colleagues were able to examine factors that affected within-participant but inter-session memory performance. Between sessions, the range of mean performance across lists was around .20 to .30 for most participants. They found significant effects for amount of sleep the prior night, self-rated alertness, and time-of-day. However, participants also varied greatly in their proportion of words recalled—those that performed worst had mean list recall proportions near .20, those performing best had recall proportions near .90. Though some episodic memory variability can be explained by wellestablished factors such as age, not all individuals of the same age have the same recall performance. Some individuals remember much more than others. Logie (2018) and Unsworth (2019) both tackled the broad question of inter-individual variability in episodic memory from different approaches. Logie (2018) examined the literature and identified a series of factors that influence memory performance: imagery ability, aging, and domain-specific expertise. My own view is very much in agreement with this, and I wish I had come across this paper earlier on as I wrote this book. As you will find in this chapter, I have converged on a similar set of inter-individual factors. That said, we present these points differently and use different studies as evidence, so this paper is still very much worth reading. Unsworth (2019) took a more systematic approach, using a confirmatory factor analysis to examine the relationships between different memory test types (e.g., source recognition, delayed free recall, and judgements of recency with pictures) related to their overarching test categories, and ultimately to longterm memory. Another analysis involved examining the relationship between memory and other cognitive abilities—including fluid intelligence, crystallised intelligence, working memory, and attention control. Other processes that were considered to have individual differences were forgetting, interference control, susceptibility to false memories, general retrieval abilities, and strategies. Here, Unsworth attempts to integrate this variety of factors into a common framework. Despite the thoroughness of this review, Unsworth ends with “In writing this review, the most important thing I have learned is that we have only scratched the surface in terms of understanding individual differences in [long-term memory]” (p. 126). Also see Stanek and Ones (2023) for a comprehensive meta-analysis of the relationships between personality traits and cognitive abilities, including memory.

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4.1 Aging Most well known of the effects of aging on memory is a relatively steep decline in episodic memory ability with age, as shown in Figure 4.1A. Tests of semantic knowledge, in contrast, hold constant or even trend upwards. Some other aspects of cognitive function are also relatively stable across age, such as interference control (e.g., Stroop accuracy) (LaPlume et al., 2022). Notably, these results are based on cross-sectional data. Similar findings have been reported often in the literature (Park et al., 2002; Salthouse, 2003; Hedden & Gabrieli, 2004). However, when longitudinal data is presented, age-related declines appear much shallower—see Figure 4.1B (Hedden & Gabrieli, 2004; Salthouse et al., 2004; Rönnlund et al., 2005; Singh-Manoux et al., 2012). While both of these findings have been sufficiently established, including their dissimilarity, this can be resolved. Rönnlund et al. (2005) demonstrated that if cross-sectional data is adjusted for cohort differences in education, there is a much weaker decline in memory performance with age. Moreover, repeated administrations of the same cognitive assessment results in improved performance (McCaffrey & Westervelt, 1995; Collie et al., 2003; Wilson et al., 2009; Gross et al., 2018)—also see Section 11.1 (p. 329). If longitudinal data is adjusted for effects of repeated testing, the age declines are more pronounced—to the degree that the differences between cross-sectional and longitudinal designs has been accounted for, as shown in panels C and D of Figure 4.1. Considering individual performance (i.e., longitudinal), age-related decline generally does not occur until the 60s (Salthouse et al., 2004; Singh-Manoux et al., 2012). MIN RE

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Even though semantic memory does not decrease much with age, it is important to acknowledge that the network itself will continue to vary with experiences. As a child you might know the names and characteristics of different dinosaurs (Chi & Koeske, 1983; Gobbo & Chi, 1986; Johnson et al., 2004), but these are likely to be lost over subsequent years. Similarly, when in school you may have learned another language, but did not use this knowledge much for years later. When you think back to this information, now learned decades ago, performance will be much poorer than when the lessons were only a year or two ago. Bahrick (1984) tested exactly this, assessing Spanish knowledge in nearly 800 participants who had taken Spanish classes in high school or college (and some who had never, as a comparison). Across all participants, the most recent Spanish instruction occurred between 1 and 50 years ago. Participants ranged in age from 17 to over 70. Results indicated

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FIGURE 4.1: Age-related differences in memory performance. Episodic memory is plotted in a solid black line; semantic memory is plotted with a grey dashed line. (A) Cross-sectional data. (B) Longitudinal data. (C) Education-adjusted cross-sectional data. (D) Practice-adjusted longitudinal data. Adapted from Rönnlund et al. (2005). that information was forgotten over the first five years, but then remained relatively stable for many decades, despite not being used or rehearsed. As semantic knowledge, it is relatively resilient to forgetting, but not impervious (also see Bahrick et al., 1975; Bahrick, 1979). A limitation of this study was the cross-sectional design, however, this was followed by a nine-year longitudinal study further demonstrating longterm retention after spaced learning (Bahrick et al., 1993). Conducting such an ambitious study, with 26 sessions in the 56-day interval schedule spanning nearly four years, was a family undertaking. The four participants—and study authors—were parents and two daughters, all psychologists. There are also developmental changes in episodic memory, these are briefly discussed in Section 8.2 (p. 239).

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While we all vary in cognitive abilities, some researchers have developed composite scores to obtain more robust and sensitive measures than could be indexed by individual tests. A variety of approaches have been developed over different studies—typically to estimate composite scores for memory and executive function (Glisky et al., 1995; Gibbons et al., 2012; Davidson & Jensen, 2023). From the large-scale Alzheimer’s Disease Neuroimaging Initiative (ADNI) study, each of these composite scores has been developed. The memory composite score is based on measures from the Rey Auditory Verbal Learning Test (RAVLT), Alzheimer’s Disease Assessment Schedule— Cognition (ADAS-Cog), Mini-Mental State Examination (MMSE), and Logical Memory (Crane et al., 2012). The executive function composite score is based on measures from the WAIS-R Digit Symbol Substitution, Digit Span Backwards, Trails A and B, Category Fluency, and Clock Drawing (Hedden et al., 2012). These composite scores, taking into account diverse tasks, provide a more comprehensive understanding of an individual’s cognitive profile, particularly useful in studies of cognitive aging and neurodegenerative diseases. They further offer more robust data for statistical analyses and clinical applications, thereby enhancing the precision and reliability of cognitive assessments. Examining brain structure can also provide insight into how cognitive functions change with age (Small, 2001; Hedden & Gabrieli, 2004; Park & Reuter-Lorenz, 2009). Figure 4.2 provides examples of how the brain changes with aging. The most pronounced indications of age-related atrophy are enlargement of the ventricles (particularly the lateral ventricles), the width of sulci, and the size of the hippocampus (Drayer, 1988; Scheltens et al., 1992, 1997; Walhovd et al., 2011; Madan & Kensinger, 2016, 2017). Measures of brain microstructure also change with age, such as cortical myelination and iron accumulation (Draganski et al., 2011; Grydeland et al., 2013; Lorio et al., 2014; Callaghan et al., 2014; Carradus et al., 2020). A more nuanced discussion of the relationship between brain and behaviour, with an emphasis on memory, will be covered in the next chapter. The acknowledgment of age-related declines in episodic memory is a fact of life, but our understanding of this is nearly wholly from humans. Recently some studies have demonstrated similar declines in other species, such as in rats (Febo et al., 2020), dogs (Sanches et al., 2022), and monkeys (De Castro & Girard, 2021)—with the caveat of the aforementioned issue of the presence of episodic memory in non-human animals. Apart from measuring memory performance directly from tests of recall or recognition, inter-individual variability can also be assessed using questionnaire methods. Gopi and Madan (2023) provided a comprehensive overview of subjective memory measures (also see Herrmann, 1982). Some of these relate to self-efficacy, for instance, “If someone showed me the pictures of 16 common everyday objects, 1 could look at the pictures once and remember the names of 2 of the objects” (Berry et al., 1989, p. 713). Others look at memory complaints, such as the frequency that you “Forgetting where you

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have put something; losing things around the house” (Sunderland et al., 1983, p. 355). Others yet have multiple dimensions within the same questionnaire (Dixon et al., 1988; Gilewski et al., 1990; Troyer & Rich, 2002).

FIGURE 4.2: Example visualisation of how individual brain structure gradually changes longitudinally. Coronal sections of structural MRIs showing the hippocampus and third ventricle. Three individuals are shown, those in the first row show two individuals with MRIs acquired at both 65 and 67 years of age, one healthy adult and one with Alzheimer’s disease. A neuropsychology test score (MMSE) is shown below each image to convey a measure of cognitive abilities. The second row shows an individual from 83 to 92 years old. Note that the brain structure looks visibly similar between the 67-year-old Alzheimer’s patient and 92-year-old healthy adult, though there is a marked difference in their MMSE scores. MRIs can provide insight into cognitive abilities, but many other factors must be considered when interpreting how these may relate to cognitive abilities. Adapted from Madan (2021b).

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4.2 Variability in memory ability With increasing age, an important symptom that can develop is the reporting of subjective memory complaints (or subjective cognitive decline [SCD]) (Jessen et al., 2014, 2020; Gopi & Madan, 2023). This diagnosis is made when there are no objective memory deficits, otherwise the individual would be instead classified as mild cognitive impairment. Several questionnaires have been developed to assess subjective cognitive decline (Gilewski et al., 1990; Lubitz et al., 2019; Ibnidris et al., 2022; Gopi & Madan, 2023). Table 4.1 provides examples of questions used in these subjective assessments. The individual is still performing within a healthy range on standardised memory assessments, but it is impossible to formally assess any deficits since pre-morbid memory ability was not assessed and cannot be used to evaluate potential intra-individual changes. While this is inherently a limitation, subjective memory complaints are nonetheless a predictor of the later development of later objective deficits (Burmester et al., 2016; Vogel et al., 2017; Taylor et al., 2018; Slot et al., 2018), particularly in those that were initially higher in ability (Wilson et al., 2009). A critical consideration of those with subjective cognitive decline is that they may be deploying compensatory strategies, such as using a narrative strategy when learning a list of words. This would be a clear, applied example of what is represented by the notion of cognitive reserve (Pettigrew & Soldan, 2019; Cabeza et al., 2018; Stern et al., 2020; Berezuk et al., 2021; Chan et al., 2021; Berkes & Bialystok, 2022). TABLE 4.1: Example questions for subjective memory complaints. Each is rated on a scale, from never to always. Adapted from Gilewski et al. (1990) and Lubitz et al. (2019). 1. It’s hard to recall recent events (e.g., holidays or birthday parties). 2. I have to make notes to prevent forgetting information. 3. I have trouble matching names to the faces of people I’ve recently encountered. 4. As you are reading a novel, how often do you have trouble remembering what you have read… (a) in the opening chapters, once you have finished the book. (b) three or four chapters before the one you are currently reading. (c) the chapter before the one you are currently reading. (d) the paragraph just before the one you are currently reading. (e) the sentence before the one you are currently reading.

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Some genes have been well studied in relation to memory performance, particularly APOE. This gene is located on chromosome 19 and codes for a protein, apolipoprotein E (or APOE), which is synthesised by astrocytes and is involved in cholesterol metabolism. More importantly, it has been found to exist in three variants (alleles) in humans: e2, e3, and e4. The frequency of the three alleles is estimated to be around 8%, 75%, and 15%, respectively (Farrer et al., 1997; Heffernan et al., 2016). However, as with all genes, everyone has two copies; around 28% of the general population has at least one copy of the e4 allele. (N.B. If 15% of alleles are e4, 85% are not e4. Thus the likelihood of having at least one e4 alleles is 1 − (1 − .15)2 = 1 − .852 = 1 − .72 = .28. For a more detailed explanation of similar logic, see Madan, 2016b.) Compared to non-carriers, individuals with one e4 allele are three times more likely to develop Alzheimer’s disease. Those with two e4 alleles are 10 times as likely to develop Alzheimer’s disease, with it estimated to onset in life in 91% of these individuals (Corder et al., 1993). The e2 allele is less common in the population, but has been found to have protective properties. The specific mechanisms whereby APOE variants have evolved and influence cognition has been a vibrant topic of study (Finch & Stanford, 2004; Liu et al., 2013; Belloy et al., 2019). Despite being related to episodic memory impairments in older age, there is evidence that the e4 allele confers better memory early in life (Han & Bondi, 2008; O’Donoghue et al., 2018; Eich et al., 2019). This variability is also reflected in brain activity (Filippini et al., 2009; McDonough et al., 2020). This impact of a gene having different effects across the lifespan is sometimes referred to as antagonistic pleiotropy. MIN RE

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While APOE-e4 is associated with Alzheimer’s disease risk, it has also been related to measurable effects in young adults. For instance, Kunz et al. (2015), observed differences in spatial navigation strategy when exploring a virtual environment used as the basis for an object-location memory test. However, in this sample of 38 e4 carriers and 37 non-carriers, no differences were observed in memory performance. Additionally, a relationship was observed between navigation spatial organisation representations and hippocampal activity observed using brain imaging. This difference in navigation strategy has since been replicated using data from the large-scale citizen science study, Sea Hero Quest (Coughlan et al., 2019). In another study, despite e4 carriers exhibiting no impairments in a comprehensive neuropsychological battery, worse autobiographical memory was observed (Grilli et al., 2018). Specifically, less details internal to specific remembered events were generated in narratives

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related to memory in all assessed time periods—ranging across adolescence, young adulthood, to earlier in the same year, and within the last week. Narrative details generated that were external to the remembered events were comparable between e4 carriers and non-carriers. (For additional information about autobiographical narratives, see Section 8.1 from p. 231.) A follow-up study indicated that impairments in e4 carriers were particularly related to fluency in producing self-related semantic information (‘personal semantics’) and not episodic memory ability (Grilli et al., 2021). Again, this was despite no deficits in standard neuropsychological tasks. In a systematic review and meta-analysis of studies examining how individuals without dementia view finding out about Alzheimer’s biomarkers, van der Schaar et al. (2023) found that most preferred to know their APOE biomarker status. Negative results (i.e., not being an e4 carrier) led to relief, while positive biomarkers induced anxiety but also clarity. Personal motivations for interest in biomarker status included gaining insight, improving lifestyle, and preparing for the future. Actor Chris Hemsworth has been hosting a TV show, Limitless with Chris Hemsworth (2023), where he explores different health topics. In the fifth episode in the series, the topic is memory—Hemsworth finds out that he is not only an e4 carrier, but that both APOE alleles are e4. He then discusses how he processes this new information about his Alzheimer’s risk. Other genetic markers can influence memory for past experiences more indirectly, by influencing the initial perception. A prime example of this is the taste of cilantro (coriander leaves), long known to have medicinal properties and described as fresh or citrusy (Pliny the Elder, 79 AD, Book 20, Ch. 82); those who dislike it describe it as tasting ‘soapy’ or even like insects (Gerard, 1597; Mauer & El-Sohemy, 2012). Julia Child, acclaimed cooking author, told interviewer Larry King in 2002 that she never ordered dishes with cilantro: “I would pick it out if I saw it and throw it on the floor.” This taste perception variation has been linked to a set of olfactory genes, as well as varying across ethnic backgrounds (Eriksson et al., 2012; Mauer & El-Sohemy, 2012). Even more unfortunate of a gene-related variation in taste perception is the association of a chemical involved in Parmesan cheese and some chocolates, butyric acid, with vomit and rancidity (Chevreul, 1815; Herz & von Clef, 2001; Drake & Civille, 2003; Kurie, 2018; Trimmer et al., 2019). Although this is influenced by a genetic predisposition, early-life experiences can mediate later preferences (Rozin, 1982; Birch, 1999; Reed & Knaapila, 2010; Lipchock et al., 2011). Inter-individual differences in perception can also be acquired later in life. Claude Monet developed cataracts in his 60s, influencing his perception such that “reds had begun to look muddy” (Marmor, 2006; Gruener, 2015). Later he underwent eye surgery, which included the removal of the lens from one eye, resulting in him seeing everything with a blueish tint (cyanopsia). Since the lens filters harmful ultraviolet light from reaching the retina, its removal altered Monet’s subjective experience of colour.

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More generally, culture can also affect how information is attended to—and later remembered. It was found that cultural variations could influence the way individuals perceive and interpret their environment, a concept they termed as cognitive style (Witkin, 1967; Masuda & Nisbett, 2001). When presented with scenes, Western participants focused on central and salient objects within a scene, independent of their context. This was viewed as an ‘analytic’ cognitive style. East Asian participants attended to the context and relationships between objects, reflecting a preference for dialectical reasoning—a ‘holistic’ cognitive style. These differences in attention have been further reflected in memory tests, related to recall and recognition of the central objects and tests of associative memory with incongruent background scenes (Masuda & Nisbett, 2001; Masuda et al., 2014; Millar et al., 2013). These findings illustrate how cultural context can shape our attention and, by extension, our perception and memory.

4.3 Ability to imagine: Phantasia Individual variation in visual imagery ability is often measured using the Vividness of Visual Imagery Questionnaire (VVIQ) (Marks, 1973). Within this variation, some individuals are unable to form visual imagery, referred to as aphantasia. There are also individuals that self-report imagery ‘as vivid as real seeing,’ hyperphantasia. The term ‘phantasia,’ was first used by Aristotle (340 BC) to describe “faculty or capacity by which an pictorial representation is presented to us.” However, aphantasia only entered the literature as recently as 2015 (Zeman et al., 2015). MIN RE

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Galton (1880, 1883) was one of the first to report that imagery ability varied between individuals, in addition to being a half-cousin to Charles Darwin. Some respondents stated they could imagine scenes vividly: “I can see my breakfast table or any equally familiar thing with my mind’s eye, quite as well in all particulars as I can do if the reality is before me” (P12; Galton, 1880, p. 305). Others were of the other extreme: “No. My memory is not of the nature of a spontaneous vision, though I remember well where a word occurs in a page, how furniture looks in a room, etc. The ideas are not felt to be mental pictures, but rather the symbols of facts” (P98, p. 306). However, Galton did not investigate inter-individual variability in imagery beyond these qualitative differences.

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While Galton made important contributions to science, he was also a strong proponent of eugenics and the first to coin the term, also in Galton (1883). It is an on-going challenge to credit pioneering researcher’s accomplishments, while being clear that not all of their views are being endorsed. Several individuals found to have exceptional memory have reportedly relied on vivid interactive imagery—including Luria’s S. (Luria, 1968; Hunter, 1977; Wilding & Valentine, 1985, 1991, 1997), though some other expert mnemonists have had imagery ability deficits—such as Rajan Mahadevan (Thompson et al., 1991, 1993). Though individual ability in imagery ability is typically assessed only subjectively, Cui et al. (2007) were able to confirm this variability using objective measures—brain activity in vision-related brain regions as well as with a psychophysics task. Later studies have since built on these findings (Logie et al., 2011; Fulford et al., 2018; Milton et al., 2021). Though the study of imagery ability dates back to Galton (1880, 1883) and Betts (1909), a Facebook post catapulted aphantasia into the spotlight. In 2016, Blake Ross—co-founder of Mozilla—wrote a thoughtful and eloquent Facebook post describing his realisation that he has aphantasia. Here is the first portion of the nearly 4,000-word essay: I just learned something about you and it is blowing my goddamned mind. This is not a joke. It is not “blowing my mind” a la BuzzFeed’s “8 Things You Won’t Believe About Tarantulas.” It is, I think, as close to an honest-to-goodness revelation as I will ever live in the flesh. Here it is: You can visualize things in your mind. If I tell you to imagine a beach, you can picture the golden sand and turquoise waves. If I ask for a red triangle, your mind gets to drawing. And mom’s face? Of course. You experience this differently, sure. Some of you see a photorealistic beach, others a shadowy cartoon. Some of you can make it up, others only “see” a beach they’ve visited. Some of you have to work harder to paint the canvas. Some of you can’t hang onto the canvas for long. But nearly all of you have a canvas. I don’t. I have never visualized anything in my entire life. I can’t “see” my father’s face or a bouncing blue ball, my childhood bedroom or the run I went on ten minutes ago. I thought “counting sheep” was a metaphor. I’m 30 years old and I never knew a human could do any of this. And it is blowing my goddamned mind.

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Though there has been speculation about the frequency of aphantasia in the general population, this has only recently been estimated in formal study (Zeman et al., 2020). In one portion of the study, participants were recruited from an on-going sample of nearly 1,300 participants. Imagery ability (phantasia) was assessed using the VVIQ, an imagery vividness scale ranging from 16–80, with 80 corresponding more vivid imagery. Zeman et al. (2020) classified individuals with scores 16–23 as aphantasic; individuals with 75–80 were hyperphantasic. Of the participants, 2.6% were aphantasic (0.7% scored exactly 16), whereas 11.2% of participants were hyperphantasic (2.6% scored exactly 80). From the full sample—which additionally included individuals who completed an online questionnaire with a specific interest in their imagery ability, prompted by press coverage of earlier work from the group— a relationship between vivid imagery ability and better autobiographical memory was also observed (Zeman et al., 2015). Conversely, aphantasics were more likely to self-report having bad memory (also see Greenberg & Knowlton, 2014; Aydin, 2018; Dawes et al., 2020). A recent study came to a slightly higher prevalence rate of 3.9% using a more representative sample (Dance et al., 2022). Subsequent research has further demonstrated quantitative differences in autobiographical memory details remembered (Milton et al., 2021). The implications of aphantasia to memory can be far reaching (see Section 1.5 from p. 19). Aphantasia has become an increasingly vibrant topic of study. Zeman et al. (2020) also found that individuals with aphantasia were more likely to report working in science-related occupations, whereas hyperphantasia individuals tended to work more in design and media professions. Wicken et al. (2021) demonstrated that aphantasic and control individuals had comparable physiological responses to emotional images, but no change from baseline for sentences describing fictitious emotional scenarios. For those that have aphantasia, the condition is usually present from birth—i.e., congenital— though there are some reported instances of it being acquired later in life due to brain injury (Zeman et al., 2020; Charcot & Bernard, 1883; Gaber & Eltemamy, 2021). A major point of controversy, however, is that aphantasia is primarily phenomenological. Some argue that variability in imagery ability may be primarily due to differences in how people describe their abilities—how real is an imagined object (Reisberg et al., 2002). Findings of differences in objective assessments, such as physiological ones, does corroborate the existence of aphantasia (Cui et al., 2007; Fulford et al., 2018; Milton et al., 2021; Wicken et al., 2021; Kay et al., 2022), this is a reoccurring argument by those new to the topic.

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4.4 Memory abilities at the extremes While most studies discussed here are based on ‘typical’ adult samples, some people have demonstrated exceptionally precise and comprehensive memory abilities—without the use of deliberate memory strategies (Palombo et al., 2018). See Section 12.5 (p. 392) for a discussion of those that have accomplished memory feats using strategies. These unintentional memory experts are described as having highly superior autobiographical memory (HSAM), otherwise referred to as hyperthmesia. Jill Price, initially referred to as A.J. for her anonymity, contacted a wellknown memory researcher with the following message: Dear Dr. McGaugh, As I sit here trying to figure out where to begin explaining why I am writing you and your colleague (LC) I just hope somehow you can help me. I am thirty-four years old and since I was eleven I have had this unbelievable ability to recall my past, but not just recollections. My first memories are of being a toddler in the crib (circa 1967) however I can take a date, between 1974 and today, and tell you what day it falls on, what I was doing that day and if anything of great importance (i.e.: The Challenger Explosion, Tuesday, January 28, 1986) occurred on that day I can describe that to you as well. I do not look at calendars beforehand and I do not read twenty-four years of my journals either. Whenever I see a date flash on the television (or anywhere else for that matter) I automatically go back to that day and remember where I was, what I was doing, what day it fell on and on and on and on and on. It is non-stop, uncontrollable and totally exhausting. Some people call me the human calendar while others run out of the room in complete fear but the one reaction I get from everyone who eventually finds out about this “gift” is total amazement. Then they start throwing dates at me to try to stump me…I haven’t been stumped yet. Most have called it a gift but I call it a burden. I run my entire life through my head every day and it drives me crazy!!!… (Parker et al., 2006, p. 35) After rigorous assessments, Price was characterised as having HSAM, the first documented case. While prior individuals have been studied for having exceptional memory abilities, these have predominately been associated with deliberate memory strategies. While deliberate memory experts generally demonstrate their feats in memorising ‘arbitrary’ word lists or sequences of cards, Price’s memory is of her own experiences—hence the specificity in describing HSAM as being autobiographical memory:

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Memories that matter AJ did not enjoy being asked questions she could not answer nor did she like neuropsychological tests on which she had difficulty. For example, she told us in no uncertain terms that she did not like the word-list recall tests. She said she “hated” trying to recall the War of the Ghosts story. During the Halstead Category Test of executive functions she repeatedly said she hoped the test would be over soon. This pattern of discomfort and even antipathy towards certain tasks contrasts with her engaging affect when recalling stories and dates from her personal life. (Parker et al., 2006, p. 39)

This is in contrast to several previously studied memory experts that enjoyed, and excelled at, recalling experimentally presented materials (Hunt & Love, 1972; Hunter, 1977; Wilding & Valentine, 1985, 1997; Thompson et al., 1993). While many of us may wish we had such abilities, at least initially, it is worth reflecting on Price’s view of this ability as being a burden. This perspective bears many similarities with the fictional story of Funes the Memorious by Borges (1954), first published in 1942 (also see Quian Quiroga, 2012). Jill Price has since written about this journey, from contacting Dr. McGaugh to personal reflections to hearing that the paper about her (i.e., Parker et al., 2006) was ready to submit (Price, 2008). Hearing about this from her perspective is quite touching. In the epilogue chapter, Price reflects: In July 2005, I got a call from Dr. Parker informing me that the scientific paper that she, Dr. McGaugh, and Dr Cahill had been working on about their study of me was ready for me to read. They were going to submit it to a scientific journal, and they wanted me to tell them about anything they’d written that I thought was inaccurate in describing how my memory works or too personal for publication. Their findings were judged to be strong, and the paper, with the title “A Case of Unusual Autobiographical Remembering,” was eventually published in a prestigious journal of brain science, Neurocase, in February 2006. Dr. Parker had written to me earlier to give me a summary of what they’d determined, but reading the full paper was nonetheless quite an experience. They referred to me as “AJ” in order to preserve my anonymity, but the person I was reading about was most certainly Jill; they had captured so much so beautifully about the experience of my life. The opening line told me that they had understood, deeply, how hard living with my memory had been for me; “What would it be like to live with a memory so powerful that it dominates one’s waking life?” (Price, 2008, pp. 241–242) Though Price was the first to be classified as having HSAM, later research re-discovered an earlier, similar case (Henkle, 1871). In contrast, some

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individuals who have been known to have impressive memory abilities did not have such capabilities for autobiographical memories. Solomon Shereshevsky, more often known as Luria’s S., was a Moscow newspaper reporter in the 1920s. S.’ boss noticed that he never took any notes, and after testing him to remember and repeat back a section of newspaper text verbatim, he asked S. to see a memory expert (Johnson, 2017). However, unlike Price, S. described memories for past events as a “haze” on several occasions (Luria, 1968, p. 159). This is not to make light of S.’s memory abilities—he was able to recall several stanzas of Dante’s Divine Comedy 15 years after memorising it—reproducing it verbatim—in Italian with the correct pronunciation, a language he did not understand (Luria, 1968, p. 45). Following the publication of this initial study with Price and associated press coverage, more individuals with HSAM have come forward and volunteered to be involved in research. Most later reports involve groups of HSAM participants (LePort et al., 2012, 2016, 2017; Patihis, 2016), but there is one other case-study report. Ally et al. (2013) describe behavioural and brain-imaging data from a 20-year-old man with HSAM—named HK; he was also born three months prematurely with a condition that results in congenital blindness. Not stated in this publication, but reported elsewhere (Bradford, 2016), HK was born prematurely due to an automobile accident that took his mother’s life and he was raised by his grandmother. HK also had several other serious medical conditions, including cerebral palsy, a heart condition, and his right side was paralysed due to a stroke days after birth. Bradford (2016) became friends with HK when he was 9 years old and in this book, The awakening of HK Derryberry, provides a detailed account of HK’s life, including when HK was identified as having HSAM. Here Ally gives a succinct description of HSAM: If I gave him a list of ten words to remember and asked him about them twenty minutes from now (episodic memory), or if I asked him who was the twentieth president of the United States (semantic memory), HK’s memory for this type of information would be a little different than ours because it’s more about memorizing than remembering. But if I asked what he had for dinner or what he watched on television on a specific day two years ago, he could remember it exactly. That’s autobiographical memory. (Bradford, 2016, p. 193)

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In a study of 30 individuals with HSAM, LePort et al. (2016) conducted more nuanced tests of autobiographical memory. Participants were interviewed twice, first about events from the past week, past year, and ten years ago—each for events occurring within a week span of the study session. One month later there was a surprise follow-up test where the recent (past week) memories were re-assessed, to allow for consistency to be evaluated. With the one-week delays, HSAM and control participants recalled similar numbers of events. However, HSAM individuals did recall less events at a one-month delay, but control participants had much more drastic forgetting. Memory was also assessed for one- and ten-year delays—HSAM individuals recalled slightly less details with longer intervals, though controls had no events. Moreover, HSAM individuals are also able to maintain consistency. Thus, it appears that HSAM is particularly associated with memory retention, rather than a process occurring during encoding. Marilu Henner, an actress, is one such individual who has subsequently been identified as having HSAM (McGaugh & LePort, 2014). A limitation of studying autobiographical memory is that often we cannot know and verify what a person individually experienced. Facts about public, historical events can be confirmed, but these are different from what a person themself was doing. However, Henner starred in a TV sitcom, Taxi, for several years. This provides a verifiable record of some of her personal experiences for this period, a clear methodological boon. Providing some evidence of traits that may cooccur with HSAM, both Price and Henner have been noted as being very particular about how household objects are organised. Shifting from HSAM, several individuals with exceptional natural memory abilities have been noted to have synesthesia and/or autism. Others with naturally impressive memory abilities include Luria’s S., but also contemporary individuals. Stephen Wiltshire, an architectural artist with autism and synesthesia, possesses extraordinary memory abilities that have earned him global recognition (Sacks, 1995a, 1995b). Known for his savant skills and eidetic memory, Wiltshire can accurately recall and reproduce cityscapes after brief observations, even years after he first saw them. An author and educator, Daniel Tammet is also a high-functioning autistic savant with synesthesia (Tammet, 2007). Tammet can perform complex mathematical calculations and recite pi to over 22,000 decimal places (Bor et al., 2008). (Also see Section 12.5 for further feats of memory, from p. 394.) His synesthesia manifests in the form of seeing numbers as colours, shapes, and textures, which helps him perform these mental feats (Baron-Cohen et al., 2007). Tammet (2007) writes: Seeing words in different colors and textures aids my memory for facts and names. When I meet someone for the first time I often remember their name by the color of the word: Richards are red, Johns are yellow, and Henrys are white. It also helps me to learn other languages quickly and easily. I currently know ten languages: English (my native language), Finnish, French,

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German, Lithuanian, Esperanto, Spanish, Romanian, Icelandic and Welsh. Associating the different colors and emotions I experience for each word with its meaning helps bring the words to life. For example, the Finnish word tuli is orange to me and means ‘fire.’ When I read or think about the word I immediately see the color in my head, which evokes the meaning. (p. 11) More generally, there is growing evidence that hyperthmesia can be related to enhanced internal temporal-spatial organisation associated with savantism (Simner et al., 2009). Furthermore, the fact that these feats are possible provide insight into the vast capabilities of the human mind, even if not representing typical performance. The opposite condition has also been identified—individuals with exceptionally poor memory abilities, despite otherwise average cognitive performance, are now known to have severely deficient autobiographical memory (SDAM). Palombo, Alain, et al. (2015) initially reported a case series based on three individuals who were healthy, high-functioning adults with deficits in being able to remember vivid personal experiences. One of these individuals, Susie McKinnon, has shared some of her personal perspective on living with SDAM (also see Fuentemilla et al., 2018). As described by Hayasaki (2016), McKinnon did not lose her ability to retain autobiographical memories—she never had the ability in the first place. MIN RE

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Another individual with SDAM is Malin Bohman (2021), who recently wrote a book about her experiences, With an eraser following me: Why don’t I remember? In this book, she provides a first-hand account of some of the challenges of SDAM. “What does it mean to lack autobiographical memory?” […] I have often tried to describe it this way: What I tell about my life might as well be what I would tell about the life story of a character in a novel; knowledge about facts I have memorized from a book, and therefore something that does not feel either alive or real within me. And although I still have access to a lot of facts about my life—like where I have lived, gone to school, what I have worked with, important events in my family’s and my own

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Reading first-person perspectives from those with aphantasia, HSAM, and SDAM cannot be understated in providing insights into the phenomology of what memory is, and how it varies between individuals. Awareness of conditions such as SDAM inform our understanding of how memory underpins our understanding of individual identity. For instance, philosopher John Locke (1690) had suggested that memory forms the foundation of self-identity, proposing that personal identity is constituted more by continuity of consciousness and memory than by physical continuity. Locke’s theory—often termed as the psychological continuity theory or memory theory of personal identity—proposes that we are our memories, implying that the experience of remembering events from our past is integral to the conception of ‘self’ (also see Section 8.3, p. 241). Hume (1739) had similar views. This is particularly relevant in the context of conditions such as SDAM, as it raises important questions. Further research on SDAM may provide insights into how memory is associated with self-identity, and this theory from Locke. Their deficiency of autobiographical memory provides a unique perspective on the role memory plays in shaping our identities. While some factors that explain variability are environmental, such as social support, and others are more state-dependent, such as those that are sleep related, others are more fixed and genetic. Some individuals have come to be referred to as superagers for exhibiting surprisingly good memory performance for their age. These individuals are often over 80 years old but able to perform better than a normative 50-year-old individual on standardised tests of episodic memory (Borelli et al., 2018; de Godoy et al., 2021). Across longitudinal follow-ups, age-related memory declines do still occur in these individuals, albeit at a much slower rate. Several studies including brainimaging components have indicated that the brain structure in superagers appear to be less affected by age (Rogalski et al., 2013; Harrison et al., 2012, 2018; Dang et al., 2019). Additionally, superagers have been found to have differences in neuronal density, as assessed using histology (Gefen et al., 2015). Garo-Pascual et al. (2023) recently published the largest study of superagers, selecting individuals from a large community-based sample. The study recruited people between 70 and 85 years old and conducted followup visits over eight years. One particularly interesting analysis compared 64 superagers to a sample of typical older adults, examining 89 lifestyle and clinical variables. Some of the variables with the strongest differences were performance on the up-and-go test—a measure of mobility and balance, and both state and trait anxiety. Some other important variables included adequate sleep, midlife activities, and musical background. As with prior studies (Harrison et al., 2012), superagers were selected based on their episodic memory, “defining a superager as a person aged 80 years or older

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with the episodic memory of a healthy person 20–30 years younger” (GaroPascual et al., 2023, pp. 374–375). However, even in the baseline assessments, superagers in this sample performed better than the control sample. This indicates that differences even before the study period are relevant to differentiating superagers from typical aging. The literature on superagers is still relatively sparse, but it is a promising topic to study further and develop recommendations for better-than-healthy aging. For further insights into the life experiences of people with atypical memory abilities, Moore (2004) provides an intriguing fictional account from the perspective of a neuropsychologist, and the individuals he encounters, in his book, The Memory Artists. These individuals, each with their unique conditions, serve as case studies, expanding our understanding of how memory anomalies can shape lives and personal identities. Noel Burun, one of the characters in the book, possesses hypermnesia and synaesthesia. The narrative provides us with a potential depiction of life with HSAM, offering a unique perspective into the cognitive functioning and life experiences of those with extraordinary memory abilities. Conversely, Stella Burun, Noel’s mother, has developed Alzheimer’s disease, which provides a stark contrast to Noel’s memory abilities. While the book is primarily written from the perspective of the neuropsychologist, several interleaved chapters include diary excerpts from the two Burun’s, offering further insight into the events discussed.

4.5 Patient H.M. Entire books can—and have—been written about patient H.M. and his contributions to our understanding of memory (Corkin, 2014; MacKay, 2019). Here, based on the focus of the present book, only a section can be dedicated to him, but I hope that this does not remain the extent of your reading. H.M. provided insight into more specific contributions of the hippocampus and surrounding regions, without the concurrent, diffuse neurodegeneration associated with many other clinical conditions. Of course, other patients have also provided important contributions to our understanding of memory—they will be briefly discussed at the end of this section. Henry Gustave Molaison, better known as patient H.M., passed away in 2008. After falling of a bicycle and becoming unconscious for several minutes around the age of 7, H.M. began to have epileptic seizures from the age of 10 (as well as having had a family history of epilepsy) (Corkin, 1984). Over the subsequent years, these seizures became increasingly severe, particularly after a major seizure on his 16th birthday. His seizures increased to having an average of ten minor seizures per day and one major seizure per week. At the age of 29, in 1953, H.M. opted for a radical experimental surgery— a bilateral medial temporal lobe resection, to be performed by the surgeon William Scoville. Details of this procedure were later published (Scoville & Milner, 1957), along with characterisations of several other cases. This was

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the first definitive evidence of how the hippocampus and surrounding medial temporal lobe structures support memory function in humans. It is worth highlighting, that even at the time, Scoville and Milner (1957) stated that H.M.’s surgery was specific to the hippocampus. Indeed, the last paragraph of the paper reads: It is concluded that the anterior hippocampus and hippocampal gyrus, either separately or together, are critically concerned in the retention of current experience. It is not known whether the amygdala plays any part in this mechanism, since the hippocampal complex has not been removed alone, but always together with uncus and amygdala. (p. 21) The initial neuropsychological research with H.M. was overseen by Brenda Milner—now known as a pioneer in clinical neuropsychology and cognitive neuroscience. In the 1960s, Suzanne Corkin, a former PhD student of Milner, took over as the lead researcher working with H.M. Later on magnetic resonance imaging (MRI) was used to acquire in vivo images of H.M.’s brain, providing a clearer characterisation of the brain—clarifying that most of his amygdala had been removed, but much of the parahippocampal cortex remained (Corkin et al., 1997). Based on this MRI data, Thiebaut de Schotten et al. (2015) constructed a simulation of the white-matter tracts affected in H.M. and two other classic neuropsychological cases. In the case of H.M., the major tracts affected were the uncinate, fornix, anterior commisure, and cingulum. MIN RE

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When assessing H.M.’s autobiographical memory, he was unable to describe remote episodic events: E: H.M.: E: H.M.:

Did you once fall in love with somebody? Yes. Okay. Tell me about it. Well, just how you felt and everything and the ways it could be. And they would fall for you. And you still don’t know. E: Can you tell me about when you first felt that you were falling in love with somebody? …one specific event? H.M.: No. E: No, you can’t think of that? …can you think of one specific event lasting for several hours from your early childhood? …can you come up with anything like that? H.M.: No, I can’t. (Steinvorth et al., 2005, p. 494) Research suggests that H.M. was able to learn some new information after his operation. In a study of famous names (O’Kane et al., 2004), H.M. (aged 76) was provided with a first name and asked for the first last name that came to mind. Of the 70 names provided, 35 became famous before his operation— 35 became famous afterwards. H.M. was able to respond with more last names for the pre-surgery famous people (18 and 12 names correct, respectively). On a second day, semantic cues were provided before the first name. For example, “famous artist, born in Spain in 1881, formulated ‘Cubism,’ works include ‘Guernica’,” followed by “When I say ‘Pablo,’ what is the last name that comes to mind?” (p. 418). H.M. performed better when provided with semantic cues (33 and 23 names correct, respectively, for pre- and post-operation famous people). In a 2 × 2 ANOVA design, both effects of time period and semantic cuing were statistically significant, but not the interaction. This suggests that H.M. was able to respond with the last names better when provided with semantic cues, even for people who became famous after his operation. One possibility was that H.M. learned new information through completing crossword puzzles, an activity he loved. Further studies examined his performance on crossword puzzles comprehensively—277 puzzles from six books, completed between 1997 and 1999 (Skotko et al., 2004). These years correspond to H.M. being 72–74 years old. The results indicated that H.M. could learn new semantic knowledge if he was able to anchor it to existing information. For instance, Marilyn Monroe was first photographed in 1944 and appeared on the cover of 33 magazines within a year. Shortly after, she starred in her first film in 1947. H.M. also knew Joe DiMaggio was a baseball player. These events that occurred prior to H.M.’s operation. H.M. was able to learn that Marilyn Monroe and Joe

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DiMaggio were married, even though this had occurred after his operation. As H.M. knew of both individuals prior to his operation, it is presumed he was able to anchor this later information to his representations of them, despite his overall memory impairment. Similarly, H.M. was able to learn new facts about John F. Kennedy—his election to president in 1961 and assassination in 1963—presumably because of his prior terms in the House of Representatives and fame of the Kennedy family. In an interview where Turk-Browne described another patient (L.S.J.) with similar memory impairments (Zalewski, 2015), he provided an eloquent analogy for the acquisition of new semantic memories: “like a Christmas tree—it’s easier to hang a new ornament on the tree than to acquire a new tree.” Skotko et al. (2008) further analysed the crossword answers to assess H.M.’s language abilities and found that they were intact, unaffected by his amnesia (also see Kensinger et al., 2001). For convergent evidence from another line of research, see Reder et al. (2013). As the body of work based on H.M. continued to develop, periodic summaries were also published (Corkin, 2002; Squire & Wixted, 2011; Eichenbaum, 2013). After passing away at the age of 82 (Squire, 2009), H.M.’s brain was examined post-mortem (Annese et al., 2014). The intact brain is shown in Figure 4.3. Subsequently, the brain was sliced into 2,401 sections of 70 µm thickness. This slicing procedure was conducted uninterrupted over 53 hours, and was streamed live over the internet. When considering the research done with H.M., two ethical discussions are prominent. First, was his procedure appropriate for the time? The surgery conducted is often described as being both a “radical” and an “experimental” treatment (Scoville & Milner, 1957; Corkin, 2002). Unfortunately, a retrospective written many years after the operation, and after H.M.’s passing, concluded that H.M. did not have temporal lobe epilepsy—and that this could have been concluded in 1953 (Mauguière & Corkin, 2015). Moreover, given current technologies and knowledge, we definitely would not use such a severe treatment ever again. A second consideration is whether an amnesic patient can sufficiently given consent to participate in research studies. Craver and Rosenbaum (2018) thoughtfully discuss this topic and elucidate the nuance surrounding the issue that likely is not apparent to those who have not worked with amnesic patients. Of the several books that have been written about patient H.M., Permanent Present Tense by Sue Corkin (2014) is the most notable, with Corkin being the researcher having worked most with H.M. over the course of nearly 50 years. Interestingly, several works of fiction have also been written about H.M. Inspired by the livestreamed slicing of H.M.’s brain, and relatedly, named after the 2,401 sections that were produced, a play was produced, entitled 2401 Objects (Barker et al., 2011). The original performances of the play were well recieved and won several awards. The play script has since been published. In The Man Without a Shadow, Oates (2017) tells of a fictionalised patient very much like H.M. and the researcher working with him. However, it unnecessarily intertwines a tale of unrequited love and immorality.

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FIGURE 4.3: Ventral view of patient H.M.’s post-mortem brain. (a,b) Regions of surgically resected temporal lobe tissue. The arrow marks damage related to a surgical clip. (c) Orbitofrontal cortex lesion. Scale bar, 1 cm. Reprinted from Annese et al. (2014). Insights into the neurobiology of memory had been learned from patients with Korsakoff’s syndrome, Alzheimer’s disease, and other disorders (Warrington, 1975; Sacks, 1985; Kopelman, 1987, 2002; Boucher et al., 2012; Aggleton, 2014). Sacks (1985) provides a detailed—and sad—account of Jimmie G., who was drafted into the navy during World War II and served for over 20 years. Afterwards he began to drink increasingly heavily and after a period of delirium, developed Korsakoff’s syndrome. After this period, Jimmie was no longer able to store new memories and thereafter thought he was only 19. At the time of meeting with Sacks, Jimmie was 49 years old. In the case of Korsakoff’s syndrome, memory deficits develop as a result of severe vitamin B1 deficiency, typically associated with alcohol use disorder. Recent work has shown that early diagnosis and targeted intervention can result in gradual remission (Oudman et al., 2023).

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Patients with herpes simplex encephalitis can also develop fairly localised medial temporal lobe damage and memory deficits (Kapur et al., 1994), such as Clive Wearing (Wilson & Wearing, 1995) and Lonni Sue Johnson (Gregory et al., 2014; Schapiro et al., 2014; Kim, Gregory, et al., 2020). Michael Lemonick, a science writer, came to write The Perpetual Now (Lemonick, 2016) after hearing that Lonni Sue Johnson (L.S.J.), who he attended high school with, had developed amnesia. While H.M. primarily exhibited anterograde amnesia, Lonni Sue Johnson suffered from both anterograde and retrograde amnesia— she could not form new memories and also lost many past memories. However, despite her profound memory impairments, Lonni Sue Johnson retained much of her personal skills and knowledge. She could still play the viola and draw, for instance, despite not remembering having learned these skills. Other patients with focal damage have also led to important insights, including Kent Cochrane (K.C.) (Tulving, 2002; Rosenbaum et al., 2005) and others (Cipolotti et al., 2001; Edelstyn et al., 2006; Patterson et al., 2007). Bereznyakova et al. (2014) detail an amnestic case study from a medical perspective, walking the reader through the diagnosis process, beginning from an individual arriving to the emergency department through to standard neurological assessments and follow-up several months later.

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End of chapter wrap-up Summary Memory ability is not a constant, either across individuals and throughout a person’s lifetime. This variability is influenced by a wide range of experiential and genetic factors, which contribute to the diversity of memory capabilities seen in people. One critical factor is imagery ability—phantasia, which has been shown to have a profound relationship with memory function. At the extremes, Highly Superior Autobiographical Memory (HSAM) and Severely Deficient Autobiographical Memory (SDAM) provide a unique lens through which we can deepen our understanding of memory capabilities. At the same time, the experiences of individuals like H.M. and other similar case studies have shed invaluable light on the neural basis of memory formation. They have revealed how memory systems can dissociate, a topic we will delve into with greater depth in the following chapter. Through this exploration of the extraordinary and the everyday, we gain a richer understanding of the complex workings of memory.

Reminder cues

Quick quiz 1. Which option best describes a problem with repeated administrations of the same cognitive assessment? (a) Participants may become overconfident, answering without sufficient deliberation. (b) The assessment may become less sensitive over time, causing minor cognitive changes to go unnoticed. (c) The cognitive assessment results become increasingly unreliable due to a potential practice effect leading to inflated performance. (d) The cognitive assessment might no longer measure the targeted cognitive domain due to familiarity with the test structure.

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2. The concept of cognitive reserve in the context of aging refers to: (a) The brain’s ability to reorganise itself by forming new neural connections throughout life. (b) The practice of regularly doing puzzles and mental exercises to maintain mental agility. (c) A measurable area of the brain that controls cognition and memory, which shrinks with age. (d) The accumulation of knowledge and skills over a lifetime, which counteracts cognitive decline. 3. Considering the characteristics of aphantasia, which of the following statements is most accurate? (a) Individuals with aphantasia have difficulty interpreting any kind of visual information, including pictures and cartoon animations. (b) Aphantasia is associated with an inability to generate mental images, including associated emotional responses. (c) Aphantasia is a condition where individuals can only think in images and have difficulties translating their thoughts into words or verbal descriptions. (d) Aphantasia solely affects an individual’s ability to imagine future events and has no impact on other cognitive functions. 4. Alex has an exceptional ability to remember personal past events in great detail without using any specific memory techniques. However, he often feels overwhelmed by the constant recollection of past experiences and sees it as more of a burden than a gift. Which individual discussed in this section does Alex’s situation most closely resemble? (a) Jill Price (b) Marilu Henner (c) Stephen Wiltshire (d) Daniel Tammet 5. How did H.M.’s memory impairments affect his ability to acquire new semantic knowledge? (a) He could not learn any new semantic knowledge. (b) He could learn new semantic knowledge only if he could anchor it to existing information. (c) He could learn new semantic knowledge without any issues. (d) He could only learn new semantic knowledge through repetition and reinforcement.

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Thought questions ▶ How do you think the understanding of memory decline with aging influences societal views on older individuals? Can this knowledge be used to create more inclusive and empathetic environments for older people? ▶ Reflect on the concept of mental imagery as a cognitive tool in memory function. How does it influence the way we recall, understand, and interpret our past experiences? How might this mechanism be used or enhanced in educational or therapeutic settings? ▶ How does the study of atypical individuals like H.M., Jill Price, or Susie McKinnon shape our understanding of normal memory function? Why is it important to study these cases despite their rarity?

Further reading ▶ Wicken, M., Keogh, R., & Pearson, J. (2021). The critical role of mental imagery in human emotion: Insights from fear-based imagery and aphantasia. Proceedings of the Royal Society B: Biological Sciences, 288(1946), 20210267. doi: 10.1098/rspb.2021.0267 ▶ Rogalski, E. J., Gefen, T., Shi, J., Samimi, M., Bigio, E., Weintraub, S., …& Mesulam, M.-M. (2013). Youthful memory capacity in old brains: Anatomic and genetic clues from the Northwestern SuperAging Project. Journal of Cognitive Neuroscience, 25(1), 29–36. doi: 10.1162/jocn_a_00300 ▶ Palombo, D. J., Alain, C., Söderlund, H., Khuu, W., & Levine, B. (2015). Severely deficient autobiographical memory (SDAM) in healthy adults: A new mnemonic syndrome. Neuropsychologia, 72, 105–118. doi: 10.1016/j.neuropsychologia.2015.04.012

Chapter 5 Neurobiological architecture

If the human brain were so simple that we could understand it, we would be so simple that we couldn’t! — Emerson M. Pugh (from Pugh, 1977)

I used to think the brain was the most fascinating part of the body. Then I thought, ‘Look who’s telling me that.’ — Emo Philips (1987)

Now that we have some foundational knowledge about the structure and organisation of memory, let’s consider how these are instantiated within the brain and what additional insights these specifics provide. Though some brain regions are more critical to memory processing—specifically the hippocampus and neighbouring regions—many other regions are relevant. We already discussed patient H.M., now let’s discuss the broader literature and our more contemporary understanding. In particular, the distributed nature of memory, and the relative specialisation of key cortical and medial temporal lobe regions. For a comprehensive human brain atlas, I recommend using Ding et al. (2016). This 356-page special issue of the Journal of Comparative Neurology provides an examination of the cerebral cortex, including histology and structural magnetic resonance imaging (MRI). An interactive version of the atlas is available at https://atlas.brain-map.org/atlas?atlas=265297126. For the brainstem, see Coulombe et al. (2021) (also see Section 10.2, particularly Figure 10.4).

5.1 Memory is distributed, yet modular While it is now well established that memory is stored distributed throughout the brain, a myth is “Memory is stored in the brain much like in a computer, 127

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that is, each remembrance goes in a tiny piece of the brain.” As shown by Herculano-Houzel (2002), from a sample of 35 senior neuroscientists, 82% think this statement is false and 12% were not sure. In contrast, in a sample of 2,158 members of the general public in the Rio de Janeiro area, approximately half believed the statement to be true. Similar responses were also found in later studies of neuroscience understanding (Deligiannidi & Howard-Jones, 2015; Pei et al., 2015; Hermida et al., 2016). Moreover, we do know that some regions of the brain are relatively more specialised for particular processes, such as vision, motor movements, language, and preferences. Memory, however, underlies all of these processes. In an early attempt to assess regional brain specialisation for memory, Lashley (1950) trained rats to complete a maze. He then caused localised brain lesions to determine a relationship between regional damage and performance. To his dismay, it did not appear that any region was particularly related to performance. He did observe, however, that more damage was associated with increased impairments. For further discussions, see Bruce (2001). A few decades later, Hebb (1949) provided evidence that memories are stored in the brains’ connections themselves—with further precision in this process being discovered in the years since (Oja, 1982; Bienenstock et al., 1982). When neurons are activated at the same time, the connections between them become strengthened. Or, more colloquially: “Neurons that fire together, wire together.” Though this adage is often attributed to Hebb himself, or considered source unknown, it was first proposed by Shatz (1992), who had used it in her teaching for several years before the publication. It was subsequently further popularised by Lowel and Singer (1992). For further historical context, see Nadel and Maurer (2020). In the recent past, there has been discussion of the idea of concept cells— sometimes referred to as grandmother or Jennifer Aniston neurons. This view is based on the idea that some neurons have 1:1 mappings to concepts, inspired by a 1969 novel, Portnoy’s Complaint. Quian Quiroga et al. (2005) provided initial support for this idea. Using single-neuron recording in a patient, it was found that certain neurons appeared to be active only in response to specific stimuli—one for Jennifer Aniston, another for Halle Berry—across multiple images of the person, including Halle Berry in a cat suit, but not other people wearing cat suits. The view suggested by later research is that concepts are neither stored in single neurons nor fully distributed throughout the brain, but are instead represented by ‘sparse networks’ of multiple neurons—though any neuron within that network would show a mapping to the related concept (Connor, 2005; Quian Quiroga et al., 2008). This finding of memory being stored in connections, rather than a specific region itself, is a parallel to the gods of memory discussed earlier (Section 1.2, p. 6). Memory is not located in a specific location in the brain; unlike vision or language processing, it is throughout the whole system, like water.

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Before advancing to the neuroscience research more central to the aims of the book, I would be remiss if I did not briefly acknowledge wealth of recent advances in our understanding of memory at the level of synapses and neurotransmitters. The last few decades have many insights into how the hippocampus is critical to both spatial navigation and the formation of cognitive relationships (Eichenbaum et al., 1999, 2016; Aggleton & Morris, 2018; Comrie et al., 2022). The characterisation of specialised memory cells, place cells, and grid cells, and how they neurobiologically support the computations involved in memory formation has been particularly monumental (Doeller et al., 2010; Deshmukh & Knierim, 2012; Buzsáki & Moser, 2013; Aronov et al., 2017; Moser et al., 2017; Benna & Fusi, 2021). However, as this book can only be so comprehensive, I have chosen to focus on the cognitive processes involved in memory and a ‘macro’ level of discussing brain regions, in-line with the precision afforded to us by MRI methods.

Subsequent memory effect Modern neuroscience methods allow us to examine brain function without causing permanent harm and in living humans—in vivo—is a necessary advance since the times of Lashley and the work done with H.M. Using neuroimaging methods—such as functional magnetic resonance imaging (fMRI) or electroencephalography (EEG)—to collect data related to brain activity, is a common approach to examine memory-related brain activity to look at subsequent memory effect (SME). In this approach, brain activity is recorded during the study phase of the experiment. This could involve intentional or incidental encoding of any stimuli type, factors that are independent of this approach. Later on memory is tested, using recall or recognition. Critically, memory performance during a test is used to categorise study trials. As an example, encoding could have been pictures of different animals. During a test, you could have an old–new recognition test, where many animal pictures are shown, some of which are new. Of the old pictures, you correctly identified the dog and cow as being previously presented (i.e., hits), but incorrectly judged the cat and horse to be new (i.e., misses). For the SME analysis, we would average brain activity across the different hit trials (dog and cow) and separately average brain activity across the miss trials (cat and horse). The SME analysis itself would be a comparison of which brain regions were differentially activated for the hits vs. misses. Some studies instead refer to this effect as the “difference due to memory” or “Dm,” as this is the difference in brain activity related to later remembering vs. forgetting (Paller et al., 1987). Figure 5.1 provides an additional example using an associative memory and cued recall design. Memory-related brain activity can also be examined during a test. A comparison of hits vs. misses here is referred to as retrieval success. In a recognition procedure, another common comparison is between items correctly identified as being old vs. new—i.e., hits vs. correct rejections.

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FIGURE 5.1: Task procedure and trial classification for subsequent memory and retrieval success effects. (A) Study block for six pairs in associative memory experiment and (B) test block based on cued recall. (C) Example responses to the cued-recall trials, with white boxes highlighting correct trials during test—along with the respective correct trials during the study. Black boxes denote incorrect trials. Incorrect trials also provide examples of three types of errors: “sponge” as a intralist intrusion, “onion” as an extralist intrusion (relative to the study words shown), “pass” as a failure to recall (based on task instructions).

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This approach can be combined with other manipulations, such as having half of the material being emotional and half being neutral. However, a difficulty of this research is that unlike experimenter-manipulated factors, the participant’s behaviour determines how many trials are remembered correctly or incorrectly (i.e., forgotten). For instance, while an experiment may be piloted and calibrated such that the average participant has about 40 each correct and incorrect trials for each type of stimuli material, a participant with a particularly good memory may only have a few forgotten trials. Since there would be insufficient trials to reliably estimate and compare the conditions, the participant would need to be excluded from these analyses. Depending on the specific research question, these can lead to a substantial number of exclusions. For instance, in one of my fMRI studies we used a cued-recall memory test, with the idea that cued-recall is more hippocampaldependent than associative recognition. As participants could not type or verbally provide their response, we asked them if they could recall the associated word as a yes/no judgement in the scanner, i.e., covert cued recall (Caplan & Madan, 2016). After they left the MRI scanner, we conducted an overt cued-recall test, acknowledging that performance would be poorer due to the repeated study–test cycles and delayed test. However, if someone responded “no” in an immediate test but recalled the associate in the out-of-scanner overt test, this would be informative of a poor covert–overt correspondence. From an initial sample of 31 participants, 4 were excluded due to poor overt cued-recall performance and another 7 due to poor covert– overt correlations. In other studies I have used hybrid associative recognition– recall procedures, such as following the yes/no judgement with a multiple alternative-forced-choice response (Madan, Fujiwara, et al., 2017; Fujiwara et al., 2021) or first testing the cue item with an old/new recognition judgement and only asking about the associate if the cue was successfully recognised (Madan et al., 2020). In this book we will focus on fMRI more than EEG, as the involvement of different brain regions is discussed in relation to the interaction and involvement of different memory systems. Nonetheless, due to the methodological differences between the two methods, EEG has allowed for the study of memory in the brain, using the SME, much earlier than it was possible with fMRI—as early as the 1980s (Sanquist et al., 1980; Karis et al., 1984; Paller et al., 1987). For an overview of the advantages in using EEG methods to study memory, see Rugg (1998) and Rugg and Curran (2007). MIN RE

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Relevant to both fMRI and EEG, the brain is always active, therefore it is important to examine regional brain activity during a particular condition— be it encoding of to-be-remembered stimuli, viewing a flickering visual checkerboard, or doing math calculations. In either case, activity can only be contrasted relative to a comparison condition. This could be an uninstructed state where a person’s mind wanders—often referred to as ‘resting state’ or ‘task negative.’ Without this baseline, we would be adrift in a sea of data, unable to discern meaningful patterns or draw valid conclusions. In essence, the baseline condition in fMRI studies is akin to the foundation of a building. It provides the necessary reference point from which we can construct a meaningful understanding of the brain’s response to various tasks and stimuli. Without it, our interpretations would be precarious, built on shifting sands. Consider the example of an experiment designed to investigate the neural correlates of memory recognition. Participants might be asked to recall specific events while their brain activity is monitored using fMRI. In this scenario, the active condition is the recognition task. However, to interpret the resulting data, we need a baseline condition—perhaps a state where participants are asked to rest or engage in a task that does not involve memory recognition. Stark and Squire (2001) compared the sensitivity of brain activity during recognition relative to different baseline conditions, examining which conditions give better contrast to memory function in the hippocampus and adjacent medial temporal regions. Comparisons relative to odd/even number judgements were shown to give better activity sensitivity. Based on these results, I used odd/even judgements in my own studies (Caplan & Madan, 2016; Hrybouski et al., 2019). Given the categorisation of trials as remembered correctly or incorrectly is determined by participants, memory studies of fMRI necessitated improved temporal resolution associated with event-related designs. Block designs could be designed to vary in difficulty, e.g., item presentation duration, but this is distinct from the inherent variability associated with which specific items are remembered or forgotten. The first fMRI studies to successfully study memory in this way were conducted in the late 1990s, not all that long ago (Brewer et al., 1998; Wagner et al., 1998). For a review of the methods, see Paller and Wagner (2002). Kim (2011) conducted a meta-analysis of 74 fMRI studies that reported SME analyses. Subsequent memory is typically associated with brain activity in regions including the hippocampus and fusiform gyrus. Interestingly, some brain regions have been shown to be more active for subsequent forgetting than subsequent memory. While the idea of activity in some brain regions being related to later forgetting may seem odd, another way to think of it is that these are regions that are associated with task-irrelevant cognitive processes, such as those involved in mind wandering (Christoff et al., 2009). Two such regions are the temporoparietal junction (TPJ) and the precuneus. While the meta-analysis provides strong evidence of this effect, I have also observed it in my own data (Caplan & Madan, 2016; Madan, Fujiwara, et al., 2017).

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With aging, some differences in brain function related to memory also occur—many of which have also been proposed with ‘catchy’ acronyms to go with them. The first of these to be proposed is that brain activations become more bilateral with aging, or hemispheric asymmetry reduction in older adults (HAROLD) (Cabeza, 2002). A second finding is that older adults tend to have more frontal activations and less occipital involvement than young adults, proposed to be caused by age-related functional compensation—labelled as a posterior–anterior shift in aging (PASA) (Davis et al., 2008). These findings laid the foundation for more comprehensive proposals, first the compensationrelated utilisation of neural circuits hypothesis (CRUNCH) (Reuter-Lorenz & Cappell, 2008) and then scaffolding theory of aging and cognition (STAC) (Park & Reuter-Lorenz, 2009; Reuter-Lorenz & Park, 2014). These later theories extended to cognition more broadly, but still include episodic memory within their frameworks.

5.2 Cortical specialisation The folding pattern of the human cortex is quite remarkable. While everyone has consistent major sulci and landmarks (Welker, 1990), everyone has an individually unique pattern of brain folding—like a fingerprint. See Figure 5.2 for an example of a structural MRI of a young adult and the related cortical surface reconstruction. Even though memory is stored in a distributed way in the brain, there are specialised regions for certain types of processes (Stigliani et al., 2015; Kanwisher, 2017). For instance, primary visual cortex is in the occipital lobe processes early visual information; primary motor cortex and somatosensory cortex are on each side of the central sulcus process body movements and touch perception. Regions that are not associated with direct input or output from the brain are referred to as association cortex. Within association cortex, a number of regions are specialised for processing particular types of information. Perhaps the most well-known of these is the fusiform face area (FFA) and the parahippocampal place area (PPA), for face and place/scene processing, respectively (Sergent et al., 1992; Kanwisher, McDermott, & Chun, 1997; Epstein & Kanwisher, 1998; Haxby et al., 2001). When these types of visual input are received, these regions are involved in identifying and understanding the visual input as the related type of stimulus. The FFA is located along the posterior fusiform gyrus, the PPA along the collateral fissure. In addition to demonstrating robust activation in these regions in response to the associated stimuli category, such as faces, convergent evidence of this functional specialisation has also been obtained from studies involving direct electrical stimulation of these regions in an epilepsy patient with implanted electrodes (Schalk et al., 2017). Other specialised functional regions are also present, many of which are on the ventral surface of the brain, as shown in Figure 5.3.

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FIGURE 5.2: Example of a brain from a structural MRI. (A) Coronal and sagittal views of an MRI. (B) Cortical surface reconstruction. MIN RE

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In fMRI studies related to these types of stimuli, sometimes sequences of unique faces, scenes, and objects are presented to aid in localising the precise regions of cortex associated with these processes, as every individual has a unique cortical folding pattern. This type of experimental task is called a localiser. Several additional specialised regions include extrastriate body area (EBA) for body (Downing et al., 2001; Spiridon et al., 2006), lateral occipital complex (LOC) for objects (Sergent et al., 1992; Kanwisher, Woods, et al., 1997; Spiridon et al., 2006), and visual word-form area (VWFA) for words (Polk & Farah, 1998; Cohen et al., 2002; McCandliss et al., 2003)—among other specialised regions (Pinel et al., 2007; Fedorenko et al., 2011). The EBA is located anterior to MT+ on the medial temporal gyrus, the LOC is anterior

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FIGURE 5.3: Ventral regions associated with domain-specific processing. Regions associated with house, face, bodies, and other objects are shown from a ventral view of an averaged cortical surface of the left hemisphere. Fusiform face area (FFA) and parahippocampal place area (PPA) are labelled. to V4, and the VWFA is mid-section of the left occipito-temporal sulcus. Examples of the stimuli used in these localiser tasks are shown in Figure 5.4. Some other regional specialisations will be discussed later, such as cortical regions that are involved in processing motor actions or manipulable objects (see Section 9.2 from p. 267). These can be thought of as regions associated with the semantic processing of these respective stimuli types. Amodal semantic knowledge, such as those related to the typical DeeseRoediger-McDermott (DRM) effects, are associated with processes in the anterior temporal lobe (Chadwick et al., 2016). This region is sometimes refereed to as the semantic hub (Rogers et al., 2004; Patterson et al., 2007).

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FIGURE 5.5: Brain regions and activations related to memory retrieval over different time scales. (A) Brain regions associated with memory retrieval, in particular the hippocampus along with regions of the cerebral cortex. Brain activity is shown as regional activations from fMRI data, overlaid on a structural MRI. Panels B and C illustrate brain activity in the (B) hippocampus and (C) cortical regions associated with memory retrieval over multiple repetitions that are either within a single experimental session or across multiple sessions. Within session, hippocampal activity will be attenuated with each subsequent presentation, whereas activation in cortical regions is slightly reduced on the second presentation and is maintained at this level for later presentations. However, across multiple sessions, hippocampal activity will reach nearly the same level, and will diminish much more gradually. In this case, activity in cortical regions will be relatively low in early sessions and later become higher after distributed practice. In this way, cortical activity becomes decoupled from the hippocampal activity, as the information transitions from episodic memory to semantic memory Based on Sommer (2017); adapted from Van Hoof et al. (2021a).

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If new types of stimuli were presented, memories for them would initially be episodic and involve the hippocampus—as discussed in the remainder of this chapter. As information is repeatedly presented, accessing the related knowledge becomes less hippocampal dependent, shifting from episodic to semantic memory (Sommer, 2017; Antony et al., 2017). This shift from hippocampus to cortex, semanticisation, is illustrated in Figure 5.5. Sommer (2017) presented participants with pairings of pictures and locations over 300 days; for some sessions, participants were scanned using fMRI. Early in the study (days 1 and 2), association retrieval was associated with hippocampal engagement. However, this decreased in later sessions (around day 100), whereas regions of cortex instead were found to be more active as the episodic information gradually transitioned to semantic knowledge. This activity shift would apply to learning foreign languages, as well as developing domainspecific expertise, such as a bird watcher or car expert (see Section 12.2 from p. 366). A recent example of this type is a study of cortical specialisation related to Pokémon pictures (Gomez et al., 2019). Adults who previously played Pokémon extensively as children had differences in brain activity in a region of posterior fusiform cortex that was not present in adults who had not played Pokémon as children. In other words, the functional organisation of this region of ventral temporal cortex was changed due to the accumulated experience from engaging with this artificial stimuli for many hours a day over several years. Srihasam et al. (2014) conducted an analogous study with monkeys, intensively training them with distinct sets of shapes—font characters, tetris shapes, and cartoon faces. Each stimulus type became associated with a distinct posterior region of primate inferotemporal cortex, across individual monkeys and regardless of training order. Despite inter-individual consistency being evidence of an organisation system, the study was unable to determine what principles determined the localisation of the cortical specialisation. Meshulam et al. (2021) examined computer science expertise and associated brain activity. This study involved both undergraduate and graduate students who had significant programming experience and knowledge of introductory computer science course material. Each undergraduate ‘student’ was scanned for six sessions (each a week apart), using a longitudinal fMRI design; the graduate ‘experts’ were only scanned once each. Brain activity patterns across sessions and participants were compared—students who had higher neural alignment with experts at the beginning of the course performed better on exams at the end of the course. This study demonstrates how learners gradually internalise new structured knowledge and acquire domain expertise.

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5.3 Medial temporal lobe The medial temporal lobe is associated with episodic memory, among other cognitive functions. This includes the hippocampus and surrounding regions, particularly the entorhinal, perirhinal, and parahippocampal cortices. Information flows into these regions from either the perirhinal or parahippocampal cortices—as illustrated in Figure 5.6. These two regions are structurally adjacent and along the same major fold, with the perirhinal cortex being more anterior than the parahippocampal cortex. The perirhinal cortex is particularly specialised for processing itemrelated information and is connected to the anterior temporal lobe and frontal regions. In contrast, the parahippocampal cortex is connected to the retrosplenial cortex and precuneus, communicating context-related information. Frameworks have been proposed to infer more organisation to these functional relationships, such as characterising these as two distinct cortical networks—a posterior-medial (PM) network and an anterior-temporal (AT) network (Ranganath & Ritchey, 2012; Ritchey et al., 2015). The regions associated with the posterior-medial and anterior-temporal networks are also illustrated in Figure 5.6. This PM-AT framework is particularly clear in defining these distinct networks, and is generally consistent with previous

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Entorhinal Cortex Parahippocampal Cortex Posterior Medial

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Perirhinal Cortex Anterior Temporal

Item

FIGURE 5.6: Circuitry of the medial temporal lobe and hippocampal formation.

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accounts (Aggleton & Brown, 2006; Mayes et al., 2007; Sekeres et al., 2018). Moreover, the distinction between these networks goes beyond differences in categories of cognitive functions—La Joie et al. (2014) proposed that the AT network is particularly affected by semantic dementia, whereas PM network impairments can be a result of Alzheimer’s disease. Information from both of these regions then flows into the entorhinal cortex, which itself is functionally specialised into lateral and medial regions. The item-related representations pass to the lateral portion, whereas contextual information goes to the medial portion. Information can interact between regions of the entorhinal cortex as well as to subfields of the hippocampus itself. This view is also consistent with the PM-AT framework (Ranganath & Ritchey, 2012), as well as convergent with conceptualisations that are specific to the medial temporal lobe (Hasselmo & McClelland, 1999; Deshmukh & Knierim, 2012; Reagh & Yassa, 2014; Takehara-Nishiuchi, 2014; Schultz et al., 2015; Nilssen et al., 2019). MIN RE

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The functional coupling of the hippocampus and other medial temporal lobe regions can also dynamically vary. Tambini et al. (2010) demonstrated this elegantly in an associative memory fMRI study. First, a baseline resting-state fMRI scan was acquired. In a resting-state scan, fluctuations in brain activity are observed in the absence of any stimuli or task, allowing for the analysis of functional connectivity between different brain regions. Participants were then presented with pairs of faces and objects and asked to remember the associations, followed by another resting-state scan. Participants then were presented with pairs of faces and scenes, then followed by another resting-state scan. The order of face-object encoding and face-scene encoding was counterbalanced across participants. In the resting-state scan after the face-object block, connectivity between the fusiform face area (FFA) and lateral occipital complex (LOC) was increased relative to the baseline scan. After the face-scene block, the FFA was instead increasingly coupled to the parahippocampal place area (PPA). Hippocampal connectivity with these stimuli-specific regions also varied in relation to the encoded content, and in relation to memory performance (also see van Kesteren et al., 2010). Tambini and Davachi (2013) replicated these main findings while additionally examining additional multivariate relationships. For more clinical-related insights, Hammoud et al. (2019) and Dekeyzer et al. (2017) provide excellent overviews of the hippocampal etiology. Komaitis et al. (2022) provide a detailed dissection manual for surrounding regions.

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Memory strength Providing some evidence that a memory strength account is sufficient for characterising medial temporal involvement in recognition memory, Smith et al. (2011) conducted a well-designed study for examining memory confidence and remember–know–guess responses in relation to medial temporal lobe activation. Participants studied 300 words and made pleasantness judgements. Participants then were given a recognition memory test in an MRI scanner. Only 60 new words were intermixed with the old words, as the focus was on variations in memory for old items and an equivalent number of new items would have necessitated the test to last over two hours, given the pacing of the memory test. A two-step recognition procedure was used, with participants first being presented with a 20-point confidence scale (1, definitely new; 20, definitely old). If the rating was between 11 and 20, corresponding to ‘old,’ participants were asked to make a remember/know/guess response. Participants were instructed to use ‘remember’ if they could describe specific details about the experience of studying the word; ‘know’ should instead be used if the participant felt the word was familiar, but could not recollect any details from encountering the word. Behavioural results indicate that the two memory measures were highly related—an average of 117 (out of 300) words were assigned a confidence rating of 20 and ‘remember,’ as shown in Figure 5.7A. As a whole, ‘remember’ responses had a mean confidence rating of 19.5, whereas ‘know’ had a mean confidence rating of 17.4 (Figure 5.7B). Examining differences in brain activity for the remember and know responses yielded bilateral regions of the hippocampus that were more active for remember responses, visible in Figure 5.7C. Despite the measure being highly correlated, the high number of old trials in the experimental design allowed Smith et al. to select a subset of trials where both remember and know were ‘strong’ and had comparable confidence ratings (means of 19.5 and 19.2, respectively), using 81% of remember and 40% of know trials (Figure 5.7B, right). Here they found that no clusters in the medial temporal lobe were statistically more activated for strong remember responses than strong know responses. Instead, comparing these versus miss responses did yield activity clusters in the left hippocampus only for the strong remember comparison and both the left hippocampus and parahippocampal cortex for the strong know comparison. This finding suggests that the qualitative difference associated with the remember vs. know distinction did not yield differences in brain activity beyond those also related to memory confidence.

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FIGURE 5.7: Results of fMRI study examining memory strength. Adapted from Smith et al. (2011). (A) Confidence responses for each trial type. A confidence rating of 1 corresponded to “definitely new,” whereas 20 corresponded to “definitely old.” Confidence ratings of 1–10 made for one of the 60 new words is considered a correct rejection (white bars), but for one of the 300 words that were studied, a response in this range is considered a miss response (black bars). When a confidence rating between 11 and 20 was given, a follow-up prompt of remember/know/guess was presented, allowing for recognition hit responses to be further subdivided. For these ratings, new items are considered false alarms (white bars), whereas old items are shown as guess (light gray), know (dark gray), or remember (black bars), based on the respective response. Note that the average number of remember responses at confidence rating 20 was 117 trials. (B) Mean confidence rating for the remember (R), know (K), and guess (G) responses. On the right are the mean confidence ratings for the subset of trials considered as strong remember (sR) and strong know (sK) responses. Error bars indicate SEM. (C) Coronal sections showing bilateral hippocampal clusters where brain activity was higher during recognition for remember than know responses. No regions in the medial temporal lobe were found to have statistically significant clusters of more brain activity for strong remember responses than for strong know responses, based on this subset of trials where memory confidence was matched. Figure adapted from Smith et al. (2011).

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5.4 Role of the hippocampus While the hippocampus is not a cortical region of the brain, and thus is considered ‘subcortical,’ it also has a distinct morphology relative to the nuclei of the amygdala and basal ganglia. Instead, its layered and folded structure is referred to as archicortex. As such, some research of hippocampus has involved computationally unfolding and flattening the region to better represent regional brain activity (Zeineh et al., 2000, 2001; Suthana et al., 2009, 2015; DeKraker et al., 2018, 2021). For recent advances in the characterisation of intra-hippocampal structure, I strongly recommend DeKraker et al. (2021). DER CU MIN E RE

Initially, the hippocampus has been viewed as being associated with spatial navigation, and this was later extended to include memory through the analogy of cognitive maps (O’Keefe & Nadel, 1978; Poucet, 1993; Moser et al., 2017; Ekstrom & Ranganath, 2017). Evidence across a variety of species suggests that the hippocampus is necessary for remembering episodes, that is, integrating across what, where, and when (DeVito & Eichenbaum, 2010; Allen & Fortin, 2013; Crystal, 2018, 2021; Barbosa & Castelo-Branco, 2022). However, current evidence suggests that the hippocampus is not dedicated to memory function, though it is definitively important within this domain. Rather, current evidence indicates that the hippocampus is a key region involved in determining when and how information is integrated and accessed. In a series of papers, a patient with selective hippocampal damage, Y.R., was administered a battery of memory tests (Mayes et al., 2001, 2002, 2004; Holdstock et al., 2002). It was found that item-recognition tests were relatively intact. However, performance on tests of associative recognition or item recall were significantly impaired (also see Madan, 2020a). These general findings were further replicated with another patient in further work (Holdstock et al., 2005). Prior to the studies with these patients, this distinction was made between hippocampal dependence and recall vs. recognition (Squire & Zola, 1998). Furthermore, associative recognition tests were across a variety of types: intra-item, between information of the same kind (e.g., two words), and between information of different kinds (e.g., object-location). Holdstock et al. (2019) provide an overview of these past studies, showing that the hippocampus is also critical for associations across different kinds. Based on these studies and others, Mayes et al. (2007) proposed that the hippocampus is particularly necessary when integrating across different domains, such as face-name or object-location associations.

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The hippocampus has also been demonstrated to be involved in learning in statistical regularities in sequences of objects (Schapiro et al., 2012, 2014; Covington et al., 2018; Ellis et al., 2021). A more general view hippocampal function in relation to behaviour is the literature on pattern separation and completion (Marr, 1971; Yassa & Stark, 2011; Stevenson et al., 2020). However, it also true that these fundamental operations are tightly interwoven within memory. The label of hippocampus—Latin for seahorse—itself provides insight into the state of modern neuroscience. Regions are based on their structural properties, not their function. This, of course, is not unique to the hippocampus, one needs only to flip through a list of neuroanatomical labels and their Latin translation—amygdala, locus coeruleus, substantia nigra— all visual descriptors rather than functional ones. Along with this, a basic understanding of the structural connections between regions preceded our understanding of regions. This does not mean nothing can be learned from these early conceptualisations of brain architecture, but this perspective of hesitancy is required. As a simple example, the Papez circuit was proposed in 1937 and the the term ‘limbic system’ only shortly after (Maclean, 1949). Both of these preceded research with patient H.M. and the more definitive mapping of medial temporal lobe regions to memory. Figure 5.8 reprints an illustration from Maclean (1949) of the then-current understanding of cognitive neuroscience. As such, modern views of how the hippocampus functions suggest terms such as the limbic system are antiquated.

FIGURE 5.8: Illustration of the hippocampus as a seahorse in the brain. Adapted from Maclean (1949).

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Specialisation within the hippocampus The hippocampus is not a unitary structure. Intrahippocampal specialisation can be examined across two principal axes: across subfields (the transverse axis), and from front-to-back (the long axis of the hippocampus). The subfields of the hippocampus include the cornu ammonis—or CA—regions, dentate gyrus, and subiculum. The relative organisation of these regions is shown in Figure 5.9. The cerebrospinal fluid (CSF) space immediately lateral to the hippocampus is the temporal horn of the lateral ventricles (Van Buren et al., 1956; Dekeyzer et al., 2017). For precise descriptions of the anatomical landmarks used to segment the subfields, see Dalton et al. (2017). While many studies have examined the role of different subfields, researchers are still refining approaches for delineating the specific boundaries (Yushkevich et al., 2015; Hrybouski et al., 2019; Meyer & Radulovic, 2021; Kahhale et al., 2023).

CA1 3 DG/CA u l m Subicu EC Pr C LEC M FIGURE 5.9: Anatomy of hippocampal subfields and surrounding medial temporal regions labelled on an MRI volume. Abbreviations: DG, dentate gyrus. CA, cornu ammonis. MEC, medial entorhinal cortex. LEC, lateral entrorhinal cortex. PrC, Perirhinal cortex. The parahippocampal cortex is not visible, it is posterior to the perirhinal cortex. Based on a combination of histological and functional data (Marr, 1971; Amaral & Witter, 1989; Norman & O’Reilly, 2003; Yassa & Stark, 2011; Lacy et al., 2011), the dentate gyrus is thought to be particularly optimised for differentiating between related concepts, otherwise referred to as ‘pattern separation.’ In contrast, CA3 is particularly optimised for integration and

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generalisation across multiple experiences, referred to as ‘pattern completion.’ As an example of a memory test: to look at a photo and remember the associated past experience, pattern completion must occur; for a face to be identified as someone we have not met previously, pattern separation is necessary. When thinking about learning episodes more directly, I personally find the view of differentiation vs. integration as a useful way of thinking of these two functions. Supporting these views, an fMRI study has recently shown that for picture stimuli varying in similarity, different subfields showed variations in how these stimuli-related representations differed based on their similarity (Wammes et al., 2022). The dentate gyrus showed clear evidence of differentiation; the CA1 activity corroborated the view of integration, but results were less compelling. Across the long-axis there are also functional differences in hippocampal processing (Small, 2002; Poppenk et al., 2013; Strange et al., 2014; Brunec et al., 2018). The most anterior portion is sometimes otherwise referred to as the head; the most posterior section, the tail; and the intermediate section, the body. The hippocampal head is linked more closely to item-related processing, smaller spatial scales, and integrating information from the anterior-temporal memory network. In contrast, the tail of the hippocampus is more attuned to processing contextual information, larger spatial scales, and integration with the posterior-medial memory network. These cortical connectivity differences are also included in Figure 5.6.

Differences in hippocampal structure Any book about memory discussing brain structure has to discuss the Maguire et al. (2000) study of London taxi drivers. Briefly, taxi drivers had regional volumetric differences in their hippocampal structure, relative to a non-taxidriver control group. However, as there is a later chapter dedicated to memory experts, these findings will be discussed further in Section 12.3 (p. 374). Briefly shifting to cross-species comparisons, avian hippocampal volumes have been found to vary systematically in relation to whether the species cached their food or not. Krebs et al. (1989) examined 52 individual birds belonging to 35 species or subspecies; Garamszegi and Eens (2004) collected brain-volume estimates from 55 species across many previous studies and more directly considered phylogeny. This result supports the notion that food caching demands more spatial memory ability to remember the cache locations and this corresponds with increased hippocampal volume (also see Sherry et al., 1989). Some studies have corroborated these conclusions with memory tests or hippocampal volume in pairs of species, where one stores food and one does not, but are closely related (Clayton, 1995; Volman et al., 1997; Biegler et al., 2001; Hoshooley & Sherry, 2007). Others have examined individual hippocampal volumes, within the same species, in relation to caching experience and environmental harshness (Clayton & Krebs, 1994; Cnotka et al., 2008; Roth & Pravosudov, 2009). Seasonal changes in

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hippocampal volume have also been observed in both birds and rodents (Smulders et al., 1995; Clayton et al., 1997; Hoshooley et al., 2007; Yaskin, 2011; Sherry & MacDougall-Shackleton, 2015). These findings suggest an interplay between behaviour, environment, and brain structure. Hippocampal structure seems to adapt in response to memory demands. This is a striking example of brain plasticity and its ability to modify its structure based on experience and environmental demands. The relative size and structure of the hippocampus across different species is shown in Figure 5.10.

FIGURE 5.10: Comparative neuroanatomy of the hippocampus within glass, whole-brain volumes. Square grid under each brain measures 20 mm across, with each grid square subtending 2 mm. Reprinted from Madan (2015a). Returning to humans—much of the literature on the relationship between the hippocampus and memory is based on individual differences in hippocampal volume or event-related brain activity, each derived from conventional structural or functional MRI approaches, respectively. However, novel MRI measures have arisen in the last decade that appear promising, still measured through MRI scanning. Some of these include examining the shape complexity of brain regions (Madan & Kensinger, 2017; Madan, 2019, 2021c) or specifically examining the dentations (sometimes alternatively referred to as bumpy ridges) along the inferior surface of the body long-axis visible in

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sagittal slices (Simić et al., 1997; Beattie et al., 2017, 2022; Chang et al., 2018; Kilpattu Ramaniharan et al., 2023), or variations in hippocampal head digitations visible transversely in coronal slices (Gertz et al., 1972; Tien et al., 1992; Oppenheim et al., 1998; Treit et al., 2018; Piccirilli et al., 2020; Solar et al., 2021). Tissue properties can also be examined through within-region variations in signal intensity—i.e., heterogeneity, which has been found to relate to age-related memory deficits, as a precursor to volumetric decreases (Wearn et al., 2021). A particularly remarkable approach has been to measure regional brain tissue elasticity, using a method known as magnetic resonance elastography (MRE). This technique involves having an air-filled pillow under the participant’s head, connected to a plastic tube. This tube is connected to a box outside of the MRI scanner room, likely the control room. This box pneumatically pressurises the air at a set frequency, creating a pulse that passes through the tube to the pillow. With this design, the pillow is able to pulsate in shape, creating vibrations in the head position. By creating these micro-vibrations it is possible to use the MRI to estimate regional brain stiffness/elasticity. In an initial study, hippocampal stiffness did not vary with age (Hiscox et al., 2018); a subsequent study with a larger sample size did see this effect reach statistical significance (Delgorio et al., 2021). Moreover, several studies have shown that hippocampal stiffness did relate to memory performance (Schwarb et al., 2017; Hiscox, Johnson, McGarry, Schwarb, et al., 2020) and dementia (Gerischer et al., 2018; Hiscox, Johnson, McGarry, Marshall, et al., 2020).

5.5 Progression of Alzheimer’s disease As Alzheimer’s disease increases in severity, there are corresponding changes in the brain. In particular, a protein called ‘tau’ becomes misfolded into a ‘tangle’ and builds up. Normally this protein is associated with the internal structure of neurons, which then lose integrity due to this misfolding and

FIGURE 5.11: Illustration of Braak staging of tau tangle accumulation. Accumulation begins from the locus coeruleus and entorhinal cortex, continues to the hippocampus and prefrontal regions, before distributing throughout the cortex. Darker regions correspond to greater tau accumulation.

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result in neuronal cell death. Braak and Braak (1991) was the first to show that this accumulation of tau occurred in some brain regions earlier than others, by examining 83 post-mortem brains from individuals that both had and had not shown signs of dementia. This progression of accumulation is referred to as Braak stages, described as six stages, each grouped into phases of two stages each. The phases are transentorhinal, limbic, and isocortical. See Figure 5.11 for an illustration of this progression of tau tangle accumulation. In the transentorhinal phase (stages 1 and 2), tau tangles begin to appear in the locus coeruleus (brainstem) through to the entorhinal cortex—no behavioural symptoms have occurred yet. (See Section 10.2 for further discussions about the locus coeruleus.) In the limbic phase, (stages 3 and 4), tangles spread to the hippocampus, amygdala, and some prefrontal regions. At this point, mild cognitive impairment begins to manifest. In the isocortical phase (stages 5 and 6), tangles distribute throughout the cortex and Alzheimer’s disease is evident, along with the associated memory difficulties and disorientation. Since Braak’s original study, we have developed methods for measuring tau in vivo using positron emission tomography (PET) imaging. Here we have also been able to see the pattern of progression of tau build up (Maass et al., 2017). In studies with mice, the APOE gene has been shown to be linked to tau-related neuron cell death (Shi et al., 2017). While natural-occurring Alzheimer’s disease has not been found to occur in many other species, Gunn-Moore et al. (2018) suggest that disrupted insulin signalling and longer post-reproductive lifespan may be some criteria that may be relevant to this being relatively unique to humans. They do provide evidence that Alzheimer’s disease, however, can be detected post-mortem in brains of dolphins. Since this initial proposal and report, further studies have corroborated and extended the evidence of Alzheimer’s disease-like pathology in several dolphin species (Stylianaki et al., 2019; Vacher et al., 2023). MIN RE

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A number of measures—biomarkers—can be used to assess the progression of Alzheimer’s disease. The most sensitive of these are associated with neurobiological measures, followed by cognitive memory tests, then clinical assessments (Jack et al., 2010). Figure 5.12 provides an illustration of this, as each measure is affected and associated with clinical severity. Novel approaches to biomarkers, such as MR elastography and wearable sensors, are emerging as additional measures (Lyall et al., 2023; Winchester et al., 2023). Subjective cognitive decline, when combined with dementia risk biomarkers, represents even greater risk (Vogel et al., 2017; Slot et al., 2018; Ben-Ami et al., 2023).

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Biomarker Magnitude

Abnormal

Amyloid-beta (Aβ) Tau tangles Brain structure Memory Clinical assessment

Normal Mild Cognitive Impairment

Cognitively Normal

Dementia

Clinical Stage

FIGURE 5.12: Alzheimer’s disease biomarker severity progression. Adapted from Jack et al. (2010). Until recently, amyloid-beta (Aβ) has been thought to be critical to the development of Alzheimer’s disease (Jack et al., 2010; Blennow et al., 2015). The absence of this protein appears to have no detrimental effects, but accumulated deposits of it are found in individuals with Alzheimer’s disease and part of its folding structure parallels that of diseases that involve protein misfolding. Unfortunately, despite several clinical therapies being developed around amyloid-beta, results are not promising (Mullane & Williams, 2013, 2020; Harrison & Owen, 2016; Kametani & Hasegawa, 2018). Further complicating matters, discussions have suggested that the emphasis and funding prioritising the amyloid-beta hypothesis have resulted in less progress in the pursuit of other possibilities. The proliferation of large-scale open datasets, like ADNI has many benefits–in making it possible for many researchers to work with large samples and potentially find new relationships between cognitive, lifestyle, and other biomarkers with the development of mild cognitive impairment and Alzheimer’s disease (Madan, 2022). However, too many analyses from the same dataset can also result in overfitting and bias expectations towards that specific dataset, rather than yielding generalisable conclusions, sometimes referred to as ‘dataset decay’ (Wirth & Nikitenko, 2011; Madan, 2017a; Thompson et al., 2020). In a systematic review of machine learning studies of Alzheimer’s disease brain imaging, Borchert et al. (2023) found that, out of 255 studies, 71% used ADNI (181 studies). The second-most used dataset was only used in five studies.

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End of chapter wrap-up Summary We began our journey through the chapter by exploring the brain’s memory structure and organisation. In particular we discussed the role of the hippocampus and surrounding regions in memory processing, while also acknowledging the relevance of many other regions. We then transitioned to the subsequent memory effect (SME), a common approach to examine memory-related brain activity. We discussed the concept of cortical specialisation, where certain regions of the brain are specialised for processing particular types of information. We delved into the fusiform face area (FFA) and the parahippocampal place area (PPA), among others. We then revisited the concept of memory strength, discussing how memory strength relates to hippocampal activity. Continuing with this spotlight on the hippocampus, we discuss that it is necessary for remembering episodes—integrating across what, where, and when. We also discuss the progression of Alzheimer’s disease, focusing on the accumulation of tau tangles, leading to neuronal cell death. We observe that this accumulation of tau occurs in some brain regions earlier than others, and this progression is referred to as Braak stages.

Reminder cues

Quick quiz 1. Which of the following acronyms represents the finding that older adults tend to have more frontal activations and less occipital involvement in memory tasks? (a) HAROLD (b) PASA (c) CRUNCH (d) STAC

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2. Given the example of adults who played Pokémon extensively as children showing differences in brain activity in a region of posterior fusiform cortex, why might the same type of cortical specialisation not be as pronounced in individuals who spent extensive amounts of time during their childhood playing chess or a musical instrument? (a) Chess and music do not involve visual stimuli, so no differences in brain activity would be expected. (b) The brain does not adapt to stimuli from games or activities like chess and music, so no changes in brain activity would occur. (c) The regions of the brain that are changed by playing chess or a musical instrument are different from those changed by playing Pokémon, so the changes would not be detectable in the fusiform cortex. (d) Chess and music are more reliant on schemas and planning, and less on visual expertise, which might not result in the same type of specialisation in the fusiform cortex as seen in Pokémon players. 3. Which part of the medial temporal lobe is specialised for processing item-related information? (a) Perirhinal cortex (b) Parahippocampal cortex (c) Entorhinal cortex (d) Hippocampus 4. What is the hippocampus necessary for when it comes to remembering episodes? (a) Integrating across what, where, and when (b) Focusing on specific details (c) Recalling only emotional experiences (d) Remembering only recent events 5. Which measures are most sensitive for assessing Alzheimer’s disease progression? (a) Subjective cognitive decline and dementia risk (b) Neurobiological measures (c) Clinical assessments (d) All measures are equally sensitive

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Thought questions ▶ Now that we have fMRI methods, are patients studies still useful in helping us understand the neurobiology of memory? Why or why not? ▶ What technical challenge caused fMRI studies of memory success to occur years later than studies of many other cognitive functions? ▶ If memory is distributed, why is the hippocampus still considered to be particularly important for memory?

Further reading ▶ Ranganath, C., & Ritchey, M. (2012). Two cortical systems for memoryguided behaviour. Nature Reviews Neuroscience, 13(10), 713–726. doi: 10.1038/nrn3338 ▶ Olsen, R. K., & Robin, J. (2020). Zooming in and zooming out: the importance of precise anatomical characterization and broader network understanding of MRI data in human memory experiments. Current Opinion in Behavioral Sciences, 32, 57–64. doi: 10.1016/j.cobeha.2020.01.017 ▶ Krebs, J. R., Sherry, D. F., Healy, S. D., Perry, V. H., & Vaccarino, A. L. (1989). Hippocampal specialization of food-storing birds. Proceedings of the National Academy of Sciences USA, 86(4), 1388–1392. doi: 10.1073/pnas.86.4.1388

Part III

Motivation

Chapter 6 Memories of emotions past

An impression may be so excitingly emotionally as almost to leave a scar upon the cerebral tissues. — William James (1884, 1890)

While our understanding of emotional memory has become more nuanced over recent years, it has long been understood that emotional experiences are generally better remembered than more mundane ones. In an article about memory in medieval times, Duby (1980) discusses how “All social acts of any importance had to be public, had to occur before a large assembly whose members kept the memory in trust and were expected to bear witness later, eventually, of what they had seen or heard” (p. 8). Admittedly, this statement bears little relevance to the specific topic of emotional memory, but was followed by: …great care was taken to have very young children present and to slap them sometimes violently at the height of the ceremony, hoping that the memory of the spectacle attached to the memory of pain would cause them to forget less quickly what had transpired before their eyes. (p. 8) Of course this practice is reprehensible now, but the underlying principle does indicate that the emotionality was being inflicted—above and beyond the event itself—with the aim of enhancing memory. (Admittedly, we also need to acknowledge that this interpretation is being conveyed through the historian, not by those dictating the practice themselves.) More typically, we want to understand how emotional events affect our everyday lives and later memory. In rare cases, this can be studied from realworld experiences that are significantly emotional.

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On August 24, 2001, Margaret McKinnon was on a flight from Toronto, Canada to Lisbon, Portugal—Air Transat 236. She was recently married and was flying with her husband for their honeymoon, but the flight did not go as planned and the plane ran out of fuel over the Atlantic Ocean (Hayasaki, 2021). Due to a mismatched engine replacement part during routine maintenance from days ago, fuel had been slowly leaking. The plane had run out of fuel over the ocean. Passengers thought they were going to die, as did McKinnon. Luckily, their pilot, Captain Robert Piché, had previously spent some time as an aerial drug smuggler. He had since spent time in prison and was considered reformed, but he had experience gliding a plane without engine power. He was able to glide the plane—the longest-ever glide of a commercial aircraft—and land in the Azores with minimal injuries. In an interview 20 years later, Captain Piché said, “I was put on a national hero pedestal, so people don’t think I was scared. But I am a human being like everyone else. I was the first to be afraid.” Before all of this, Margaret McKinnon was a PhD student studying memory. Soon after this harrowing event, the 9/11 terrorist attack occurred; over the next year, details of the incident came to light. As McKinnon continued her career as a scientist, and also was in touch with fellow passengers, she wondered how they would remember the event and how they were changed by it. McKinnon suffered from anxiety-inducing flashbacks, but her husband did not—why did some people process it differently than others? McKinnon et al. (2015) studied autobiographical memory for 15 passengers and 15 healthy adult non-passengers, asking them to provide detailed recollections of three events—a neutral event from 2001, their experience during 9/11, and their experience in the Air Transat 236 disaster. The nonpassengers instead were asked to recall a highly negative event from 2001. All passengers had rich episodic recollections from the airline disaster. Passengers that had since developed PTSD produced more non-episodic details across all three events, but did not otherwise differ from the passengers that did not develop PTSD. In a subsequent study, brain activity was examined for these memories (Palombo et al., 2016). Findings showed that remote, traumatic memories are mediated by amygdalar activity, likely enhancing vividness through influences on hippocampal and ventral visual regions. Typically, studies of emotional memory are much more mundane— participants are asked to sit in front of a computer and view a sequence of words or pictures. Later, memory is tested for these stimuli and comparisons are made between negative words or pictures relative to neutral ones. In the case of negative words, these are often not any more emotional than words you may see in the news, such as HOMICIDE, TERROR, or HURRICANE. In this chapter we will be discussing a range of studies and approaches, from experimental studies to naturalistic events. I will not be discussing repressed memories here, as it is tangential to the current focus and a complex topic unto itself; however, for nuanced discussions, see Memory and Miscarriages of Justice by Howe et al. (2017).

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6.1 Flashbulb memories Do you remember where you were when you first heard about the Capitol Riots in January 2021? Can you recall the shock, the disbelief, as you watched the scenes of chaos unfold on your screen? The sight of a mob storming one of the most iconic buildings in the United States, the heart of its democracy, was a moment that transcended geographical boundaries—a shared experience for millions around the world. Or perhaps you remember the devastating explosion in Beirut in August 2020. The capital of Lebanon, a city rich in history and culture, was brought to its knees by one of the largest non-nuclear explosions in history. The photos were haunting: a towering mushroom cloud, buildings reduced to rubble, the stunned faces of people trying to comprehend the magnitude of the disaster. This was a moment of collective grief and shock. Or maybe, you have a better memory of hearing about the military coup in Myanmar in February 2021. The sudden seizure of power by the military sent shockwaves around the globe. As the news broke, the world watched in stunned silence as the military detained the country’s elected leaders and declared a state of emergency. Photos of peaceful protesters flooding the streets, the reports of violent crackdowns, and the resilient spirit of the Myanmar people fighting for their democracy. These recent events are but the latest entries in a long chronicle of historical incidents that have etched themselves into our collective memory. For some readers, the mention of the Challenger space shuttle explosion in 1986 might stir vivid memories. The shuttle, a beacon of human ingenuity and the spirit of exploration, tragically disintegrating in the clear blue sky. Similarly, the events of September 11, 2001, have left an indelible mark on our collective consciousness. The morning when the unimaginable unfolded before our eyes, as planes crashed into the World Trade Center towers. For others, these events might be known only through historical accounts and documentaries. These moments are more than just public events in a timeline. They are ‘flashbulb memories,’ vivid and enduring snapshots of moments that have shaped our shared history (Brown & Kulik, 1977; Conway et al., 1994). In these instances, ‘encoding’ is incidental and details for these events are more memorable than the events of any other day, often tested over long periods, ranging from weeks to even a decade after the original flashbulb event— though only a few studies have examined memory after these extreme delays (Colegrove, 1899; Hirst et al., 2015). These details can include information about the events themselves—which can be externally verified—as well as individualised attributes, such as where someone was when they heard the news, how they heard the news, and how they initially reacted to the news. Many studies have examined memory for real-world emotional experiences as flashbulb memories, such as the deaths of public figures (Abraham Lincoln, John F. Kennedy, Martin Luther King, Princess Diana) (Colegrove, 1899; Yarmey & Bull, 1978; Brown & Kulik, 1977; Kvavilashvili et al., 2003),

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terrorist attacks (e.g., 9/11, 2013 Boston Marathon) (Talarico & Rubin, 2003; Hirst et al., 2015; Ford et al., 2018), natural disasters (e.g., earthquakes and floods) (Neisser et al., 1996; Sotgiu & Galati, 2007), and other traumatic events (e.g., 1986 Challenger space shuttle explosion, near meltdown of Three Mile Island) (Bohannon, 1988; McCloskey et al., 1988; Neisser & Harsch, 1992; Baum et al., 1993). While flashbulb events are generally considered to be negative, some have studied positive events that may also be considered flashbulb memories, such as the fall of the Berlin Wall (Bohn & Berntsen, 2007), President Obama’s inauguration (Koppel et al., 2013), and when sports teams win—though there also is a reciprocal team that loses (Kensinger & Schacter, 2006b; Breslin & Safer, 2011; Talarico & Moore, 2012). There also have been events with mixtures of both positive and negative emotions, such as communities coming together to support each other after the 2013 Boston Marathon bombing (Ford et al., 2018). MIN RE

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Additionally, it is important to acknowledge that some have suggested that flashbulb memories are not ‘special.’ While these are undoubtedly distinctive and vivid, they are not more accurate than other memories (Bohannon, 1988; McCloskey et al., 1988; Neisser & Harsch, 1992; Talarico & Rubin, 2003). This suggests that the mechanisms underlying the formation and retention of flashbulb memories may not be fundamentally different from those of other types of memories. Colegrove (1899) conducted an interview of 179 adults, asking them: “Do you recall where you were when you heard that Lincoln was shot?” This is specifically prefaced as being related to the influence of emotion on memory vividness, though this study was conducted before the notion of flashbulb memories had developed. The following extract is an example of an affirmative response, though some other replies were less detailed. My father and I were on the road to…in the state of Maine to purchase the “fixings” needed for my graduation. When we were driving down a steep hill into the city we felt that something was wrong. Everybody looked so sad, and there was such terrible excitement that my father stopped his horse, and leaning on the carriage called: “What is it, my friends? What has happened?” “Haven’t you heard?” was the reply—“Lincoln has been assassinated.” The lines fell from my father’s limp hands, and with tears streaming from his eyes he sat as one bereft of

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motion. We were far from home, and much must be done, so he rallied after a time, and we finished our work as well as our heavy hearts would allow. (pp. 247–248) J. P., age 76:

I was standing by the stove getting dinner, my husband came in and told me.

M. B., age 79: I was setting out a rose bush by the door. My husband came in the yard and told me. It was about 11 o’clock AM. H. R., age 73:

We were eating dinner. No one ate much after we heard of it.

J. T., age 73:

I was fixing fence, can go within a rod of the place where I stood. Mr. W. came along and told me. It was 9 or 10 o’clock in the morning.

L. B., age 84:

It was in the forenoon; we were at work on the road by K.’s mills; a man driving past told us. (p. 248)

Despite these interviews being conducted 33 years after the incident, 127 of the 179 interviewees (71%) were able to provide sufficiently detailed recollections. However, a detailed recollection is not necessarily an accurate one. Neisser and Harsch (1992) found that despite the vividness of memories related to the Challenger space shuttle explosion, many contained false details. After the Challenger incident in 1986, Neisser and Harsch (1992) asked 44 students to recall what they were doing when they heard the news and write it down, giving the written account to the researchers. Two-and-a-half years later, the students were asked about the incident again and the two reports were compared. First, only 11 of the 44 participants (25%) reported having previously participated in a study related to the Challenger shuttle. Moreover, some participants were in disbelief with the discrepancy with their past account: “Whoa! That’s totally different from how I remember it,” and “I still think of it as the other way around.” As we discussed John Dean’s memory and eyewitness testimony as exemplars of memory biases, President Bush’s recollections of September 11, 2001, are a case study in flashbulb memory. Greenberg (2004) provided an overview of three instances where President Bush gave recollections of the incident; Greenberg demonstrated that not only were they inconsistent, but some details were impossible—such as watching a film of the first plane crash. (Also recall Crombag et al., 1996, discussed in Section 2.3, p. 41.)

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6.2 Emotional experiences Emotional events do not need to be at the magnitude of flashbulb events to be more memorable than our day-to-day mundane experiences. Using autobiographical methods (further discussed in the next chapter), Wardell et al. (2021a) asked participants to think of past emotionally positive, negative, and neutral experiences and describe them. Experiences recalled had to be either recent (less than 3 months ago) or remote (1–5 years ago). To help understand the events that people discussed, many of the recent memories were related to academics and entertainment, followed by a mix of illness, relationships, and work. Remote memories shared many of the same event categories, but also less frequently occurring types of events, such as achievements, deaths, and violence. Benuzzi et al. (2018) specifically examined autobiographical memory for emotional and personally relevant events—own weddings and those who had a sudden death of a loved one. A limitation of most autobiographical studies, however, is a lack of being able to verify what actually happened. There are some exceptions to this, however, such as the Air Transat disaster described earlier (McKinnon et al., 2015). Another emotional memory study with verifiable details was Metcalfe et al. (2019). This study explored the impact of extreme stress on the memory recall of firefighters, focusing specifically on the New York City Fire Department (FDNY). Firefighting is one of the most stressful civilian professions and provides a unique context for studying the effects of stress on memory. The study involved 54 FDNY firefighters who were asked to recall recent fires they had fought. These recollections were documented within five hours of each event, and the veracity of the events was cross-verified through fireground communications. Each recall was then scored based on the inclusion of ‘schematic’ or standard fire events, and ‘emergency’ or high-stress events. Both the firefighters and experienced coders rated the stress levels associated with each incident. Memory recall decreased as stress level increased. This relationship between stress and memory exhibited a quadratic relationship, forming an inverted-U shape. Emergency events were remembered better than schematic ones, and events that had personal relevance to the firefighters were recalled significantly better than those without. Pezdek et al. (2022) examined the influence of police officers watching the recordings from body-worn cameras and found that re-watching the events improved their performance in a later memory test. While we generally may desire memory to be closer to the true experience, there may be instances where assessing what the officer experienced in the moment and later remembered is more important. For instance, in reviewing the officers’ behaviour in court, it may be more important to know that the officer did not see and later remember the full situation because their attention was focused elsewhere, even though the full situation was recorded on camera. Memory can also be assessed for prolonged events, such as the COVID19 pandemic. Rouhani et al. (2023) collected autobiographical memory data

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from over 1,000 American adults during the pandemic. There was increased recall of autobiographical memories from March 2020, when the COVID-19 pandemic reached emergency status in the US, compared to other months. Additionally, when stronger emotions were experienced—generally negative emotions—there was greater memory retrieval for that month. Memory for some public events was also assessed; pandemic news events were remembered more vividly and evoked more surprise and negative affect compared to other news. Time estimates between news events spanning lockdown periods were compressed—a topic we will revisit later in this chapter. When examining phenomenological characteristics of emotional memories, the list of potential ratings is extensive. Across several experiments, Rubin et al. (2010) explored 39 different characteristics—listed in Table 6.1. These were from the Autobiographical Memory Questionnaire (AMQ; Rubin et al., 2003) and Impact of Events Scale (IES; Horowitz et al., 1979). The AMQ is comprised of 21 ratings on a 7-point scale, spanning reliving, belief, sensory properties, re-experiencing emotions, visceral emotional responses, fragmentation, and narrative coherence. The IES consists of 15 items characterising the frequency of intrusive and avoidant thoughts associated with each memory on a 5-point scale. Let’s shift our focus from naturalistic experiences to more experimental procedures. Emotion influences on memory can occur across a variety of time scales: trial, state, or trait. (Another framing of these same distinctions is moment-to-moment fluctuations, session-to-session differences, and individual differences, respectively.) Trial-level effects of emotion on memory are often due to the to-be-remembered information itself being emotional in content, such as a negatively valenced emotional word or picture, being interleaved TABLE 6.1: List of phenomenological ratings used in Rubin et al. (2010), including the Autobiographical Memory Questionnaire (AMQ; Rubin et al., 2003) and Impact of Events Scale (IES; Horowitz et al., 1979). Item

Brief Description of Rating Scale

Reliving Back in Time Remember/Know Real/Imagine Persuade

Recollection and Belief I am reliving the original event. I travel back to the time when it happened. I remember it rather than just knowing it happened. I believe the event in my memory really occurred. I could be persuaded that my memory was wrong.

See Field/Observer Setting Hear

Sensory I can see it in my mind. I see it out of my own eyes. I can recall the setting where it occurred. I can hear it in my mind.

continued…

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Brief Description of Rating Scale

Same Emotions Same Strength Intensity Positive Negative Valence Heart Tense Sweaty Butterflies Reaction

Emotions I feel the same emotions I felt then. I feel the emotions as strongly as I did then. The emotions are extremely intense. The emotions are extremely positive. The emotions are extremely negative. The emotions are extremely positive/negative. I feel my heart pound or race. I feel tense all over. I feel sweaty or clammy. I feel knots, cramps, or butterflies in my stomach. I had a physical reaction.

Out of the Blue Evoke Thought About Talked About Thought or Talked

Availability This memory has come to me out of the blue. Things may unexpectedly evoke my memory. I have thought about this event. I have talked about this event. I have thought or talked about this event.

Think as Little Elaborate Part of Identity See Connections

Coping and Identity I think as little as possible of the event. I elaborate the event to myself and others. The event has become part of my identity. I see connections b/w the event and experiences.

In Words Story Pieces Specific to Me Occurred Once Merged Events

Language, Narrative, and Specificity It comes to me in words. It comes to me as a coherent story. It comes to me in pieces with missing bits. My memory is based on details specific to my life. It occurred once within a day. It was merging of events not an extended event.

Current Stress IES IES: Avoidance IES: Intrusions

Impact of Events Scale and Current Stress Question I am still distressed by it. (0 to 5 scale used in IES) Measures PTSD-like symptoms of an event. Subscale measuring avoidance of memory of event. Subscale measuring intrusions of memory of event.

with the presentation of emotionally neutral material. State effects are more transient, but still have a meaningful duration to them, such as a mood induction or physiological stressor task (Westermann et al., 1996; LeBlanc et al., 2015; Joseph et al., 2020). Trait effects of emotion may be a predisposition to process information as more or less emotionally, for instance due to trait anxiety or alexithymia. While traits are relatively stable over time, there is yet some dynamics to them—for instance, personality traits change as we get older (Srivastava et al., 2003; Harris et al., 2016; Weidmann et al., 2023).

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Trial This is the dominant approach to studying emotional memory. Even when the state- and trait-level effects are studied, they often involve examining differences in memory for emotional and neutral trials, along with those additional factors. When participants are shown a list of emotional and neutral words and later tested for their memory, they will remember the emotional items better (Kleinsmith & Kaplan, 1963; Maratos et al., 2000; Buchanan & Lovallo, 2001; Kensinger & Corkin, 2003). This occurs across a wide variety of task variations, including words or pictures, intentional or incidental encoding, and with either recall or recognition memory tests. Example picture stimuli, across a variety of types, are shown in Figure 6.1. The majority of studies of emotional memory are built on the circumplex model of affect, where the two fundamental dimensions of emotion are valence and arousal (Russell, 1980; Yik et al., 2011). Valence refers to the intrinsic pleasantness, attractiveness, or aversiveness of an event, object, or situation. It is the dimension that allows us to categorise experiences as emotionally positive or negative. For instance, happiness is an emotion with positive valenced state, while sadness has negative valence. Arousal—in the context of emotion research—refers to the intensity of an emotional response. It is a spectrum that ranges from states of calm or relaxation to states of excitement or agitation. High-arousal states are typically associated with intense emotions, whether they are positive, such as joy or excitement, or negative, such as fear or anger. Low-arousal states, on the other hand, are linked to feelings of tranquillity or boredom. While these two dimensions are not the only ways to categorise emotional experiences, this is the dominant view in the field and will be the focus here. Other frameworks for studying emotion include Ekman’s (1992) basic/universal emotions, Plutchik’s (1980, 2001) wheel of emotions, and others (Panksepp, 2005; Izard, 2009, 2010)— though study of more nuanced emotional states are also phenomenologically important (Tsikandilakis et al., 2024). For word and picture stimuli, the most common databases have been the Affective Norms for English Words (ANEW) (Bradley & Lang, 1999) and the International Affective Picture System (IAPS) (Lang et al., 2008; Bradley & Lang, 2017). Both were developed by Margaret Bradley and Peter Lang of the Center for the Study of Emotion and Attention at the University of Florida. These databases have been thoroughly normed and rated for valence, arousal, and dominance. Valence refers to the extent to which a stimuli evokes a positive or negative emotion. The most evocative positive pictures include cute animals and erotic scenes; negative pictures include snakes and mutilated bodies. Arousal refers to the intensity of emotion provoked by a stimuli. Dominance refers to the degree of control exerted by a stimuli—this measure is much less used than the other two dimensions. These databases are commonly used in psychological and neuroscientific studies to investigate the effects of

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FIGURE 6.1: Examples of emotional stimuli. Adapted from Madan, Bayer, et al. (2018). emotional content on various cognitive processes, including memory. As these databases were developed decades ago, they are now becoming a bit dated, and can be somewhat limited in their number of stimuli when additionally considering other stimuli properties. These are becoming superceded by other stimuli databases. For word stimuli, Warriner et al. (2013) provides ratings for nearly 14,000 English stimuli. Other databases exist for other languages. For picture stimuli, several databases exist with some of the more common ones being the Nencki Affective Picture System (NAPS) (Marchewka et al., 2014), the Geneva Affective Picture Database (GAPED) (Dan-Glauser & Scherer, 2011), and EmoMadrid (Carretié et al., 2019). These more recent databases generally have higher quality pictures than would have been practical in the 1990s. A variety of other stimuli can also be used to elicit emotional reactions. For instance, some other procedures use brief narrative vignettes, where pairs of stories begin the same but then diverge into either a neutral or emotional variant (Heuer & Reisberg, 1990; Christianson & Loftus, 1991; Burke et al., 1992; Parent et al., 1999; Brierley et al., 2007). There are some nuanced potential confounds to consider, however, which will be discussed in detail in the next sections. Emotional effects on memory can also be measured using psychophysiological methods, which provide a direct window into the physiological processes associated with emotional experiences. Key measures include pupil dilation, skin conductance response (SCR), and heart rate. Pupil dilation is a measure of autonomic nervous system activity, specifically the sympathetic branch which is associated with arousal and alertness. When we experience strong emotions, our pupils often dilate as part of the body’s automatic

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response. This response can be measured using pupillometry, a non-invasive method that tracks changes in pupil size over time. Research has shown that emotional stimuli, both positive and negative, can lead to greater pupil dilation compared to neutral stimuli (Hess & Polt, 1960; Hutt & Anderson, 1967; Brady et al., 2008; Hermans et al., 2013; Hämmerer et al., 2017). Pupil dilation is also related to activation of a brain region called the locus coeruleus, which will be further discussed in Section 10.2 (p. 299). Skin conductance response (SCR), also known as galvanic skin response or electrodermal activity, is another measure of autonomic nervous system activity. It measures the electrical conductance of the skin, which varies with its moisture level. Since our sweat glands are controlled by the sympathetic nervous system, increases in emotional arousal often lead to increased sweating and, consequently, increased skin conductance. SCR can therefore provide a measure of emotional intensity, with larger responses typically associated with more intense emotional experiences (Binswanger, 1919; Jones, 1935; Brady et al., 2008; Boucsein, 2012; Ksander et al., 2018; Tsikandilakis et al., 2024). Heart rate, measured through electrocardiography (ECG or EKG), pulse oximetry, and other heart rate monitoring techniques, is another critical indicator of emotional arousal. Changes in heart rate can reflect the body’s automatic response to emotional stimuli (Hare, 1973; Buchanan, Etzel, et al., 2006; Hermans et al., 2013; Madan, Harrison, & Mathewson, 2018; Tsikandilakis et al., 2024). Increases in heart rate are often associated with heightened emotional states, providing another layer of understanding to how emotional experiences are encoded into memory. Collectively, measures such as pupil dilation, SCR, and heart rate offer valuable insights into the emotional processes that can influence memory. By providing a direct measure of physiological arousal, they can help us understand how emotional experiences are encoded into memory and how these memories are subsequently retrieved.

State A variety of procedures have been used to induce emotional states in laboratory settings. Some of these are more cognitive, such as viewing film clips (Adamson et al., 1972; Eisenberg et al., 1988; Hewig et al., 2005), listening to emotional music (Konečni, 2008; Vuoskoski & Eerola, 2012), or imagining feeling the stated emotion (Velten, 1968; Carroll et al., 1982; Larsen & Sinnett, 1991) to induce feelings of sadness or anxiety. To make the induction more personally relevant, film clips or music could also be selected based on the person’s past, evoking nostalgia and stronger feelings of affect (Michels-Ratliff & Ennis, 2016; Rasmussen et al., 2021). Some studies have used videogames as a means of emotion regulation, particularly to induce either joy or frustration (Villani et al., 2018). Moreover, of particular interest, some studies have used autobiographical memory recall as a mood induction task (Brewer et al., 1980; Ekman et al., 1983; Baker & Guttfreund, 1993; Göritz & Moser, 2006).

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For a comprehensive overview of mood induction findings across over 800 samples and 50,000 participants, see the meta-analysis by Joseph et al. (2020). (See Westermann et al., 1996, for an earlier meta-analysis.) Consider the following instructions as an example of an autobiographicalrecall mood-induction procedure: I would now like to ask you to take a few minutes to look into your past and think about what have been the two happiest events in your life. When you finish reading these instructions, take 10 minutes to think of these events. I will tell you when the time is over. I would like you to try and think of all the details of what was happening at the time, to the point that you could imagine this happening to you right now. Think about how old you were, who were the people or events involved, and what your feelings were. (Baker & Guttfreund, 1993, p. 568) Training to retrieve past autobiographical episodes or to project future autobiographical episodes can also be used for more sustained effects. A recent meta-analysis found significant effects (d = 0.32 across 12 studies) of autobiographical recall as a treatment for depression (Hitchcock et al., 2017). Some approaches to study state effects have been more physiologically oriented. Dutton and Aron (1974) conducted a study where young adult men crossing a bridge were approached by an experimenter and asked to fill out a questionnaire. Two nearby bridges were used, equally often, when approaching potential participants. The ‘experimental’ bridge was described as: The bridge has many arousal-inducing features such as (a) a tendency to tilt, sway, and wobble, creating the impression that one is about to fall over the side; (b) very low handrails of wire cable which contribute to this impression; and (c) a 230-foot drop to rocks and shallow rapids below the bridge. (p. 511) This was the Capilano Suspension Bridge in Vancouver, Canada. In contrast, the ‘control’ bridge was more solid, had high handrails, and was only tenfeet above a shallow rivulet. Additionally, the experimenter was either a man or woman, yielding a 2 × 2 design. Moreover, at the completion of the questionnaire, participants were debriefed, followed by the experimenter tearing off a corner of paper and providing their name and phone number, offering that the participant could call if they want to discuss the study further. (A different name was provided by the experimenter to help track if a participant was in the experimental or control group.) More of the young men participants accepted the woman experimenter’s phone number than from them man experimenter, particularly in the experimental group. This was further reflected in the number of participants

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that called the experimenter afterwards. The questionnaire itself also included a measure of arousal and showed a similar pattern of results. Two further experiments in the same study also provided convergent support. The findings of this study are interpreted as being due to a causal phenomenon known as mistattribution of arousal. Here one source of arousal, the arousal-inducing bridge likely causing an increase in heart rate, carries over and becomes associated with the woman experimenter as well. This phenomenon with the arousal-inducing bridge demonstrates that one ‘task’ can induce an emotional state, that then influences behaviours in a second task. Some other task procedures are also physiological in nature, but more amenable to experimental studies, such as the cold pressor test (Hines & Brown, 1936; Lovallo, 1975). In this procedure, participants are asked to submerge one hand in an ice-cold water bath for up to three minutes. Here the intention is not to elicit an emotional state per se, but to cause physiological stress. As a control task, warm water can be used. Alternatively, the Trier Social Stress Test (TSST) (Kirschbaum et al., 1993) has participants prepare a speech on a designated topic for ten minutes, to be delivered to a committee. The speech is then delivered to a committee of research assistant actors and recorded; this entire procedure often takes 15–20 minutes (Allen et al., 2017). A friendly variant has been designed as a control task (Wiemers et al., 2013). This task follows similar timing as the TSST but instead has the participant talk about their life and career aspirations. Those assigned the friendly variant did not experience an increase in physiological stress (measured via salivary cortisol), unlike those who were administered the TSST (Wiemers et al., 2013). A hybrid procedure also has been developed, where participants follow the cold pressor protocol, but are also told that they will be videotaped and that these video recordings would be analysed for facial expression (Schwabe et al., 2008; Schwabe & Schächinger, 2018). All of these stress tests have been used in countless studies of emotional memory (Buchanan, Tranel, & Adolphs, 2006; Bos et al., 2014; Murphy et al., 2020). A more recently proposed variation has been the Simple Singing Stress Procedure (SSSP) (Le et al., 2021), where the participant is told: Later on you will be asked to think of a song that you can sing to the experimenter. Your performance will be assessed for memory of the lyrics, in addition to the tone, pitch, and rhythm of your singing. You will be assigned a particular category and will have 60 s to prepare a song from that category. Please note that your performance will also be recorded. You now have the chance to practice singing a song (from a different category to that used later). (p. 1481) This task requires only one experimenter (unlike the TSST) and requires less time than either the cold-pressor test or TSST.

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Even more broadly, some studies have taken advantage of naturalistic stressful situations that people voluntarily partake in, sometimes referred to as ‘recreational fear’. For instance, some studies have examined phenomenological and physiological processes associated with visiting an exotic pet store (with spiders and snakes) or a haunted house (Wessel & Merckelbach, 1997; Valentine & Mesout, 2009; Feinstein et al., 2011; Andersen et al., 2020; Tashjian et al., 2022; Stasiak et al., 2023). Several studies have even been conducted with skydivers in relatively experimental designs (Thompson et al., 2001; Cavenett & Nixon, 2006; Yonelinas et al., 2011), with some participants learning word lists in the plane and others learning them on land during a waiting period. As expected, skydiving increased physiological arousal, but did not interact to enhance memory for emotional words. Cavenett and Nixon (2006) included an additional factor of relevance, with both emotional and neutral skydiving-related and unrelated words being presented. Related words included PARACHUTE and CRASH. Skydiving was associated with enhanced recall of related words in an interaction effect, relative to both unrelated words and the waiting control group. MIN RE

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In addition to the aforementioned mood induction tasks that can be used for both positive and negative states (e.g., film clips, autobiographical recall), some additional options exist specifically for positive mood induction. One approach is as simple as giving participants cookies or candy, or the participant unexpectedly finding money (Isen & Levin, 1972; Isen et al., 1988; Estrada et al., 1994). Incidental occurrences can also induce positive mood states, such as local sports teams winning and even unexpectedly sunny days (Otto et al., 2016; Otto & Eichstaedt, 2018). Exposure to nature environments, green fields and clear blue skies, has also been shown to induce positive moods (Tyrväinen et al., 2014; Browning et al., 2020), even if only experienced virtually (Baños et al., 2012; Yeo et al., 2020; Mostajeran et al., 2021; Pouso et al., 2021). Inducing emotional states can also have influences on memory accessibility. Several studies have demonstrated that people can more readily recall memories that are mood consistent (Bower, 1981; Greenberg & Meiran, 2014; Xie & Zhang, 2017), providing another line of support for context-dependent recall (see Section 3.2, p. 77). This effect also generalises the false memory in a Deese-Roediger-McDermott (DRM) procedure (Howe & Malone, 2011). A further examination of stress effects on memory has been conducted with paramedics, more errors of commission (details not in the original scenario) were observed in the high-stress clinical scenario (LeBlanc et al., 2012).

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To assess emotional state, questionnaire measures can be used. PANAS, the Positive and Negative Affect Schedule, has two subscales: positive affect— which reflects the extent to which a person feels enthusiastic, active, and alert—and negative affect—representing a variety of aversive mood states, including anger, contempt, disgust, guilt, fear, and nervousness (Watson et al., 1988). Another effect is state anxiety—an acute response to perceived threat or stressor. State anxiety is characterised by feelings of tension, nervousness, and heightened arousal, and it can vary in intensity and duration depending on the situation (Spielberger et al., 1970; Zsido et al., 2020).

Trait Several traits can relate to emotional memory effects. One such measure is trait anxiety—as opposed to the aforementioned state anxiety. Trait anxiety is a psychological construct and part of an individual’s personality that refers to a degree of tendency to experience and report negative emotions such as fears, worries, and anxiety across a wide range of situations (Spielberger et al., 1970; Zsido et al., 2020). Trait anxiety has been found to significantly influence emotional memory effects. Individuals with high trait anxiety tend to have stronger emotional memory effects (Reidy & Richards, 1997; Miu et al., 2005; Schümann et al., 2018). High trait anxiety also interacts with a variety of emotional memory-related abilities (Broadbent & Broadbent, 1988; Bar-Haim et al., 2007; Herrera et al., 2015; Toffalini et al., 2015). Depression also influences emotion processing. The Beck Depression Inventory (BDI) is a widely used self-report inventory for measuring the severity of depression. It consists of 21 multiple-choice statements about how the individual has been feeling in the last week (Beck et al., 1961). Depression, as assessed by the BDI, has been linked to impairments in various cognitive functions, including memory. Individuals with higher scores on the BDI may exhibit difficulties in encoding new information, retrieving stored information, and may also show a bias towards recalling negative information (Burt et al., 1995; Gotlib et al., 2004). The Center for Epidemiologic Studies Depression Scale (CES-D) is another widely used self-report questionnaire designed to measure symptoms of depression in the general population (Radloff, 1977; Lewinsohn et al., 1997; Roth et al., 2008). The CES-D consists of 20 items that assess various symptoms associated with depression, such as feelings of sadness, hopelessness, lack of appetite, sleep disturbances, and difficulty concentrating. Respondents are asked to rate how frequently they have experienced each symptom within the past week on a 4-point Likert scale, ranging from 0 (rarely or none of the time) to 3 (most or all of the time). However, both the BDI and CES-D are intended as screening tools, rather than diagnostic instruments. While they can identify individuals who may be experiencing symptoms of depression, a clinical interview is typically required for a formal diagnosis.

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Another emotion-related trait related to memory performance is alexithymia, a trait associated with difficulties in identifying and interpreting internal emotional states (Roedema & Simons, 1999; Luminet et al., 2021), as well as introception more generally (Murphy et al., 2018). As a trait, it is considered more of a continuous distribution, thus individuals vary in their ability to process their internal emotional states. Based on questionnaire thresholds, around 10–20% of the population can be considered high in alexithymia (Mattila et al., 2008; Williams & Gotham, 2021). Additionally, alexithymia tends to be higher in individuals with autism, such that approximately 50% are considered to be high in alexityhmia compared to only 5% in neurotypical individuals (Kinnaird et al., 2019; Williams & Gotham, 2021). There is evidence that some disorders are also associated with higher rates of alexithymia, including schizophrenia, eating disorders, and Parkinson’s disease (Bird & Cook, 2013), Alexithymia is most sensitively measured using the 8-item general alexithymia factor score (GAFS-8) (Williams & Gotham, 2021), a questionnaire refined from the 20item Toronto Alexithymia Scale (TAS-20) (Taylor et al., 1985; Bagby et al., 1994; Li et al., 2015). Individuals with high alexithymia scores demonstrated weaker emotional memory effects than those low in alexithymia (Vermeulen & Luminet, 2009; Vermeulen et al., 2010; Meltzer & Nielson, 2010; Dressaire et al., 2015). Taking a more naturalistic approach, Battista et al. (2021) had participants watch a video depicting a staged fight between two armed men. Here alexithymia did not have direct effects on memory, but did interact with executive function ability in impairing memory. In other words, alexithymia traits only impaired memory in those that had less executive function resources available. Many reasons could explain the discrepancy between prior studies and this one, particularly the change in stimuli from a series of unrelated words or pictures to the use of a naturalistic video. This serves as a reminder that consideration is needed in evaluating how generalisable experimental findings might be to real-world situations.

Neurobiology The brain region most involved in emotional processing is the amygdala. Innumerable studies have shown that the amygdala is more active in response to emotional words or pictures than those that are neutral, as well as when remembering emotional experiences (Cahill et al., 1996; Dolcos et al., 2004, 2005; Kensinger & Corkin, 2004; Kensinger & Schacter, 2006a, 2008; Dougal et al., 2007). These findings have been further aggregated in reviews and meta-analyses (LaBar & Cabeza, 2006; Kensinger, 2009; Murty et al., 2010; Dolcos et al., 2011; Hermans et al., 2014). While many are initially taught that the amygdala is particularly involved in fear or negative emotional processing, it is also involved in positive emotions and can flexibly change in activation profile based on task goals (Cunningham, Van Bavel, et al., 2008).

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Additional insight is provided from patients that have Urbach-Weithe disease, a rare genetic disease. While symptoms can vary across individuals, the disease can lead to bilateral calcification of the blood vessels that supply the amygdala, leading the region to gradually die. As the damage occurs gradually, other regions are able to partially compensate for the amygdala, where the damage is quite specific and pronounced (Markowitsch et al., 1994). Patients with Urbach-Weithe disease have no cognitive deficits, but are unable to judge emotional expressions and have no bias to remembering emotional experiences (Siebert et al., 2003; Hurlemann et al., 2007; Bach et al., 2015). Other individual differences can also influence emotional processing. Alex Honnold is a renowned professional rock climber known for free solo ascents of some of the world’s most challenging rock faces. Free solo climbing is the act of climbing without ropes, harnesses, or other protective equipment— relying solely on physical strength and skill. It’s considered one of the most dangerous forms of climbing. In an fMRI study (Donovan, 2019; Walton, 2022), his amygdala was barely active; he has reported feeling anxiety and fear, but has a strategy for managing it. A woman in Scotland, Jo Cameron, has been reported to have no sensation of pain due to a rare genetic mutation (Habib et al., 2019). In a news article about her, Murphy (2019) reports: “On an anxiety disorder questionnaire, she scored zero out of 21. She cannot recall ever having felt depressed or scared.” While this may sound delightful, the condition is not without its downsides, as “Cuts, burns, fractures—these did not hurt either. In fact, it often took the smell of burning flesh or her husband identifying blood for her to notice something wrong.” Insight into the neurobiology of emotional processing can also help us understand and appreciate the nuances of our brains even more. Patients who are blind due to damage to early visual cortex have been able to judge the facial expressions of presented faces (de Gelder et al., 1999; Pegna et al., 2005; Striemer et al., 2019; Burra et al., 2019) and learn conditioned affective stimuli (Hamm et al., 2003). This ability to process emotional features, despite cortical blindness, is referred to as affective blindsight (Tamietto & de Gelder, 2010; Celeghin et al., 2015). This finding is supported by evidence of at least two paths, often referred to as “roads” in the literature, from visual perception to the amygdala (LeDoux, 1994; Liddell et al., 2005; Pessoa & Adolphs, 2010; Garrido et al., 2012). Specifically, visual information travels from the eyes, through the superior colliculus and thalamus, to early visual cortex, through higher-order visual regions, to the amygdala—the well-known, primary route. However, supplementing this route is a direct pathway from the thalamus to the amygdala. There is also some evidence of direct pathways from the thalamus to other regions, such as the insula or orbitofrontal cortex, that can then pass information to the amygdala. The relationship between affective blindsight and the dichotomy of innate versus learned experiences leaves some questions unanswered. The classic study of Little Albert offers compelling evidence supporting the notion that fear is a learned response (Watson & Rayner, 1920). In this classic experiment,

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Albert—a nine-month-old infant—was presented with a white rat, which initially did not elicit any fear response. However, each time Albert reached out to touch the rat, Watson would create a loud noise by striking a metal pipe with a hammer. This noise startled Albert, causing him to cry and exhibit signs of fear. After several repetitions of this procedure, Albert began to associate the white rat with the loud, frightening noise. Eventually, the mere sight of the rat—or anything vaguely similar, including a Santa Claus beard—was enough to induce fear in Albert, even in the absence of the noise. This phenomenon, known as classical conditioning, demonstrated that fears could be learned rather than being purely innate. The findings of this study have had long-lasting implications to how we understand conditioned responses (Vervliet & Boddez, 2020). The question of what happened to Little Albert after the experiment has been a subject of much speculation and debate (Harris, 1979). For a time, it was believed that Little Albert was a child named Douglas Merritte, who had neurological impairments and died of hydrocephalus at the age of 6. However, more comprehensive investigations have since provided evidence that he was likely Albert Barger, who lived into his 80s (Digdon et al., 2014; Powell et al., 2014). This revelation challenges earlier views that some of Albert’s behaviours were due to neurological impairment. The study also provides a basis for discussions of ethics—while the experiment would be viewed as unethical by today’s standards, it’s important to note that the first formal code of ethics in the field was not adopted until the early 1950s. Ethical considerations should be discussed alongside the study, while also acknowledging that research is not unbound from the societal and ethical context of the time period in which it was conducted. The amygdala—like the hippocampus—is not a unitary structure. Comprised of 13 distinct nuclei, the amygdala is often divided into two or three functional groups, particularly in human fMRI studies. However, as our understanding of the amygdala deepens, researchers are increasingly focusing on characterising emotional responses within its subregions (McGaugh, 2004; Hrybouski et al., 2016; Ritchey et al., 2019; Zeng et al., 2021). The basolateral complex (including the lateral, basal, and accessory basal nuclei) and the centromedial group (comprising the central and medial nuclei) are the most commonly studied and are often the focus of discussions about the amygdala due to their prominent roles in emotional processing. This shift towards a more nuanced view recognises that different nuclei within the amygdala may have distinct roles in emotional processing. For instance, recent research has suggested that the lateral nucleus is particularly important for fear conditioning, while the central nucleus plays a crucial role in the expression of conditioned fear responses. Moreover, the connectivity between these nuclei and other brain regions is also a subject of intense study. For example, the amygdala’s connections with the prefrontal cortex are thought to be critical for the regulation of emotional responses, while its connections with the hippocampus play a key role in the formation of emotional memories.

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I would be remiss to not acknowledge that emotional processing, as with all processes, involves a network of brain regions. Other key regions involved in emotional processing include the dorsomedial and ventromedial prefrontal cortex, the insula, and the temporal gyri (Kensinger & Ford, 2020, 2021; Underwood et al., 2021). The dorsomedial and ventromedial prefrontal cortex are thought to be involved in the regulation of emotional responses, with the ventromedial prefrontal cortex playing a particularly important role in the extinction of conditioned fear responses. These regions are also implicated in the formation and retrieval of emotional memories, contributing to the specificity and vividness of these memories. The insula, on the other hand, is believed to play a key role in interoception—the sense of the physiological condition of the body. It is involved in the subjective experience of emotion. These regions, along with the amygdala and others, form an intricate network that allows us to experience, express, and regulate our emotions. They contribute to our ability to form vivid, specific emotional memories and to be self-aware of our emotional states. Pharmacological agents can also modulate emotional memory. Propranolol and metoprolol, β-adrenergic receptor antagonists, can attenuate emotion effects on memory (Hartley et al., 1983; Liang et al., 1986; Chamberlain et al., 2006; van Stegeren, 2008; Schwabe et al., 2012). In a meta-analysis, Pigeon et al. (2022) estimate the effect size as g = −0.51. Propranolol is used to treat high blood pressure, tachycardia, and anxiety. In contrast, yohimbine—agonist of the same receptor—can enhance emotional memory effects (O’Carroll et al., 1999; Southwick et al., 2002; Rombold et al., 2016). Yohimbine is used to help treat sexual dysfunction (Wibowo et al., 2021). More tangential, but worth considering, drugs can also cause changes in emotional states. While this is the primary function of some drugs, here I will briefly highlight the evidence that a common over-the-counter drug can also influence emotional processing—acetaminophen. A study of emotional processing found that an acute dose of 1000 mg of acetaminophen led to ‘blunted’ emotional responses (Durso et al., 2015). That is, when asked to rate a set of pictures, both positive and negative emotional pictures were rated as less strongly emotional. Other studies have also reported decreases in sensitivity to social pain (e.g., rejection) and empathy (DeWall et al., 2010; Randles et al., 2013; Mischkowski et al., 2016). There is also evidence that hormonal contraception, i.e., birth control pills, also influence cognitive and emotional processes (Pletzer & Kerschbaum, 2014). This has been specifically observed with emotional memory effects (Nielsen et al., 2011, 2013), as well as reward-memory interactions (Bayer et al., 2020; Joue et al., 2022). Though likely not consumed for the purpose of influencing emotional processing, the intention in highlighting these findings is to demonstrate that a wide variety of factors can influence emotion processing, among other cognitive faculties.

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6.3 Confounds and considerations While some emotional studies rely on real-world events, most emotional memory studies instead rely on the presentation of emotional stimuli, often negative in valence, intermixed with emotionally neutral stimuli. These stimuli are often words or pictures, though it can vary if the participants are explicitly instructed that the stimuli are being presented for a subsequent memory test, or are encoded incidentally while participants perform a rating or judgement task. Memory is then tested after a brief delay of tens of seconds or perhaps the following day. While this summary provides allowances to account for some variations in experimental design, it is broad enough to include hundreds of studies, all that generally demonstrate an emotional enhancement of memory, often abbreviated as EEM. There are several mechanisms that allow for emotional stimuli to be better remembered than neutral stimuli. While these can be at least somewhat controlled for in an experimental task, if desired, it is first necessary to discuss them and how they occur. In principle, most of these potential confounds can apply to other categories of stimuli. As such, these considerations will not be discussed as much in other chapters. Moreover, other topics have not been studied to the same extent as emotional memory.

Attentional capture Attentional allocation is likely the most readily observable mechanism for the emotional enhancement of memory. Emotional words, and especially pictures, capture attention more than neutral information based on a bottomup attention. This effect can be demonstrated using procedures such as attentional blink (see Shapiro et al., 1997a; Dux & Marois, 2009, for a review), where a series of stimuli is rapidly presented and participants are instructed to press a specified key when a certain stimuli is presented. If an emotional stimuli precedes this stimuli’s presentation, participants often do not consciously process the following stimuli (Most et al., 2005; Arnell et al., 2007). This interpretation here is that attentional resources are still occupied by the preceding emotional item, causing a ‘blink’ before resources are available again for subsequent items to be processed, sometimes referred to as emotion-induced blindness. Other procedures yield convergent results, for instance, emotional stimuli are preferentially processed when a complex scene or array of stimuli are simultaneously presented (MacLeod et al., 1986; Strange et al., 2003; Gerritsen et al., 2008; Lamy et al., 2008; Strauss & Allen, 2009). This attentional bias towards emotional stimuli can be equated for if items are presented sequentially and for a sufficient duration that attentional resources are not limited (Madan, Caplan, et al., 2012; Madan, Scott, & Kensinger, 2019).

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Semantic relatedness When asked to remember a list of words with some emotional and some neutral, there is an inherent issue in how inter-related the words are. In principle, this is the same issue of semantic clustering alluded to earlier (Section 3.3, p. 88), however, it is based on the inherent semantic relatedness present in emotional words. For instance, consider the emotional word list: PAIN, FAILURE, DEATH, DESPISE, BOMB; along with the unrelated neutral word list: PHASE, CHAIR, LOUD, FLOW, CABINET. With these lists we would find better free recall for the emotional list (Talmi & Moscovitch, 2004). However, if we instead used a list of neutral words that were matched in semantic relatedness, using a model of topic space, we can generate a categorised neutral list such as: VEHICLE, MOVE, IGNITION, ROUTE, WHEEL. Here we find comparable free recall for the emotional and categorised neutral lists, as demonstrated by Talmi and Moscovitch (2004). Providing convergent evidence that emotional stimuli are semantically related, recall intrusions can be elicited using a DRM procedure (Budson et al., 2006; Holland et al., 2010; Dehon et al., 2010). As an example: FESTIVAL, GALA, BIRTHDAY, ADVENTURE, FRIENDS, REJOICE, JUBILEE, ANNIVERSARY, HOLIDAY, FIESTA, TRAVEL, OCCASION, CEREMONY, SOCIAL. The falsely recalled target is CELEBRATION. MIN RE

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Based on the results of Talmi and Moscovitch (2004), several studies have used categorised-neutral words as a control condition but still found emotion effects in other measures, such as psychophysiological responses or other memory tests (Buchanan, Etzel, et al., 2006; Madan, Caplan, et al., 2012). Moreover, while this is a feasible approach to match emotional and neutral word stimuli using a model of topic space (Landauer et al., 1998), it is markedly more difficult when using picture stimuli due to the differences in semantic content present in pictures (Palombo, Elizur, et al., 2021). Jackson et al. (2019) examined the semantic structure of emotional language itself, conducting an analysis of emotion concepts across 2,474 spoken languages across 19 families. While there were cultural variations, a universality was also observed—providing insights into how all humans commonly understand and experience emotions. Semantic networks of emotion concepts were primarily characterised by hedonic valence and physiological activation. Other dimensions considered included certainty, dominance, approach–avoidance, and sociality—informed by past literature.

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Distinctiveness Some studies present emotional items only infrequently within lists, leading them to be distinct and have enhanced memory due to both emotionality and von Restorff/oddball effects (Strange et al., 2003; Schmidt & Saari, 2007; Smith & Beversdorf, 2008; Schlüter et al., 2019). When both both semantic relatedness and distinctiveness are matched for between emotional and neutral lists of items, memory can be equivalent in an immediate memory test (Talmi et al., 2007; Talmi & McGarry, 2012). Distinctiveness differences can, however, be considered beyond the scope of the experimental session itself (Schmidt, 1991). Most studies of emotional memory present emotional and neutral stimuli equally often—this matches them for primary distinctiveness (see Section 3.5, p. 95). As emotional experiences inherently occur less often than mundane ones in everyday life, the conditions still differ in secondary distinctiveness. Because of this, even when seeing a list of emotional and neutral words with either occurring equally often, the emotional ones are being presented much more often than they normally would be—even if they are merely negative words that are similar to those used in news articles. Unfortunately this limitation simply needs to be acknowledged and cannot be fully corrected for. Christianson and Loftus (1991) conducted a series of five experiments involving 397 participants, based on this principle. Using carefully designed slideshows, they presented participants with emotional, neutral, and unusual versions of the same event, then tested their memory for both central and peripheral details. Interestingly, participants who viewed the emotional version—depicting a woman injured next to a bicycle—demonstrated superior memory for central details, such as the colour of the woman’s coat. However, those who viewed the neutral version, where the woman was simply riding the bicycle, remembered peripheral details—like the colour of a background car—more accurately. This suggests that emotional stimuli may focus our attention and enhance memory for central details, at the cost of peripheral details. The unusual version of the event, where the woman was carrying the bicycle on her shoulder, did not improve memory for any details, indicating that the impact of emotion on memory extends beyond merely making an event distinctive.

Taboo stimuli To elicit stronger emotional responses without using pictures, some studies have instead used taboo words (such as BREAST, DILDO, and AMPUTATE) (Buchanan, Etzel, et al., 2006; Schmidt & Saari, 2007; Guillet & Arndt, 2009; Kensinger & Corkin, 2003; Madan, Caplan, et al., 2012; Madan, Shafer, et al., 2017). Taboo stimuli are defined as “a class of emotionally arousing references with respect to body products, body parts, sexual acts, ethnic or racial insults, profanity, vulgarity, slang, and scatology” (Jay et al., 2008). As expected,

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memory effects in these studies are more pronounced than what is found with less arousing, negative words. Though taboo words can be used to elicit emotional responses, important caveats are necessary—such as comparisons with appropriately matched control word lists, again making an understanding of memory fundamentals critical; for instance, awareness of word-frequency effects on memory (as discussed in Section 3.5, p. 93) as well as effects of semantic relatedness. Taboo words are also difficult to construct as a long list of stimuli, as only a narrow list of words is able to elicit strong taboo responses. Additionally, some words that otherwise would be neutral may be perceived as having taboo-related connotations if presented in the context as taboo words, such as SCREW. While these are associated with greater emotional arousal, studies have also found that they are unique in other ways, both with respect to other common word properties, such as being particularly low in word frequency, but also having an additional unique property related to a shock value or tabooness (Bertels et al., 2009; Janschewitz, 2008). Madan, Shafer, et al. (2017) examined this with particular interest, investigating emotion and taboo words in lexical-decision and free-recall tasks. Replicating prior studies, taboo words were associated with slower response times in lexical decision (i.e., lexical accessibility) and higher recall probabilities in free recall (i.e., retrievability). Through item analysis, it was determined that different sets of word properties best explained these effects: Lexical decision performance was best explained by non-emotional word properties linked to lexical accessibility (word frequency, familiarity). However, free recall was best explained by emotional word properties, and of the emotional properties considered, the inclusion of tabooness was necessary to best explain memory performance. As such, the processing of taboo words is influenced by distinct sets of factors, and taboo words are not merely high-arousal emotional words, but also possess an intrinsic tabooness property. These findings should not be taken as generalisable to all individuals, however. Recent research has demonstrated that individual differences can mediate how people evaluate taboo words, including age, gender identity, and sexual identity (Edmondson, 2022).

Response bias People tend to endorse emotional items as ‘old’ more often than neutral ones (Maratos et al., 2000; Dougal & Rotello, 2007; Kapucu et al., 2008). This can be otherwise interpreted as a bias in response criterion in the recognition judgement. If response bias—this increased rate of false alarms—is not adequately considered, a higher hit rate for emotional than neutral items might simply be viewed as evidence of an emotional enhancement of memory (EEM). For more nuanced discussions of this phenomenon, see Brainerd et al. (2008) and Rotello and Macmillan (2007).

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Related to this response bias in old/new recognition procedures, other studies have observed emotion influences on both judgements of learning (Zimmerman & Kelley, 2010; Caplan, Sommer, et al., 2019; Palombo, Te, et al., 2021) and confidence ratings (Talarico & Rubin, 2003; Sharot et al., 2004, 2007; Phelps & Sharot, 2008). Briefly, judgements of learning (JOLs) occur during encoding and are a rating of how likely the participant thinks they will successfully remember the memoranda. Confidence ratings are made during recognition and are a measure of how sure the participant is of their response. In some instances, both of these metamemory judgements are discussed as ‘confidence.’ Across these studies, emotion leads to overestimations of subjective measures of memory, both judgements of learning and confidence, relative to objective measures of memory accuracy. This bias in subjective remembering can also manifest as more recollection responses for emotional items in remember/know paradigms. While responses biases are problematic when the goal is to assess veridical memory, they can be addressed by using different memory test procedures (see Section 3.2, p. 68). However, the presence of these biases and how they relate to different motivational processes provides insight into how the content is being processed and into memory itself.

Test–retest reliability Despite the large and quite conclusive literature demonstrating that emotional items are remembered better than neutral items, recent results demonstrate that the reliability of this result is relatively poor. When conducting an experiment, it will be clear that the emotional enhancement of memory (EEM) is larger in some participants than others. The next question you might ask, is if this effect is consistent in strength as an individual difference measure—for those that show a strong EEM at one timepoint, would they still be one of the stronger EEM participants at a later session? Schümann et al. (2020) found that the test–retest reliability of the EEM over a ten-week interval was quite poor (e.g., r = .16, all variations were similarly weak). This was further replicated in another sample, and the work was inspired by a previous study’s report of a weak correlation with a 3.5year interval (Schümann & Sommer, 2018). For the study with a several-years delay, it was suggested that the low reliability may be due to a large number of life changes between the sessions, such as finishing university studies and entering the workforce, and differences in the procedure such as behaviouronly vs. concurrent fMRI scanning. Even with a ten-week delay, it is possible that state differences may be relevant, such as being in a different mood. Regardless, these ‘limitations’ in the viability of using EEM effect size as an individual difference measure have been underestimated in past work. Another recent study has also observed poor test-retest reliability in a attentional bias measure related to negative emotional expressions (Gladwin et al., 2020), providing further generalisation of this limitation. This may very

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well relate to a quite general limitation of cognitive psychology task designs, rather than being particularly specific to emotional memory research (see Hedge et al., 2018).

6.4 Memory is multifaceted The relationship between memory and emotion is complicated. As highlighted earlier, numerous factors can influence the effects of emotional memory, such as the selection of interleaved items and their correspondence to everyday situations. In addition to these, we need to consider how emotionality itself might be understood, in terms of how it can bias memory, how emotional items inter-relate, how these effects change over different time intervals, and even how emotion can influence how we remember time intervals.

Emotion as a semantic property Emotion itself serves as a semantic property of stimuli that is presented. This is evident in the discussion of considering semantic relatedness—the degree to which items are related in meaning. When presenting stimuli that are a string of letters or arrays of pixels, this is not what a participant truly processes, but rather are concepts that evoke scenes and feelings. When we look at an emotional picture, the evoked feelings occur because we automatically process the semantic meaning of the picture. While the picture is likely sufficient to evoke an emotional response regardless, pre-existing or concurrently presented semantic knowledge can increase this response. To delve deeper into this dynamic, we will examine the background of a few IAPS pictures, a process informed by the research undertaken in the course of writing this book. IAPS 2830 is a famous picture—I am actually quite surprised it is in the database given the pre-existing associations that some may have for it. This photo features a 12-year-old girl with vibrant green eyes in a refugee camp, now widely known as ‘Afghan Girl.’ In June 1985 it was the cover of National Geographic and has since become the most recognised and memorable photo from the publication’s history (McCurry, 2001). The photo has been praised for capturing the determination and resilience of the Afghan people in this time of adversity. While current research study participants are much less likely to be already familiar with the photo than those from generations past, knowing the historical significance behind the photo likely would affect how well people remember it. IAPS 5470 is also quite famous, featuring an astronaut in space with the Earth in the background. This photo was taken in February 1984 from the space shuttle Challenger, during the first untethered spacewalk (mission STS41-B). Here Bruce McCandless II is testing the maneuverable spacesuit. IAPS 9050 shows a mass of people walking away from a crashed plane. Of the nearly 400 passengers and crew, most survived the crash, but 50 people

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died in the tragedy. Spantax 995 crashed almost immediately after take-off in Malaga, Spain in 1982 (Aviation Safety Network, 1982). Part of one of the wheels had broken off and resulted in strong vibrations, the pilot tried to abort take-off but was unable to. The plane collided with a nearby building and stopped 500 metres after the end of the runway, with a fire erupting in the plane cabin. IAPS 3550_1 uses this same photo as the background. IAPS 2900 shows a crying boy. Obviously a negative picture, knowing the context makes it much more poignant—the IAPS picture is cropped from a larger photo that shows a family mourning. The photo is from the funeral from the child’s father, murdered in the 1991 war for Croatia’s independence—taken by photojournalist Ron Haviv (Walsh, 2019). Understanding the agony behind the photo makes the same picture evoke much stronger emotions. IAPS 2730 was taken in March 1993 by Kevin Carter, a photojournalist covering the famine in Sudan. Another photo from this same trip, “The Vulture and the Little Girl,” was featured in The New York Times on March 26, 1993, and won the Pulitzer Prize for Feature Photography award in 1994. However, Carter was deeply affected by what he saw in Sudan and committed suicide four months after winning the prize (Marinovich & Silva, 2000). Carter’s suicide note specifically references being haunted by vivid memories from what he saw during this trip. Knowing these facts about the IAPS pictures, you likely will not see them the same way again. Even for other pictures, you might think a bit more about how the photo came to be—I know I will, now that I have delved into the history of these few. This perspective has parallels to the instruction manipulation used by Bransford and Johnson (1972); understanding the situation surrounding information can make it much more meaningful and memorable than when it is presented isolated from this context. Studies supporting this are discussed in Section 11.4 (p. 345). For these pictures to be effective in eliciting their associated emotional reaction, they need to be parsed for semantic meaning. Individual variations in how these meanings are interpreted are relevant to their use as stimuli. For instance, individual variations in trait alexithymia could influence the understanding of emotional pictures and the subsequent emotional memory effects. People with high levels of alexithymia may have a reduced ability to connect with the emotional content of a picture, as they might struggle to recognise and articulate the feelings that the picture would typically evoke. This could result in a less intense emotional reaction to the picture and, consequently, differences in memory encoding and retrieval. For example, the emotional intensity and historical context of a picture like ‘Afghan Girl’ might not resonate as strongly with an individual high in alexithymia, leading to a less vivid memory trace. This highlights the importance of considering individual differences in emotional understanding and expression, which in turn will influence memory processes. Implications may also be more practical—such as for therapeutic interventions—where understanding a client’s level of alexithymia would influence emotional awareness.

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Memory for associations Emotional stimuli are not processed as singular ‘items’; stimuli such as a scene can be interpreted as constituent parts. Even with words, the font colour can be a source property, distinct from the emotional content of the word’s meaning. When viewing an emotional scene, people will tend to focus on the central emotional details, at the cost of the peripheral information. As this phenomenon was first identified in eyewitness memory studies, it is referred to as the weapon-focus effect—where people would remember details about the gun, but not the individual holding it (Loftus, Loftus, & Messo, 1987; Fawcett et al., 2013). The effect is more generally referred to as attentional narrowing (Easterbrook, 1959; Christianson, 1992; Berntsen, 2002). This selective focus on central details is thought to be adaptive, as it allows individuals to concentrate on the most important information in emotionally charged situations. MIN RE

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Within experimental studies, this has been further demonstrated with presentations of sequences of scenes, followed by recognition tests of central objects and peripheral backgrounds. Critically, emotional stimuli can enhance memory for central details while impairing memory for peripheral details (Christianson & Loftus, 1991; Kensinger et al., 2007a; Payne et al., 2008). This interaction effect is described as an emotion-induced memory tradeoff. The study of this trade-off often involves experimental paradigms where participants are presented with sequences of scenes, each containing a central object and a peripheral background. These scenes can be either emotionally neutral or emotionally charged. Subsequent recognition tests reveal that participants tend to remember emotional central objects better than neutral ones. However, peripheral backgrounds of neutral scenes are remembered better than those of emotional scenes, demonstrating the emotion-induced memory trade-off (Kensinger, 2007). The selective enhancement of memory for central details in emotional situations has been demonstrated across various experimental paradigms, including studies using pictures, narratives, and real-life events. Depending on the specific circumstances, however, what is considered ‘central’ may be unclear (Levine & Edelstein, 2009). It could be the aspect of the scene that captures the most attention (Laney et al., 2004) or what is spatially or temporally most distinct (Christianson & Loftus, 1991; Burke et al., 1992). In other situations it may be more relevant to consider the conceptual integration of features (Yuille & Cutshall, 1986; Heuer & Reisberg,

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1990; Peterson & Whalen, 2001; Berntsen, 2002) or what is contextually more goal relevant (Gable & Harmon-Jones, 2010b; Turkileri et al., 2021). Sequences of pictures can also involve central-peripheral trade-offs, even with instructional cues only differing between two conditions. Kramer et al. (1991) showed participants a series of 19 picture slides, with the middle (tenth) slide serving as the between-group manipulation. The tenth slide depicted a disfigured face; for the high-stress group, it was labelled “NYPD”; for the moderate-stress group, the same image was instead labelled “MGM Studios.” For an additional control group, a neutral image of a tourist was shown. The results indicated an increase in anxiety for the NYPD-labelled group compared to the other two groups, suggesting a successful manipulation of stress levels. In terms of recall, baseline performance was the same for slides presented before the critical tenth slide. However, impaired recall quality and quantity was observed for slides shown after the tenth slide in the highstress group, compared to the control group. Recall was negatively related to anxiety, supporting the hypothesis that stress exposure can impair memory for subsequent events. Thus, this study shows that the interpretation of an emotional experience affects how it is processed. Also see Section 11.4 (p. 345) for a well-known example of an instruction manipulation affecting memory. These findings also have implications for eyewitness memory, suggesting that traumatic events impair memory for details after the event. Some studies have also used video stimuli to assess emotional memory effects. Luna and Albuquerque (2018) showed participants a four-minute CCTV video of a bank robbery. Half of the participants were given intentional memory instructions; the other half only encoded it incidentally. The study was primarily interested in the types of details that participants remembered, assessing the centrality, production frequency, and forensic relevance of what was remembered. Results suggested that production frequency should not be used as a measure for centrality, but forensic relevance may be a better indicator. Dev et al. (2022), in contrast, examined emotional effects on memory sequences in the absence of schema information. Participants were shown a sequence of clips from the 2018 movie Pihu. This movie is relatively unique in including only one character (a young girl) for most of the duration with nearly no speech or schema information. Two versions of clips—high and low emotion—were made for the study (each approximately eight minutes in duration); each version was assigned to participants in a between-groups design. Participants given the high-emotion clips performed better in an order reconstruction task but were similar in several measures derived from their narrative recall of the video. The object-based framework proposed by Mather (2007) provides a theoretical perspective on these findings. According to this framework, emotional arousal enhances memory for the object or event that is the source of the arousal, while impairing memory for other, unrelated objects or events. This framework suggests that the effects of emotional arousal on memory are not simply due to a general enhancement or impairment of memory,

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but rather are due to a selective effect on memory for emotionally relevant information. This perspective was further developed and refined in subsequent work by Mather and Sutherland (2011). They proposed that the effects of emotional arousal on memory are mediated by a process of emotional binding, in which emotional arousal enhances the binding of emotional information to other, related information. This process of emotional binding can enhance memory for emotionally relevant information, while impairing memory for unrelated information. This work has provided a more nuanced understanding of the emotion-induced memory trade-off, highlighting the complex interplay between emotional arousal, attention, and memory. Emotional stimuli are usually remembered better than their neutral stimuli, but what about memory for associated information? Guillet and Arndt (2009) presented some words centrally—which were either neutral, negative, or taboo—along with a neutral word in the periphery. Using the central word as the cue in a cued recall test, participants performed better when the central word was taboo than when it was neutral. Though there was no difference in recall for the trials with negative vs. neutral cues, this was viewed as evidence that emotion enhances association-memory. Around the same time, however, Zimmerman and Kelley (2010) conducted a study where participants learned word pairs where both items were positive, negative, or neutral. Here the negative pairs were remembered worse than the neutral pairs, and the positive pairs were remembered best (also see Okada et al., 2011). These studies presented conflicting findings, but also had variations in the procedure that may be relevant in resolving this apparent discrepancy. Madan, Caplan, et al. (2012) asked participants to learn pairs of words where both words were negative or neutral, or were one of each. This design here also presented the two words sequentially, to attenuate emotional attentional capture effects, and either the first or second word presented could be used as the cue. With this approach, there were pairs where both words were negative or neutral, as in Zimmerman and Kelley (2010), but also cued recall trials with ‘mixed pairs’ where a negative word is used as the cue for a neutral word, as in Guillet and Arndt (2009). Though this 2012 study was initially planned prior to either of the other studies’ publication, the use of a ‘complete’ experimental design was well suited to follow these studies. Indeed, both patterns of results were replicated. Using a mathematical modelling approach previously designed for this item—association design (Madan et al., 2010)—it was shown that while negative emotion had enhanced item retrieval, it was impairing association-memory. An additional comparison group given categorised neutral and random neutral words was also included, to provide a control for the semantic relatedness confound, previously identified by Talmi and Moscovitch (2004). A follow-up experiment with taboo words indicated that taboo words both served as better memory cues and targets, but were not enhancing the association per se, also serving as a demonstration that taboo words are not functioning merely as higher arousing stimuli, but also carry taboo-specific characteristics.

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This result with negative emotion impairing association-memory has since been replicated in subsequent studies (Bisby & Burgess, 2014; Bisby et al., 2018; Caplan, Sommer, et al., 2019; Palombo, Te, et al., 2021; Stewardson et al., 2023). Broadly, this work and others (Mather & Knight, 2008) can be viewed as an emotion-related impairment of contextual binding. These findings have some practical implications as well—advertisers would do well to not evoke too strong emotions, lest viewers have worse memory for their brand compared to more mundane advertisements (Bushman & Bonacci, 2002). Subsequent work includes an adaptation to use pictures instead of words to elicit stronger emotional responses and additional modifications to make the procedure more suitable for fMRI data collection (Madan, Fujiwara, et al., 2017). Hippocampal engagement was comparable for both negative and neutral pairs, with a clear SME evident for both. While the amygdala was more active for negative pairs than neutral ones, the SME was not significant here, but was in a region of the posterior insula. Additionally, a region of parahippocampal cortex was involved in an SME specific to neutral pairs. Using different experimental procedures, species, and neuroscientific methods, Holmes et al. (2013) observed a nearly identical dissociation between amygdala and perirhinal memory function. A follow-up study with whole-brain coverage replicated the behavioural and initial fMRI results, but also provided insight into the role of prefrontal cortical regions (Fujiwara et al., 2021). A region in the dorsomedial prefrontal cortex was selectively involved in negativepair learning, while a region in the ventromedial prefrontal cortex supported learning of neutral pairs. In some studies, negative emotion does enhance association memory— though the form of this varied, e.g., word–colour vs. object–background (Doerksen & Shimamura, 2001; Kensinger & Corkin, 2003; MacKay et al., 2004; Madan et al., 2020). While the specific experimental differences that result in this enhancement, rather than impairment, are unclear, one possibility is that conceptual congruence may be necessary for the enhancement; whereas situations where the to-be-associated items are more distinct result in impairments (Madan, Caplan, et al., 2012; Madan, Fujiwara, et al., 2017; Bisby et al., 2018; Palombo, Te, et al., 2021; Stewardson et al., 2023). This could be viewed as a distinction between intra-item vs. inter-item associations (Mayes et al., 2007; Mather, 2007). The specific characteristics that distinguish these two outcomes are a current topic of research. Providing some evidence of an interaction between memory systems, some studies have further shown that associating emotionally neutral stimuli with emotionally negative (or positive) images can lead to a change in the perceived valence of the previously neutral stimuli (Mather & Knight, 2008; Palombo, Elizur, et al., 2021). While this phenomenon has been understudied within the emotional memory literature, it is a more developed topic in the marketing literature under the term evaluative conditioning (Kunst-Wilson & Zajonc, 1980; Jones et al., 2010; Walther et al., 2011). In a meta-analysis, Hofmann et al. (2010) report the mean evaluative conditioning effect size as d = 0.52.

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Immediate and delayed memory tests From the findings highlighted thus far, you may think that emotional items are more easily remembered than neutral ones—though these effects could, at least partially, be attributed to differences in attentional capture, semantic similarity, and distinctiveness. The literature on emotional memory, however, is more nuanced. Kleinsmith and Kaplan (1963) conducted an early study of the influence of retention interval on emotional memory. Participants in this study learned associations between words, varying in emotional arousal, and single digit numbers. After the study session, participants were divided into groups, each with a different interval between study and test. Participants were tested using cued recall, given the word and asked to respond with the associated number. The five intervals were immediate (2 minute), 20 minute, 45 minute, 1 day, and 1 week. In the immediate memory test, more low-arousal associations were recalled than high-arousal associations. For the 20-minute delay, recall was equivalent for the two conditions. At later delays, recall was better for the high-arousal associations, with the effect strongest after the 1-week delay. Convergent results—demonstrations of weak to no effects of emotion on memory at immediate tests, but definitive enhancements of emotional memory—have been found in many later studies (Sharot & Phelps, 2004; Sharot & Yonelinas, 2008; Pierce & Kensinger, 2011). One explanation for this pattern of findings is that memories involving emotion are forgotten more slowly (Cahill & McGaugh, 1998; Yonelinas & Ritchey, 2015). Mnemonic similarity procedures have also been used with emotional stimuli (Kensinger et al., 2007b; Leal et al., 2014, 2017). As with previous studies, memory is better for emotional items and is forgotten more slowly over a delay. However, memory precision is lost over the delay, suggesting that only gist representations are maintained for these emotional experiences. A comic, shown in Figure 6.2, is convergent with these findings. In a well-designed study, Schümann et al. (2018) examined immediate and delayed emotional enhancements of memory. Here a sample of 646 participants studied 120 pictures (40 each for positive, negative, and neutral) in an incidental encoding procedure. Half of the pictures were tested tenminutes later in an immediate recognition memory test, while the remaining pictures were tested 20 hours later in a delayed recognition test. In aggregate, emotional enhancements of memory (EEM) were present at both test intervals. However, different participants demonstrated immediate vs. delayed EEMs; these effects were not correlated across participants. The authors propose that the immediate EEM is associated with activation of the locus coeruleus (LC) and noradrenergic system. In contrast, the delayed EEM may be due to a direct connection between visual regions and the amygdala, related to arousal detection. We will discuss the locus coeruleus further in Section 10.2 (p. 299).

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FIGURE 6.2: When they look back. Credit: Lunarbaboon Comics, by Christopher Grady.

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Slowing down time Emotional experiences tend to feel like they last longer than their actual duration. As an example, people involved in an acutely stressful situation— such as a car accident or bank robbery—often describe feeling that everything slowed down (Noyes & Kletti, 1977; Loftus, Schooler, et al., 1987; Cardeña & Spiegel, 1993; Petrucci & Palombo, 2021; Safi et al., 2024). In an interview performed by Noyes and Kletti (1977), one participant described an incident from four years earlier where he had been driving a car at 60 mph when the steering gave out: …my mind speeded up. Time seemed drawn out. It seemed like five minutes before the car came to a stop when, in reality, it was only a matter of a few seconds. I remember that my sense of touch and hearing became more acute. I was unusually aware of my grip on the steering wheel and of my body touching the seat behind me. The grass brushing the door was unusually loud. On the other hand, my vision was blurred except for an instant when my attention became focused on the abutment ahead…My mind was working rapidly and reviewed information from driver’s education that might bear on what I should do to save myself. It seemed to be working on more than one level, however, for at the same time I had a clear image of myself being killed. I saw this as though watching it on a television screen from an unusual angle; that is, I saw it from a distance of about 50 feet as though looking at the car from the side. I pictured this wreck occurring in slow motion… (p. 376) Chapman and Underwood (2005) investigated this phenomena experimentally by showing participants video clips of safe and dangerous driving events, artificially edited to play faster or slower than the original speed. When asked to judge the speed of the event, participants judged the dangerous situations as occurring faster than expected—corresponding to a perspective that time should be moving slower when in danger (also see Chapman et al., 2005). Convergent results have also been found in later studies (Cœugnet et al., 2013). William James (1890) also described this phenomenon: “In general, a time filled with varied and interesting experiences seems short in passing, but long as we look back. On the other hand, a tract of time empty of experiences seems long in passing but in retrospect short” (p. 624). This view was later independently echoed by Ornstein (1969):

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Memories that matter a ‘boring’ situation often seems very long to us. Why? […] Situations which we label ‘boring’ are ones in which we are forced to attend to more of the stimulus array than we normally would, like listening to a professor drone on and on. Again, an increase in attention, relative to normal experience, would cause a lengthening of duration experience. (p. 112)

If you are reading this book as part of a class, I hope this description feels unfamiliar to you. These perspectives have been corroborated empirically. In an experimental task with video stimuli, a greater number of events within the video lengthened subjective duration and accelerated the felt passage of time (LamprouKokolaki et al., 2024). As described in the study of COVID-19 pandemic events and memory (Rouhani et al., 2023), time estimates were compressed due to the lack of distinct events during this period. The table-top role-playing game Dungeons & Dragons can provide some convergent insight here (Madan, 2016b; Wizards of the Coast, 2018). In an adventure, players can journey between cities within a single game session— such that many in-game days occur within minutes to hours of real time. Conversely, when in combat, where the players need to think quickly, each round of combat corresponds to six seconds, and hours of real time are only mere seconds in-game. To provide a concrete example, I examined Critical Role, a popular online show where professional voice actors play Dungeons & Dragons. The overall show has been produced for over seven years now. Critical Role Campaign 2 occurred over 141 episodes (average play time of 3 hours 26 minutes per episode session) (CritRoleStats, 2021). Across these sessions, 484 hours of real time were played, corresponding to 327 in-game days. However, of these 484 hours, 109 hours was spent in combat (across 139 encounters). The total in-game duration of these encounters was only 57 minutes. Taken together, overall playing the game had two-thirds of an in-game day pass every hour of real time; but, for 23% of the real game time, time slowed to less than one in-game minute for every real hour. Thus, convergent with the emotion time dilation principle, when experiences are rich and eventful, time relatively slows down. Returning to direct empirical studies, Stetson et al. (2007) found that this elongating of durations occurs retrospectively, rather than due to faster processing in the moment. Participants jumped and free fell for 31 metres before being caught in a net. Retrospectively, participants estimated their fall to have a longer duration than when they watched another person fall— replicating past findings. Critically, however, while falling, participants wore a wrist-mounted LED display that presented numbers. After landing, they verbally reported the numbers displayed to the experimenter. If time slowed down ‘in the moments,’ participants would be expected to process the number presentation with higher temporal resolution—but this was not found. DroitVolet and Meck (2007) proposed a cognitive mechanism for these effects,

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suggesting that we have an internal, mental pacemaker that keeps track of time. However, the rate of this pacemaker is modulated by attentional deployment—given the results of Stetson et al. (2007), however, this is only affected in retrospective judgements. This emotional time-dilation is not only a slowing—in a study with novice skydivers, fear was associated with a slower passage of time, but excitement was associated with faster time perception (Campbell & Bryant, 2007). Similar results are also reported by Bailey and Chapman (2023) from a study conducted with a vertical-drop rollercoaster at the UK theme park, Alton Towers. Studies of emotional time-dilation tend to focus on stressful and traumatic events, just as most of the emotional memory literature studies negative emotion.

6.5 Good is not merely the opposite of bad In emotional memory research, a bias towards the study of negative emotions is evident. This bias is not without reason, as negative emotions often have a more profound impact on our memory systems. Negative events tend to be more salient and impactful in our lives, making them more memorable. Consider the vivid memories that traumatic events create. These experiences, though unfortunate, tend to engrave themselves deeply into our memory. Personal losses, such as the death of a loved one, have a long-lasting impact on our memories. The grief and sadness associated with such events can strengthen our recall of these experiences and often remain in our minds for years, if not a lifetime. Crimes, particularly those experienced first-hand, are another example where negative emotions enhance memory. The fear and stress associated with being a victim of a crime can lead to vivid, though not always accurate, memories of the event. This negativity bias has been well-documented in the literature (Baumeister et al., 2001; Lazarus, 2021). The bias towards studying negative emotional memory can be attributed to both clinical and evolutionary reasons. Clinically, negative emotions and traumatic experiences are often the focus of mental health research and treatment. Conditions such as post-traumatic stress disorder (PTSD), anxiety disorders, and depression are characterised by an overemphasis on negative experiences and an inability to forget or move past these experiences (Brewin, 2001; Öhman & Mineka, 2001; McNally, 2006). Understanding how negative emotions impact memory can provide valuable insights into these conditions and inform treatment strategies. Positive emotions generally are not as strong as negative emotions (Fredrickson, 1998; Baumeister et al., 2001). For instance, taxonomies of discrete emotion—e.g., Ekman and Izard—have more emphasis on negative emotions. Other approaches to differentiate emotional states have also indicated that positive emotional states are less distinct from each other than negative states (Ellsworth & Smith, 1988; Koch et al., 2016).

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In contrast, however, more languages tend to have more words representing positive emotions (Dodds et al., 2015). This is not to say that the effects of positive emotions on memory are unknown. People tend to view their lives as pleasant and can recall more positive events than negative ones (Waldfogel, 1948; Thompson et al., 1996; Diener & Diener, 1996; Walker et al., 2003). Studies have also found that individuals may be willing to forego monetary rewards just to reminisce about positive events (Speer et al., 2014), indicating the powerful influence of positive emotions on our cognitive processes. Positive emotions are often associated with broadening the scope of attention and creative thinking (Estrada et al., 1994; Gasper & Clore, 2002; Fredrickson & Branigan, 2005; Rowe et al., 2007), and is the basis of the broaden-and-build framework (Fredrickson, 2001). Other views also highlight the importance of positive emotions in day-to-day life (Walker et al., 2003; Lyubomirsky et al., 2005). Positive emotion has also been associated with broadening in memory—measured as better memory for peripheral details or better memory for associations (Talarico et al., 2009; Okada et al., 2011; Yegiyan & Yonelinas, 2011; Madan, Scott, & Kensinger, 2019). In some ways, this is the opposite of the memory narrowing observed with negative emotion. MIN RE

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Positive experiences, by their very nature, tend to be more idiosyncratic and subject to individual interpretation than negative ones. What constitutes a positive experience can vary greatly from person to person—influenced by factors such as cultural background, personal values, and life experiences. For example, one person might find joy in solitude and quiet reflection, while another might derive happiness from social interactions and lively gatherings. Moreover, the context in which positive experiences occur can also influence their interpretation and the emotions they evoke. A surprise birthday party might be a delightful experience for someone who enjoys being the centre of attention, but it could be a source of stress and discomfort for someone who prefers low-key celebrations. Effects of emotional valence on memory are not static; they can change over time due to various factors. One of these factors is the fading affect bias (FAB), a psychological phenomenon where the emotions associated with past events tend to fade more for negative events than for positive ones. This means that as time passes, the emotional intensity of our memories tends to decrease, but this decrease is more pronounced for memories associated with negative valence. The FAB is thought to serve a self-enhancing purpose, helping individuals to

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maintain a positive self-concept and promoting psychological health and wellbeing (Matlin & Stang, 1978; Linton, 1982; Wagenaar, 1986; Walker et al., 1997, 2003). A second factor is the Pollyanna principle—or positivity bias— which also plays a role in how emotional valence effects change over time. The name ‘Pollyanna principle’ is derived from the 1913 novel Pollyanna by Eleanor H. Porter. The novel’s protagonist, Pollyanna, is a young girl known for her unwavering optimism and positivity. She is characterised by her unique approach to life, which she calls the “glad game.” In this game, Pollyanna strives to find something to be glad about in every situation, no matter how dire or challenging it may seem. This relentless pursuit of positivity in the face of adversity is the essence of the Pollyanna principle. It encapsulates the human tendency to remember the past as being more positive than it was, viewing life through ‘rose-tinted glasses.’ Over time, our memories may become more positive due to this bias, further enhancing our overall sense of well-being and happiness (Boucher & Osgood, 1969; Matlin & Stang, 1978). This principle underscores the dynamic and subjective nature of memory, highlighting how our recollections are coloured by our emotions. Focusing on brain activity associated with emotional valence effects in memory, Bowen et al. (2018) proposed the NEVER model—an acronym for Negative Emotional Valence Enhances Recapitulation. The model emphasises the role of valence beyond arousal, the importance of encoding–retrieval interactions, and the integration of sensory processes into emotional memory networks. They found that negative valence often leads to enhanced subjective recollection and memory for sensory details, as compared to positive valence. At encoding, negative valence tends to enhance sensory processing more than positive valence. As such, there are greater subsequent memory effects and connectivity between the amygdala and sensory cortices for negative stimuli. At retrieval, negative memories show greater recapitulation of sensory activity compared to positive memories—this valence-based sensory recapitulation is related to recollection success. Taken together, this account helps explain enhanced vividness and recollection for negative memories. Beyond valence effects that are found in young adults, there are also ageby-valence interactions. Despite an overall decline in memory due to aging, older adults tend to have a bias to remembering positive stimuli. This finding has been shown across a variety of experimental procedures (Carstensen & Turk-Charles, 1994; Charles et al., 2003; Comblain et al., 2005; Kensinger, 2008). One account of this is socioemotional selectivity theory (or SST), which suggests that our goals change with age (Carstensen et al., 2003; Mather & Carstensen, 2005; Carstensen, 2006; Barber et al., 2016). As we get older, we tend to focus on our emotion regulation and mental well-being (Ford et al., 2018, 2021; Sun & Sauter, 2021).

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Other age changes in our selves may also help explain these changes in emotional memory—our personality traits also gradually shift (Srivastava et al., 2003; Williams et al., 2006; Carstensen et al., 2011; Harris et al., 2016; Schwaba et al., 2022; Weidmann et al., 2023). With age, people tend to decrease in narcissism and increase in emotional stability—characterised by consistent and balanced emotional responses. These changes are also associated with a more balanced memory of emotional experiences (RuizCaballero & Bermúdez, 1995; Reed & Derryberry, 1995; Lilgendahl et al., 2013; Jensen et al., 2019). As individuals with high emotional stability are less likely to perceive situations as threatening or difficult, this can reduce the memorability of negative experiences. The relationship between age, emotional stability, and memory of emotional experiences provides an alternative account for the well-known age-by-valence interactions. Moreover, these patterns underscore the importance of considering individual differences and developmental changes when studying memory, and it offers valuable insights into how our emotional experiences shape our memories and our lives.

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End of chapter wrap-up Summary The relationship between memory and emotion is complicated. Flashbulb memories illustrate how significant emotional public events can be etched into our minds, such as where we were when we first heard significant news. Studying emotion requires a multifaceted approach, including emotional stimuli, mood induction techniques like music, and examining real-world experiences. The neurobiological connection between emotion and memory is signified by the interactions involving the amygdala and prefrontal cortex. Emotion can even distort our retrospective perception of time, making frightening events seem slowed down. While research predominantly focuses on negative emotions, the impact of positive emotions on memory and attention is profound—this is highlighted by the positivity bias in older adults. Emotion does not enhance all aspects of memory, as recall of contextual details can be impaired. Furthermore, the complexity of selecting emotional stimuli and potential differences in distinctiveness and relatedness add further complexity to this relationship. These nuances underscore the multifaceted nature of the interaction between memory and emotion, and how it defines our understanding of ourselves and the world around us.

Reminder cues

Quick quiz 1. Consider a public event that you remember vividly. Which of the following additional statements would make it LESS LIKELY that your memory of this event is a flashbulb memory? (a) You remember the event in great detail, including where you were and who you were with when you first heard about it. (b) The event had a significant impact on society and was widely covered in the media. (c) The event elicited a strong emotional response from you. (d) The event is often replayed in the media, but it didn’t have a significant personal impact on you.

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2. What is alexithymia? (a) A state of prolonged sadness (b) A trait involving challenges in processing emotions (c) A selective inability to remember emotional experiences (d) A condition causing increased sensitivity to emotions 3. Which of the following is the main reason for emotional and neutral stimuli being matched for primary distinctiveness but still differing in secondary distinctiveness? (a) Emotional experiences are less frequent in everyday life (b) Emotional experiences are more frequent in everyday life (c) Emotional words have higher semantic relatedness (d) Emotional words are inherently more memorable 4. Consider a character in a novel who has just embarked on a long, uneventful journey. According to William James’ principle, how might this character perceive the duration of this journey and why? (a) The journey will seem short while it is happening, but long when looking back because it was uneventful. (b) The journey will seem long while it is happening, but short in retrospect due to a lack of notable experiences. (c) The journey will seem long both during the journey and in retrospect due to the monotony. (d) The journey will seem short both during the journey and in retrospect because it was uneventful. 5. Consider a person with high levels of narcissism in a romantic relationship. If their partner frequently gives both positive and negative feedback, which type of comments is the individual more likely to focus on and remember, based on their narcissistic traits? (a) The positive comments about their appearance and charm. (b) The negative comments about their lack of empathy and consideration. (c) The comments that align with their self-perception, regardless of whether they are positive or negative. (d) The comments that are most repeated, regardless of whether they are positive or negative.

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Thought questions ▶ Emotion can enhance memory, but some argue that these memory effects can be attributed to separable considerations, such as semantic relatedness and attentional biases. Are these attributes inherent to how emotional stimuli are processed, or are these confounds? ▶ Much of the emotional memory literature has focused on negative emotion. Should we continue to focus on negative emotion, or should we move towards a more balanced approach, increasing research in how positive emotion influences memory? ▶ A variety of approaches for inducing emotional states have been used— from music and movie clips to staged performances and parachuting. Choose three approaches discussed in this chapter and discuss some of their relative pros and cons.

Further reading ▶ Bowen, H. J., Kark, S. M., & Kensinger, E. A. (2018). NEVER forget: Negative emotional valence enhances recapitulation. Psychonomic Bulletin & Review, 25(3), 870–891. doi: 10.3758/s13423-017-1313-9 ▶ Colegrove, F. W. (1899). Individual memories. American Journal of Psychology, 10(2), 228-255. doi: 10.2307/1412480 ▶ Talmi, D. (2013). Enhanced emotional memory: Cognitive and neural mechanisms. Current Directions in Psychological Science, 22(6), 430– 436. doi: 10.1177/0963721413498893

Chapter 7 Remembering the wins

If in their course the animal does accidentally work the mechanism (claw the button round, for instance), and thus win freedom and food, the resulting pleasure will stamp in the act and when again put in the box the animal will be likely to do it sooner. This continues; all the squeezings and bitings and clawings which do not hit the vital point of the mechanism, and so do not result in any pleasure, get stamped out, while the particular impulse, which made the successful clawing or biting, gets stamped in, until finally it alone is connected — Edward L. Thorndike (1898a; but further see 1898b)

In the early 20th century, the bustling of Wall Street was quite different than we know it today. The stock exchange operated but was not yet digital and computerised. Traders of this time were reliant on something far more fundamental: their memory (Smitten, 1999; Wigglesworth, 2021). Consider the story of Jesse Livermore, a famed trader of the early 20th century, who began his career in the era of chalkboards and ticker tape. Livermore was known for his remarkable ability to remember and analyse patterns in stock prices. His memory, honed and sharpened by the thrill of a successful trade, was his most precious asset in the fast-paced environment of the stock exchange. Reminiscences of a Stock Operator (Lefèvre, 1923, 2010) is a fictionalised account inspired by Livermore. Lefèvre (1923) wrote: A man can have great mathematical ability and an unusual power of accurate observation and yet fail in speculation unless he also possesses the experience and the memory. And then, like the physician who keeps up with the advances of science, the wise trader never ceases to study general conditions, to keep track of developments everywhere that are likely to affect or influence the course of the various markets. After years at the game it becomes a habit to keep posted. He acts almost automatically. He acquires 199

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Memories that matter the invaluable professional attitude and that enables him to beat the game—at times! This difference between the professional and the amateur or occasional trader cannot be overemphasized. I find, for instance, that memory and mathematics help me very much. Wall Street makes its money on a mathematical basis. I mean, it makes its money by dealing with facts and figures. (pp. 219–220)

This reliance on memory in the early days of Wall Street trading highlights how memory for reward-related outcomes can be much more meaningful than just the stuff of psychology experiments. Even now, memory is relevant to trading from an investor’s memory-based assessments of points of stability (Garzarelli et al., 2014) to recollections of past performance (Walters & Fernbach, 2021; Gödker et al., 2022; also see Huffman et al., 2022).

7.1 Experimental procedures While real-world implications are certainly relevant, the rigour of experimental control and the clarity provided by focused study designs are critical. Laboratory experiments allow us to isolate specific variables and effects, providing a more precise understanding of the underlying mechanisms. Studies of reward effects of memory involve associating reward values with to-be-remembered information. However, two broad approaches are approximately equally represented in the literature. On one hand, rewards can be instructed during encoding, here referred to as ‘value prioritisation’ or ‘value-directed remembering (VDR)’ (Castel et al., 2002; Castel, Farb, & Craik, 2007; Adcock et al., 2006; Gruber & Otten, 2010; Spaniol et al., 2013). Alternatively, rewards can be associated with a response and presented as feedback, related to ‘reward anticipation’ processes (Wittmann et al., 2005; Madan, Fujiwara, et al., 2012; Duncan & Shohamy, 2016). These two procedures are illustrated in Figure 7.1. As these studies are quite different in their procedure, I will discuss these procedures and their related mechanisms and findings in separate sections. For a more thorough review of the literature and how it fits with this categorisation, see Simonsen and Madan (2024).

Value prioritisation Some reward-memory studies have participants associate reward values with items during encoding, with rewards earned during memory retrieval. One of the first studies of this approach was Castel et al. (2002). In their first experiment, participants were presented with lists of 12 words, one-at-a-time, each alongside a unique number between 1 and 12, indicating the word’s reward value. After the 12th word, participants were prompted to verbally recall the words, but had been instructed to prioritise the words with the

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A. Value Directed Remembering Study Phase

Test Phase

$2

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B. Reward Anticipation Study Phase

Test Phase +$

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FIGURE 7.1: Two prominent reward-memory study procedures. (A) Valuedirected remembering, where participants are instructed to the reward value for each item. (B) Reward anticipation, where participants learn reward values through feedback. highest values, such that they would optimise the total score for the words recalled. This procedure was repeated for 48 lists (interleaved with short breaks), in samples of both young adults (mean age of 20 years old) and older adults (mean age of 72 years). As it was expected that older adults would have worse recall than young adults, the researchers instead asked if older adults could selectively recall the highest value words. For instance, if a participant only recalls two words, ideally they would recall the words associated with the 12- and 11-point values, with a total score of 22 points; if four words are recalled, ideally they would be the words associated with the values of 12, 11, 10, and 9 points, resulting in a total score of 42 points. This was calculated as a ‘selectivity index,’ incorporating the total score for the specific words recalled, chance score based on the number of words recalled, and the ideal score. This selectivity index was developed in prior work conducted by Watkins and Bloom (1999) in an unpublished manuscript. Despite the immediate recall, this task was quite difficult. Results indicate that young adults recalled significantly more words, with a mean of 4.8 words (out of 12), while older adults recalled a mean of 3.8 words. However, older adults have a significantly higher selectivity index than younger adults (.72 vs. .58). In a second experiment, the procedure is repeated nearly as-is with the single change of values being presented after the words, removing the possibility that older adults could deliberately pay more attention to the higher value words. This change to presenting values after

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the corresponding word makes the procedure more similar to a directedforgetting procedure, increasing the role of deliberate, strategic memory control. The results replicated, with significantly more recalled words in the young adults, and significantly higher selectivity in the older adults. Two further experiments were conducted with a variety of manipulations and the results were consistent—i.e., better recall selectivity for older adults. However, one condition did lead to a meaningful change in results, the insertion of a oneminute filled delay between study and test. In this condition, the selectivity index was not significantly different between young and older adults. See Castel (2007) for a comprehensive overview of this line of work. Stefanidi et al. (2018) present figures showing value prioritisation effects as orthogonal to serial-position effects. Value prioritisation can also lead to increased false memories when combined with a DRM procedure (Bui et al., 2013). MIN RE

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A second particularly foundational study used a relatively similar procedure, but converged from a distinct literature. Adcock et al. (2006) presented participants with images of scenes, preceded by reward cues of $5 (high value) or 10¢ (low value), indicating the reward amount to be earned for successful recognition. The encoding task consisted of being presented with an intermixed sequence of scenes with 60 of each value. fMRI data was collected during this period and an active baseline condition was also interleaved. Recognition memory was tested 24 hours later with 120 new scenes also presented, with a penalty of $2.55 for each false alarm response to discourage responding “old” for all trials. Memory was tested with a two-step procedure, first indicating “old” or “new,” followed by a confidence judgement of “remember,” “know,” “pretty sure,” and “guess.” Results indicated better recognition memory for high-value scenes (70%) than low-value scenes (60%; 19% false alarms). Recognition for hits could be further subdivided by confidence ratings; responses were aggregated into high confidence (“remember” and “know” responses) and low confidence (“pretty sure” and “guess”). High-value scenes were associated with more high-confidence responses than low-value scenes (45% and 33%, respectively), but did not differ in the proportion of low-confidence responses (25% and 27%, respectively). Reward-related recognition bias could not be assessed with this procedure, as new scenes were not associated with a reward level. fMRI analyses were based on the high-confidence memory responses for the high- and low-value scenes, demonstrating differences in brain activity associated with well-known reward-processing regions such as the ventral

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tegmental area (VTA) and nucleus accumbens. Differences in brain activity were also observed in medial temporal regions including the hippocampus, entorhinal cortex, and parahippocampal cortex. Despite variations in the experimental design such as the number of reward levels and type of memory test, both of these procedures involved providing participants with explicit cues during study that signalled the item values, and rewards were ‘earned’ for successful memory performance. Similar procedures have been used in many other studies of reward effects on memory (Gruber & Otten, 2010; Kuhl et al., 2010; Wolosin et al., 2012; Spaniol et al., 2013; Mason et al., 2017; Elliott et al., 2020). A noteworthy aspect to consider when evaluating recognition performance is the inherent need for all reward levels to share the same set of false alarm responses. This results in certain constraints when trying to estimate response bias for each condition. Furthermore, these constraints are not exclusive to this context but are also present in other experimental designs that depend on experimentally determined categories, such as directed forgetting, repeated presentations, or object-background congruence. However, such limitations do not affect manipulations based on inherent properties of stimuli, such as emotionality and imageability. One critique of studies that use reward cues almost as instructions during study is that the reward-memory effects may be primarily due to preferential attention or rehearsal of the higher-value items. While this may be possible for some studies, reward-cue effects have been demonstrated in studies with blocked presentation (Shigemune et al., 2010), between-group manipulations (Murayama & Kuhbandner, 2011), and even when reward cues are only presented during the recognition test (Shigemune et al., 2017). Despite these findings providing evidence against a superficial approach to memory prioritisation, this procedure can still be thought of as memory control. As such, we would expect it to be reliant on similar mechanisms as are generally ascribed to cognitive control and executive function (Chiew & Braver, 2017; Bajo et al., 2021), and bearing some commonalities to a directed-forgetting paradigm (Bjork & Woodward, 1973). This approach of signaling reward values with visual cues has a much longer history, having been used in several studies in the 1960s through to the 1980s (Weiner & Walker, 1966; Tarpy & Glucksberg, 1966; Loftus & Wickens, 1970; Eysenck & Eysenck, 1982). Unfortunately, the procedures used in these older studies are somewhat difficult to parse and these studies are often not cited, leading to a discontinuity in the literature.

Reward anticipation In contrast to these studies that present reward values as instructional cues, to be earned upon success on the memory test, other studies provide rewards during encoding itself. Here rewards are earned as feedback and associated with the item, bearing more procedural similarities with operant conditioning

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than episodic memory. As an example, Madan, Fujiwara, et al. (2012) tested reward-memory effects using a study with four parts. In the first part, two words were presented, with participants told that each will lead to a reward and their goal is to try and earn as many points as they can. At the end of the experiment, points will be converted to a monetary bonus. Words in this part are each associated with either a 1- or a 10-point reward, and always presented with a word of the other reward value. Using a total of 36 words, 18 for each reward level, there were 18 trials per block. This was repeated for 13 blocks, with words shuffled to be presented alongside a different option each time. As such, over successive presentations, participants learned which words to choose and which to avoid. Initially starting at chance, mean choice accuracy—choosing the 10-point word—increased to 80% by block 5 and then asymptotically increased over the following blocks to end around 90% at block 13. Rewards were only earned in this part. In the second part, participants were presented with a lexical decision task. The words used in this task had previously been associated with the 10-point (high-value) or 1-point (low-value) reward outcome, or were not previously shown in the experiment. The third block was a free recall task—recall all the words you can from the experiment. The fourth and final part asked participants to judge the value for each of the previously rewarded words. At the beginning of the experiment, participants were not provided with any information about the subsequent parts, such that the memory test would be incidental. Participants demonstrated reward-memory effects in both memory tests— faster response times for the high- than low-value words in the lexical decision task, as well as more high- than low-value words recalled in free recall. Other studies have shown better episodic memory associated with choice (Takahashi, 1992; Murty et al., 2015; Coverdale & Nairne, 2019). Interestingly, these two effects were negatively correlated across participants. Even though they both occurred in the full sample, individuals that demonstrated more of the reward bias in lexical decision, had less of the reward bias in free recall, and vice versa. Further analyses quantified the rate that they learned the reward values, based on the first block number that the participant surpassed 80% in the valuelearning task. Here it was found that participants that learned the reward values earlier had more of the reward effect in lexical decision; whereas those who took longer had stronger reward biases in free recall. These results suggest that participants may have been using a mixture of both operant and episodic learning strategies, with each leading to a bias in a different form of memory test. Nonetheless, participants had good conscious access to the reward values, achieving nearly 90% accuracy in the value judgement task. In a second experiment, the same value-learning task was used, followed by a brief distractor, then multiple cycles of list presentation and free recall. In these study–test cycles, each list was comprised of 9 words: 3 previously high-value, 3 previously low-value, and 3 new words. This was repeated for 6 lists, re-presenting all of the words from the value-learning task once. Here,

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free recall performance did not differ across word types. However, two rewardrelated differences in recall did occur: (1) high-value words were output earlier during recall; (2) participants made more intrusions of high-value words—that is, they incorrectly recalled high-value words more often, even though it was not in the just-presented list. This finding was taken as evidence of impaired binding of high-value items to a temporal context. The procedure used by Madan, Fujiwara, et al. (2012) was directly inspired by studies from the 1960s and 1970s, that also used distinct value-learning and memory procedures (Estes, 1966; Humphreys et al., 1968; Medin, 1972). More broadly, other studies have also used rewards as feedback, though sometimes in a manner that was not directly related to the to-beremembered item. Wittmann et al. (2005) presented pictures embedded with a probabilistically rewarded number-judgement task. As such, there was no contingency relating the picture to the feedback, apart from temporal proximity. The intention was to have the picture presentation occur during the reward anticipation, resulting in pictures being indirectly associated with the reward outcome. In intermixed trials there was no reward earned, due to the nature of the probabilistically rewarded task, resulting in two levels of reward values for the pictures. In an immediate memory test, there was no difference between reward levels, potentially due to ceiling effects. However, a second memory test was also administered after a three-week delay. Here there was a significantly higher hit rate for the previously rewarded pictures than those that were not rewarded. Unlike the value prioritisation procedure, these studies involve rewardrelated feedback during the encoding phase. As such, the memory test itself is unrewarded; reward becomes a feature of the stimuli due to the associative learning and reward anticipation experienced when the item was first presented within the experiment. In some ways, this procedure makes reward memory more similar to emotional memory, where the motivational features are more like a ‘part of’ the to-be-remembered information. As with emotion and across a variety of procedures, reward has been demonstrated to capture attentional resources (Raymond & O’Brien, 2009; Anderson & Yantis, 2013; Anderson, 2013; Cheng et al., 2021). Reward anticipation studies blur the lines between episodic memory and associative learning, relying on both memory systems to achieve learning. This type of learning thus bears similarities to the neurobiological mechanisms underlying operant conditioning (Schultz, 1998, 2015, 2016; Shohamy & Adcock, 2010). This principle of associating rewards to each iterative preceding neural and cognitive state, so-called credit assignment, is a key principle of computational models of learning—most notably, reinforcement learning (Sutton, 1988; Watkins & Dayan, 1992; Ludvig et al., 2011; Gershman & Daw, 2017), but also other models such as the “Neural Bucket Brigade” (Schmidhuber, 1989). Reward-prediction error is described in more detail in the neurobiology subsection. Briefly, the Neural Bucket Brigade uses a metaphorical ‘bucket’ of credit, which is passed back from each state

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to its predecessors, akin to a line of firefighters passing buckets of water, thus forming a chain of reward distribution reflecting the role of each preceding state in the learning process. The relatively minor difference between value prioritisation and reward anticipation approaches may also relate to a distinction between strategic and motivation-related influences on memory; a topic yet to be explored in sufficient detail in the reward-memory literature. One limitation of this value-learning procedure used in Madan, Fujiwara, et al. (2012) is that it is not possible to distinguish choice ‘for’ a high-reward word from ‘rejecting’ a low-value word (also see Shafir, 1993; Meloy & Russo, 2004). For instance, maybe a participant remembers the low-value word and knows not to choose it, and therefore chooses whatever the other option is. This is a general limitation of 2-AFC procedures; in an old/new task you might be very sure that one item is ‘new,’ so you choose the opposing stimuli and respond ‘old’ (Rotello & Heit, 1999, 2000)—a sort of push/pull dynamic. This rationale gave rise to a follow-up study with multiple reward levels (Madan & Spetch, 2012), where we did observe better memory for the lowest-value items relative to the intermediate-value items, as well as a modified value-learning task with single items (Chakravarty et al., 2019). Value-learning procedures can also be used to increase false memories when combined with a DRM procedure (Wang, Otgaar, et al., 2023). Murty et al. (2016) similarly looked at the role of episodic memory in decision making. In a series of experiments, participants first received rewards associated with a unique stimulus—either a house, with the cover of a lottery game, or, in a different experiment, a face, with the cover being a dictator game. This was repeated for 60 trials, though only one trial from this task was resolved as a payment to the participant. After a short delay, participants were given a choice test, asking which option (e.g., house picture) they would prefer to interact with again. After this block of choices, participants were tested on their memory, first with old/new recognition, then asked to estimate the reward amount previously associated with the picture. When reward outcomes were remembered, these drove participants’ choice behaviour. When this associated information was forgotten, choices were not affected by their prior rewards. The study using social cues (faces) had a stronger effect than the non-social (house) version, implicating that the social aspect facilitated learning and adaptive choice. Subsequent experiments provided convergent evidence and replicated these main findings. In these studies, we observe the potent influence of reward on the processes of memory encoding and retrieval. Both operant and episodic learning mechanisms emerge as key players, their roles varying across situations. This integration blurs the boundaries between episodic memory and associative learning, invoking principles from reinforcement learning and other computational models. Studies of reward anticipation also provide parallels between reward memory and emotional memory, suggesting that rewards, akin to emotional stimuli, become an integral component of the tobe-remembered information.

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Neurobiology The primary brain regions associated with reward processing are the striatum and ventral tegmental area—often abbreviated as VTA. Studies using both value prioritisation and reward anticipation procedures have shown rewardrelated activation of these regions (Wittmann et al., 2005, 2011; Adcock et al., 2006; Kuhl et al., 2010; Wolosin et al., 2012; Spaniol et al., 2013). Moreover, in all of these studies, there was significantly higher activation in these regions for later-remembered than later-forgotten stimuli, following from a subsequent memory effect analysis. Worth noting as research continues into rewardmemory effects, recent findings suggest that these regions are particularly susceptible to artifacts associated with some advanced fMRI imaging methods (i.e., multiband imaging) (Srirangarajan et al., 2021; Wall, 2023). To localise the brain regions associated with reward processing, some memory studies have also included a reward-processing task. The monetary incentive delay (MID) task is now often used in this way (Knutson et al., 2001; Srirangarajan et al., 2021). Briefly, this task involves showing participants abstract cues (circles, squares, triangles with lines) as instruction cues to signal potential monetary gain, loss, or no outcome for responding quickly to an upcoming target. This is followed by the target—a white square—that appeared after a delay. Participants have to press a button quickly while the target is displayed on the screen. Subsequent feedback then shows whether the participant won/lost money on that trial. By using the reward-related brain regions active in this task as regions of interest, memory studies could then observe reward-memory activations (Adcock et al., 2006; Kuhl et al., 2010; Cohen et al., 2014). A critical neurobiological process involved in reward and memory is reward-prediction error (RPE), a concept from reinforcement learning (Sutton, 1988; Watkins & Dayan, 1992; Ludvig et al., 2011; Gershman & Daw, 2017). Imagine you’re at a new restaurant, trying a dish for the first time. You take a bite, expecting it to be good. But it’s not just good, it’s amazing, far surpassing your expectations. This surprise is a real-world example of a positive RPE. The brain is constantly computing expectations as we go through our daily activities and compares expected and the actual outcomes of our actions. When reality outdoes expectations, like with the unexpectedly delicious dish, we experience a positive RPE. When reality falls short, this is a negative RPE. Neurobiologically, RPE corresponds to the firing rate of dopamine neurons (Schultz, 1998, 2015, 2016). A positive RPE relates to an increased firing rate; a negative RPE with a decreased firing rate. The focus on expectations is key though; now that you know the dish is really good, there will be a positive RPE next time you order it, occurring even before you take the first bite. If it fulfils your new expectations, there will be no prediction error when you actually eat it. In a classic study, Schultz et al. (1997) gave monkeys juice rewards under varying conditions. The dopamine neurons didn’t cheer for the juice itself, but for the surprise element—the

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difference between the expected and actual reward. Experiences that cause a high RPE, like that first bite of the amazing dish, influence decision making by becoming memorable and shape our beliefs (Shohamy & Adcock, 2010). The RPE makes the choice come to mind more readily when it is time to choose what to order, or where to eat next. Pharmacological agents have also been shown to be able to modulate the effects of reward on memory. Levadopa, a dopamine precursor, and other dopamine agonists can enhance memory through reward-related brain networks (Schuck et al., 2002; Knecht et al., 2004; Morcom et al., 2010). In contrast, sulpiride and haloperidol can be used to block dopaminergic receptors and reduce memory (Rammsayer et al., 2000; Frank & O’Reilly, 2006; Mehta et al., 2008; Morcom et al., 2010). Levadopa is used as a treatment for Parkinson’s disease, whereas sulpride is used for schizophrenia.

7.2 Choices and lingering biases The concept of attention in visual selection has traditionally been understood in terms of two primary forces: top-down and bottom-up processes. Top-down attention, as traditionally understood, is a conscious, goaloriented process. It is the observer’s deliberate focus, guided by their intentions and informed by their prior knowledge and expectations. For instance, when reading a book, a reader uses top-down attention to focus on the words and comprehend the story, ignoring other potential distractions in the environment like background noise or movement. On the other hand, bottom-up attention is an automatic, involuntary response to the physical characteristics of stimuli, such as their salience or novelty. It is the environment that captures the observer’s attention, regardless of their goals or intentions. Bottom-up attention is also the one more relevant to motivational factors, such as emotion or reward. For example, if you’re walking in a forest and a snake suddenly slithers across your path, your attention would be immediately drawn to it, regardless of your previous priorities and goals. Recent explorations into the realm of attention have unveiled a third option, one that operates subtly yet significantly in the background: selection history. This concept, first proposed by Awh et al. (2012), and later elaborated by Theeuwes (2018) and Failing and Theeuwes (2018), has added a new dimension to our understanding of attentional selection. Selection history operates differently. It is the ghost of past experiences, the echo of previous rewards and punishments, subtly influencing the observer’s attentional selection. It is neither a conscious decision nor an automatic response to stimuli. Instead, it is a lingering bias, a residue of past interactions that guides attentional selection, often without the observer’s awareness.

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Consider a scenario where a participant is asked to choose between stimuli to earn a reward. This process of value-learning cannot be classified as either top-down or bottom-up attention. An observer who stumbles upon the experiment midway would not attend to the stimuli in the same way as the participant who has been engaged from the beginning. The stimuli lack the bottom-up attentional pull present in most emotional memory studies, and without the top-down instructions, the observer would not know which stimuli to prioritise. The attentional biases at play here are neither top-down nor bottom-up; they are history-based biases. These history-based biases, or selection history effects, are a testament to the influence of past experiences and associations on attentional selection (Doallo et al., 2013; Failing & Theeuwes, 2015; Suárez-Suárez et al., 2019). They are the silent reminders of rewards earned or punishments received, subtly guiding the observer’s attention. While they may operate in the background, their impact on attentional selection is significant. MIN RE

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This understanding is further enriched by theories such as arousal-biased competition theory (Mather & Sutherland, 2011), which posits that arousal increases the competitive advantage of high-priority stimuli over low-priority stimuli. This theory underscores the role of arousal in shaping attentional selection, adding another layer of complexity to the interplay of top-down, bottom-up, and selection history effects. Similarly, Todd and Manaligod’s (2018) priority state space framework provides a comprehensive model of how different factors, including selection history, influence the prioritisation of stimuli. This framework emphasises the dynamic nature of attentional selection, highlighting how the priority of stimuli can change over time based on various factors, including past experiences and associations.

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7.3 Decisions from experience Some reward-memory studies use choice procedures to have participants learn about reward values. These are convergent with procedures used in behavioural economics. Given the choice between (a) 100% chance of winning $20 or (b) 50% chance of winning $40 and a 50% chance of winning nothing, which would you choose? You likely realise that these two options have the same expected value, that is, if repeated indefinitely both options would result in the same average outcome. As both options have the same expected value, there is no definitive correct answer, this choice is a matter of preference. Most people here would choose the ‘safe’ option and take the guaranteed $20. If the same problem was reframed as losses, which would you choose? That is, if you must choose between (a) 100% chance of losing $20 or (b) 50% chance of losing $40 and a 50% chance of losing nothing, which would you choose? If you think about it for a moment, most here choose the ‘risky’ option, with the hope of losing nothing. The risk pattern, more risk seeking for losses than gains, is consistent with the well-established prospect theory (Kahneman & Tversky, 1979). In this example, odds and outcomes were described, with this type of procedure referred to as ‘decisions from description.’ However, what happens if the odds and outcomes are learned from experience, rather than explicitly described?

Description-experience gap If someone is presented with outcomes over successive trials, rather than provided with odds, this is referred to as a decision from experience. Many studies have shown that people make different risky choices when information is acquired through experience (Hertwig et al., 2004; Hertwig & Erev, 2009; Fox & Hadar, 2006; Camilleri & Newell, 2011). Specifically, in decisions from experience, people tend to be more risk seeking for gains than losses (Ludvig et al., 2014a). In some ways this difference can be related to differences in expertise and approach, akin to the difference between a cook and a chef. A cook follows a recipe, carefully following a described protocol. A chef, in contrast, is less closely following precise measurements and may instead use intuition, ‘a pinch of this and a spoonful of that,’ perhaps judging time on a heating element by the colour and consistency, rather than minutes passed. While decisions from description studies generally do not provide trial-wise feedback, some have (Jessup et al., 2008) and this may be more naturalistic. As experience accumulates, the cook may develop into a chef, having more experience of what does and does not work—knowing when to add a bit more salt before calling the dish ‘done.’

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With decisions from description, odds and outcomes are known. In some instances, probabilities are expressed verbally (Beyth-Marom, 1982; Budescu & Wallsten, 1985, 1995; Brun & Teigen, 1988; Juanchich & Sirota, 2013; Vogel et al., 2022). Stewart et al. (2006) comprehensively examined the judged values associated with over 70 different verbal probability phrases with UK participants. Some phrases were at 0%, such as “impossible” and “never,” 50%, such as “even odds” and “‘toss up,” and 100%, such as “always” and “absolute certainty.” Here are a few highlights from these many phrases with the median associated odds in parentheses: highly unlikely (5%), improbable (10%), unlikely (15%), slight chance (15%), rather unlikely (20%), possible (50%), maybe (50%), fair chance (50%), probable (65%), likely (70%), usually (75%), rather likely (75%), very likely (80%), fairly certain (85%), and very certain (90%). Note, however, that cultural differences have also been observed in verbal probability judgements (Doupnik & Richter, 2003, 2004; Brooks, 2015). In experience, it is difficult to estimate probabilities. In one videogame, XCOM 2, actions are presented with their associated probability of success. On the hardest game difficulty, these percentages are accurate; however, on easier modes, probabilities between 50% and 95% are adjusted with a boost of 10–15 percentage points (in the game settings this is referred to as “aim assist”). The developers described including this bias based on psychological principles; they wanted to entertain the players and want to attenuate the emotional distress associated with failed actions (Solomon, 2016). In some cases this difference in experimental procedure is described as ‘information format,’ learning odds and outcomes from experience can introduce some issues that do not apply to description. For instance, in an experience-based procedure, a participant may not choose the risky option enough to obtain a reliable sampling of the odds associated with the outcomes (Fox & Hadar, 2006; Hau et al., 2008; Hadar & Fox, 2009; Barron & Ursino, 2013; Wulff et al., 2018). This is known as the sampling error, and it can significantly skew the participant’s perception of the risk and reward associated with a particular option. Experience-based choices would also involve reward-prediction error, described earlier—a process not relevant to description-based choices. DER CU MIN E RE

Relatedly, if the first outcomes were relatively unfavourable, a participant may subsequently avoid further choices of that option—otherwise known as a hot-stove effect (Denrell & March, 2001). This effect illustrates the tendency to avoid repeating actions that have previously led to negative outcomes, even

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if those outcomes were due to chance and not inherently linked to the action itself; named after a quote from Mark Twain (1897): We should be careful to get out of an experience only the wisdom that is in it and stop there; lest we be like the cat that sits down on a hot stove lid. She will never sit down on a hot stove lid again and that is well; but also she will never sit down on a cold one. (p. 124) To mitigate these issues, experiments can incorporate certain strategies. For instance, allowing participants to sample outcomes without consequential feedback prior to the final decision can help them form a more accurate understanding of the odds. Additionally, requiring participants to intermittently choose each option by occasionally only presenting one option that must be chosen for the experiment to advance can ensure a more balanced sampling of outcomes (Hertwig & Erev, 2009; Camilleri & Newell, 2011; Ludvig et al., 2014a; Madan et al., 2014, 2021). Several theories have been proposed that link memory retrieval to decisionmaking behaviour. In decision by sampling, individuals draw a limited number of samples from a larger set and make decisions based on the evaluation of those samples (Stewart et al., 2006). Here, the samples are drawn from memory, a process susceptible to biases such as recency and distinctiveness. This means that recent or distinctive memories are more likely to be recalled and therefore more likely to influence the decision. Query theory, on the other hand, assumes an underlying query generation and response process, putting a more central emphasis on memory (Johnson et al., 2007). This theory posits that the decision-making process involves generating and answering questions about the options at hand. If some outcomes can more easily come to mind, this would lead to overweighting in decision making. Instance-based learning theory suggests that decision making involves retrieving contextually related instances, which are not necessarily unique episodes (Gonzalez & Dutt, 2011). This means that decisions are influenced not just by specific memories of past outcomes, but also by the broader context in which those outcomes occurred. All three theories provide related, yet distinct, accounts of how memory can serve as a cognitive mechanism to support decision making. A number of other theories also propose mechanisms where memory is used to support decision making, especially where accumulating experience leads to the development of choice heuristics (Nosofsky, 1986; Klein, 1993; Aamodt & Plaza, 1994; Reyna & Brainerd, 1995; Giguère & Love, 2013). Decisions from experience are inherently dependent on memory, but as we have discussed throughout this book, memory is not veridical. As such, biases in memory availability can become biases in decision making.

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Memory biases A series of studies has shown that people tend to be more risk seeking for gains than losses in decisions from experience—illustrated in Figure 7.2 (Ludvig & Spetch, 2011; Ludvig et al., 2014a). Initially this was explained as subjective overweighting of the most extreme outcomes—both the best and worst outcomes experienced within the experiment. These studies were initially inspired by the foundational work of Kahneman and Tversky (1979), with the goal of adapting them for cross-species comparisons (Ludvig et al., 2014b; Pisklak et al., 2019; Madan, Ludvig, & Spetch, 2019). Of course, odds and outcomes cannot be readily expressed to non-human animals. As such, this involved adapting the procedure to rely on experienced odds and outcomes over blocks of trials, resulting in an operant-like procedure and converging on prior work studying the description-experience gap (Hertwig & Erev, 2009; Garcia et al., 2021). Note, there can be some exceptions to this, such as training non-human primates to understand described odds, such as in the work of Heilbronner and Hayden (2015).

FIGURE 7.2: Overview of decision-from-experience study. (A) Illustration of outcomes associated with each option. (B) Mean risk preferences. In the next experiments, a set of memory tests was added. After the choice trials, participants were asked to report the first outcome that came to mind for each option. For the risky options there were two valid responses, however, more participants did report the extreme outcomes from the experiment than the equally occurring non-extreme outcomes (Madan et al., 2014). Participants were also asked to estimate the percentage associated with each of the options and possible outcomes. Here a subjective overweighting was observed in how often participants thought the risky option occurred, correlating with biases in risky choice. As such, it appears that extreme outcomes are more memorable, referred to as the extreme-outcome rule. Based on these findings, the extremeoutcome rule could be considered a more specific version of the availability bias (Madan, Ludvig, & Spetch, 2019).

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Salience

While some experiments involved gains and losses, others involved only gains or only losses, using high- and low-value decision sets (Ludvig et al., 2014a; Madan et al., 2014). Risky choices appeared similar, such that participants made choices based on the range of values experienced. The consistent interpretation appears to be that participants are more risk seeking for relative gains than losses—as illustrated in Figure 7.3.

Valence or Value FIGURE 7.3: Reward salience relationship relative to the range of values experienced. The solid line denotes that reward salience has a U-shaped relationship relative to reward valence. Findings suggest that this can be observed even when the range of values experienced is constrained to either the gain or loss domain, as in the dashed line. Adapted from Madan (2013). As people make different relative risk preferences when making decisions based on described odds or learned experiences, a few studies have examined both within the same participants (Camilleri & Newell, 2009; Ludvig & Spetch, 2011). Madan, Ludvig, and Spetch (2017) found both classic effects— more risk seeking for gains than losses in decisions from experience, but more risk seeking for losses than gains in decisions from description. Overall risk seeking correlated across decision formats—i.e., those who are more risk seeking in one format are also more risk seeking in the other. Despite the same numerical values being used, participants exhibited different risk preferences, in accordance with the description-experience gap. A later study used a similar approach, but instead used two separate sets of decisions from experience (Madan et al., 2021), i.e., one set with gains and losses, another set with high- and low-value gains. Some prior studies had used intermixed gains and loss trials, finding more risk seeking for gains

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than losses (Ludvig et al., 2014a; Madan et al., 2014). Other studies had used all-gain trials with high- and low-value decisions, observing more risk seeking for high- than low-value decisions. Though these had been conducted between different experiments, they had been conducted multiple times and the overall range of values used was the same—just shifted upward for the all-gain studies. Additionally, the specific values used for the gains and low-value decisions were the same. As such, it could be described as a target risky decision being presented within the same context as a relatively higher-value decision set (i.e., high-value) or a relatively lower-value decision set (i.e., losses). In this new study then, we used contextual cues to examine different decision contexts within the same study, rather than between-experiment. For each context, a distinct background and set of option and feedback cues was used, borrowing from methods used in studies of context in the memory literature (Anderson & Bower, 1974; Davies & Milne, 1982; Reder et al., 2013; Ezzyat & Davachi, 2014). We were successful in observing both more risk seeking for gains than losses and high- than low-value decisions, as well as the previously discussed biases in memory measures (Madan et al., 2014). An additional set of decision trials was included where the ‘target’ risky choice was made on the same background context as previously experienced or with a conflicting background context. Here results indicated that participants relied more on the contextual cues when outcomes were first learned, suggesting that bias occurred primarily during encoding, rather than retrieval. For instance, it could be that participants learned a heuristic to ‘choose the red door,’ rather than actively sampling outcomes from memory for each choice. A limitation of the studies discussed thus far is that the relationship between memory and decision making is purely correlational. There is some measure of memory bias and it seems to correlate with choice biases, but there is not experimental control of the effect. Another similarly structured study of door stimuli and reward outcomes attempted to address this by including ‘reminder cues’ before some decisions, only in the last block of trials (Ludvig et al., 2015). Rather than showing the same outcome picture with each reward feedback, an outcome unique picture was shown of a cartoon-fruit picture (e.g., bananas, grapes). The goal was to use casino-like imagery that can then be shown separate of the reward values, to cue memories of the rewarding experiences. Here it was shown that these reminder cues could prime memories of past wins and experimentally cause people to be more risk seeking on the trials where they were presented, as opposed to no prime or primes associated with relatively worse outcomes (also see Gibson & Zielaskowski, 2013). Extreme outcomes are memorable. While I have now been studying this phenomenon for a decade (Madan & Spetch, 2012; Madan et al., 2014, 2021), it is also supported by a convergent line of experiences. As I discussed parallels between emotion time dilation effects and Dungeons & Dragons (Wizards of the Coast, 2018) in the last chapter, it is even more true here. When extreme outcomes occur—both critical successes and critical failures—those are the memorable events, when something goes particularly well or poorly. At its

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heart, Dungeons & Dragons and games like it serve as a form of collaborative procedural storytelling (Howard, 2008; Lumpkin, 2019). These are determined by a roll of a 20-sided die, commonly referred to as a d20 (Wizards of the Coast, 2018; Madan, 2016b). A roll of 20 signifies a critical success, a moment of extraordinary achievement, while a roll of 1 represents a critical failure, a moment of spectacular mishap. When these extreme outcomes occur—the exhilarating highs of critical successes and the crushing lows of critical failures—those are the memorable events. They are the instances when something goes particularly well or disastrously wrong. These moments serve as pivotal points in the narrative, shaping the course of the story and defining the characters’ arcs. They are memorable not just for their extremity, but also for their narrative significance. Moreover, these extreme outcomes create shared experiences that players can bond over, strengthening their social connections. The shared joy of a critical success or the collective disappointment of a critical failure can bring players closer together, creating a sense of camaraderie and shared identity. These social bonds, in turn, can make the memories of these extreme outcomes even more salient. In another line of convergence, a key measure of computer performance when playing videogames is the rate the screen is updating—frames per second (FPS). While average FPS is a common measure, a more recent development is the use of 1% FPS as well, corresponding to the slowest frame rates experienced (i.e., the 99th percentile) (Wasson, 2011; Burke, 2016). Higher frame rates are preferable, but pronounced drops in frame rate are noticeable and are judged to be worse performance—even if the average frame rate is higher. This 99th percentile, and 99.9th (0.1% lows), stand out in experience, and memory.

Two systems The dual-system theory, popularised by Kahneman’s Thinking, Fast and Slow (2011), distinguishes between two modes of thought: System 1—the automatic, quick, and often subconscious mode—and System 2—the slower, deliberative, and more logical mode (also see Sloman, 1996; Evans, 2008; Evans & Stanovich, 2013; Croskerry, 2009a, 2009b; Djulbegovic et al., 2012). While this approach has provided valuable insights into decision making and cognitive biases, it is quite simplistic. Our cognitive architecture is not limited to two gears for intuition and deliberate reasoning (Glöckner & Witteman, 2010; De Houwer, 2019; Rencic et al., 2020); it encompasses a myriad of intertwined processes, including memory availability and emotional states. When faced with a risky decision—such as whether to pursue a new, uncertain business venture—an entrepreneur does not just rely on gut feeling or calculated logic. They may recall past ventures, assess potential emotional outcomes like excitement or fear, and weigh the risks associated with success. Cognitive processes that underlie an overarching

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decision result in a dynamic interaction of problem solving, memory, and more. For instance, a person’s hesitation to invest in a venture that resembles a past failed business might not solely be a product of analytical caution. The memory of the past failure and the associated emotions can influence their present decision, blurring the lines between intuitive and deliberate reasoning. Such interactions suggest that decision making is more fluid than the strict boundaries proposed by the dual-system view. In another instance, consider a physician deciding on a high-risk surgical procedure. Past experiences— successes and complications—might influence the decision. Concurrently, they would weigh the current patient’s unique circumstances—a situated model of multidimensional contexts (Tversky & Simonson, 1993; Higgs & Jones, 2008; Rencic et al., 2020). Decision making is flexible and context-dependent, moulded by our experiences and the demands of our environment (Huber et al., 1982; Payne et al., 1988; North et al., 1997, 1999; Berger et al., 2008; Madan et al., 2021).

7.4 Variations in procedures Effects of value or salience In the studies of value prioritisation, rewards are earned for the successful recall or recognition of the item. As such, participants should exert strategic control of their attention and encoding resources to earn the highest reward they can. However, in the reward anticipation procedure, rewards are earned during encoding itself and the memory test is unrewarded. This allows us at least several possible outcomes—people may remember information in an increasing relationship with reward value. This could be linearly or more steeply, e.g., exponentially. Alternatively, there may be a bias where both the highest- and lowest-value items are more memorable, with intermediatevalued items being the least memorable. This would most simply be reflected by a quadratic or U-shaped relationship. This does not necessarily need to be symmetric in memory for the highest and lowest, but rather simply that there is some memory benefit for the least-valued items. In the broader literature, we know that both positively and negatively valenced emotional events are remembered better than neutral events. Here the procedure from Madan, Fujiwara, et al. (2012) was modified to have multiple reward levels, rather than just two. Specifically, three or six reward levels were used, each in its own experiment (Madan & Spetch, 2012). As described earlier, the rationale was that people would remember the lowestvalue items, but also remember not to choose it and instead choose the other option (also see Shafir, 1993; Rotello & Heit, 1999; Meloy & Russo, 2004). This result did bear out, resulting in a U-shaped or salience-based recall finding. Later studies have extended this finding, observing U-shaped reward salience effects in other procedures (Castel et al., 2016; Halamish, 2018; Yankouskaya

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et al., 2020). Moreover, these salience results of Madan and Spetch (2012) were a key finding for motivating the investigation of memory as a basis for the extreme-outcome rule (Madan et al., 2014; Madan, Ludvig, & Spetch, 2019). The results of several fMRI studies have indicated relative value or salience activation functions in reward-related brain regions (Zink et al., 2004; Jensen et al., 2007; Cooper & Knutson, 2008; Litt et al., 2011). Taken together, it appears that regions of the insula and fusiform gyrus are activated in relation to reward salience. Posterior cingulate cortex was activated in relation to reward value. Demonstrating more within-region heterogeneity, regions of the striatum, orbitofrontal cortex, and anterior cingulate cortex can be responsive based on either value or salience. Though these results support salience effects influencing memory behaviour and regional brain activity, a further demonstration of the relevance of this is how learned reward values influence decision-making behaviour.

Types of rewards Many types of stimuli can be used as reward-related outcomes (see Figure 7.4). The most common rewards are money or hypothetical ‘points.’ Some studies have used other forms of rewards, such as foods (Hare et al., 2011; Lim et al., 2011; Polanía et al., 2015; de Water et al., 2017; Duif et al., 2020; Watson et al., 2021), erotic images (Sescousse et al., 2010; Sescousse, Barbalat, et al., 2013; Ferrey et al., 2012; Gola et al., 2016; Attard-Johnson & Bindemann, 2017; Knauth et al., 2023), or verbal praise (“Great job, that’s one of the highest scores we’ve seen!”) (Deci, 1971, 1972; Williams & DeSteno, 2008; Albrecht et al., 2014). Reward-related outcomes can also be negative, i.e., punishment, often through the use electric shocks (Weiner & Walker, 1966; Mery & Kawecki, 2005; Jensen et al., 2007; Bauch et al., 2014). Other studies have instead varied the amount of effort a participant needs to exert to earn a reward (Nagengast et al., 2011; Apps et al., 2015; Finn, 2010; Chong et al., 2018; Mason, Madan, et al., 2023; Mason, Sun, et al., 2023). Some stimuli can be varied to be either rewards or punishers, such as juice, either sweet or saltwater (Krug & Braver, 2014; Yee et al., 2016, 2021). More generally, some outcomes may be more individualised in their preference—meat to someone that is vegetarian, chocolate to a diabetic, or a cigarette to a non-smoker. It is worth noting that many of these have previously also been used as means to make otherwise neutral stimuli have emotional properties or as part of a mood-induction task. For instance, gifting candy has been used as a positive mood-induction procedure (Isen & Levin, 1972). Many emotional studies have used shocks or aversive sounds, within the guise of studying fear conditioning (Bisby & Burgess, 2014; Dunsmoor et al., 2015). Procedurally, some of these studies may have been identical to what could have been presented as a reward-memory study—providing evidence suggesting there is some overlap in these two literatures (Madan, 2013, 2017b).

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Valence FIGURE 7.4: Approach-avoidance motivation tendencies for different stimuli. Tendencies can be context-dependant, based on not only the stimulus itself, but also the current state of the individual (e.g., thirst, hunger) and interindividual differences (e.g., socioeconomic status, smoker, dieter, vegetarian). Individual preferences within a given context are denoted by the black dots, and range from approach (dot closer to the stimulus) to avoid (dot closer to the empty box). The grey dotted line denotes the point of indifference. Adapted from Madan (2013). While these are clearly an array of different stimuli, some work has been done to examine brain activity in relation to them, with some regions active across different reward stimuli. These results have been used to suggest that there is a ‘common currency’ of value that generalises across stimuli (Montague & Berns, 2002; Chib et al., 2009; Vlaev et al., 2011; Sescousse, Caldú, et al., 2013). DER CU MIN E RE

Conditioning aversive responses can be more subtle yet effective than many of us realise. A number of consumer products include light coating of the chemical compound denatonium benzoate—more commonly known as Bitrex. This chemical holds the title of the world’s most bitter substance and is detectable at a few parts per million, with no known long-term side

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effects. As such, it is used widely as a deterrent, added to potentially harmful substances to discourage accidental ingestion. Small objects that might end up in the mouth of a child, such as batteries and videogame cartridges, are now typically coated with Bitrex as a safety measure. It can also be bought separately. Imagine, for instance, a child who has a habit of biting their nails. By applying a Bitrex solution to the child’s nails, the unpleasant taste serves as a deterrent, discouraging the child from continuing the behaviour. The child will associate nail-biting with the unpleasant taste, leading to a reduction or cessation of the habit. This is a classic example of aversive conditioning at work. Moreover, when we taste Bitrex, the experience is often so potent that it creates a vivid episodic memory. We remember not just the taste, but the context in which we encountered it. Some non-human animal studies are also relevant here. In demonstrating the episodic memory properties of scrub jays, Clayton and Dickinson (1998) had the birds cache different types of foods—peanuts and fresh worm larvae. While the fresh worms are preferred, over time they decay and are also more likely to be taken by another animal. In contrast, the peanuts are less preferred as a food source, but keep longer. In this study, the jays were only able to return to the caches after a 4-hour delay and after a 124-hour delay. The birds were not only able to keep track of which food caches they had visited previously and are now depleted, but also prioritise returning to the caches with the worms at the 4-hour test and then prioritised the peanut caches at the 124-hour test. Thus, the birds demonstrated memory of the locations (‘where’), the food type (‘what’), and at least some information about the delay (‘when’). Several later studies have replicated and extended this work (Clayton et al., 2001, 2003; Dally et al., 2006).

Curiosity Studies investigating curiosity, or more precisely, information that individuals are intrinsically more interested in, has emerged as a fascinating way to study motivated memory. When participants are asked how curious they are about something, for instance a trivia question, these judgements of curiosity correlate with later recall (Gruber et al., 2014; McGillivray et al., 2015). Moreover, if unrelated information is presented in the interval between the trivia question and answer, participants are also more likely to remember this unrelated information if they are more curious (Gruber et al., 2014; Stare et al., 2018; Swirsky et al., 2021). To allow you to assess your general knowledge and curiosity, I selected the top 15 trivia questions rated for post-answer interest from a large-scale study (Fastrich et al., 2018: 244 questions, N = 1, 498), listed in Table 7.1. While pre- and post-answer interest were generally quite correlated, r = .53, I view post-answer interest as more indicative of how satisfying the answer was perceived. I included the percentage of respondents that already knew the correct answer in parentheses. Answers are at the end of this chapter.

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While trivia questions can be interesting, what does it have to do with reward? Critically, several research groups have suggested that curiosity may have shared cognitive processes with reward anticipation (Kidd & Hayden, 2015; Marvin & Shohamy, 2016; Gruber & Ranganath, 2019; Murayama et al., 2019; FitzGibbon et al., 2020). As such, these studies with interleaved unrelated information presented between the trivia question and answer bears some direct commonalities with procedures used for reward anticipation (Wittmann et al., 2005, 2011; Murty et al., 2016; Braun et al., 2018; Swirsky et al., 2020) and may be able to be used as a strategy for remembering the embedded, less-interesting, information. In the study by Swirsky et al. (2020), reward anticipation selectively enhanced memory for gist characteristics, but not details. This may indicate some limitations to the richness of encoding available for the unrelated stimuli. TABLE 7.1: Top 15 most interesting trivia questions, with percentage of people that knew the correct answer in parentheses, from Fastrich et al. (2018). 1. The liquid found in what fruit can be used as a substitute for blood plasma in emergencies? (17%) 2. What is the only food that never spoils? (27%) 3. What water-dwelling creature can make a sound loud enough to break glass? (2%) 4. What American State has the highest percentage of people who walk to work? (1%) 5. What is the name of the largest desert on earth? (4%) 6. What color are Amazon river dolphins? (15%) 7. Which animal’s milk is used to make authentic Italian mozzarella cheese? (8%) 8. What is the only living part of the human body that has no blood supply? (1%) 9. Which company is the largest manufacturer of tires? (1%) 10. What wild animal in Africa has killed the most people? (30%) 11. What animal can eat only when its head is upside down? (4%) 12. What spice is extremely poisonous if injected intravenously? (12%) 13. Which island’s wildlife is 90% unique? (18%) 14. What type of bean must be cooked thoroughly for all the cyanide to be extracted? (13%) 15. Which product, after oil, is the most frequently traded product around the world? (6%)

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Episodic memory induction Being explicitly directed to think about future episodic events can influence decision-making behaviour. Two approaches to do this are episodic future thinking and episodic specificity induction. Episodic future thinking is a cognitive strategy that involves envisioning future events or scenarios (Atance & O’Neill, 2001) (also revisit Section 1.5, p. 19). This strategy has been shown to influence delay discounting, a cognitive process that measures how the perceived value of future rewards decreases as the delay to receiving them increases. The procedures discussed thus far have primarily focused on experienced outcomes and risk probabilities. These involved reward outcomes or anticipation biasing memory, and potentially also subsequent choice behaviour. A much larger literature exists around another reward-based choice procedure: delay discounting. Of particular interest, however, is the influence of memory on delay-discounting behaviour. As an example of delay discounting, consider which you would prefer, $20 now or $22 in a week? In this choice, nearly everyone would rather receive the $20 now (i.e., ‘smaller sooner’). However, if the delayed option was increased to $40 (in a week), most would choose this ‘larger later’ option. Apart from varying the amount, the delay can also be adjusted. In a choice between receiving $20 now or $40 in a year, preferences will be more variable. Delay discounting involves modelling this decrease in value in relation to increased delay across a variety of amounts and delays (Kirby & Maraković, 1996; Kaplan et al., 2016). These originally were developed with set values that have since been used in many studies, referred to as the monetary choice questionnaire. Delay discounting is typically measured by the rate at which an individual’s willingness to wait for a larger reward decreases as the delay to that reward increases. The hyperbolic discount function is often used to model delay discounting, and the parameter k in this function represents the steepness of the discounting curve. Higher values of k indicate steeper discounting, meaning that individuals are more likely to choose the smaller, sooner rewards. In other words, later rewards are ‘discounted’ and are subjectively not worth as much because of the delay. Several factors relate to choice preferences, including sequences in the question order and individual differences (such as smoking status and age), further discussed in the next section. Peters and Büchel (2010) investigated how episodic future thinking affects delay discounting. Participants made choices between smaller sooner rewards and larger later rewards. However, in half the trials, episodic tags referring to specific future events were shown alongside the later reward. The episodic tags were participant-specific cues of specific future events that were collected from a task from the previous day, e.g., “vacation paris” and “birthday john.” Episodic tags reduced impulsive choice and lowered discount rates compared to the control condition without tags. The degree of discount rate reduction

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correlated with ratings of how vividly the tags evoked mental imagery. fMRI results showed that the episodic tags activated brain regions involved in episodic future thinking like the posterior cingulate cortex. Anterior cingulate cortex (ACC) valuation signals and functional connectivity between ACC and hippocampus and amygdala tracked individual differences in discount rate changes. The study suggests episodic future thinking affects intertemporal choice by modulating valuation processes in medial prefrontal and medial temporal regions. Episodic predictions from the hippocampus may influence subjective valuations to enable more future-oriented choices. Bulley et al. (2019) similarly assessed episodic future thinking on delay discounting, but additionally examined the emotional valence of the future events. Between groups, future events were cued to be either positive, negative, or neutral. Cuing both positive and negative episodic future events led to reduced delay discounting (increased patience for larger later rewards) compared to the neutral condition. This effect was around a 7—10% increase in preference for later rewards. Participants also completed a risk-taking task, the balloon analogue risk task, though there was no effect of the manipulation on behaviour here. Episodic future thinking selectively reduced impulsive decision making in the intertemporal choice—but not on behavioural risk taking that lacks an explicit temporal component. The delay discounting results have since been replicated and extended in a later study with 600 participants (Ballance et al., 2022). Episodic specificity induction, on the other hand, is a technique that involves the detailed recall of past events. This technique has been shown to enhance the specificity of episodic memories and can also influence decisionmaking behaviour (Madore et al., 2014, 2016; Madore & Schacter, 2016). St-Amand et al. (2018) used this procedure in a decisions-from-experience study. One group of participants was trained to recall specific episodic details, another group was trained to recall general impressions; in a second experiment, a baseline group with no induction procedure was also included. Participants then completed a risky decision-making task where they choose between a risky option with a 50% chance of a higher reward or no reward, and a safe option with a small guaranteed reward. This procedure is similar to the decisions-from-experience studies described earlier (Ludvig et al., 2014a; Madan et al., 2014), but with only one set of decisions (i.e., gains, but no losses). Risk taking was lower in the general impressions group compared to the episodic specificity group. The baseline group with no induction showed similar risk taking as the episodic group. The general impressions group showed decreasing risk taking over time compared to stable risk preference in the episodic and baseline groups. In a following memory test, the episodic group was more likely to first recall the better risky outcome when queried, indicating a memory bias. Reinforcement-learning modelling showed that the general impressions group weighed negative prediction errors more than positive ones, indicative of a negativity bias; the episodic and baseline groups weighed positive and negative prediction errors equally.

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Simulations showed that the negativity bias produced lower risk taking over time, matching the general impressions group behaviour. Overall, the results suggest that engaging episodic memory leads to higher risk taking. The general impressions induction reduced access to episodic memory, decreasing risk taking. Individuals may naturally use episodic memory during experiencebased decisions, so modulating memory emphasis altered choice behaviour.

Preferences Given the myriad of types of rewards and individual variations in how people value them, how can we study choices between options that are not simply options along a continuous scale? A choice between $20 now or $22 now is obvious, but what about a choice between $20 now or a pizza? Preferences. Weber and Johnson (2013) proposed the preferences-as-memory framework, suggesting that preferences are not static but are dynamically constructed based on the memories that are most accessible at the time of decision making. This view is grounded in the reconstructive nature of memory, with the availability of past experiences and knowledge mediated by contextual factors such as mood and recency. As such, the memories we retrieve when making a decision can vary widely, leading to different preferences and in different contexts. Consider, for example, choosing a restaurant for dinner. If you recently had a fantastic meal at a particular restaurant, that memory is likely to be highly accessible and may sway your preference towards choosing that restaurant again. However, if you had a negative experience at that restaurant a long time ago, that memory may be less accessible and less likely to influence your decision. Critically, this framework suggests that decisions are influenced by memories, not just stimuli properties. The preferences-as-memory framework also emphasises the role of emotion in influencing memory accessibility. This work further converges with more recent discussions of memory forming the basis of our beliefs (KunstWilson & Zajonc, 1980; Morewedge et al., 2005; Sloman, 2022; Madan, 2024), but also that memories are based on our beliefs (Rozeboom, 1965). Our memories—comprising past experiences, learned information, and observed events—naturally serve as a foundation for our beliefs.

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7.5 Individual differences in reward sensitivity As with emotion, there are trait-level differences that can relate to how strongly someone’s behaviour is influenced by rewards. One of the most well-known individual differences measures of reward processing is delay discounting. Many studies have used variations to the procedure where trial order is randomised, instructions are manipulated, or even the values themselves—as described in the previous section. However, it was first developed as a pencil-and-paper task with a fixed item order and set values (Kirby & Maraković, 1996; Kaplan et al., 2016). To briefly re-cap, an example of delay discounting would be to consider if you would prefer $20 now or $22 in a week. Many individual differences relate to delay discounting, including smoking (Stillwell & Tunney, 2012), obesity (Amlung et al., 2016), and substance use disorders (MacKillop et al., 2011). Delay discounting has been a sensitive neurobiological marker of impulsivity and decision-making deficits (Bickel et al., 2012; Levin et al., 2018). In a large sample of young adults, robust relationships between delay discounting and brain structure have also been observed (Owens et al., 2017; McIntyre-Wood et al., 2022). Reward sensitivity is another trait associated with reward processing. In a study of reward learning in Parkinson’s patients and healthy controls, Housden et al. (2010) found greater reward sensitivity in the patients. Moreover, some of the Parkinson’s disease (PD) patients also had impulsive— compulsive spectrum behaviour (ICB), determined based on an interview with a neurologist. Reward sensitivity and salience to irrelevant stimuli were graded effects across controls, PD-ICB, and PD+ICB. These results were found across the reward-learning task, delay discounting (k), and questionnaire measures. More generally, Parkinson’s disease is associated with a diversity of non-motor symptoms; I recommend Poewe et al. (2017) for a comprehensive primer. The BIS/BAS scales (Carver & White, 1994) are also related, measuring two motivational systems: the Behavioral Inhibition System (BIS) and the Behavioral Activation System (BAS) (Gray, 1982). The BIS is concerned with the sensitivity to punishment, negative outcomes, or the avoidance of novel or challenging situations. It represents a tendency to move away from or avoid negative or threatening stimuli. Individuals with a high BIS score may be more prone to feelings of anxiety, fear, or frustration. The BAS, on the other hand, is related to sensitivity to rewards, positive outcomes, or the pursuit of goals. It represents a tendency to approach or move towards positive or rewarding stimuli. Individuals with a high BAS score may be more driven, optimistic, or eager to engage in new opportunities. While BIS is a single scale, BAS has three subscales: reward responsiveness, drive, and fun seeking. The BIS/BAS scales consist of 24 statements, rated for level of agreement. The questionnaire is intended as a tool for understanding individual differences in approach and avoidance motivation. By assessing the sensitivity to punishment and reward, these scales offer insights into a person’s behavioural tendencies, emotional responses, and overall motivational orientation.

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Studies have looked at self-reported estimates of gambling wins and losses and found that people tend to have a favourable bias, where they overestimate their winnings and underestimate their losses (Gilovich & Douglas, 1986; Braverman et al., 2014; Auer & Griffiths, 2017). Greater discrepancies between estimates and actual outcomes were also associated with problem gambling behaviour (also see similar behaviour in investors and workplace managers Walters & Fernbach, 2021; Gödker et al., 2022; Huffman et al., 2022). In a more extreme situation, treatment with a dopamine agonist in Parkinson’s disease and restless leg syndrome patients has resulted in problem gambling (Dodd et al., 2005; Rigoli et al., 2016; Heiden et al., 2017). This has been associated with dopamine dysregulation and anhedonia. MIN RE

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Other traits associated with impaired reward processing include anhedonia—characterised by a reduced ability to experience pleasure from activities that are normally enjoyable, and apathy—which involves a lack of interest or motivation to engage in activities (regardless of their potential for pleasure). These are discussed further in Section 10.2 (p. 301). Aging also brings changes in how individuals process rewards. There is some evidence that older adults learn more slowly in decisions from experience compared to younger individuals (Mata et al., 2011). Additionally, accumulated life experiences may result in better calibration of emotional responses (Carstensen & Turk-Charles, 1994; Labouvie-Vief, 2003; Peters et al., 2007; Scheibe & Carstensen, 2010). Neurobiologically, aging is accompanied by changes in brain regions pivotal for reward processing, such as the striatum and the prefrontal cortex. The decline in the functionality of the dopamine system can particularly influence reward-based learning and decision making in the elderly (Mohr et al., 2010; Samanez-Larkin et al., 2011; Samanez-Larkin & Knutson, 2015; Seaman et al., 2019). Another relevant bias is the age-related positivity effect, as described in Section 6.5 (p. 191). Older adults focus more and have better memory for positive information relative to negative, compared to their younger counterparts. This shift can influence their evaluation of rewards and losses (Carstensen et al., 2003; Mather & Carstensen, 2005). The answers for the trivia questions included earlier in the chapter are: 1. Coconut; 2. Honey; 3. Pistol Shrimp; 4. Alaska; 5. Antarctica; 6. Pink; 7. Water Buffalo; 8. Cornea; 9. Lego; 10. Hippo; 11. Flamingo; 12. Nutmeg; 13. Madagascar; 14. Lima bean; 15. Coffee.

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End of chapter wrap-up Summary Memory and reward are closely connected, underpinning a wealth of human behaviour. Procedures that study these reward effects employ methods such as value prioritisation—using instructed values and reward anticipation— facilitated through learning from feedback. These procedures bear parallels to directed forgetting and reinforcement learning, respectively. Rewards can come in many forms—from financial incentives to primary reinforces, such as food, electric shocks, and erotic pictures. Extreme outcomes, in particular, are most memorable, thus influencing decisions from experience. These reward-memory interactions are further exemplified by phenomena like the hot-stove effect—an interplay between memory availability and choice. The preferences-as-memory framework posits that our accessible memories construct our preferences, reinforcing the importance of memory availability in shaping decision-making processes. Traits and physiological components also correlate with tendencies in reward processing. Interestingly, even impatience in intertemporal choice can be altered by manipulating episodic memory. Rewards are fundamental to behavioural change—but this is only true because memory persists to ensure learning.

Reminder cues

Quick quiz 1. What is one critique specific to studies that use reward cues as instructions during the study phase in the value prioritisation procedure? (a) The procedure is unable to differentiate between the effects of reward value and item difficulty. (b) Reward-memory effects may be primarily due to preferential attention or rehearsal of higher-value items. (c) The procedure is insensitive to individual differences in motivation or value representation. (d) The procedure does not account for the influence of inherent stimulus properties, such as emotionality and imageability.

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2. Consider a scenario where you repeatedly fail a particular level in a videogame because a specific enemy always manages to surprise you. Eventually, you begin to anticipate the enemy’s appearance and can counteract it effectively. Which attention process does this scenario best illustrate and why? (a) This scenario illustrates top-down attention because you consciously focus on anticipating the enemy’s appearance. (b) This scenario illustrates bottom-up attention because the surprise appearance of the enemy is a salient event that captures your attention. (c) This scenario illustrates selection history because your repeated experiences with the enemy subtly guide your attention to anticipate its appearance. (d) This scenario illustrates arousal-biased competition because your arousal from failing the level increases the priority of the enemy. 3. What is the main driving force behind the hot-stove effect? (a) Selectivity during encoding (b) Reinforcement learning (c) Sensitivity to early outcomes (d) Attentional biases 4. What is a ‘common currency’ of value in the context of reward-related outcomes? (a) A brain region that responds to all types of rewards. (b) A standard monetary value assigned to all reward outcomes. (c) The subjective value of a reward based on individual preferences. (d) A neural mechanism that generalises value across different stimuli. 5. Tom, a Parkinson’s patient, started medication involving dopamine agonists. His family has noticed that he’s developed a tendency to gamble, which he never did before. What might this new behaviour suggest? (a) Tom’s gambling behaviour is likely unrelated to his Parkinson’s treatment. (b) The dopamine agonist treatment might have led to problem gambling behaviour. (c) Tom’s Parkinson’s disease has caused high delay discounting leading to gambling. (d) Tom’s gambling is a symptom of schizotypy induced by Parkinson’s disease.

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Thought questions ▶ Discuss similarities and differences between procedures for (a) value prioritisation, i.e., monetary rewards earned for successful recall or recognition, and (b) directed forgetting. ▶ Does it matter if a study of reward effects on memory uses monetary rewards or only provides ‘points’? (I.e., with the instruction to ‘try and earn as many points as you can.’) ▶ Does a preference test between items of different values count as an indirect test of memory? Is this a test of episodic memory? Does your answer change if values were learned through value prioritisation or reward anticipation?

Further reading ▶ Palombo, D. J., Keane, M. M., & Verfaellie, M. (2015). How does the hippocampus shape decisions? Neurobiology of Learning and Memory, 125, 93–97. doi: 10.1016/j.nlm.2015.08.005 ▶ Kidd, C., & Hayden, B. Y. (2015). The psychology and neuroscience of curiosity. Neuron, 88(3), 449–460. doi: 10.1016/j.neuron.2015.09.010 ▶ Gershman, S. J., & Daw, N. D. (2017). Reinforcement learning and episodic memory in humans and animals: An integrative framework. Annual Review of Psychology, 68(1), 101–128. doi: 10.1146/annurevpsych-122414-033625

Chapter 8 Making it personal

Throughout our life, we reorganize our memories and ideas of the past, conserving more or less the same material, but adding other elements capable of changing its significance and, above all, of changing our viewpoint. — Jean Piaget (1973)

Stimuli related to ourselves tends to be preferentially attended to. This phenomenon is best exemplified by the cocktail-party effect, where people are able to focus on a particular conversation amidst a variety of concurrent sounds, but can readily and automatically attend to a different conversation if their name is mentioned (Moray, 1959; Wood & Cowan, 1995; Conway et al., 2001; Röer & Cowan, 2021). The cocktail-party effect can also occur visually (Shapiro et al., 1997b). More generally, our individual past experiences can influence daily experiences, such as hearing a song that reminds you of childhood events (for instance, a school dance or graduation). These cues may not consciously come to mind if someone were to ask you about important events from your childhood, but nonetheless have become something that is personally relevant. We have discussed autobiographical memory in a few prior instances, particularly in Chapter 3, but now let’s bring it to the forefront and then gradually transition towards self-relevant stimuli.

8.1 Autobiographical memory Autobiographical memory is memory for one’s own life, spanning both episodic and semantic memory systems. For instance, autobiographical memory includes episodic memories of events such as moving to a new city, going on vacation, and your first kiss. Autobiographical-related semantic memories can include your parents’ middle names, name of first school attended, and the

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name of first person you dated. Many online security questions are based on semantic autobiographical details (further discussed in Section 13.4, p. 430). Some suggest that there is a continuum between episodic and semantic memory systems in relation to autobiographical memory (Dalla Barba et al., 1997; Renoult et al., 2012; Strikwerda-Brown et al., 2018; Montemayor, 2018). In the framework proposed by Strikwerda-Brown et al. (2018), memory details can be classified as specific events, personal experiences that are several days in length or re-occur (e.g., “Every Christmas I…”), autobiographical traits and facts (e.g., “I used to design websites” and “I live in Nottingham”), and general knowledge (e.g., “Spoons are typically kept in the kitchen”). These four details are more succinctly described as specific episodes, extended episodes, personal semantics, and general semantics, respectively. Renoult et al. (2016) provide a comprehensive list of each of these four types of statements. This work built on an existing memory detail classification approach (Levine et al., 2002), but particularly made the advance in re-classifying episodic external event details and semantic details into a continuum. Personal semantics have been explored more thoroughly in previous literature, particularly in an influential review paper by Renoult et al. (2012). Personal semantics is a form of declarative memory that concerns knowledge of one’s past, such as autobiographical information and personal experiences. It is idiosyncratically personal, meaning it is unique to each individual and not culturally shared. Personal semantics differs from what is typically considered semantic memory as it is not general knowledge, but rather is personal to each individual. On the other hand, personal semantics shares similarities with episodic memory in that it is personal, but is detached from its context of acquisition—like semantic memory. MIN RE

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Two approaches to study autobiographical memories are to examine narratives of the events through interviews or diaries. Though both of these are subjective accounts of past events, they do both allow for the potential to assess consistency. The narratives provided in either form could be compared over a time interval (Neisser & Harsch, 1992; Southwick et al., 1997; Curci et al., 2001; van Giezen et al., 2005; Orbach et al., 2012; Odinot et al., 2013; Wardell et al., 2023). Alternative, and potentially more informative, is that narratives can be compared from different perspectives (Bradbury & Fincham, 1990; Halford et al., 2002; Catal & Fitzgerald, 2004; King, 2010). Taking a step back, apart from using narratives to understand memory itself, it is important to consider the use of autobiographical memory in naturalistic interactions,

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not only findings from laboratory-based studies (Hyman & Faries, 1992; Wank et al., 2020; Dev et al., 2022). In some cases—such as those discussed in the chapter on emotion—veridical recordings do exist, such as with police officers and firefighters (Jones et al., 2018; Metcalfe et al., 2019; Pezdek et al., 2022).

Interviews An alternate approach is to interview participants about their personal experiences. This is sometimes done using a set of predefined nouns as prompts (e.g., PENCIL, DOG, WINDOW), known as the cue-word or Galton-Crovitz technique (Galton, 1879; Crovitz & Schiffman, 1974; Robinson, 1976). With each of these nouns, the experimenter asks the participant to think of a memory related to the cue word, along with a date and place. In a large, online study of 2,341 participants, aged 16 to 74, Janssen et al. (2011) used this approach, presenting participants with ten cues each: 24% of memories recalled were from the most recent year, with a graded recency effect over the years prior. Notably, there is a peak around ages 6–20, replicating a well-established finding known as the reminiscence bump. This will be discussed in more detail later in this chapter. An alternate approach is to specifically ask for important events (Brown & Schopflocher, 1998). Glück and Bluck (2007) interviewed 2,255 adults, aged 50–90, to list up to 15 events or experiences that were personally important in their life. Of memories reported that corresponded to ages 50 and younger, nearly 50% occurred between the ages 16–30. The most frequent important life events (in descending order) were marriage, having children, parents’ death, first job, and others’ deaths (also see Koppel & Berntsen, 2016a). Other interview approaches are also used, depending on the study goals, such as asking for memories from a specific time period, e.g., childhood or early adult life (Kopelman et al., 1989). Complementing these interview approaches, the field has established protocols for interpreting autobiographical interview narratives. In particular, Levine et al. (2002) developed a robust scoring method for autobiographical interviews to assess the types of details produced, particularly in relation to describing the part of a specific event (i.e., ‘internal’ to the event) or those external to the event. Each of these is comprised of different types of details: internal details can be either event, perceptual, emotional, place, or time. External details can be coded as event, semantic, repetition, or other. This protocol has since become a staple in the field, though some variability in reporting has developed—resulting in the proposal of standardised guidelines (Miloyan et al., 2019). Modern developments have also been made to ease implementation of the scoring method—such as using typed vs. spoken narratives (Pearson et al., 2023) and streamlining the detail annotation process (Wardell et al., 2021b).

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Diaries Since autobiographical memories occur over a lifetime and are individual specific, it can be difficult to assess the ground-truth of what events occurred and when they happened. One often used approach is to use diaries. These are particularly useful if they are initiated prior to enrolling in a research study. Many have kept diaries as children and diary use has been associated with better than average writing ability (Clark, 2014) and enjoyment of writing (Clark & Teravainen, 2017), though girls are three times more likely to maintain diaries than boys (Clark, 2011, 2014, 2018). Younger children (aged 8–11) are much more likely to write in diaries, with nearly 60% reporting writing in a diary at least once per month (Clark, 2018). Unfortunately, diary use has been decreasing in recent years (Clark, 2016) and may be at least partially attributed to increasing internet use (Clark, 2018), as older children begin to increasingly use social media platforms (e.g., Facebook, Twitter, Instagram, etc.). Several foundational studies of autobiographical memory over long intervals have been conducted by memory researchers on themselves using diary records. Marigold Linton (1982) conducted a foundational diary study over a six-year period that significantly advanced our understanding of memory dynamics over long periods. In this study, Linton meticulously recorded each day’s events on individual index cards, generating over 5,500 memory records. She used this extensive self-generated database to examine the nature of memory, particularly exploring how people remember and forget over extended timeframes. She also characterised the memories using a few dimensions, including importance, emotionality, probability of rehearsal, distinctiveness. Among her critical findings was the discovery that more recent and frequently occurring events were more likely to be recalled, providing valuable insights into the influence of recency and frequency on memory retention—this aligned with the work of Ebbinghaus (1885), but extended it from shorter periods using nonsense syllables to much more naturalistic circumstances. Linton’s research in autobiographical memory has had a significant impact on the field, contributing to a broader and deeper understanding of how long-term memory works in real-world contexts. Wagenaar (1986) was inspired by Linton (1982), and conducted a similar study on himself, but made a few variations. For his study, Wagenaar characterised each event with four specific details: what, where, when, and who else was involved. He would then test himself by providing two details as cues and having to recall the other two characteristics. An example of his recording sheet is included in the paper. He found that his memory had similar forgetting curves to Linton’s, but also compared the number of type of cues used. He performed best with the ‘what’ cue and worst with the ‘when’ cue. In a subsequent analysis, Wagenaar (1992) observed that he had better memory for self-related unpleasant events than other-related unpleasant events (also see Chapman & Underwood, 2000). Sotgiu (2021) has conducted a review

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of these two studies and the six others that similarly fit into this rigorous examination of their own memory—Francis Galton, Madorah Smith, Steen Larsen, Dorthe Berntsen, Alan Baddeley, and Richard White. Several other studies of autobiographical memory using diaries to provide verifiable information are also notable. A limitation of the investigations of Linton and Wagenaar is that the researcher was also the participant and examiner. Barclay and Wellman (1986) had several participants that were tested over a two-and-a-half year interval. Memory was tested using recognition, allowing for false memories to be endorsed. Correct recognition (hits) was relatively stable over the period examined. However, false recognition increased after a 1–3-month period. Many aspects of this work were later replicated (Conway et al., 1996), though some of the more nuanced analyses—not discussed here—were dissimilar.

Traumatic memories A limitation of interview and diary methods to investigate memory for one’s personal experiences is that participants may not always feel comfortable recounting experiences that happened to them, even if they are saliently remembered—such as in the case of traumatic memories. Even if vividly recalled, the participant may not want to describe the memory out loud, verbally characterising an event that was painfully seared into their mind. These traumatic memories may have also been suppressed as part of a coping mechanism to make the experiences less painful (Wagenaar & Groeneweg, 1990; Melchert & Parker, 1997; Goodman-Brown et al., 2003; Merckelbach et al., 2003; Mary et al., 2020). Alternatively, survivors of traumatic events may sometimes feel obligated to pass on their experiences (Schiff et al., 2001; Kraft, 2002, 2006; Cappelletto, 2003; Krondorfer, 2008; Brehm & Fox, 2017). For instance, Kraft (2002) conveys: The most powerful message of memory that witnesses convey is the fundamental necessity of remembering itself. All witnesses provide testimony to document the events of the Holocaust. All witnesses externalise their memories to leave behind a permanent record for future generations. (p. 165) These two possibilities are at odds, “Though the emotional pain of remembrance is of great concern to them, witnesses state that the motivation to make memory public is powerful enough to overcome this concern” (Kraft, 2002, p. 166).

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On September 27, 2018, Christine Blasey Ford—a professor of psychology—testified to a US Senate committee describing sexual assault she experienced as a teenager (U.S. Senate Committee, 2018; Edwards, 2018). Given her academic background, she was able to describe the incident with knowledge of how memory works: Indelible in the hippocampus is the laughter, the laugh—the uproarious laughter between the two, and their having fun at my expense. […] It’s—just basic memory functions. And also just the level of norepinephrine and epinephrine in the brain that, sort of, as you know, encodes — that neurotransmitter encodes memories into the hippocampus. And so, the trauma-related experience, then, is kind of locked there, whereas other details kind of drift.

8.2 Lifespan distribution of memories When considering the age distribution of when people recall their autobiographical memories from, three major features emerge. First, there are a large proportion of memories remembered from late childhood and early adulthood, the reminiscence bump. Second, there is also a dearth of memories from the first years of childhood (ages 0–3), known as infantile amnesia or childhood amnesia. Third, there is a tendency to remember relatively recent events—a recency effect. A hypothetical distribution of the age of recalled events is shown in Figure 8.1. The highest proportion of autobiographical memories occur between late childhood and early adulthood, approximately ages 6 and around 25 to 30 (Rubin & Schulkind, 1997; Rubin et al., 1998; Berntsen & Rubin, 2002; Zaragoza Scherman, 2013). Conway et al. (2005) replicated the reminiscence bump across several cultures and countries, with participants from Japan, China, Bangladesh, England, and the United States (also see Benson et al., 1992; Zaragoza Scherman et al., 2017; Coleman et al., 2023). This period is also associated with better memory for public events (Belli et al., 1997; Janssen et al., 2008; Koppel & Berntsen, 2016a). The specific peak age, however, differs based on how memory is assessed, e.g, word cues vs. personally important events (Koppel & Berntsen, 2015, 2016a, 2016b; Koppel & Rubin, 2016). MIN RE

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FIGURE 8.1: Hypothetical proportion of recalled events by decade for an 80-year-old individual. Responses based on cue words are shown in a solid line; personal importance is shown in a dashed line.

Life transitions Two prominent theories explain how life events provide structure to our life stories. Berntsen and Rubin (2002) suggest that life script and life story chapters help us organise our autobiographical memories (also see Bluck & Habermas, 2000; Thomsen, 2009; Janssen & Rubin, 2011). This view suggests that autobiographical memories are centred on the journey towards culturally defined goals, such as graduation, marriage, and having children. Our life story is organised into distinct chapters, each marked by a significant life transition. These chapters provide a narrative structure that helps us to make sense of our past, to understand our present, and to anticipate our future. Each chapter is characterised by a unique set of experiences, emotions, and social relationships, which shape the content and quality of our autobiographical memories. Aspects of our lives can have their specific scripts—such as our love life—as people tend to experience many ‘firsts’ in sequenced order, followed later by marriage, and possibly divorce (Dunlop et al., 2017). Table 8.1 reports the love life events reported by a sample of participants across the adult lifespan, asked to provide a list of major love life events and their associated estimated age. Identify formation is also related to this view (Markus, 1977; Fitzgerald, 1988, 1996; Rathbone et al., 2008). Here the reminiscence bump is reconsidered in relation to “I am” statements, considering how one’s identity becomes defined with age. Examples of key sentences included “I am a mother” and “I am adventurous.” Alternatively, the variations in remembering could be due to brain development/maturation (Somerville, 2016; Dahl et al., 2018).

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TABLE 8.1: Love life script events and associated ages from Dunlop et al. (2017). Event

Age at event M SD

First crush First time holding hands/hugging Experiencing puberty First kiss First time engaging in foreplay First girlfriend/boyfriend First date First heartache/rejection First time falling in love First break-up Losing virginity First time saying “I love you” First “serious” relationship Experiencing a major conflict in relationship Meeting romantic partner’s family Meeting the “one” Moving in with romantic partner Getting engaged Getting married Having a child Getting a divorce Death of spouse

9.36 11.70 12.05 13.58 14.64 14.78 15.15 15.75 16.73 16.92 17.41 17.71 21.08 22.54 22.71 24.38 24.41 24.81 26.29 27.72 35.27 72.93

3.01 4.14 2.43 1.96 2.40 2.21 1.67 2.80 3.63 3.19 4.04 2.64 6.92 7.16 12.42 6.41 3.30 2.64 2.78 3.67 6.03 12.05

A recent systematic review of 68 studies explored the different methods and interpretations of the reminiscence bump (Munawar et al., 2018). Transition theory (Brown, 2016) suggests that life transitions serve as landmarks, providing a temporal framework that helps us to locate memories in time. These landmarks act as anchors, around which we organise our autobiographical memories. For instance, we might remember an event as occurring “before I moved to Boston” or “after I finished my PhD.” This temporal framework is not just a passive record of events; it actively shapes how we remember our past, influencing which memories we recall and how we interpret them. Related to this, the “living in history” project (Brown et al., 2009) found that these landmarks were more related to personal significance, rather than historical importance. In addition to these typical variations in the age distribution of memories, there are more individualised periods of increased autobiographical memories being reported (also see Svob et al., 2014). Some examples of these landmark life events are positive, such as marriages and having children (Thomsen et al., 2011, 2021), as well as residential moves (Schrauf & Rubin, 1998, 2001; Koppel

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& Berntsen, 2016a; Enz et al., 2016). In other instances, major life events are negative—such as a significant injury or the death of a loved one (Thomsen et al., 2011; Uzer & Brown, 2015). Public events can also be important events in one’s memory, such as regional wars and natural disasters (Kraft, 2002; Brown et al., 2009; Brown & Lee, 2010; Koppel & Berntsen, 2016a; Štěpánková et al., 2020). Smaller landmarks, such as birthdays, can also be useful in categorising and clustering life events (Rathbone & Moulin, 2010; Peetz & Wilson, 2013). As an example, we can consider the events of a fictional character, Forrest Gump (1994). Figure 8.2A provides an illustration of the major life events for Forrest—his initial walking challenges, running, football, time in the army, shrimp business, cross-country running, and marriage to Jenny. The movie has been used in a number of brain-imaging studies to study narrative processes (Hanke et al., 2014; Ben-Yakov & Henson, 2018; Kumar, Ellis, et al., 2020). Luke Skywalker’s development through the Star Wars movie series can also be studied for its major life events, see Figure 8.2B. Several other fictional characters have had sufficient development and life transitions to have potential for use in memory research, such as Harry Potter (Wilbers et al., 2012; Brown & Shi, 2017), as well as Elizabeth Bennet (Pride and Prejudice) and Walter White (Breaking Bad).

FIGURE 8.2: Timeline of major life events for (A) Forrest Gump and (B) Luke Skywalker.

Infantile amnesia Typically there are no autobiographical memories for ages 3 and under (Kihlstrom & Harackiewicz, 1982; Fitzgerald, 1991; Rubin, 2000; Jack & Hayne, 2010; Hayne & Imuta, 2011). Often our earliest memories are of an emotional experience, such as a birthday party, a vacation, or the birth of a sibling. In some cases, memories are retained from younger ages—highly salient experiences, such as a hospital emergency visit (Peterson & Whalen, 2001). Even with HSAM there is infantile amnesia (Price, 2008, p. 26). The term ‘infantile amnesia’ was first used by Freud (1905) to refer to this inability to remember our experiences from early childhood—though our understanding of this phenomenon has advanced much over the years. While

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Freud had his own interpretation for the cause of infantile amnesia, here I will focus on perspectives supported by empirical evidence. A few explanations have been proposed and are currently being debated in the literature—and it is likely that multiple mechanisms could be at play. One explanation is insufficient language ability; it is difficult to remember an experience if we cannot attach words to what is happening (Neisser & Harsch, 1982; Fivush & Nelson, 2004; Nelson & Fivush, 2004; Simcock & Hayne, 2002). While this contributes to infantile amnesia, there are also studies of infantile amnesia in non-human animals (Campbell & Spear, 1972; Madsen & Kim, 2016; Harmon-Jones et al., 2020). Moreover, it could be that the brain pathways and storage mechanisms for maintaining episodic autobiographical memories over long periods are not sufficiently developed (Bauer, 2004, 2006; Bauer & Leventon, 2013; Josselyn & Frankland, 2012; Akers et al., 2014; Jabès & Nelson, 2015; Travaglia et al., 2016; Guo et al., 2024). In some instances, vivid ‘memories’ from childhood may be falsely constructed. Jean Piaget, the famous child psychologist, believed for many years that he had almost been kidnapped at the age of 2, and had memories of the incident. This story that was told to him by his nursemaid, and later reinforced by his family. However, 13 years later, his nursemaid sent a letter to his family confessing that the incident was made up and returned the reward she was given for saving him. Here is the original text from Piaget (1951): There is also the question of memories which depend on other people. For instance, one of my first memories would date, if it were true, from my second year. I can still see, most clearly, the following scene, in which I believed until I was about fifteen. I was sitting in my pram, which my nurse was pushing in the ChampsÉlysées, when a man tried to kidnap me. I was held in by the strap fastened round me while my nurse bravely tried to stand between me and the thief. She received various scratches, and I can still see vaguely those on her face. Then a crowd gathered, a policeman with a short cloak and a white baton came up, and the man took to his heels. I can still see the whole scene, and can even place it near the tube station. When I was about fifteen, my parents received a letter from my former nurse saying that she had been converted to the Salvation Army. She wanted to confess her past faults, and in particular to return the watch she had been given as a reward on this occasion. She had made up the whole story, faking the scratches. I therefore must have heard, as a child, the account of this story, which my parents believed, and projected it into the past in the form of a visual memory, which was a memory of a memory, but false. Many real memories are doubtless of the same order. (pp. 187–188) For a broader discussion of fictional first memories, see Akhtar et al. (2018).

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8.3 Self narratives and identity It cannot be understated that memory is critical to our self identity; indeed, several conceptual frameworks are based on this very idea (Locke, 1690; Wang & Brockmeier, 2002; Kihlstrom et al., 2003; Bluck, 2003; Conway, 2005; McAdams, 2008). Locke (1690, Book 2, Ch. 27) presents a view of self identity based on continuity of consciousness, mediated by memory. He famously illustrates this idea with the concept of a ‘day-person’ and a ‘nightperson.’ If a person remembers what happened during the day but not at night, and another person remembers what happened at night but not during the day, these are effectively two different people, even if they occupy the same body. In other words, Locke posits that memory gives us our sense of self, and without memory, we would lose our identity (also see Parfit, 1984). This view is sometimes referred to as psychological continuity theory. Providing empirical support, Addis and Tippett (2004) evaluated measures of sense of identity from Alzheimer’s disease patients and found impairments relative to healthy adults (also see Prebble et al., 2013; Strikwerda-Brown et al., 2019). Several movies present fictional scenarios where two selves share one body and have distinct personalities, particularly Jonathan (2018), but also some others to a lesser degree, such as Fight Club (1999); also the videogame Pathfinder: Kingmaker (2018). In Jonathan (2018), two brothers—Jonathan and John—share the same body but have separate consciousnesses. They each have distinct personalities and memories, and they communicate through video messages to explain what happened during their respective time in control of their shared body. Jonathan is active during the day (7am–7pm), while John takes over at night. As such, they live separate lives in the same body, maintaining their individual identities through strict rules. Bluck et al. (2005) suggested that there are three key main functions of autobiographical memory: directive, self, and social (also see Bluck, 2003). The directive function refers to the role of our past experiences in guiding our present and future actions. This function is akin to the adage of learning from one’s mistakes. It is through the recollection of past events, successes, and failures that we can make informed decisions and plan for the future. For instance, remembering the discomfort caused by procrastination might motivate an individual to start a project early. This function of memory is particularly relevant in the context of problem solving and decision making. The self function is concerned with self identity and self coherence. Our memories, particularly those that are personally significant, contribute to our sense of self. They provide a narrative that links our past, present, and future selves, thereby fostering a sense of continuity and coherence. For example, remembering your childhood passion for drawing might reinforce your current identity as an artist. This function of memory is crucial for self understanding and self expression. The social function involves the sharing of personal memories with others. Our memories serve as tools for social interaction, allowing us to form connections with others. By sharing our past

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experiences, we can elicit empathy, provide advice, or entertain others. For instance, sharing a memory of a travel adventure can strengthen a bond with a friend who has had a similar experience. This function of memory plays a vital role in maintaining and enhancing social relationships. It’s important to note that these functions are not mutually exclusive and often interact with each other. For example, sharing a memory with others (social function) might also help us understand ourselves better (self function) and guide our future actions (directive function). To evaluate these functions, Bluck and Alea (2011) developed a 30-item questionnaire (revised from Bluck et al., 2005), shown in Table 8.2. The instructions state: Sometimes people think back over their life or talk to other people about their life: it may be about things that happened quite a long time ago or more recently. We are not interested in your memory for particular events, but more generally in how you bring together and connect the different events and periods of your life. The stem for each of the 30 items is: “I think back over or talk about my life or certain periods of my life…” The stem completion items (see Table) are presented in random order. Responses are made on a 5-point Likert-type scale, ranging from 1 (almost never) to 5 (very frequently). While TALE is typically used to assess how an individual views memory function, it can be adapted for memory-specific ratings (see Yang et al., 2022). What we remember helps define who we are, and who we are defines what we remember (Demiray & Janssen, 2015; Janssen et al., 2015; Garland et al., 2021). Even then, our identity is also subtly changing as we accrue experiences; our ‘self’ is not a stable entity (Markus, 1977; Markus & Nurius, 1986; Barclay, 1993). Major life events can also lead to more marked changes in personality (Lüdtke et al., 2011; Lavner et al., 2018). For instance, results from a metaanalysis show that entering a new relationship is associated with an increase in conscientiousness and life satisfaction, the birth of a child is associated with a decrease in extroversion (Bühler et al., 2023). As summarised in Section 6.5 (p. 194), as people age, they tend to decrease in narcissism and increase in emotional stability (Srivastava et al., 2003; Williams et al., 2006; Carstensen et al., 2011; Harris et al., 2016; Schwaba et al., 2022; Weidmann et al., 2023), which is related to weaker biases for remembering negative emotional experiences (Ruiz-Caballero & Bermúdez, 1995; Reed & Derryberry, 1995; Lilgendahl et al., 2013; Jensen et al., 2019).

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TABLE 8.2: The 30-item Thinking About Life Experiences (TALE) scale, adapted from Bluck and Alea (2011). When administered, order is randomised. Item Phrase 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 13. 14. 15. 16. 17. 18. 19. 20. 21. 22. 23. 24. 25. 26. 27. 28. 29. 30.

Self Function When I want to feel that I am the same person that I was before. When I want to think about how I am different now than I was in the past. When I am concerned about whether I am still the same type of person that I was earlier. When I am concerned about whether my values have changed over time. When I want to get a better sense of who I am now. When I want to understand who I am now. When I want to think about whether my life has a coherent story. When I want to see if I have an overall theme in my life. When I am concerned about whether my beliefs have changed over time. When I want to understand how I have changed from who I was before. Social Function When I want to help someone by telling them about my own past experiences. When I hope to also find out what another person is like. When I want to develop more intimacy in a relationship. When I want to empathise with something that someone else has experienced. When I want to make someone else feel better by talking to them about my similar past experiences. When I want to develop a closer relationship with someone. When I want to introduce myself to other people. When I want to maintain a friendship by sharing memories with friends. When I hope to also learn more about another person’s life. When I want to let other people know more about me. Directive Function When I want to remember something that someone else said or did that might help me now. When I think about my goals for the future. When I am searching for a solution to a current life difficulty. When I believe that thinking about the past can help guide my future. When I want to try to learn from my past mistakes. When I need to make a life choice and I am uncertain which path to take. When I want to remember a lesson I learned in the past. When I want to see whether my life is going in the right direction. When I feel that if I think about something bad that happened I can learn some lesson from it. When I am facing a challenge and I want to give myself confidence to move forward.

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When experiences are not accumulating in memory, in the case of patients with anterograde amnesia, personality traits instead remain stable—further emphasising the role of memory in updating one’s sense of self (Garland et al., 2021). No one has described this relationship more masterfully than Oliver Sacks (1985), in the chapter entitled “A matter of identity”: We have, each of us, a life-story, an inner narrative—whose continuity, whose sense, is our lives. It might be said that each of us constructs and lives, a “narrative,” and that this narrative is us, our identities. If we wish to know about a man, we ask “what is his story—his real, inmost story?”—for each of us is a biography, a story. Each of us is a singular narrative, which is constructed, continually, unconsciously, by, through, and in us—through our perceptions, our feelings, our thoughts, our actions; and, not least, our discourse, our spoken narrations. Biologically, physiologically, we are not so different from each other; historically, as narratives— we are each of us unique. To be ourselves we must have ourselves— possess, if need be re-possess, our life-stories. We must “recollect” ourselves, recollect the inner drama, the narrative, of ourselves. A man needs such a narrative, a continuous inner narrative, to maintain his identity, his self. (p. 111) With variations in how we remember our past, such as due to reminiscence bump and life transitions, the sampling of events and experiences forms our self narrative and identity. Particularly when considering personally important events, these are the very fabric of memories that comprise our lives. Additionally, this bias to remembering our ‘firsts’—first kiss, first job, first time living on our own—are formative experiences, and themselves could be examples of primacy effects. This perspective is convergent with the identity formation and culture life scripts. Many studies have shown that people first encounter their favourite books and movies during the reminiscence bump years (Larsen, 1996; Sehulster, 1996; Janssen et al., 2007; Kuhn, 2013). Nicoll (2022) took a creative approach to asking this question, examining the records from a videogame-themed podcast that ran between 2015–2018, Checkpoints. In each of the 115 podcast episodes, the guest was asked “what was your first experience of a videogame?” While the specific games discussed varied, there were some common themes, amazement, social interactions (e.g., hearing about a game from a friend, being enabled/prohibited from playing by a parent), to the reality of being able to play (e.g., going to a friend’s house, walking to the arcade). Formative experiences related to preferences have also been observed for music (Holbrook & Schindler, 1989, 1996; Smith, 1994; Zimprich, 2020). Just like the Ampelmännchen logo, music can be a strong cue for memory in everyday life. In a particular instance, I saw the screen of a friend’s music device with the song name “Metallica—Am I Evil?” With songs you know

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well, often you can instantly hear it playing in your mind—and this can be true for thousands of songs, without any deliberate effort. Krumhansl and Zupnick (2013) examined music preference in young adults using an autobiographical memory inspired procedure. Researchers selected two ‘top 100’ songs for each year from 1955 to 2009 and asked participants to rate how much they liked the songs, as well as report on different kinds of memories they had associated with the song. Participants preferred the songs that were relatively recent, with a gradual decrease in ratings until those were released around when they were born (also see Schulkind et al., 1999). However, a second peak was also present, slightly before their birth, corresponding to songs that came out when their parents were in their adolescent years. Through further research it was found that participants recognised these songs, but often did not know the artist, title, or lyrics— or have specific memories associated with them. This effect was labelled as a ‘cascading reminiscence bump’ where songs from the parents’ generation were likely played in the home and preferences transmitted across generations. In another study providing convergent findings, Stephens-Davidowitz (2018) examined the popularity of songs across different ages and separately for men and women. Results indicated that regardless of age, people tend to listen to songs that were released around when they were 12 to 20 years old. Using data shared along with the article, I examined this for several songs myself, shown in Figure 8.3. While this approach did not work well for songs that are very popular, for instance, “Eye of the Tiger,” this is otherwise indicative that the music we heard when we were in our adolescent years stay with us. Some songs have better staying power across ages and may even be re-discovered later on, such as Rick Astley’s “Never Gonna Give You Up,” while other songs are popular with only a relatively narrower age range, such as “Baby Got Back.” In Canada, radio stations need to play a specified minimum amount of Canadian content. When this requirement was initially set in 1971, the minimum amount of Canadian content was 25%, but has risen over the years and since 1999 is set at 40% (Muia, 2020). When I was growing up, I mostly listened to the radio. While I could choose the radio station, all of them played a large proportion of Canadian content, as they were required to. Knowing what I know now, this is likely related to why some of my favourite bands growing up were Finger Eleven, Three Days Grace, and Sum 41, but also Nickelback and Theory of a Deadman. I distinctly remember that one of my first favourite songs was “Stereo” by The Watchmen. “That Song” by Big Wreck is also quite fitting to mention, a song about nostalgia itself. Of course, I also liked music from other countries, but my preferences are disproportionately Canadian, likely due to this Canadian content requirement on the radio stations. In April 2023, the Canadian parliament passed Bill C11, seeking to extend this curated cultural experience to now apply to online streaming. This approach to content regulation underscores the recognition of media’s role in identity formation (Madan, 2024).

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FIGURE 8.3: Song popularity across different ages, based on data from Stephens-Davidowitz (2018) collected in 2016. Men are shown in black; women in grey. Vertical dashed lines indicate the age that the song is most popular with, along with the age that those individuals would have been when the song was released. As an example, for a song released in 1973 heard by a 17-year-old individual, that individual would be aged 60 as of 2016. In the USA, there was a period when music publishers would pay radio stations to play specific songs more (Randle, 1961; Mol & Wijnberg, 2007). This has since become regulated, and is referred to as payola. With internet music websites, this has become further complicated (Wautlet, 2021). Knowledge of music (and TV shows) can also be used as a test of age verification (Hartman et al., 2022). That is, an older adult is much more likely know the artist of the song “Wooly Bully” (first released in 1964) and choose it correctly in a multiple-choice test. Conversely, a young adult would much more likely select the correct artist for the song “How You Remind Me” (released in 2001). In principle, the same approach should apply to any age-specific general knowledge (see also Toth et al., 2011; Coane & Umanath, 2021), though it is important to acknowledge that the content should be re-evaluated if used across different cultures. For instance, the song “Gangnam Style” quickly

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became known around the world, whereas the song “One Pound Fish” was very popular, but only within the UK. The band “The Rubberbandits” has done well in Ireland, but is relatively unknown elsewhere. Moreover, songs from children’s TV shows may become unbearably familiar to parents, but completely unfamiliar to their childless same-aged peers. Songs that become associated with emotional and formative experiences become a part of our identity and stay with us for a long time. When I ‘graduated’ from primary school, “Boulevard of Broken Dreams” by Green Day was played at the celebration. Savage Garden’s “Truly Madly Deeply” still reminds me one of my first relationships. Music can be an important part of creating lasting memories, particularly those that are shared with others (Rentfrow & Gosling, 2006; Wood & Kinnunen, 2020). MIN RE

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Music can also be useful as reminiscence therapy to cue memories, as episodic memory abilities declines—such as in patients with dementia (Sambandham & Schirm, 1995; Simmons-Stern et al., 2010, 2012; Jacobsen et al., 2015; Reschke-Hernández et al., 2020; Rasmussen et al., 2021). Depending on the severity of the disease progression, music may or may not be able to cue episodic memories, but can still elicit positive emotions that have been associated with the music (i.e., related to the notion of multiple, complementary memory systems). In addition, to positively influence the quality of life of patients with dementia, sharing familiar music can improve social well-being (Elliott & Gardner, 2018). One example of this is the shared enjoyment and connection between the patient and caregiver.

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8.4 Self-reference effect In studies of the self-reference effect (SRE), participants are asked to relate to-be-remembered content to themselves or an alternate encoding task. Items related to one’s self are better remembered. With emotion, nearly always the stimuli themselves are inherently emotional. In contrast, with reward, the ‘property’ of being rewarded is experimentally assigned. Here, with the self-reference effect, both approaches are used in the literature: in some procedures, to-be-remembered material are either self-related or not, such as with trait adjectives or personal information—sharing commonalities with emotion studies. In other procedures, ownership is experimentally assigned—similar to reward studies.

Traits Rogers et al. (1977) conducted a foundational study in the field, based on the levels-of-processing approach. Using a within-subjects design, participants were presented with lists of words and had to make one of four judgements for all of the words in that list. In all cases, lists were comprised of words that were adjectives that could be characteristics and selected from previously published trait descriptions. As examples, some potential stimuli were ADVENTUROUS, FOOLISH, and RELIABLE (words selected from Bentley et al., 2017). The most shallow condition involved merely judging if the word was presented in big letters or not. In this condition, words were presented either at a specific size or double the font size. The second condition required a judgement of the word rhyming (or not) to a target word. The third condition involved judging if the presented word was a synonym with a target word. Finally, and most critically, participants had to make a judgement of whether the presented word “Describes you?” with a yes or no response. In their first experiment, mean recall accuracy was .30 for the selfreference condition, but ranged between .03 and .13 for the other three conditions. In a second experiment, the same general conditions were used, with some modifications to the specific instructions to address potential confounds of the task design. Here mean recall was .32 for the self-reference condition, but between .19 and .20 for the other three conditions. These results provided strong evidence that relating information to one’s self makes words more memorable than relatively typical encoding instructions and laid the foundation for this literature. This has since become a long-standing approach to studying SRE. Though meta-analyses are becoming increasingly common, in 1997 a meta-analysis was published on the SRE, including 129 studies (Symons & Johnson, 1997). The findings of this meta-analysis demonstrate that this effect is highly robust and replicable. Overall, the mean weighted effect size was d = 0.50. When specifically compared to the semantic (synonym) control condition, the effect

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size was d = 0.65. More recently, Bentley et al. (2017) tested the SRE in an online format and larger samples; otherwise, this study followed a very similar methodology to the original 1977 study. Further demonstrating the robustness of this effect, across several experiments with a total sample size of 658 participants, the effect size for SRE vs. semantic condition was d = 0.63, closely matching the prior meta-analysis. The SRE can also bias false memories, as demonstrated using a DRM procedure—in both Western and Eastern samples (Wang et al., 2019). While incidental encoding with a self-reference rating task has benefits, it is not necessarily better than intentional encoding. Nairne et al. (2008) compared a variety of encoding procedures, including these two options, in a large-scale study (N = 300, across six groups). Mean recall for a 30-word list was between .45 and .50 for five of the groups. Only one encoding procedure (survival processing) outperformed the other five, which we will discuss in Section 10.5 (p. 310). Gilliam and Gutchess (2024) examined the SRE in a sample of nearly 100 individuals who had recently immigrated to the US from mainland China, having lived in the US for fewer than five years. Here the focus was on how early impacts of acculturation from an Eastern to Western setting may influence the magnitude of the SRE. While questionnaire measures of acculturation and cultural values did not correlate with the SRE, the overall effect was weaker in these participants than in typical Western samples, replicating prior studies (Sui et al., 2007; Ng & Lai, 2009; Zhang et al., 2020). In a study of healthy adults and individuals with amnestic mild cognitive impairment, considered to be an early form of dementia, the SRE has also been assessed (Carson et al., 2019). Participants were presented with short narratives and after each were immediately asked to make a judgement that was self-related, semantic, or sentence structure. In both recall and recognition tests, memory was superior for the self condition than the structure condition, despite overall impairments in memory. In another study, APOE-e4 carriers retained the SRE, but had an impaired emotional enhancement of memory (EEM) (Grilli et al., 2017).

Personal information A second procedure to examine self-related effects is based on autobiographical memory. Here, autobiographical data is collected in advance of the experimental session, such as ‘hometown,’ ‘high school mascot,’ and ‘mother’s first name’ (Gray et al., 2004). As mentioned at the beginning of this chapter, this is the same principle as underlies the cocktail-party effect. In some ways, these question prompts are similar to those used for security questions (see Section 13.4, p. 430). In the experiment, the autobiographical words were presented intermixed with other names, hometowns, etc. This procedure is not amicable to an episodic memory test, but is more aligned with the online stimulus processing, akin to the cocktail-party effect

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(Moray, 1959; Wood & Cowan, 1995; Conway et al., 2001; Röer & Cowan, 2021). Relatedly, presenting personal details captures attention moreso than control stimuli (Gray et al., 2004; Alexopoulos et al., 2012). Self-related trait adjectives have also been shown to capture attention (Wentura et al., 2000). These studies and others demonstrate convergence with both emotion and reward; self-referential stimuli can elicit attentional capture (Bargh, 1982; Pratto & John, 1991; Shapiro et al., 1997b; Arnell et al., 1999; Tacikowski & Nowicka, 2010; Alexopoulos et al., 2012). MIN RE

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Ownership Taking a more experimental approach to self-relatedness, are studies that assign item ownership (see Beggan, 1992). Cunningham, Turk, et al. (2008) invited participants to the session along with an experimenter who posed as a second participant, each was given a different coloured shopping basket. The two individuals were given a stack of cards with object pictures and asked to imagine that they won a shopping basket of items. Each of the cards had a coloured dot on it, matching one of the shopping baskets. The two were asked to sort the cards into their respective shopping carts. In a subsequent recognition test, the individuals remembered the objects they were assigned as the owner far better than those owned by the other individual. The main effect of who sorted the object was not significant, nor the interaction. An adaptation of the design for research with 4- to 6-year-old children showed similar results (Cunningham et al., 2012). A subsequent study with further adaptations designed for 7- to 9-year-old children also extended these findings (Cunningham et al., 2018). Early versions of this procedure involved two people, some with physical objects or picture cards, some on a computer; a child or young adult with an experimenter (Cunningham et al., 2008, 2011, 2018), or two children tested in pairs (Cunningham et al., 2012). However, some adaptations have tested single participants and, for instance, asked them to sort objects belonging to them or another—pressing a button corresponding to “my house” or “stranger’s house” (Truong et al., 2013, 2017; Daley et al., 2020a, 2020b). Another approach involves making judgements about the present object that you (as the participant), a close other, or Albert Einstein would buy (Hamami et al., 2011). The ‘close other’ was specified in advance using a preceding task. Participants often chose a close friend, parent, romantic

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partner, or sibling. As with other approaches, this incidental encoding task was later followed by a recognition test. Memory was best for items associated with self, with a graded effect of social distance (also see Serbun et al., 2011). The endowment effect is a well-known and related phenomenon, referring to the finding that people put more value on objects that they own or otherwise identify with than an alternative (Kahneman et al., 1990, 1991; Harbaugh et al., 2001; Flemming et al., 2012). People similarly place more value on objects they had constructed themselves—such as with IKEA furniture, origami, Lego sets—the IKEA effect (Norton et al., 2012; Marsh et al., 2018; Radtke et al., 2019). These differences in valuation likely further relate to memory mechanisms, related to preference-memory relationships (Weber & Johnson, 2013; Madan & Spetch, 2012) and considerations of object functionality (discussed in the following chapter). In some cases, companies have been able to associate themselves with us in a way that becomes part of our identity. This level of brand loyalty is special, where the brand and the user are not just a community, but the brand becomes a part of the individual’s group identity—achieving a ‘brand cult’ like status. Apple is probably the most well known for doing this, achieving a strong relationship with its users decades ago—and furthered with the iconic advertising campaign and for the first generation of iPod devices (Muñiz & Schau, 2005; Belk & Tumbat, 2005; Constantin & Stoenescu, 2014; Wu & Minor, 2019). Other brands that have achieved extreme levels of brand loyalty include Nike, Starbucks, and Lego (Acosta & Devasagayam, 2010; Muñiz et al., 2013). In the mid-2010s, Coca-Cola did an even more ingenious advertising campaign—putting names of customers on the bottles themselves, as in Figure 8.4. Given its existing brand recognition, the product itself did not need any introduction, but instead using people’s names they motivated customers to buy bottles that featured their own name or those of friends and family as a thoughtful gift.

FIGURE 8.4: Photo of a cola bottle with ‘Chris’ on it.

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Neurobiology fMRI studies of the self-reference effect typically demonstrate task-related activity in medial cortical regions, particularly the ventromedial prefrontal cortex (Kircher et al., 2000; Fossati et al., 2004; Northoff et al., 2006; Gutchess et al., 2010; Yamawaki et al., 2017). In the case of personal semantics, amodal semantic regions can also be involved, such as the anterior temporal lobe (Tsukiura et al., 2008). Autobiographical memory has also been associated with similar brain regions (Cabeza & St. Jacques, 2007; Janata, 2009; Addis et al., 2017; Belfi et al., 2018; Benuzzi et al., 2018; McCormick et al., 2020). Choices based on an individual’s product preferences (e.g., cola and car brands) are also associated with ventromedial prefrontal cortex function (McClure et al., 2004; Schaefer et al., 2006; Koenigs & Tranel, 2008). The uncinate fasciculus, a white matter tract shown in Figure 8.5, may be particularly relevant to autobiographical memory and self-referential processing—communicating information between frontal regions and the medial temporal lobe (Schott et al., 2011; Olson et al., 2015). Levine et al. (1998) report an amnesic case with selective damage to this white matter tract due to traumatic brain injury. The patient performs well on standardised tests of recall and recognition, but exhibits impaired episodic memory for preinjury experiences. Conclusions suggest that medial temporal lobe regions still support episodic memory, but that phenomonlogical aspects of reexperiencing, associated with autonoetic awareness, are specifically impaired.

FIGURE 8.5: Illustration of the uncinate fasciculus tract, connecting frontal and medial temporal regions. Shown from the right-side and inset front view. The tract in the right hemisphere is shown in black; the left tract in grey.

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8.5 Egocentric bias If you ask people who work on a group project to estimate their contribution percent and add up their values, they very likely will add up to over 100%. This has been demonstrated in group projects (Forsyth & Schlenker, 1977; Ross & Sicoly, 1979; Kruger & Savitsky, 2009; Schroeder et al., 2016), academic research (Caruso et al., 2006; Schroeder et al., 2016; Herz et al., 2020), and team sports (Ross & Sicoly, 1979). The most evidence for this, however, is in studies of the most prevalent and naturalistic of ‘group projects’: married couples (e.g., individual contributions to housework) (Ross & Sicoly, 1979; Thompson & Kelley, 1981; Fincham & Bradbury, 1989; Deutsch et al., 1993; Kruger & Savitsky, 2009; Yavorsky et al., 2015; Carlson et al., 2020). This overestimation is not present with positive/desirable activities, but also in disagreements between married partners, where each person thinks they cause more of the arguments than their partner would estimate (Ross & Sicoly, 1979; Thompson & Kelley, 1981; Kruger & Savitsky, 2009). With respect to the egocentric bias findings in married couples, the approach used by Christensen et al. (1983) addressed some confounds present in prior work, such as focusing on only a recent time period, rather than the entire relationship, as well as the framing of the question, where a focus on self vs. partner and question order may have influenced the observed bias results (also see Schroeder et al., 2016). Given the pervasiveness of these findings, both in studies of egocentric bias as well as in the literature on marriage and relationship satisfaction without any tie to egocentric bias, the underlying phenomenon appears highly robust and replicable. To briefly summarise, people tend to overestimate their contributions to group tasks, and that this occurs regardless of if the contribution is a positive or negative activity (though this does modulate the magnitude of the effect). Why is this bias so prevalent across different types of group interactions? One account is that our own effort and experiences are more salient to us than the efforts of others; what we did ourselves is more available in memory and is overestimated. This phenomenon has been referred to as an egocentric bias (Ross & Sicoly, 1979). In their study, Ross and Sicoly (1979) found this effect in several studies, each with a different context. These included married couples (Exp. 1), basketball team (Exp. 3), self-selected group assignment (Exp. 2), researcher-assigned group assignment (Exp. 4), and student-supervisor research contributions (Exp. 5). Increasing the availability of others’ contributions reduced the magnitude of this bias. The contributions of others could be done by asking the participant to more deliberately consider the contribution of others (Ross & Sicoly, 1979; Schroeder et al., 2016). These biases are weaker when the participant was more aware of the others’ contributions in advance (e.g., better inter-personal communication or knowledge of the others’ abilities) (Kruger et al., 2008; Carlson et al., 2020). This egocentric bias was attenuated when the participant was provided with

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this information (Kruger et al., 2008), such that the contributions of others was explicitly made more available. Based on these findings, the egocentric bias—sometimes referred to as a myside bias—could be considered a narrower version of the availability bias. People also tend to be optimistic and think they complete a task more quickly than others (Buehler et al., 1994). MIN RE

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There is another bias that overlaps highly with the egocentric bias: the spotlight effect. This effect refers to people’s tendency to overestimate the extent to which their actions and appearance are noticed by others (Gilovich & Savitsky, 1999). In other words, people often feel like they are in the spotlight, and that others are paying more attention to them than they actually are. This can lead to self-consciousness and anxiety in social situations. Gilovich et al. (2000) conducted several studies along these lines. In the first study, participants were asked to wear a potentially embarrassing t-shirt and estimate how many observers would notice it. Results showed that participants significantly overestimated the number of observers who noticed their t-shirt. The second study was very similar to the first, but participants wore a t-shirt depicting a famous person they liked; participants overestimated the number of observers who noticed their t-shirt. In a third study, participants engaged in a group discussion and overestimated how prominent their positive and negative utterances were to their fellow discussants. Additional studies are reported in the paper and provide further convergent evidence. People anchor on their own rich phenomenological experience and then adjust, insufficiently, to take into account the perspective of others. This leads to an overestimation of how much they stand out to others, demonstrating the spotlight effect and its relation to egocentric bias. Further demonstrations of the spotlight effect were reported in Gilovich et al. (2002).

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Extensions of self prioritisation Self-reference effects on memory need not be constrained to information specific to an individual and their unique experiences. As already foreshadowed with the example of Holocaust survivors, more widespread experiences that shape a group’s identity can also be considered self relevant, and include an added dynamic of collective remembering. It may be surprising how many groups we can be a part of, but each of the following can be considered as an example of an in-group bias, also referred to as an own-group bias. One of the most well-studied of these is the own-age bias. When asked to remember a booklet of names and faces, young and older adults tend to better recognise those that are of the same age group as themselves (Mason, 1986; Anastasi & Rhodes, 2005; Strickland-Hughes et al., 2020). In a study with children, this own-age bias was found to only occur for faces within two years of their own age (Hills & Lewis, 2011). In a meta-analysis across 43 studies, Rhodes and Anastasi (2012) found better own- than other-age face discriminability (g = 0.37). Apart from the default in-group interpretation, one account for the own-age bias is that people tend to interact with people of a similar age—an effect of daily contact (Harrison & Hole, 2009; Wiese et al., 2012, 2013). This account is supported by a lack of own-age bias in individuals that have more contact with those in other age groups, such as teachers and geriatric nurses. This account has also been discussed more generally as evidence of perceptual expertise, where people have more prior experience with own-age faces. Most similar is the own-race bias, where people remembered faces of individuals of the same racial background better than those of another race (Malpass & Kravitz, 1969). Wright et al. (2001) used a procedure akin to the sequential line-ups used in criminal settings and demonstrated that the bias generalised to this procedure as well. Other motivational factors can also interact with the own-race bias, such as value prioritisation (DeLozier & Rhodes, 2015) and recognition of emotional expressions (Tsikandilakis et al., 2021b, 2023). Meissner and Brigham (2001) conducted a meta-analysis, finding verifiable evidence across 91 samples from 39 studies. A more recent meta-analysis examined 207 samples from 96 independent samples (Singh et al., 2021). As with the own-age bias, but proposed even earlier, Rhodes et al. (1989) suggested that the own-race bias could be due to greater perceptual expertise with faces of your own race. People tend to overestimate the prevalence of minority groups (Kardosh et al., 2022)—potentially due to similar sampling bias and memory availability mechanisms as discussed in decision making in the previous chapter. A study of computational models of facial expressions did provide convergent evidence that performance was better when tested on races that better matched the training dataset (Sham et al., 2023). However, as we move towards more multiethnic societies, the contact hypothesis—less own-race bias given more exposure to other races— was not supported in a recent study (Wong et al., 2020).

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Beyond own-age and own-race biases, a much more pronounced difference is the better identification of humans than other species, an effect that could be considered an own-species bias (Pascalis & Bachevalier, 1998; Parr et al., 2000; Dufour et al., 2006; Jakobsen et al., 2021). Even if you have difficulty remembering faces, you likely fare much better than you would with pictures of chimpanzees. Computers can be trained to identify individual chimpanzees with near perfect performance (Schofield et al., 2019), demonstrating that identification is possible and visual information is sufficient. Examining other species can, however, provide additional insights into the role of experience. For instance, Sugita (2008) reported data from monkeys that were not exposed to any faces for up to two years after birth, and were then initially only exposed to monkey or human faces for a month. During this face deprivation period, human caregivers wore a mask covering their entire face when interacting with the infant monkey. The monkeys were able to discriminate individuals well for the species they were first exposed to and had difficulty with discriminations of the other species, even when they were monkeys. After the initial exposure month, the monkeys were moved to a cage with other monkeys and also interacted with humans for several hours per day. Even after being exposed to both faces from both species, initial preferences were sustained for at least a year. In fMRI studies, primates have been found to have a homolog of the fusiform face area (Ku et al., 2011). Identification of non-primate individuals can be even more difficult for humans. When conducting studies, researchers add their own identifier, such as a tag around a bird’s leg or a mark of coloured paint to the abdomen of an ant (Fiedler, 2009; Legge et al., 2010). Other instances require machinelearning approaches, such as to identify individuals as part of monitoring the seasonal migration of whales (Bergler et al., 2021; Cheeseman et al., 2023). We would expect, however, that animals can identify and recognise other individuals of their species, i.e., conspecifics, and this is supported by empirical evidence across many species, including sheep (Kendrick et al., 2001), bats (Balcombe, 1990), lobsters (Karavanich & Atema, 1998), and ants (Guerrieri et al., 2009; Bos & d’Ettorre, 2012). Lewis et al. (2023) examined memory for conspecifics in bonobos and chimpanzees using eye tracking in a preferentiallooking task. The time since last seeing groupmates varied between 9 months and 26 years. In both species, individuals looked longer toward former groupmates than strangers, looking biases were stronger for individuals with whom they had more positive histories of social interaction. A carefully conducted study with vampire bats also demonstrated that they not only can recognise each other, but can keep track of previous interactions. Critically, vampire bats can only feed on blood and they need to feed frequently. As such, the bats share food with others, but this is only adaptive if later those others will share food with them. Carter et al. (2020) observed the formation of new social bonds among newly introduced vampire bats and found that bats use low-cost grooming to test the waters before sharing food. The first food donations were preceded by an increasing rate of reciprocal grooming, and

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new food-sharing relationships were rare and formed in a reciprocal pattern, with behaviour observed over a 15-month period. These findings demonstrate memory for individual conspecifics as the bats selectively escalate low-cost grooming to develop higher-cost food-sharing relationships. Returning to research with humans, own-group biases can also be experimentally assigned and still lead to biases in face recognition (Bernstein et al., 2007; Van Bavel et al., 2012; Yan et al., 2017; but see Harrison et al., 2020; Fuller et al., 2021). In such cases, group membership can be through university affiliation or sports team, while being presented as images within an experiment. This result provides evidence that another mechanism, rather than daily contact related perceptual expertise or familiarity can underlie own-group biases. If the effect can be imbued by experimental assignment, there is no difference in the visual properties of the faces. Instead, this finding is suggested to be based on social categorisation (Hugenberg et al., 2007). This interpretation can apply to own-age and own-race biases, though those cases cannot themselves be experimentally adjusted to test this—the evidence for this being a contributing factor is this very result, that assigned groups can also produce comparable biases. Unlike age and race, other aspects of our identity are self-determined. Perhaps the most self-evident of these examples, is when people remember and react to the outcomes of sports events differently based on the team they identify with (Kensinger & Schacter, 2006b; Botzung et al., 2010; Breslin & Safer, 2011; Talarico & Moore, 2012). Similar findings have also been observed in relation to political affiliation (Frenda et al., 2013; Fetterman et al., 2021; Chiew et al., 2022; Raw et al., 2023). People tend to exaggerate their nation’s role to world history, referred to as national narcissism (Zaromb et al., 2018). Here over 6,000 participants across 35 countries estimated their countries’ contribution to world history, with the total adding up to 1156%. The instruction was presented as: “What contribution do you think the country you are living in has made to world history?” The countries with the highest percent contribution ratings were Russia (61%), United Kingdom (55%), and India (54%). Putnam et al. (2018) asked nearly 3,000 participants across all states of the USA about their states’ contribution to American history—responses from all states added up to 907%. The highest contribution responses came from those living in Virginia, Massachusetts, and Delaware— with responses of 41%, 35%, and 33%, respectively. Several additional studies have shown related findings (Taylor et al., 2017; Abel et al., 2019; Topcu & Hirst, 2020; Yamashiro & Roediger, 2021). Nationalistic identity has also been shown in several other procedures (Wang et al., 2009; Dimitriadou et al., 2019). These biases all appear to be related to the availability heuristic. In sum, people have better recognition for that which they have more experience and also have biased views related to their own experiences. Having more relevance to everyday life, a similar bias in memory is present when you ask people about their contributions to a group project or even relationship events; this is an egocentric bias.

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Individual differences Autism is associated with atypical self-related processing (Hobson, 1990, 2010; Frith & Happe, 1999; Lind, 2010). In a series of experiments, Lind et al. (2020) found no effect of autism on the self-reference effect—though some previous studies have suggested smaller effects based on smaller samples. Grisdale et al. (2014), however, report an absence of the ownership effect in individuals with autism. Several studies have found that individuals with autism have impaired memory for faces and social scenes (Williams et al., 2005; Chawarska & Shic, 2009; Weigelt et al., 2012). Many questionnaires have been developed to assess autism. One of the earliest and most popular is the Autism-spectrum Quotient (AQ) (BaronCohen et al., 2001; Woodbury-Smith et al., 2005). This measure assesses autism spectrum symptoms with 50 statements, each on a 4-point Likert scale, across five domains: attention to detail, attention switching, communication, imagination, and social. The questionnaire has since been modified for younger ages and validated in other demographics (Auyeung et al., 2008; Suzuki et al., 2017; Tan & Ashwin, 2023). Shortened assessments have since also been develoepd, such as a 28-item version (Hoekstra et al., 2011) and a 10-item version (Allison et al., 2012; Lundin et al., 2018). The 10-item version retains two questions for each of the five domains. Five questions, one per domain, are: “I often notice small sounds when others do not” (attention to detail). “I find it easy to do more than one thing at once” (attention switching). “I find it easy to ‘read between the lines’ when someone is talking to me” (communication). “I like to collect information about categories of things (e.g. types of car, types of bird, types of train, types of plant etc)” (imagination). “I find it difficult to work out people’s intentions” (social). Social anxiety is a prevalent individual difference that can significantly impact memory. Individuals with high levels of social anxiety often experience heightened attention for socially threatening information (Hirsch & Clark, 2004; Bar-Haim et al., 2007; Staugaard, 2010; Folz et al., 2023). This can be measured as a heightened sensitivity to perceived social threats or increased recall for negative social experiences (Coles & Heimberg, 2002; Hirsch & Clark, 2004; Morrison & Heimberg, 2013). This bias in memory recall can contribute to the maintenance and exacerbation of social anxiety, creating a self-perpetuating cycle. During encoding, individuals with social anxiety may pay more attention to threatening social cues, leading to enhanced memory for these cues. During retrieval, these individuals may be more likely to recall threatening or negative social information, even when not relevant to the current situation. This bias in memory can reinforce their anxious feelings and behaviours, further entrenching their anxiety (Hackmann et al., 2000; Hertel et al., 2008; Staugaard, 2010; Çili & Stopa, 2021).

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End of chapter wrap-up Summary Our experiences, identities, and social contexts profoundly shape the way we remember. To understand these factors, we often need to step outside the experimental session and delve into autobiographical interviews or diaries. These methods allow us to examine how our personal histories and experiences mold our memories and identities. Not all events from our lives are equally memorable. Apart from recent experiences, people tend to recall events from their adolescence and early adulthood more vividly, a phenomenon known as the reminiscence bump. Our memories not only reflect our past but also help define our sense of self. Music preferences serve as a prime example of the reminiscence bump, defining who we are and demonstrating the therapeutic potential of music on self and identity. We also discussed the self-reference effect, which highlights our tendency to better remember information that we can relate to ourselves. Finally, we explored the egocentric bias, where people tend to overestimate their contributions to group projects or relationship events. These topics underscore the intricate interplay between our identities, our experiences, and our memories.

Reminder cues

Quick quiz 1. At a recent family dinner, Fred reminisces about reading a night-time story to his daughter every night when she was a child. What type of autobiographical memory would this be classified as? (a) Specific episodes (b) Extended episodes (c) Personal semantics (d) General semantics

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2. One interpretation for the reminiscence bump is the life script narrative, which suggests that autobiographical memories are centred around: (a) Culturally defined goals (b) Early childhood experiences (c) Negative life events (d) Personal accomplishments and failures 3. In the context of reminiscence therapy, which of the following is a primary benefit of using music to cue memories for patients with dementia? (a) Music can help patients regain their lost cognitive abilities. (b) Music can improve patients’ communication skills and language abilities. (c) Music can elicit positive emotions and improve social well-being. (d) Music can reverse the progression of dementia. 4. Which of the following is NOT a common method used in the literature to study the self-reference effect? (a) Trait adjectives (b) Personal information (c) Ownership (d) Diaries 5. In a classroom scenario, students were divided into groups for a project. After the project was completed, the students were asked to report their contribution. However, the sum of all students’ estimated contributions exceeded 100%. Which of the following strategies could be employed to attenuate the effect of an egocentric bias and the resulting overestimation? (a) Implement a peer-assessment component, where each student evaluates the contributions of their group mates. (b) Encourage students to focus on their individual challenges and achievements related to the group project. (c) Increase the overall difficulty level of the group project to stimulate more individual effort from all students. (d) Foster intra-group competition, providing bonus marks for being the student that contributed the most.

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Thought questions ▶ Think of some of your favourite books, songs, and movies. How does your first exposure to them align with the reminiscence bump? Ask some of your friends and colleagues about their favourites, do their preferences align with your relative age differences? ▶ Hundreds of studies have been conducted on the self-reference effect. What are some factors that lead to the effect being larger or smaller in magnitude? ▶ How might you design an ‘intervention’ task that could attenuate the magnitude of an egocentric bias? How would you assess its efficacy?

Further reading ▶ Northoff, G., & Hayes, D. J. (2011). Is our self nothing but reward? Biological Psychiatry, 69(11), 1019–1025. doi: 10.1016/j.biopsych.2010.12.014 ▶ Bradbury, T. N., & Fincham, F. D. (1990). Attributions in marriage: Review and critique. Psychological Bulletin, 107 (1), 3–33. doi: 10.1037/0033-2909.107.1.3 ▶ Zaromb, F. M., Liu, J. H., Páez, D., Hanke, K., Putnam, A. L., Roediger, H. L. (2018). We made history: Citizens of 35 countries overestimate their nation’s role in world history. Journal of Applied Research in Memory and Cognition, 7 (4), 521–528. doi: 10.1016/j.jarmac.2018.05.006

Chapter 9 Moving to remember

Knowing is not enough; we must apply. Willing is not enough; we must do. — Johann Wolfgang von Goethe (1906)

It is well established that emotion, reward, and self-relevance influence memory—these are well-trodden paths in the landscape of motivational influences on memory. Yet, there lies another significant domain that is less intuitively linked to memory, yet holds substantial importance— motor processing. Some argue that the entire purpose of the human brain is to produce movement, allowing us to interact with the world (Wolpert et al., 2001). This view is self-described as a ‘motor chauvinist’ perspective, prioritising the role of motor functions in cognitive processes. It has some convergence with ideas of embodied cognition, emphasising the fundamental connection between movement and thought. As such, even though the literature on motor effects on memory is a much less developed topic than the motivation-related approaches described in the previous chapters, it is worth discussing this literature as it stands, and in relation to these motivation-related topics. More broadly, this domain of memory research is closely related to theories of embodied cognition and ecological psychology, reflecting a shared focus on the connection between body, mind, and environment (Gibson, 1977, 1979; Rosenbaum, 1988, 2005; Glenberg, 1997; Klein, 2015). Views such as grounded cognition take this further, proposing that perception and action experiences underpin cognitive processing, rather than more abstract and amodal semantic representations (Glenberg & Kaschak, 2002; Gallese & Lakoff, 2005; Barsalou, 2008, 2020; Mizelle & Wheaton, 2010b). From this perspective, cognition is situated in the interaction between individual and environment, supported by automatic simulations, not something that only happens in the mind—dissociated from body states and environmental context.

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As we venture into this domain, we will encounter various facets of motor processing and their impact on memory, including the effect of physical actions, the differential cognitive processing invoked by manipulable objects, and the influence of real objects compared to their pictorial or verbal representations. Though the exploration of these topics may initially seem like charting unexplored territory, the interplay between motor processes and other aspects of cognition provide insights into the rich semantic knowledge and automatic motor simulations that underpin our day-to-day activities.

9.1 Enactment The levels-of-processing approach (Section 3.2, p. 76) suggests that information is remembered better if it is processed relatively deeper and more elaboratively. Some studies have used between-group designs to compare memory for word lists with verbal task instructions, experimenter performed tasks, and participant performed tasks. One of the first of these studies was Cohen (1981). Most task instructions involved interacting with objects, such as ‘close the purse,’ ‘bounce the ball,‘ and ‘sharpen the pencil.’ Other task instructions did not involve any object, such as ‘cross your fingers,’ ‘stick your tongue out,’ and ‘salute.’ In a final free recall test, participants that performed the actions themselves recalled 35.6% of the instructions, 35.2% recall when the experimenter performed the action, 24.5% for just the instruction, and 21.1% for the words. As such, enactment led to better memory. Denis et al. (1991) extended this by comparing overt actions with imagined actions. As you may expect, there was better memory for enacted instructions than imagined ones. Enactment effects have been explored extensively in comprehensive reviews (Kormi-nouri, 1995; Engelkamp, 1998; Zimmer & Cohen, 2001). Demonstrations of enactment benefits were further demonstrated across subsequent studies (Cohen, 1983; Senkfor et al., 2002; van Dam et al., 2013; Roze et al., 2018; Daprati et al., 2019; Makri & Jarrold, 2021). MIN RE

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Nilsson et al. (2000) examined brain activity during memory retrieval, comparing encoding conditions of verbal phrases, imagined actions, and enacted actions. It was predicted that motor-related brain areas would be selectively involved in retrieval when encoding involved overt motor actions. As expected, recall was best after enacted encoding. Activation in right motor cortex was found to be highest during retrieval following enacted

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encoding, intermediate following imagined enactment, and lowest following verbal encoding. These findings demonstrated that initial encoding experience influences subsequent retrieval-related brain activity. Enactment could be considered the ‘deepest’ level of processing. Whereas superficial processing could relate to a word’s font or length, and engaging in semantic processing is deeper, interpreting a phrase and acting it out is even more extreme. Meaning must be processed and the action acted out, bridging into the territory of embodied cognition. The processing of actions is not just in the mind and also engages the body as part of the encoding processing. This journey into embodied cognition highlights a unique aspect of memory processing. It is worth highlighting again that memorisation here occurs incidentally through enactment statements rather than the intention to learn.

Dual coding and beyond Words that correspond to physical objects, otherwise referred to as concrete or high-imageability words—e.g., CLOCK and PENCIL, are remembered better than those that correspond to abstract or low-imageability words—e.g., JUSTICE and THEORY (Gorman, 1961; Paivio, 1965, 1968; Paivio & Csapo, 1969; Lockhart, 1969). Paivio (1971, 1986) suggested that information can be mentally represented using two systems or ‘codes,’ one for verbal mental representations and one for pictorial ones—this is dual-coding theory. As such, this difference in memory is because concrete words can be mentally represented as both pictures and words, whereas abstract words can only be mentally represented as words. Relatedly, pictures that clearly represent objects are better remembered than abstract picture stimuli (Ranken, 1963; Del Castillo & Gumenik, 1972). Colours of objects are better remembered when they are typical (McCarthy, 1990), but objects are better recognised when presented in atypical colours (Westerbeek et al., 2014)—an effect bearing a resemblance to the word-frequency paradox. Providing support for dual-coding theory, Binder et al. (2005) compared brain activity for processing of concrete and abstract words. Several regions were more active for the concrete words, including the angular gyrus, posterior cingulate gyrus, and precuneus. Similar conclusions were determined in a meta-analysis of 19 fMRI studies (Wang et al., 2010). Dual-coding theory is also well-aligned with the adage, “A picture is worth a thousand words;” though, this phrase itself was not based on scientific research and instead is a marketing slogan from the 1920s (Mieder, 1990). Dual-coding theory has become a staple in the literature (Paivio, 1991, 2007; Bi, 2021) as well as used to improve pedagogical practices in other disciplines (Sadoski, 2005; Hartland et al., 2008; Mayer, 2010; Ortegren et al., 2015; Aleixo & Sumner, 2017). Additionally, Engelkamp and Zimmer (1984) suggested that in addition to verbal and pictorial codes, some information may further involve a motor code, such as being presented with the stimuli TURNING THE HANDLE or RATTLE THE KEYS. For each of these,

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a pictorial representation could easily be consciously conjured, as can the motor movement related to the phrase. From this view, the enactment effect— and even imagined actions—may be remembered better than just reading a sentence due to the additional involvement of a motor code. This possibility has been further discussed in later theories of motor action effects on memory (Engelkamp & Zimmer, 1989; Madan & Singhal, 2012b, 2012c; Weinstein et al., 2018).

Learning pyramid In the education literature, a frequently used diagram is the ‘learning pyramid,’ indicating specific learning retention rates in increasing order for: lecture, reading, audio-visual, demonstration, discussion, practice, and teaching others, as shown in Figure 9.1A. Unlike learning styles, which is based on individual differences in learning preferences (see Section 11.3, p. 344), the learning pyramid is similar to levels of processing (Section 3.2, p. 76) and the broader notion of elaboration. However, like learning styles, the pyramid is considered a myth because it grossly oversimplifies learning and ascribes retention rates with more certainty than can sensibly be guaranteed. The learning pyramid was initially proposed as Dale’s (1946, 1969) ‘cone of experience’ and was intended for a summary of an approach to teaching; and was valid in this function. However, the addition of retention percentages was not based on research and distorted the message, and unfortunately this was the version that was shared widely. Though the erroneous aspects of this idea have been proposed over a hundred years ago (Haskell, 1913; Treichler, 1967), it remains in the literature (Subramony et al., 2014; Letrud & Hernes, 2016; Masters, 2020). Bloom’s taxonomy, further discussed in Section 11.4 (p. 345), is supported by evidence and is shown in Figure 9.1B. Another framework takes a convergent approach: “Learn, See, Practice, Prove, Do, Maintain” (Sawyer et al., 2015). As an example where ‘doing’ can be beneficial for learning, Quinn (2022) provides a craft guide for visualising cranial nerves in the brainstem using pipecleaners. The paper includes a quote from a student: It gave me an appreciation of the origins (midbrain, pons etc.) of the cranial nerves which I hadn’t appreciated before. This has been really helpful in neuro especially with regards to lesions (whether or not they effect sensation of the face). Having something physical to take away is a good reminder! (p. 280)

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FIGURE 9.1: Two pyramids common in the learning literature. (A) The learning pyramid. Each level corresponds to a deeper level of processing and each number within the pyramid conveys the retention rate associated with the learning method. However, this is considered a myth (see main text). (B) Bloom’s taxonomy. Each level corresponds to higher-order cognitive processing. This is discussed in further detail in Section 11.4 (p. 345).

9.2 Semantic properties of motoric stimuli Objects have many semantic properties associated with them. Each object has a name and belongs to a specific category. For instance, a spoon is a kitchen utensil, while a tennis racket is associated with recreational activities. Other objects, such as staplers, hammers, and guitars, fall into distinct categories of their own. Objects are also linked with specific locations based on their typical usage. Some, like a spoon or a stapler, are commonly found in the kitchen or office, respectively. Others, perhaps a hammer or a wrench, are more likely to be located in a garage or in a toolbox. The physical structure of objects also varies widely. Many tools possess an elongated form, facilitating their use in tasks requiring reach or leverage. Conversely, other objects are more compact, designed for tasks that demand precision or control—such as key or analog watch, where small and precise movements are necessary. Beyond these characteristics, objects are defined by their functional uses and the specific ways they are manipulated. Each object affords certain actions based on its design and purpose, dictating the type of grasp used to handle it. For example, a spoon is held in a precision grip, with the handle resting against the palm and the fingers and thumb providing control for scooping or stirring. A guitar, on the other hand, requires a more complex manipulation, with one hand pressing the strings against the fretboard to form chords, while the other hand strums or picks the strings. These examples illustrate how the design and function of an object influence the way it is grasped and manipulated. Studies have shown that motor regions are activated when processing words and pictures that refer to objects that can be more easily functionally interacted with (Kellenbach et al., 2003; Just et al., 2010; Rueschemeyer et al., 2010; Madan et al., 2016). As discussed, dual-coding theory has been expanded

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to have a third: motor code (Engelkamp & Zimmer, 1984). A number of studies have collected ratings of motor-related properties for word stimuli (Putnoky, 1979; Amsel et al., 2012; Heard et al., 2019). This could be thought of as an automatic motor simulation associated with semantic processing of the stimuli’s meaning (Aylwin, 1990; Campanella & Shallice, 2011; Madan & Singhal, 2012b; Weinstein et al., 2018). An illustration of the semantic representations associated with each code is shown in Figure 9.2. VERBAL SPOON [=word]

SNOOP [=anagram]

MOON, TUNE, PRUNE [=rhyme]

VISUAL

MOTOR

SPOON [=category prototype]

SPOON [=subject of attribution]

shallow bowl [=shape] eating utensil [=category]

FORK CHOPSTICKS

metallic [=attribute]

kitchen table [=location]

SPOON [=instrument]

stir coffee [=functional intention]

rotate in coffee mug [=manipulation action]

FIGURE 9.2: Words used to describe objects can be thought of as having many semantic properties, including verbal, visual, and motor features. Research has also explored the semantic features of man-made objects, particularly distinguishing between tools and non-tools. This distinction is significant as it influences the way we interact with these objects and how we process information about them. Several studies have developed concept property norms, where participants were asked to describe the features associated with specified concrete noun concepts (Cree & McRae, 2003; McRae et al., 2005; Devereux et al., 2014; Martin et al., 2018). Concept property norms are based on semantic knowledge for the physical, functional, and encyclopedic features of an object. For example, five features associated with a spoon are: (1) is found in kitchens (encyclopedic), (2) is used for eating (function), (3) holds liquid (function), (4) has a handle (physical), and (5) is made of plastic or metal (physical). Tools are a special subset of objects—ones that we interact with to perform specific tasks. They are extensions of our physical capabilities, allowing us to manipulate our environment in ways that would be difficult or impossible with our bodies alone. As such, our cognitive systems have developed to recognise and understand tools in a unique way, distinct from other objects. Nontool objects, while also man-made, do not serve the same functional purpose as tools. They may be decorative, symbolic, or serve other non-physical functions. Consequently, our cognitive processing of these objects differs from that of tools. We may focus more on aesthetic qualities, symbolic meanings, or emotional significance. This distinction in processing even generalises to images and words that represent these real-world objects.

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Another approach to characterising the motoric properties of words has been body-object interaction (BOI) ratings. In a typical BOI rating task, participants are asked to rate words or images of objects on a scale based on how easily they can interact with the object using their body (Siakaluk et al., 2008; Pexman et al., 2019; Heard et al., 2019). An object like SPOON would have a high BOI rating because it is easy to interact with (you can hold it, stir with it, scoop food, bring it to your mouth, etc.). An object like MOUNTAIN would have a low BOI rating because it is not easily interacted with. MIN RE

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Guérard et al. (2015a) delved into the relationship between manipulability ratings of object photos. They examined four distinct aspects of an object’s motor attributes: graspability, moveability, ease of pantomime, and the number of possible actions with the object. These aspects, while inter-related, each contributed uniquely to the speed of object recognition, suggesting that different types of motor information are integrated into our cognitive processing of objects. Heard et al. (2019) generalised this from pictures to words, exploring the relationships between BOI ratings and several more specific motor dimensions for a database of words. Here graspability, ease of pantomime, and number of actions together explained more variance in BOI ratings than any one alone. Moreover, these motor dimensions together better explained performance in semantic decision tasks than BOI alone. This indicates that multiple sensorimotor attributes, especially graspability, ease of pantomime, and number of actions, influence lexical-semantic processing. While the motoric properties of words and objects play a significant role in our cognitive processing, another semantic dimension that cannot be overlooked is microvalence (Lebrecht et al., 2012). Microvalences are subtle positive or negative associations that we have with objects, which exist along the same overall continuum as valence. Even objects that seem neutral can have a slight microvalence. These associations can arise from past experiences with the object, or from innate reactions to perceptual features like shape and colour. For instance, curvy objects may be intrinsically preferred over sharp ones. An illustration of microvalence is shown in Figure 9.3. Microvalences play a crucial role in our interactions with objects. They help us orient towards preferable objects and make quick unconscious choices between objects, such as deciding which mug to grab from the cabinet. Importantly, these microvalences are automatic and intrinsic to object perception, not deliberate judgements applied after recognising an object. Note that while valence is

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related to aesthetics, it is distinct from it. Aesthetics is a more multifaceted concept, and preference formation incorporates goals and context.

FIGURE 9.3: Illustration of the notion of microvalence. Valence ranges from positive and negative. Microvalence is more subtle variations in preference for everyday objects, typically considered between different items within a narrow category, e.g, teapot. Pictures adapted from Lebrecht et al. (2012). The concept of microvalence underscores the richness and complexity of object representations. Unlike words, which have a one-to-one mapping with their referents, pictures can capture a multitude of properties and nuances. Consider that for the word MOUNTAIN or BALL—an infinite number of pictures could exist that can be described with these single word labels (Madan, 2021a). Each picture would capture a unique combination of properties, such as size, shape, context, lighting, and viewing angle—all of which contribute to our understanding and memory of the object. Even something as simple as SPOON can be represented by numerous objects, as illustrated in Figure 9.4. They differ in the material they are made from and vary in shape, but all are adequately described simply as ‘spoon.’

FIGURE 9.4: Multiple objects map to a single word, here ten distinct spoons.

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Language evoked motor simulations Words representing objects are not semantic dimensions that otherwise represent physical objects that can be interacted with, there are automatic motor simulations that also occur. This view is supported by many studies linking language comprehension with the motor system (Pulvermüller, 2005; Fischer & Zwaan, 2008). Gentilucci and Gangitano (1998) explored whether automatic word reading could exert an influence on the motor control processes involved in reaching and grasping movements. Participants were asked to to reach out and grasp a block, which had either the word “long” or “short” printed on it, with the block’s position on the table and size varying across trials. Interestingly, kinematics of the reaching component was influenced by the words printed on the block. Peak acceleration, velocity, and deceleration were all higher when the word “long” was printed on the block, suggesting that participants were automatically activating motor programs for reaching farther distances when they saw the word “long.” This effect was more pronounced for smaller blocks, which might be due to the need for more careful visual analysis when grasping smaller blocks, or perhaps the words were more visible and salient when near the grasping points for smaller blocks. The findings demonstrate that semantic information can bias automatic movements. Relatedly, Glover et al. (2004) presented words corresponding to large or small objects—e.g., APPLE and GRAPE, respectively—while participants grasped a block. Participants were found to approach the block with a relatively larger or smaller grip aperture based on the word presented, suggesting that processing of the word interfered with overt movement actions. Shebani and Pulvermüller (2013) demonstrated that unrelated arm or leg motor movements can impair language processing associated with the same limb (also see Lindenberger et al., 2000). Other studies have shown that processing action-related sentences evokes activity in motor-related brain regions (Hauk et al., 2004; Tettamanti et al., 2005; van Elk et al., 2010) and muscles (Buccino et al., 2005)—measured through motor-evoked potentials. Motor-evoked potentials (MEPs) are a measure of electrical activity recorded from muscles following transcranial stimulation of the motor cortex in the brain. MEPs are typically elicited using a technique called transcranial magnetic stimulation (TMS). In this procedure, a magnetic field is generated by a coil placed over the scalp, which induces an electrical current in the underlying brain tissue. When the motor cortex is stimulated, it sends a signal down the spinal cord and out to the muscles, causing them to contract. This muscle response—the MEP—is then recorded using electromyography (EMG). One measure is the amplitude of pulse needed to evoke the MEP in the muscle. In the case of Buccino et al. (2005) the TMS pulse amplitude to evoke an MEP was lower when the participant was processing an action sentence related to the associated body part (foot). This demonstrates that the processing of action-related sentences modulated the excitability of the

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motor cortex, convergent results were also reported by Pulvermüller et al. (2005). Additionally, response times were slower, a finding that aligns with the results of Shebani and Pulvermüller (2013). These studies provide evidence for the involvement of the motor system when processing action-related language. As a demonstration of motor-related semantic influences on episodic memory, Madan and Singhal (2012a) presented participants with nouns representing objects that are easy or difficult to interact with functionally. Participants were assigned to one of three groups. The first group of participants was shown 80 words and asked to judge if the word had an odd or even number of letters—the word length group. There were 40 words that represented objects that were easy to functionally interact with, such as SPOON and CAMERA. The other 40 words were still objects, but could only be interacted with volumetrically—i.e., picked up or thrown—such as SIGN and TABLE. Words were selected from prior studies that had examined processing of manipulable objects (Buxbaum & Saffran, 2002; Kellenbach et al., 2003; Just et al., 2010; Rueschemeyer et al., 2010). A second group was asked to judge if the objects could be interacted with functionally—the functionality group. A third and final group was asked to respond yes or no if they have seen the object within the last three days—the personal experience group. The three groups were intended to vary in levels of processing (refer back to Section 3.2, p. 76). The first group did not require the meaning of the word to be processed, whereas the third group relied on autobiographical memory and elaborative search processes. Additionally, the intermediate group (functionality) required deliberate attention to the functional properties of the represented objects, unlike the other two groups that only incidentally involved functional processes as part of the interpretation of the semantic meaning of the words (also see Guérard et al., 2015b). After each of these respective judgement tasks, participants were asked to recall all of the words they could. The levels-of-processing effect was replicated, and people who processed the meaning of the words more deeply recalled more words. However, there was also an interaction where the groups that incidentally processed functional characteristics of the words recalled more of the high-functionality words. In contrast, the participants in the functionality group recalled more of the low-functionality words, but also took longer to make the judgements in the preceding task. This suggests that the low-functionality words were processed more effortfully as participants attempted the deliberate motor simulation. A follow-up EEG study involving picture stimuli and the functionality and personal experience groups provided convergent evidence of hand-related motor simulations (Madan et al., 2016). In a subsequent study using the same word lists, Madan (2014b) examined association-memory in relation to functionality. Results indicate that highfunctionality words were more difficult to associate with each other. A following recall test, however, demonstrated that high-functionality words were more easily retrieved from memory. These findings suggest that the automatic motor simulations involved in processing of the semantic meaning

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of words can enhance item-memory, but impair the intentional binding of the words into a singular representation Studies with enactive verbs, rather than object nouns, have similarly shown better memory for items (Montefinese et al., 2013), but impaired associative memory (Lippman, 1974). For example, high enactive verbs include MOW and WADE; low enactive verbs include BEGIN and OBEY. Given that these studies show advantages related to automatic motor processing, it would be reasonable to assume that unrelated motor actions would interfere—as in the online processing effects discussed earlier (Gentilucci & Gangitano, 1998; Glover et al., 2004; Shebani & Pulvermüller, 2013). Evidence is sparse, but current results suggest that motor interference does not impair effects of manipulability on memory (Pecher et al., 2021).

9.3 Neurobiology When viewing motor-related stimuli—words or pictures—some brain regions are activated to a greater degree than when viewing man-made objects that have less motoric properties (Chao & Martin, 2000; Rueschemeyer et al., 2010; Just et al., 2010). Even more specifically, a set of ventral brain regions are reliably more activated for tool-related objects than other categories, including non-manipulable objects and animals.

Dorsal and ventral pathways As we navigate through the world, our interactions with objects are not solely dependent on our immediate perception. Memory plays a pivotal role in object processing, particularly in understanding an object’s properties. This information is not limited to the object’s appearance, but extends to its function and how to interact with it. For instance, once we learn how to use a pair of scissors, we do not need to relearn this each time we encounter scissors again. Our memory provides us with the necessary information about the object’s function (cutting) and how to manipulate it (the specific hand shape and motion required). The interplay between memory and object processing is a fascinating interaction of cognitive processes, underpinned by the dorsal and ventral streams of object processing (Mishkin & Appenzeller, 1987; Goodale & Milner, 1992). To illustrate, let’s continue with our example of a pair of scissors. When you first encounter a pair of scissors, your ventral stream—the ‘what’ pathway—processes the visual information, recognising the object as a pair of scissors. This recognition is not just about identifying the object, but also about understanding its function. The ventral stream helps you remember that scissors are used for cutting. This information about the object’s function is stored in your memory, ready to be retrieved the next time you encounter a pair of scissors. Simultaneously, your dorsal stream—the ‘how’ pathway—

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guides your hand movements, helping you understand how to hold and manipulate the scissors correctly. This might involve adjusting your grip, positioning your fingers in the loops of the scissors, and learning the opening and closing motion required to make a cut. This information about how to physically interact with the scissors is also stored in your memory. MIN RE

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Patients with brain damage, e.g., due to stroke, can develop apraxia— impaired tool use. One assessment of apraxia, the Florida Praxis Imagery Questionnaire (FPIQ), involves asking participants to make responses related to the function and manipulation of tools (Ochipa et al., 1997)—this questionnaire has also been used in some studies with healthy adults as a test of object-related imagery (Madan & Singhal, 2013; Madan, Ng, & Singhal, 2018; Donoff et al., 2018). Some studies have shown that apraxia also relates to impairments in manipulation, but not function, knowledge (Buxbaum et al., 2000; Buxbaum & Saffran, 2002; Negri et al., 2007; Sunderland et al., 2013). These tests used a similar logic as described earlier: given an instruction, e.g., “manipulation,” they were presented with three object images and had to choose the odd one out. Devereux et al. (2018) developed and explored a computational model of the ventral stream that integrates visual and semantic object processing. The model used a deep convolutional neural network for visual processing along with an attractor network for semantic processing—designed to investigate the mapping of visual information onto semantic representations (also see Cree et al., 2006). The model demonstrates a general-to-specific account of semantic processing, with initial coarse-grained activation followed by later fine-grained activation. Using representational similarity analysis (RSA), the model layers are compared to fMRI data from an object naming study. The comparison reveals that early visual layers of the model correspond to early visual cortex; later semantic model layers fit brain activity from the perirhinal cortex. This model, therefore, captures the posterior-to-anterior transformation of visual to semantic object representations in the ventral stream. The model provides a computational account of the emergence of conceptual representations from visual inputs grounded in neural network implementations of vision and semantics (also see Kietzmann et al., 2019). Shifting to the dorsal stream, manipulation knowledge—sensorimotor representations of how to manipulate tools—is particularly associated with activity in the left inferior parietal lobe (Chao & Martin, 2000; Creem-Regehr & Lee, 2005; Johnson-Frey, 2004; Lewis, 2006). Of particular importance

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is the intraparietal sulcus (IPS), which is involved in the retrieval of fine grasping movements—e.g., involving the fingers and hand—associated with tool use (Kellenbach et al., 2003; Gallivan et al., 2009, 2013; Lesourd et al., 2023). Different tools require different grasps and movements. A spoon might require a palmar grasp, where the handle rests against the palm, and the fingers curl around it. This allows for both scooping and stirring motions, with subtle wrist movements controlling the angle and depth of the utensil. Scissors necessitate a more precise coordination of the thumb and index finger, allowing for precise cutting actions. Playing a guitar demands complex finger placement and movement patterns. Some studies have proposed that the IPS is also involved in understanding the functional properties and potential uses of tools, contributing to our cognitive flexibility and problem-solving abilities (Cisek & Kalaska, 2010; Menz et al., 2010; Martin-Ordas et al., 2014). The role of memory in object processing, while crucial, is not always straightforward. Consider, for instance, the case of a butter knife and a screwdriver. At a glance, these objects may look somewhat similar—they both have a handle and a long, thin metal part. However, their functions are quite different. A butter knife is used for spreading, while a screwdriver is used for turning screws. On the other hand, consider scissors and tongs. These objects have a similar function—they both involve a grasping or clamping action. However, the manipulative actions required to use them are different. Scissors require a specific finger placement and a two-way motion to open and close the blades, while tongs can be operated with a simple squeeze of the hand, typically without specific finger placement. Garcea and Mahon (2012) asked participants to make each type of judgement in blocks of trials. Participants were shown triads of objects—either as pictures or words; one object was presented centrally and participants had to judge which of the lower two objects (left or right) were most similar in either manipulation or function. For manipulation judgements, pictures were responded to faster than words; for function judgements, words were responded to faster than pictures. This interaction suggests function knowledge is more closely tied to lexical semantics while manipulation knowledge is more visual. These findings provides evidence against claims that simulating manipulation is necessary for retrieving function knowledge. Instead, results indicate that function and manipulation knowledge are represented separately. Advances in neuroscience have shed light on the role of chromatic properties in the differential processing of visual information by the dorsal and ventral streams. This sensitivity is mediated by three types of cells in the retina: the magnocellular, parvocellular, and koniocellular pathways. Each of these pathways is differentially sensitive to certain chromatic properties. For instance, the magnocellular pathway is more responsive to changes in luminance, while the parvocellular pathway is more sensitive to colour. Interestingly, these retinal pathways have been linked to the streams of object processing (Meissirel et al., 1997; Tapia & Breitmeyer, 2011). The magnocellular pathway, with its sensitivity to luminance and movement, is

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thought to feed more into the dorsal stream. This mapping is supported by the dorsal stream’s role in spatial awareness and movement (Kveraga et al., 2007; Kristensen et al., 2016; Adams et al., 2019; Edwards et al., 2021). The parvocellular pathway, with its sensitivity to red-green colour contrast, are thought to contribute more to the ventral stream, aligning with the ventral stream’s role in object recognition (Almeida et al., 2013; Kristensen et al., 2016; Adams et al., 2019; Edwards et al., 2021). The koniocellular pathway, sensitive to blue chromatic colour, has been found to project to the dorsal stream—without passing through early visual cortex (Almeida et al., 2013). Recent studies have capitalised on these differential sensitivities to investigate the functional roles of the dorsal and ventral streams. By manipulating the chromatic properties of pictures, researchers can preferentially engage one stream over the other. For instance, images with high luminance contrast and little colour may engage the dorsal stream more (Dubbelde & Shomstein, 2022), while coloured images with less luminance contrast may engage the ventral stream more (Kveraga et al., 2007; Almeida et al., 2013; Dubbelde & Shomstein, 2022). Based on these insights, it is possible to present variations of stimuli that preferentially activate function (ventral/what) or manipulation (dorsal/how) knowledge.

Substitute tool-use As we interact with the world around us, we often find ourselves in situations where the ideal or typical object for a task is not available. In such scenarios, our ability to use substitute objects based on what’s available becomes crucial. This requires a degree of flexibility and creativity in our object processing, allowing us to adapt to the situation at hand. Consider, for instance, the act of stirring coffee. The typical object for this task would be a spoon. But what if a spoon is not readily available? You might find yourself looking around for a substitute. Among a string, a key, a dumbbell, and a glass, a key would be the most suitable substitute. While it’s not the typical object for the task, its shape and rigidity make it capable of stirring coffee—a functional substitute. Some studies have investigated brain activity related to the processing of functionally congruent or incongruent pairs of objects (Mizelle & Wheaton, 2010a; Mizelle et al., 2013). The results showed that there were significant differences in neural activation between matched and mismatched tool-object pairs. These differences were limited to posterior brain structures, suggesting a limited prefrontal involvement in this process. This type of typical and substitute tool-use was further studied in Tobia and Madan (2017). Using fMRI, we examined brain activity associated with selecting the best tool available to accomplish a given goal. On some trials, the prototypical tool was one of the provided options; on other trials, only a functionally substitutable object could be chosen. As expected, participants were more accurate and faster in the prototypical trials, suggesting that these were easier and required less deliberation. Of interest, were the brain regions involved with each type

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of trial. Prototypical trials activated areas associated with semantic memory, such as bilateral anterior middle temporal gyrus—regions of the ventral pathway. Substitute trials, however, activated regions involved in praxis and action knowledge—including left intraparietal sulcus, supplementary motor area, and precuneus—regions of the dorsal pathway. Thus, the findings demonstrated a dissociation between ventral semantic regions for prototypical tool selection and dorsal praxic regions for substitute object selection. The fMRI study provides a neuroscientific perspective on how we process objects based on their typical or substitute uses. To further illustrate this concept, let’s consider an example from another study. A baseball bat is typically used to hit a ball in a game of baseball. This is the prototypical use of the object. However, a baseball bat can also be used as a walking support if a cane is not available (Madan, Ng, & Singhal, 2018). This is an example of a substitute use of the object, which is less typical but still within the realm of possibility. A person could also bite into a baseball bat, but this would be considered a bizarre action because it falls outside the typical uses of the object. This example illustrates how our understanding and use of objects are not fixed, but can adapt based on the context and our needs—within limits. This flexibility in object use is a key aspect of our cognitive processing and is reflected in the different brain activations.

FIGURE 9.5: Typical and atypical object interactions. Adapted from Shir et al. (2021). Objects themselves can also be atypical or unexpected. A cake floating in the place of a balloon would be atypical—as shown in Figure 9.5. For studying such expectations, Shir et al. (2021) developed a database of objects being used in typical and atypical actions. In a classic study by Wheatley (1973)— which may be apocryphal—the concept of object typicality was explored in the

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context of food. Here people were served food in a lighting that made it difficult to see the colour of the food. After partaking in most of the meal, normal lighting was used and it was now visible that the food was oddly coloured— blue steak, red peas, and green fries. Almost all participants immediately felt ill. While it is unclear if this study actually occurred (see Spence, 2021), the notion was that we have certain expectations about what food should look like, and when those expectations are suddenly violated, this can result in automatic responses. While less drastic, other studies have also shown that colour cues influence expectations and perception (Melcher & Schooler, 1996; Herz & von Clef, 2001; Morrot et al., 2001; Zampini et al., 2008; Spence, 2015).

9.4 The treachery What do you see in Figure 9.6?

FIGURE 9.6: The Treachery of Images by René Magritte (c. 1929). The painting depicts an image of a pipe, above the text “Ceci n’est pas une pipe.” This text is French for “This is not a pipe.” While the picture is of a pipe, it is not actually a pipe—it is not a real object, only a picture. Magritte (1929) thoughtfully explored this idea further (also see Bowman, 1985). Some studies of memory have used physical objects (Mishkin & Appenzeller, 1987), but that is not the norm. This nuance has been largely neglected in experimental psychology, where we so often use pictures of objects, faces, and scenes, but refer to the results as being related to object,

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face, or scene processing, without continuing to acknowledge that they were merely pictures. The key question then is, does it matter? While most consider that presenting pictures of objects is sufficiently comparable to real 3D objects in a psychology or neuroimaging study, there is evidence that this is not the case. Snow et al. (2014) conducted experiments comparing memory for common household objects displayed either as real 3D objects or 2D pictures. In Experiment 1, participants studied objects presented as real objects, colour photos, or line drawings. In a surprise free-recall test, participants recalled more real objects than photos or line drawings. Recognition was also better for real objects vs. the 2D conditions. In Experiment 2, the researchers controlled for viewing angle by having real objects and colour photos both presented vertically. The memory advantage for real objects was replicated—participants recalled and recognised more real objects compared to photos. Across both experiments, the recall advantage for real objects generalised across categories of objects. This study provided novel evidence that real-world objects are more memorable than 2D representations of the same items. Several factors may underlie this difference, including depth cues, action affordances, and unambiguous size (Gibson, 1971; Freud et al., 2018; Korisky & Mudrik, 2021; Fairchild et al., 2021). Stimuli formats can be thought of as a continuum, trading off between experimental control to ecological validity—as shown in Figure 9.7. Words can be relatively readily characterised on different stimuli properties. Pictures can be characterised, but are more difficult. Consider, for instance, the idea of control stimuli. For a word you might generate nonwords, which are still sequences of letters. Scrambled pictures, however, may be disjointed and differ in spatial frequency—among many other properties—if they are merely scrambled from an object on a white background. Perhaps it would be more suitable to keep coherence between sections of the picture that have object vs. background. If the object is generally elongated, e.g., one that has a handle

FIGURE 9.7: Continuum of stimuli experimental control to ecological validity.

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and a main functional part—such as a spoon, baseball bat, or a garden rake, it is worth considering if the scrambling process should take into consideration the inherent structure and orientation of these objects. By doing so, the representation maintains a semblance of the original form, allowing for more matched properties. This may or may not be desirable, based on the research question. Real objects are much more difficult to dissociate from specific stimuli properties. MIN RE

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Hebart et al. (2020) determined relevant dimensions of picture stimuli by collecting a large dataset of similarity judgements for 1,854 object pictures using an odd-one-out triplet task. In this task, participants were shown three object pictures and had to choose the one that was least similar to the other two. They then developed a computational model to learn an interpretable low-dimensional embedding from the similarity judgements. The model determined 49 dimensions which explained 92% of the variance. Some dimensions were animacy, colourful, valuable, and roundness. More broadly, these ranged from physical properties—size, colour, and shape—to more semantic properties. (For additional data expanding on this database, see Hebart et al., 2019, 2023; Stoinski et al., 2023.) Presenting real objects within an MRI scanner is particularly challenging, though a few solutions have been developed, such as the DROID (Delivery of Real Objects for Imaging Device) system by Jody Culham’s lab (Snow & Culham, 2021). Another approach has been used in a recent study from Nancy Kanwisher’s lab, where a 3D-printed haptic turntable was used (Ratan Murty et al., 2020). A number of other studies have also taken advantage of recent technological advances to 3D-printed object stimuli (Cooke et al., 2007; Madan, 2016a; Derzsi & Volcic, 2019; Chow et al., 2021; Korisky & Mudrik, 2021), including for studies with animals (Inayat et al., 2021). Some stimuli databases are intended to be parametrically varied for studies of categorisation or rule learning (Watson et al., 2019; Lebaz et al., 2020). Other databases of naturalistic 3D objects have recently been published, with the intention of making stimuli readily available for VR or 3D printing (Tromp et al., 2020; Popic et al., 2020; Deitke et al., 2023). Garlinghouse et al. (2018) used 3Dprinted objects as reminiscence cues for participants with memory loss. VR may be a useful intermediate to using real objects. Rubo et al. (2021) presented objects either using a standard 2D computer monitor, real objects, or using VR. Participants made more source errors confusing real and VR than either with the 2D monitor.

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Affordances Most theories suggesting that functional objects should be preferentially attended to—for instance, Gibson’s (1977, 1979) theory of affordances, rely on the object itself being ‘real.’ In other words, words and pictures representing functional objects should not have affordances. Affordances are inherently linked to the physical properties of an object and the capabilities of the observer. They are not properties of the object or the observer alone, but rather emerge from the interaction between the two. As such, affordances only exist for real objects, as only these objects have physical properties that can be directly interacted with. Handy et al. (2003) investigated whether recognition of objects’ motor affordances can bias visual spatial attention towards those objects. In Experiment 1, participants were presented with two task-irrelevant objects: one tool and one non-tool were presented in the left and right visual fields. After a delay, a target appeared over one object and participants responded to the target location. Eventrelated potentials (ERPs) elicited by the target showed increased sensory gain, larger P1 amplitude, when targets appeared over tools in the right visual field compared to the left, suggesting spatial attention was drawn to tool locations in the right hemifield. Experiment 2 replicated and extended these results, additionally comparing upper and lower visual fields—here showing lower visual field advantages for visuomotor processing. Experiment 3 used event-related fMRI, demonstrating that tools in the right hemifield specifically activated premotor and parietal regions associated with motor planning and visuomotor transformations. Activity was greater on tool-right vs. tool-left trials. These results show that automatic processing of object motor affordances bias visual spatial attention, but only when affordances are in the right visual field, likely due to handedness. Critically, the concept of affordances becomes more complex when we consider words and pictures that represent functional objects. Many studies have shown that participants are faster when responses are congruent with how an object would be interacted with (Tucker & Ellis, 2001, 2004; Bub et al., 2008; Osiurak & Badets, 2016; Scerrati et al., 2021). Making movements towards one’s self can also enhance memory for presented object pictures (Oakes & Onyper, 2017). These representations do not have the same physical properties as the objects they represent; they should not have affordances. Evidence that automatic motor simulations can be elicited by words—let alone pictures—complicates how affordances relate to motor processing. Motor simulations based on words and pictures do occur. If incidental reading of words can influence unrelated movement kinematics, these cognitive systems interacted. This evidence of automatic motor simulations elicited by words and pictures complicates our understanding of how affordances relate to motor processing. It suggests that our perception of affordances is not limited to direct physical interactions with objects, but can also be influenced by symbolic representations and mental simulations.

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9.5 Drawing Some studies have used drawing as an encoding task (Wammes et al., 2016, 2018; Fernandes et al., 2018). While enactment is arguably the ‘deepest’ level of processing, drawing is not far behind. Drawing requires semantic processing to derive meaning from the word, but also engages in motor processing as part of the further semantic process. Unlike enactment, drawing likely is a more active and constructive process, as the final drawing is not immediately apparent and needs to be developed gradually, unlike the enacted statement of ‘sharpen the pencil’ which can be carried out immediately (Ainsworth et al., 2011; Ainsworth & Scheiter, 2021; Cromley et al., 2019). Drawing enhances learning and memory by engaging visual, motor, and generative processes. Drawings produced from memory integrate information from perception, episodic and semantic memory. They are the product of perceptual biases but also distortions reflecting semantic knowledge, expectations, and false memories. Drawing can be used to obtain richer insights into memory representations than verbal memory tests (Osterrieth, 1944; Servos et al., 1993; Milner & Goodale, 1995; Leek et al., 2000). Drawings conveying concepts rather than visual appearances emphasise informative features, sometimes sacrificing visual accuracy (Freeman & Janikoun, 1972; Bremner & Moore, 1984). Children tend to draw concrete features over abstract spatial relationships. Adults, however, highlight functional over visual properties when explaining mechanisms. Drawings reveals how people interpret and understand the presented visual information. MIN RE

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To investigate the content and detail of visual memories for complex realworld scenes, Bainbridge et al. (2019) used a drawing recall task. Participants studied 30 real-world scenes for ten seconds each. After a distractor task, participants were asked to draw as many of the studied images as possible. On average, participants recalled 12 of the 30 pictures in the free recall phase (via drawing). When given category cues, they recalled 6 more scenes. The drawings were scored by another cohort of participants. The memory drawings were matched to the correct original image by 84% of scorers, showing they contained diagnostic details beyond just the category. Each drawing contained many objects—on average 11 objects per scene. Even when removing schema-consistent objects for the scene category, memory drawings still had 4 additional distinctive objects. The memory drawings were also spatially accurate. Additional control experiments had participants draw the images immediately after seeing them (96% diagnosticity), directly copy

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the images (92.5% diagnosticity), or draw from category names only (30.7% diagnosticity). In summary, this study demonstrates surprisingly detailed and accurate object and spatial memories for complex scenes that can be assessed using drawing recall tests. Bainbridge et al. (2021) examined drawing in individuals with aphantasia. Participants studied three scene photos, then completed a drawing recall task where they drew the images from memory. Their drawings were scored by online participants for number of objects, spatial accuracy, object details, and memory errors. Participants also copied the photos to assess perceptual drawing ability. Aphantasic participants drew fewer objects from memory compared to controls, indicating impaired object memory. However, there was no difference in number of objects drawn during the perceptual copying task. Despite impaired object memory, aphantasic participants showed equivalently high spatial accuracy as controls in placing and sizing objects. Fewer memory errors—falsely recalled objects not present in the original photos—were made by the aphantasic participants. Aphantasic participants also relied more on symbolic and verbal strategies, with more text labels in drawings. The study provides an important objective validation of aphantasia through drawing analysis. Bainbridge (2022) provides a tutorial on conducting online drawing studies. As a reminder, refer back to the study of brand logo reproductions from early in the book (see Section 2.1 from p. 36). Drawing and similar generation tasks, like clay forming, can also have therapeutic benefits (Rankanen et al., 2022).

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End of chapter wrap-up Summary Motor processing has a surprising and multifaceted dynamic with memory. Enactment effects show that motor actions can enhance memory. According to dual-coding theory, this enhancement engages various codes, such as verbal, visual, and motor. Manipulable objects—represented by words or pictures— are often remembered better than non-manipulable objects. Distinct brain regions are also associated with tool-related processing. The dorsal stream involves manipulation knowledge and substitutable tool selection, while the ventral stream aids object recognition and function. Real 3D objects are remembered better than 2D photos or line drawings—a finding that may reflect the underlying affordances and depth cues. In a technological context, virtual reality (VR) and 3D printing allow for more experimental control when studying object processing and memory. Drawing is also an integral part of this process, tapping into visual and motor processes—either encoding or retrieval. Motoric features can be present in actions, objects, and language providing a basis for memory’s embodied nature.

Reminder cues

Quick quiz 1. According to dual-coding theory, why are concrete words like CLOCK and PENCIL often remembered better than abstract words like JUSTICE and THEORY? (a) Concrete words can be mentally represented as both pictures and words, whereas abstract words can only be represented as words. (b) Concrete words are more frequently used in daily language. (c) Concrete words are easier to spell and pronounce. (d) Concrete words have fewer synonyms compared to abstract words.

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2. Imagine you are a researcher studying the motor attributes of different objects. You choose a wrench and a stapler for your study. Based on the text, how might the results of your study differ for these two objects in terms of graspability, moveability, ease of pantomime, and the number of possible actions? (a) The wrench would likely score higher in all categories because it is designed for physical interaction. (b) The stapler would likely score higher in all categories because it has multiple functions. (c) The wrench would likely score higher in graspability, moveability, and the number of possible actions; the stapler might score higher in ease of pantomime. (d) The stapler would likely score higher in ease of pantomime; the wrench might score higher in moveability. 3. According to Gibson’s theory of affordances, what properties lead to an object being preferentially attended to? (a) The object must be large. (b) The object must be visually appealing. (c) The object must be associated with a reward. (d) The object must be a real object. 4. How does the evidence of automatic motor simulations elicited by words and pictures challenge the traditional understanding of affordances? (a) It proves that affordances can only exist for real objects. (b) It shows that our understanding of affordances is incorrect. (c) It suggests that perception of affordances can also be influenced by symbolic representations and mental simulations, not just direct physical interactions. (d) It provides conclusive evidence that images of objects have the same affordances as the actual objects.

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5. During a study session, Lily decides to use drawing as her primary method of studying. She believes that this method will enhance her memory of the study material. Which statement best describes the cognitive processing involved in her study method? (a) Drawing will require less cognitive processing as it is a passive activity that does not involve any meaningful interpretation of the material. (b) Drawing will require more cognitive processing as it engages semantic processing to derive meaning from the material and motor processing to create the drawings. (c) Drawing and reading the material aloud would require the same level of cognitive processing as both involve the same type of memory encoding. (d) Drawing won’t involve any cognitive processing as it is an artistic activity rather than a learning method.

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Thought questions ▶ How does the enactment effect fit with the levels-of-processing paradigm? How do these align with the learning pyramid and Bloom’s taxonomy? ▶ Real objects are more naturalistic and better remembered, but 2D image representations are clearly sufficient when studying memory from an experimental psychology approach. Should we shift to be more focused on using real objects in our future studies? Why or why not? ▶ Discuss how manipulation and function knowledge align with the dorsal and ventral streams. Do studies showing automatic motor simulations challenge this dissociation? How would you design a study to test this further?

Further reading ▶ Bainbridge, W. A., Hall, E. H., & Baker, C. I. (2019). Drawings of real-world scenes during free recall reveal detailed object and spatial information in memory. Nature Communications, 10(1), 5. doi: 10.1038/s41467-018-07830-6 ▶ Guérard, K., Lagacé, S., & Brodeur, M. B. (2015). Four types of manipulability ratings and naming latencies for a set of 560 photographs of objects. Behavior Research Methods, 47 (2), 443–470. doi: 10.3758/s13428-014-0488-5 ▶ Sawyer, T., White, M., Zaveri, P., Chang, T., Ades, A., French, H., … & Kessler, D. (2015). Learn, see, practice, prove, do, maintain: An evidence-based pedagogical framework for procedural skill training in medicine. Academic Medicine, 90(8), 1025–1033. doi: 10.1097/acm.0000000000000734

Chapter 10 A domain-general influence of motivation

You have to begin to lose your memory, if only in bits and pieces, to realize that memory is what makes our lives. Life without memory is no life at all […] Our memory is our coherence, our reason, our feeling, even our action. Without it, we are nothing. — Luis Buñuel (1985)

Many characteristics can make experiences memorable—emotion, reward, self relevance, motor functionality. But, perhaps there is a more coherent interpretation that captures all of these effects and some of their nuances, such as attentional capture, higher rates of false memories, and impaired memory for context—as discussed throughout these last chapters. While some situations put different motivational processes in conflict, these are often deliberate—such as the unpleasant imagery used on cigarette packages (Christie & Etter, 2004; Farrelly et al., 2012; Noar et al., 2016).

10.1 Considering a common motivational process Across these last few chapters, there are some influences of motivational domains that had similar effects on memory. Attentional blink effects can occur due to emotion, reward, and personal relevance, suggesting that these motivational factors can temporarily impair our ability to process subsequent stimuli (Shapiro et al., 1997a, 1997b; Strange et al., 2003; Most et al., 2005; Raymond & O’Brien, 2009). These motivational processes also have commonalities in impairing contextual binding (Madan, Caplan, et al., 2012; Madan, Fujiwara, et al., 2012; Bisby & Burgess, 2014; Madan, 2014b). Some other effects not discussed as consistently in their respective chapters also demonstrate some generality. For instance, like emotion, reward also can distort time estimation (Failing & Theeuwes, 2016). 289

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What is common to these various types of motivation? We can consider a few potential underlying principles. In all cases, the goal is to describe an over-arching relationship between a range of motivational domains and how they relate to memory (Young, 1959; Kleinginna & Kleinginna, 1981; White, 1989; Madan, 2013), but the nuances of this relationship are explored. Hedonism is a long-standing perspective that emphasises the maximising of pleasure and the minimising of pain (Plato, 353 BC; Klopf, 1982; Drakopoulos, 1990). From this perspective, we might expect to remember experiences that were particularly pleasurable or painful. This aligns well with many of the findings discussed through these last chapters—both positive and negative emotional experiences, extreme reward value outcomes, and self-relevance— both good and bad. This view has some validity but is also too simplistic. For instance, experiences that are personally relevant or involve motor action can be memorable, even if they’re not particularly pleasurable or painful. The notion of hedonistic principles being relevant to memory has been discussed in the literature nearly a century ago (Gilbert, 1937; Pintner & Forlano, 1940). MIN RE

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A second perspective with some promise is utilitarianism. Utilitarianism is a perspective rooted in ethics and decision-making, proposing a prioritisation of rational and objective evaluation of experiences—Homo economicus (Bernoulli, 1738, 1954; Bentham, 1789; Mill, 1836; von Neumann & Morgenstern, 1947; Kreps, 1990). In the context of memory, a utilitarian perspective might suggest that we remember experiences that have the greatest utility, or usefulness, to us. This could include experiences that provide valuable information, help us achieve our goals, or enable us to avoid mistakes in the future. However, this perspective is too rigid. Our memories are subject to various biases, such as the context in which an event occurred or the availability of information at the time of recall (Godden & Baddeley, 1975; Feather, 1995; Kahneman, 1994; Kensinger & Corkin, 2003). These biases can distort our memories, making them less than objective and rational. For instance, a subjective bias in valuation is critical to the extremeoutcome rule (Madan, Ludvig, & Spetch, 2019). The reminiscence bump, prior knowledge influences on false memory, and egocentric bias are all biases in memory availability. Moreover, the utilitarian perspective suggests a relatively deliberate process. This contrasts with the automatic nature of attentional capture and still does not sufficiently span all four types of motivation.

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A relevance to survival and related evolutionary mechanisms has been proposed more recently from a few converging directions (Sherry & Schacter, 1987; Nairne & Pandeirada, 2008; Wurm, 2007). This perspective posits that our cognitive systems have been shaped by evolutionary pressures to prioritise information that has survival relevance. This evolutionary perspective is at the core of the concept of adaptive memory, which proposes that memory systems have been optimised for survival and reproductive success throughout human evolutionary history. Within the context of these evolutionary mechanisms, danger and usefulness appear to be particularly relevant semantic features that bridge across motivational domains (Wurm, 2007, 2015; Van Havermaet & Wurm, 2017). Both of these features are intrinsically tied to survival and thus hold a special place in our cognitive-perceptual processing. Danger, in this context, signifies the potential harm or threat that a stimulus might pose. An increased level of danger is associated with a preparatory avoidance response (also see Leding, 2019a, 2019b). Conversely, usefulness refers to the potential value or benefits that a stimulus might offer. A higher degree of usefulness is associated with quicker processing, reflecting an approach response (also see Castegnetti et al., 2021). These approaches are based on the notion that our cognitive systems have been shaped by the demands and pressures of survival throughout human evolutionary history. A fourth, more contemporary view of motivation is based on goals and context. This largely is convergent with the third—survival-related mechanism—but does not intertwine evolutionary principles as part of the basis (Braver et al., 2014; Freund et al., 2021). This perspective posits that motivation is a dynamic construct, shaped by our goals and the contexts in which we find ourselves. Goals, in this framework, are not static but evolve over time in response to changing desires, resources, and opportunities. The processes of goal setting, pursuit, and disengagement are central to this perspective, enabling individuals to continue pursuing what they value despite constraints that may arise. Contexts, encompassing cultural, social, technological, physical, and organisational aspects, provide opportunities and constraints for goal attainment. They shape our goals and the ways we approach or withdraw from them. In this view, motivation has two functions: activation, which energises actions; and direction, which involves approach/avoidance and transient/sustained influences. In essence, this contemporary view of motivation underscores the complex interplay between goals, the contexts in which we operate, and the cognitive and neural mechanisms that underpin motivations. It emphasises the dynamic nature of motivation and its profound influence on behaviour, cognition, and memory. By no means am I suggesting that I am the first to examine a more general role of motivation across emotion, reward, and other facets of cognition. Here I merely intended to provide an overview of how I have journeyed between these perspectives and where I settled. My goal here is rather to highlight that these various perspectives have already been proposed and developed far before I have entered the field.

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Motivational salience Perhaps a more parsimonious view would be to borrow from the literature on utilitarian or hedonistic motivations: a non-conscious goal pursuit of maximising pleasure and minimising pain (Berridge, 2004; Hassin et al., 2009; Madan, 2013, 2017b). Each of the motivational factors discussed through Chapters 6 to 9 is associated with different mental processes and brain regions. However, these domains are also not wholly distinct—there are commonalities. One potential unifying interpretation could be the concept of salience. Salience refers to the state or quality by which something stands out relative to its context. Emotion, reward, self-relevance, and motor functionality can all increase the salience of an experience, making it more likely to be remembered. This interpretation could also account for the observed effects of attentional capture and impaired memory for context. Highly salient experiences can capture our attention, making us more likely to remember the experience itself but less likely to remember the context in which it occurred. This concept of salience could provide a more coherent framework for understanding the diverse effects of different motivational domains on memory. Here I suggest that motivational salience may be this cohesive mechanism and discuss related findings that do not fit as well within any of the prior chapters. Emotion and reward are both constructs that are more nuanced than experiences simply being ‘emotional’ or ‘rewarding.’ One prominent theory of emotion suggests that emotional experiences exist within two dimensions: arousal and valence (Russell, 1980; Yik et al., 2011). Briefly, arousal describes the intensity of the emotional experience, ranging from calm to excited; valence describes the pleasantness of the experience, ranging from negative/unpleasant to positive/pleasant. Despite these dimensions being thought to be orthogonal with regard to emotional states, emotional words and images have often been found to fall along a U-shaped function, where stimuli that are relatively extreme in valence, either positive or negative, are also higher in emotional arousal (Lang et al., 1998; Warriner et al., 2013). Arousal and valence have also been shown to have separable influences on memory (Kensinger, 2009; Bowen et al., 2018). While theories of the dimensions underlying reward processes are less developed, recent evidence shows a somewhat comparable structure as in emotion. As expected, the amount of reward, i.e., reward value or reward magnitude, modulates related behaviour. However, some brain regions, including the striatum and orbitofrontal cortex, have been found to exhibit a U-shaped relationship with respect to reward value (Zink et al., 2004; Janssen et al., 2007; Cooper & Knutson, 2008; Litt et al., 2011), suggesting that the salience of the reward is also processed. Behavioural studies investigating memory have come to similar findings, where both items associated with the highest and lowest values are remembered best (Madan & Spetch, 2012; Castel et al., 2016; Wispinski et al., 2017); similar findings have also been shown in decision-making studies (Ludvig et al., 2014a, 2014b; Madan et al., 2014;

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Madan, Ludvig, & Spetch, 2017; Lieder et al., 2018). Several studies of reward processing have also examined comparisons between different types of rewards (Chib et al., 2009; Sescousse et al., 2010; Sescousse, Caldú, et al., 2013; Yee et al., 2016; Zhang et al., 2017). From this evidence, it is possible to liken reward salience and emotional arousal, where both correspond to the intensity of the related experience. Here I will refer to this commonality as motivational salience, describing experiences associated with strong appetitive (i.e., positive emotional valence or highest experienced reward value) or aversive outcomes (i.e., negative emotional valence or lowest experienced reward value). As an approach to integrate emotion and motor processing into the well-established operant (S—R—O) conditioning framework, Madan (2013) proposed the SIMON framework, shown in Figure 10.1. As in operant conditioning, stimuli elicit a response, which then produces an outcome—the solid grey lines. Both the stimulus and outcome can elicit emotional/affective responses, shown in dashed black lines. Additionally, the stimulus and initial emotional state may potentiate motor approach/avoidance responses—shown in dotted grey lines.

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FIGURE 10.1: SIMON framework. Line arrows correspond to the portions of the framework that are intrinsic to each of the three component constructs: reward (solid grey lines), emotion/affect (dashed black lines), and motor processing (dotted light grey lines). In conditioned place preference, a rodent learns that a reward-related outcome, such as food or a shock, may occur at a specific location (Young & Fanselow, 1992; Harris & Westbrook, 1998; Rudy & O’Reilly, 2001; Cassaday et al., 2023). For simplicity’s sake, consider a two-chamber enclosure. Initially, both chambers are equivalent, with no reward-related outcome occurring in either (Figure 10.2A). However, if there is a probability of electric shock occurring in one chamber, but not the other, the rodent will learn to spend

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more time in the other chamber (Figure 10.2B). If the manipulation is removed and there is no probability of shock in either chamber, the rodent will still have a preference of spending more time in the ‘safe’ chamber, commonly referred to as preference testing. In the SIMON framework (Madan, 2013), this behaviour can be viewed as the stimulus being the chamber associated with the shock, leading to an avoidance response—as illustrated in Figure 10.2C. This avoidance is related to the possibility of experiencing a future electrical shock and an emotional response of threat. In an alternate study, if there was a contextual food reward, there would be an approach-related movement towards food (Figures 10.2D and E).

FIGURE 10.2: SIMON framework applied to conditioned place preference. (A) Illustration of a two-chamber enclosure for the baseline condition. (B) Avoidance behaviour when electric shocks occur in one chamber. (C) Description of shock avoidance with the SIMON framework. (D) Approach behaviour if food is instead added to one chamber. (E) Description of foodinduced preference with the SIMON framework. In such experiments, some consideration is needed for how freezing is assessed. For instance, if the study design involves evaluating the effects of a pharmacological agent (i.e., drug) on threat conditioning, it is possible that the drug decreases movement ability or pain perception, rather than affecting freezing behaviour itself.

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While emotion, reward, self, and motivation have been sometimes discussed in relation to each other (Cardinal et al., 2002; Pessoa, 2009; Lang & Bradley, 2010; Chiew & Braver, 2011; Northoff & Hayes, 2011), motor-related processes are often not considered within the same framework. Critically, movement processing and motivation are intertwined constructs—both approach and avoidance motivations are associated with increased motor potentiation, as movements are necessary either towards or away from the relevant stimulus. However, this relationship extends into stimuli that are not clearly associated with emotion- or reward-related processes, but are associated more directly with movement-related processes, e.g., words and images corresponding to tools or other objects associated with high functionality, e.g., grapes. As summarised in Chapter 9, studies investigating the influence of movementrelated words and images on movements have shown that these stimuli can prime movements or interfere with them, depending on their relative correspondence (Gentilucci & Gangitano, 1998; Glover et al., 2004; Madan & Singhal, 2012a; Shebani & Pulvermüller, 2013). Beyond these domains, cues can be learned to predictive of outcomes— the learned predictiveness effect (Mackintosh, 1975; Le Pelley & McLaren, 2003), bearing commonalities with some reward-learning procedures. Learned predictiveness can capture attention across a variety of procedures (Esber & Haselgrove, 2011; O’Brien & Raymond, 2012; Le Pelley et al., 2016; Luque et al., 2020). As discussed later in this chapter, some other topics also fit within our domain-general view of motivation, such as animacy and food stimuli.

10.2 Neurobiology of motivational domains Part of the motivation for this book—and this chapter in particular—grew from the initial goal of extending the SIMON framework (Madan, 2013). Characterising brain networks associated with each factor To evaluate the functional brain networks associated with each motivational domain, I used NeuroSynth (Yarkoni et al., 2011)—a tool designed to conduct automated meta-analyses of the fMRI literature. The principle it is built on is that papers that study a topic will use that term relatively frequently, and this calculated term frequency can be paired with the table of activation cluster peaks typically reported in these papers. Analyses were conducted on a local installation of NeuroSynth, as opposed to the online version, as this allowed for some additional features. The database contained 10,903 fMRI studies, with a total of 386,455 activation clusters. As the goal was to assess activations associated with each of these motivational domains, e.g., what brain networks are associated with emotional processing, I only used the forward inference maps (Poldrack, 2006). Forward inference calculates the likelihood a voxel was found to be active given a

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term was used, i.e., P (Activation|Term). Forward inference is more strongly influenced by a priori research questions, e.g., a study of the brain’s response to emotional images yields activation in the amygdala. Additionally, many relevant studies use region-of-interest masks or constrained analyses using localiser tasks (e.g., small volume correction when testing for differences in the activation of the amygdala or striatum). In all cases, Z-score inference images were output with 2 mm3 isotropic voxels and thresholded at p < .001-FDR. Inference map visualisations were generated using the approach described in Madan (2015a). (N.B. This visualisation approach was developed for this project—characterising brain networks of each motivational domain—despite being the method being published in 2015, many years before this book.) For emotion processing, I initially used the term “emotion*” (to capture related terms, such as “emotional”); similar was done for reward and self. For motor, I initially used the union of “motor” and “movement.” In all cases, I used a term (feature weight) threshold of 0.1 (units represent a normalised term frequency metric, term frequency–inverse document frequency [tf-idf]); this relatively high term threshold was specifically used to reduce number of irrelevant articles for the motor search (e.g., “movement correction”) and only resulted in minor reductions in studies found for the emotion and reward meta-analyses. Using each of these terms independently, emotion returned 1,048 studies, reward returned 408 studies, self returned 469 studies, and motor returned 920 studies. For comparison, using a term threshold of 0.001, the searches yielded 1,541 (emotion), 602 (reward), 812 (self), and 2,082 (motor) studies, for each of the four meta-analyses, respectively—clearly misrepresenting which studies are associated with motor processing, with a relative increase of 226% with the runner-up being 173% (self). To prevent studies from contributing to more than one of these metaanalyses, I determined the number of studies that would be included using terms that were mutually exclusive, e.g., “emotion* NOT (reward* OR self* OR movement OR motor).” With these additional caveats, emotion returned 907 studies, reward returned 334 studies, self returned 330 studies, and movement returned 869 studies. Given this relatively minor decrease in the number of studies included using mutually-exclusive searches (i.e., for emotion, 907/1,048 = 87%; reward = 82%; self = 70%; motor = 94%), we only used the inference maps from the mutually-exclusive meta-analyses, as to reduce the interdependence and inherent associated common brain regions would be found across the meta-analyses. The forward inference maps for each of these meta-analyses are shown in Figure 10.3. To provide additional contextual information about the included studies, word clouds generated from the titles of the included studies are also shown. Note, the word clouds are not from the included papers’ full text, as was used for the tf-idf thresholding and study inclusion, only the titles; this was due to limitations in how much information can be extracted from the underlying database. Conducting these mutually-exclusive meta-analyses and exporting the titles for all of the associated studies is only possible with the local installation of NeuroSynth.

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FIGURE 10.3: Brain regions associated with each motivation factor based on forward inference maps: (A) emotion, (B) reward, (C) self, and (D) motor. Brain regions derived from an automated meta-analysis using Yarkoni et al. (2011), visualised based on Madan (2015a). To improve visual clarity, the 3D renderings were thresholded with a minimum cluster volume of 1,000 mm3 (k > 125 voxels). Word clouds show the 100 most frequent words from the titles of the papers included in the corresponding meta-analysis (after removing common words such as “the,” “on,” etc.). Font size corresponds to the word frequency count; font colour corresponds to the frequency rank (most frequent in black, 100th in near-white).

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Some brain regions came up in the partial intersection of all four search terms—the supplementary motor area, amygdala, striatum, and insula. Of course, it is important to acknowledge that these are heterogeneous. A portion of the striatum involved in reward processing may not be the same region involved in motor processing. However, there are also limitations of conducting meta-analyses across many experimental procedures; fMRI inherently has spatial precision limitations, and regions are mixtures of different cellular structures. We do know of regional heterogeneity from a variety of neuroscience techniques, and some gradients and regional specialisations are well established. In particular, I would like to highlight a few review papers for the amygdala (Roy et al., 2009; Entis et al., 2012), striatum (Voorn et al., 2004; Di Martino et al., 2008; Gruber & McDonald, 2012), and insula (Kelly et al., 2012; Chang et al., 2013; Uddin, 2015). Nonetheless, that we do observe some relatively consistent clusters across motivational domains is noteworthy. MIN RE

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A few regions are present in all four domains: the medial prefrontal cortex, thalamus, and superior parietal cortex. These regions are also generally convergent with regions associated with the salience network (Seeley et al., 2007; Seeley, 2019; Menon & Uddin, 2010). Convergent evidence was also established in a literature review, examining theoretical reviews and meta-analyses published between 2000 and 2015 that were focused on either the motivational domains investigated here, a related topic (e.g., neuroeconomics or pain), or one of the key indicated brain regions. This literature search yielded 259 publications, across 104 journals. Four journals that each contributed ten or more papers are: Trends in Cognitive Science (21 papers, 8.1% of the included papers), Nature Reviews Neuroscience (20, 7.8%), Neuroscience & Biobehavioral Reviews (16, 6.2%), and Current Opinions in Neurobiology (10, 3.9%). Combined, these four journals represented 67 papers and 26.0% of the included papers. Results from this literature analysis supported the emphasis on this set of brain regions—supplementary motor area, amygdala, striatum, and insula—as the intersection of the four motivational domains.

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Locus coeruleus The locus coeruleus (LC)—latin for ‘blue spot’—is a small nucleus in the brainstem, with a volume of only 100–200 mm3 (Keren et al., 2015; Liu et al., 2019; Morris et al., 2020; Coulombe et al., 2021)–see Figure 10.4. For comparison, the bilateral total volume of the hippocampus in a healthy adult is around 7,500–10,000 mm3 (Nobis et al., 2019; Madan & Kensinger, 2017) and about 3,000–4,000 mm3 for the amygdala (Brierley et al., 2002). Despite being so small, the LC is the primary source for generating norepinepherine within the brain, regulating the overall arousal state and adapting to the presentation of salient stimuli (Berridge & Waterhouse, 2003; Benarroch, 2009; Sara, 2009; Aston-Jones & Cohen, 2005; Mather & Harley, 2016; Takeuchi et al., 2016; Grella et al., 2018). Imagine you’re hiking in a forest and suddenly spot a snake on the path ahead. The sight of the snake triggers a rapid response in your LC, which releases norepinepherine throughout the brain. This surge of norepinepherine heightens your attention, sharpens your senses, and prepares your body to either confront the snake or make a hasty retreat. The LC also plays a crucial role in long-term goal-directed behaviour. For instance, consider a student studying for an important exam. The prospect of doing well on the exam and the potential consequences of failing can motivate the student to put in long hours of study. This kind of sustained, goal-directed behaviour is also influenced by the LC. The LC’s influence extends to physiological responses such as pupil dilation. Pupil dilation is a reflexive response to changes in light, but also with cognitive and emotional processes. In the context of memory, studies have shown that pupil dilation can serve as an index of recognition memory, with greater dilation occurring for recognised stimuli (Võ et al., 2007; Otero et al., 2011; Montefinese et al., 2013; Bradley & Lang, 2015; Taikh & Bodner, 2022). The LC’s role in this process is thought to be related to its function in regulating arousal and attention. When a stimulus is recognised, it triggers an arousal response in the LC, which in turn leads to the release of norepinephrine and subsequent pupil dilation. This response can be particularly pronounced when the recognised stimulus is of high emotional salience or relevance to the individual’s current goals or interests (Sterpenich et al., 2006; Brady et al., 2008; Mathôt, 2018; Murphy et al., 2014; Clewett et al., 2018; Clewett et al., 2020; Strauch et al., 2022). In addition to its role in memory, pupil dilation has also been linked to other cognitive processes that are influenced by the LC, such as attention, decision-making, and cognitive effort. For example, studies have shown that pupil dilation can increase during tasks that require high levels of attention or cognitive effort, suggesting that the LC may play a role in modulating these responses. The LC is a key region in modulating the activity of many others, including the amygdala, striatum, and hippocampus (Aston-Jones et al., 1986; Jacobsen et al., 2015; Weinshenker, 2018; Liebe et al., 2020; Matchett et al., 2021).

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FIGURE 10.4: Images of the locus coeruleus (LC). (A) Mask of the locus coeruleus on a T1-weighted MRI shown on different planes, localised using a neuromelanin-sensitive scan sequence in a large population of adults. Adapted from Liu et al. (2019). (B) Histological staining of a post-mortem section of brainstem, including the locus coeruleus, using cresyl violet. The dashed line on the brain outline denotes the location of the post-mortem section. Adapted from Coulombe et al. (2021).

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Also refer back to Section 5.5 (p. 148) for details about Braak staging, where tau tangles are found to develop in the LC early in the progression of Alzheimer’s disease, before propagating throughout the cerebral cortex. This early involvement of the LC in Alzheimer’s disease suggests that changes in LC function could contribute to the cognitive and behavioural symptoms associated with the disease. For example, disruptions in LC activity could lead to alterations in norepinephrine release, which could in turn affect a range of cognitive processes, including attention, memory, and emotional regulation. Moreover, given the LC’s role in regulating arousal and responses to stress, changes in LC function could contribute to sleep disturbances and increased stress sensitivity often observed in individuals with Alzheimer’s disease.

Additional considerations Dysfunctions in motivation are often anhedonia or apathy (Husain & Roiser, 2018; Starkstein & Brockman, 2018). Anhedonia, derived from the Greek words ‘an-,’ meaning without, and ‘hēdonē,’ meaning pleasure, is a condition characterised by the inability to experience pleasure from activities usually found enjoyable. This condition is often associated with several mental health disorders, notably major depressive disorder and schizophrenia. It is crucial to note that anhedonia is not merely a transient lack of interest, but a persistent state that can significantly impair quality of life. Anhedonia can manifest in two primary forms: social anhedonia, an indifference towards social contact and a lack of enjoyment in social situations; and physical anhedonia, a lack of pleasure in sensory or bodily experiences. The presence of anhedonia can influence memory processes, as the lack of emotional response and motivation can lead to difficulties in encoding and retrieving information. Memories of past pleasurable experiences may become less accessible, further decreasing motivation. Anhedonia can be measured using questionnaires such as the Scales for Physical and Social Anhedonia (Chapman et al., 1976) and the Snaith– Hamilton Pleasure Scale (SHAPS) (Snaith et al., 1995). Questions include Likert responses of agree—disagree statements such as, “I would enjoy being with my family or close friends” and “I would find pleasure in small things, e.g. bright sunny day, a telephone call from a friend.” Another questionnaire that measures anhedonia is the Oxford-Liverpool Inventory of Feelings and Experiences (O-LIFE), a self-report questionnaire that assesses four dimensions of schizotypy: unusual experiences, cognitive disorganisation, introvertive anhedonia, and impulsive nonconformity (Mason et al., 1995). Schizotypy includes personality traits related to schizophrenia-spectrum disorders in the general population. Originally requiring 104 items (Mason et al., 1995; Mason & Claridge, 2006), a shortened scale of 43 items is now widely used (Mason et al., 2005).

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Apathy is characterised by a lack of interest, enthusiasm, or concern. It is a state of indifference that can manifest in various ways, such as diminished motivation, reduced goal-directed behaviour, and a lack of emotional response. Apathy is often associated with several neurological and psychiatric disorders, including Alzheimer’s disease, Parkinson’s disease, and depression. Questionnaires have been developed to measure apathy status. The Apathy Evaluation Scale (AES) is an 18-item questionnaire with four subscales: emotional, behavioural, cognitive, and other (Marin et al., 1991; Lee et al., 2020). Example items are: “Seeing a job through to the end is important” and “I am interested in having new experiences.” A second questionnaire is the Apathy Motivation Index (AMI), also with 18 items, consisting of three sub-scales: emotional apathy, behavioural, and social apathy (Ang et al., 2017; Hewitt et al., 2023). Apathy is correlated with impulsivity. Impulsivity, in a broad sense, refers to a tendency to act on a whim, displaying behaviour characterised by little forethought, reflection, or consideration of the consequences. Impulsivity can be seen in various psychological disorders including attention deficit hyperactivity disorder, substance use disorders, bipolar disorder, and personality disorders. Impulsivity can manifest in decision making (making hasty decisions without considering the consequences), actions (acting without thinking), and choice (preferring immediate rewards over delayed, potentially more valuable ones). A common measure of impulsivity is the Barratt Impulsiveness Scale (BIS) (Barratt, 1959, 1965; Patton et al., 1995). The BIS is a questionnaire designed to assess the personality/behavioural construct of impulsiveness and is widely used in research. It includes items that measure attentional impulsiveness (making quick decisions), motor impulsiveness (acting without thinking), and non-planning impulsiveness (a lack of forethought). While both involve a reduction in motivation, apathy is characterised by a lack of motivation, while anhedonia is characterised by a lack of pleasure. A lack of motivation or interest can lead to difficulties in the encoding and retrieval of information, as well as a reduced engagement with the environment, which can further exacerbate memory difficulties. Shifting focus, unfortunately, the literature examining cross-domain effects of pharmacological agents on different types of motivation-related memory processes is too sparse to make reliable inferences. For instance, too few studies have looked at how levodopa or oxytocin may modulate emotional memory.

10.3 A generalised view of availability A key finding discussed in each of the last four chapters is that these motivation-related processes can influence memory availability, and in turn, future decisions. As these all involve biases in memory recognition and sampling of past experiences, these can be considered as extensions of the

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the availability heuristic (Tversky & Kahneman, 1973), such as the peak-ends rule (Redelmeier & Kahneman, 1996; Stone et al., 2005) and related principles (Hastie & Park, 1986; Mitchell et al., 1997; Hilbert, 2012; Aldrovandi et al., 2015). Early in the book, we first discussed this heuristic and initial supporting findings (see Section 2.5, p. 48). As foreshadowed, this heuristic is foundational to our broader understanding of memory and decision making and can be treated as a fundamental principle of cognition. From a generalised view, any retrieval bias can be thought of as being related to the availability heuristic. Most basic of all effects discussed thus far, items presented early and late in a list—primacy and recency effects, respectively—are more available than items that were presented in intermediate positions. Primacy and recency are also the most extreme or anchor items in a list sequence (Strack & Mussweiler, 1997; Mussweiler et al., 2000; Jou, 1997, 2011; Liu et al., 2014; Liu & Caplan, 2020). In free recall, words output earlier or more reliably correspond to those with better availability within the local context (Bjork & Whitten, 1974; Rubin & Friendly, 1986; Howard & Kahana, 1999; Madan, 2021a). Each of the four types of motivation discussed over the last four chapters corresponds to a source of memory availability. Extremity in reward value also led to better memory availability. Emotional items are more retrievable, facilitated by a number of cognitive processes beyond emotionality itself, such as distinctiveness. Self-related items are also prioritised and more readily processed, evidenced by the cocktail-party effect, self-reference effect, national narcissism, and egocentric bias. Similar is also true for representations of objects that can be functionally used, even if only presented as words or pictures—perhaps due to automatic motor simulations. Many of these effects can be considered as effects of motivational salience. Memory availability can sometimes be inappropriate, as in the case of recall intrusions found with some reward procedures or, more generally, with the DRM approach. Each of these motivation-related phenomena is associated with attentional capture effects, often demonstrated with variations of the attentional blink effect. These could be related to preferential encoding effects, though this is more likely to be unrelated to the availability heuristic. Perhaps the perspective taken here has over-generalised when seeking a domain-general view of motivation influences on memory, but this view is more parsimonious than each being wholly distinct and unrelated from the others. Further consideration is needed to determine the degree of uniqueness that is necessary, and where a domain-general account is sufficiently accurate. Some reading this book might have been surprised by the amount of discussion attributed to decision-making studies and related topics, such as valuation and preferences. The perspective here is that, particularly for motivation-related concepts, decisions are primarily made based on memory. If presented with a choice between two options, a selection must be made based on existing information. This information may come from any combination of sources, including semantic memory, episodic memory, and operant conditioning.

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Several theoretical models have been proposed to bridge memory and decision making. One of the more conceptual models that bridges memory and decision making is the Preferences as Memory model proposed by Weber and Johnson (2013). This model suggests that preferences are not stable, preexisting constructs, but rather are constructed in the moment based on the memories that are most readily available. This model was later succeeded by Query Theory, which further elaborates on the process of preference construction (Johnson et al., 2007). Decision by sampling also provides a compelling account of how memory influences decision making (Stewart et al., 2006). This model suggests that people make decisions by sampling from their memories and comparing these samples to a reference point. This process is akin to drawing gumballs from a machine, where the colour of the gumball represents a particular memory or experience. Kahneman’s work on the experiencing self and the remembering self (Kahneman & Riis, 2005) also provides valuable insights into the relationship between memory and decision making. According to Kahneman, our decisions are often influenced more by how we remember events than by how we actually experienced them. This discrepancy between our lived experiences and our memories of those experiences can have profound implications for our decisions. MIN RE

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The role of emotion, reward, and motivation in memory is also a topic of considerable interest. These motivation-related factors can significantly influence memory availability, and by extension, decision making. This is consistent with the idea of multiple memory systems (Squire & Zola-Morgan, 1988), where different types of memories (e.g., semantic, episodic) are stored and processed in different ways. Work on how these biases in memory further influence decision making has only started to be explored (Palombo, Keane, & Verfaellie, 2015; Madan, Ludvig, & Spetch, 2019). Recent research has also highlighted the role of beliefs in memory and decision making (Madan, Ludvig, & Spetch, 2019; Palombo, Elizur, et al., 2021; Mason et al., 2022). Beliefs can shape our memories and influence our decisions, often in ways that we are not consciously aware of. This suggests that our memories are not passive records of past events, but rather are active constructions that are continually being updated and revised. The study of memory is not just about understanding how we remember the past; it is also about understanding how our memories shape our present and future decisions.

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10.4 Animacy effects The influence of animacy on cognition has been of interest for many decades. In a broad sense, all ‘objects’—all concrete nouns—can be divided into animate or inanimate categories. In the last chapter we focused on a subset of inanimate objects—tools, as discussed in Section 9.2 (p. 267). At least four distinct research approaches have provided convergent support for animacy as an important dimension of stimulus processing.

Animacy as a semantic feature The concept of animacy has been studied in cognitive science for its potential effects on various cognitive processes, including memory. Animate objects, due to their potential for independent action and their relevance for survival, might be expected to capture attention more readily and thus be more memorable than inanimate ones. This is a fundamental principle grounded in our evolutionary past, where discerning between animate and inanimate entities could have crucial survival implications. Perhaps a confound in many prior studies, then, is that making judgements about animacy has often been used as an incidental encoding task (Schulman, 1971; Dobbins et al., 1998; Chee et al., 2004; Kensinger & Schacter, 2006a). To ensure the notion of animacy as a word (or picture) property is clear, here are the rating instructions used when collecting stimulus ratings: The referents that words refer to vary in terms of whether they are animate or inanimate. An animate thing is something that is living and capable of self-propelled motion whereas an inanimate thing is something that is nonliving and incapable of self-propelled motion. In this study your task is to rate the animacy of the word’s referent. Ratings will be made on a scale from 1 to 7. Any referent you believe is completely inanimate should be rated a 1 and any referent you believe to be completely animate should be rated a 7. For example, the word “wall” should be rated as a 1 since its referent is completely inanimate whereas the word “rabbit” should be rated as a 7 since its referent is completely animate. (Heard et al., 2019, p. 11) Linguistic studies have shown that animacy is a relevant dimension. Animate words are more accessible and processed more quickly than inanimate words, reflecting an inherent sensitivity to animacy in language comprehension (Trueswell et al., 1994; Yang et al., 2012; Bugaiska et al., 2018). Moreover, in many languages, animacy influences word order in a sentence. Animate words often precede inanimate ones, reflecting a universal tendency to structure sentences around animate entities (Rosenbach, 2005, 2008; Branigan et al.,

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2008). These findings collectively demonstrate that animacy is not merely a semantic feature but a fundamental property that shapes language processing. Studies with pictures also show biases towards processing of animate entities— as evidenced using a variety of procedures, including categorisation by children, attentional blink, and change blindness (Massey & Gelman, 1988; New et al., 2007; Altman et al., 2016; Guerrero & Calvillo, 2016).

Animacy-related brain activity From brain-imaging studies, there is convergent evidence that distinguishing animate objects from inanimate objects occurs through both ventral and dorsal visual pathways. Many studies have specifically focused on the contrasting brain activity elicited by pictures of tools and animals (Lewis et al., 2005; Mahon et al., 2007; Anzellotti et al., 2011; Fairhall et al., 2011; Robert et al., 2023). Activations related to animate objects are particularly prevalent in ventral regions—particularly regions of the lateral fusiform gyrus. This region’s involvement suggests that the brain has developed specialised mechanisms for processing information related to living entities.

Animacy by inference In 1944, Heider and Simmel conducted a foundational study where simple shapes moved in a video such that they appeared to interact socially and be animate. Figure 10.5 shows frames from this animation, where these animated shape characters interact with each other and their environment. Despite being mere simple shapes, the narrative of the animation is quite clear and shows social interactions. Still frames from the animation do a poor job of conveying the animation, but hopefully the series here provides some indication.

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FIGURE 10.5: Frames from the Heider and Simmel (1944) animation. The shapes move around and appear to interact with each other. In this animation, simple geometric shapes of triangles and a circle moved around a rectangular area. The movement of these shapes was choreographed in a way that seemed to depict social interactions—such as chasing, fighting, and playing. Participants were then asked to describe what they saw in the animation. The simplicity of the shapes and their non-human nature allowed the researchers to investigate how people perceive and interpret movement and interaction without the influence of facial expressions or other

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human-like features. Despite the abstract nature of the shapes, the majority of participants described the movements in anthropomorphic terms. They attributed intentions, emotions, and social roles to the shapes, interpreting the animation as a coherent narrative with characters and actions. The larger triangle was often described as aggressive or bullying, while the smaller shapes were seen as fearful or playful. Participants’ descriptions were rich with human-like attributes, even though the stimuli were devoid of any inherent meaning or human characteristics. Later adaptations of the Heider and Simmel (1944) video have extended this idea to develop further animations and use the stimuli as a test of theory of mind (Klin, 2000; Klin & Jones, 2006; Martin & Weisberg, 2003; Brown et al., 2019). As an aside, the use of still images to provide a summary of movement is itself an important and rich topic. Even now, providing succinct summaries of movement is beneficial for scientific research (Madan & Spetch, 2014). The static visualisation approach takes its inspiration from the renowned Horse in Motion by Muybridge (1878, 1985), as illustrated in Figure 10.6. This breakthrough work elegantly portrayed the dynamics of motion, marking a significant leap forward for scientific understanding. The ground-breaking technology of the time allowed for the detailed study of animal locomotion with unprecedented precision. Until these photos, it was not known that a galloping horse has moments where all four feet are simultaneously off the ground.

FIGURE 10.6: Frames from a video of a running horse, adapted from “Horse in Motion” (Muybridge, 1878). VanArsdall et al. (2013) extended this animacy-by-inference work to nonwords. Participants were instructed as follows: In this task, please imagine that you are being shown a series of objects and living things that you have never seen before. They will have unusual names such as “BRUGUE,” “FRAV,” or “JOTE.” Some of these names might be considered objects, whereas others might be considered living things. Each name will be shown with a property. The property will be listed directly under the word name. You will see each name and its property for 5 s. Your task is to try to remember the property that is associated with each name. For example, you might see the following: FRAV has a round shape. In this case, you would want to remember that this name (FRAV)

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Memories that matter has the given property (has a round shape). We will be giving you a memory test later in the session. Additionally, we would like you to rate how likely this is to be the name of an object or living thing using a scale from one (1) to six (6). A rating of one (1) corresponds to “very likely to be an object” whereas a rating of (6) corresponds to “very likely to be a living thing.” So, if you think that the fact that a FRAV has a round shape (in the previous example) makes it more like an object than a living thing, you might give it a rating of one, two, or three. If you think the opposite is true, you might give it rating of four, five, or six. Some of the names might seem more like objects while some may seem more like living things—it’s up to you to decide. (p. 173)

Some of the animate properties used include: “loves to travel,” “is a photographer,” and “has a short temper.” After this rating task, participants were given a surprise recognition memory test. Recognition was better for the nonwords that had been rated as higher in animacy. In a second experiment, a free recall test was used instead—again finding better memory for the nonwords rated as animate. These findings suggest an evolutionarily developed mechanism for ‘animacy detection’ based on inferences of social causality (Vallortigara, 2011). MIN RE

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Animacy enhances memorability Words representing animate entities are better remembered. Nairne et al. (2013) showed this in two studies. Study 1 re-analyses data from Rubin and Friendly (1986) on the recall of 925 nouns. Nairne et al. (2013) categorised the nouns as animate or inanimate and added animacy as a predictor variable in regression models of recall. Results show animacy is one of the strongest predictors of recall, comparable to imagery and meaningfulness. Study 2 directly compared recall of matched lists of animate and inanimate words. Participants recalled more animate words, demonstrating an animacy advantage even when controlling for other variables. Overall, the studies provide evidence that animacy is a critical dimension for memory. Animate stimuli are remembered better than inanimate stimuli, in line with the evolutionary hypothesis that memory systems preferentially process fitnessrelevant animate content (also see Nairne, VanArsdall, & Cogdill, 2017).

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Subsequent studies have shown that this generalises and is not due to other factors. Animacy enhancements have been shown in studies of pictures and recognition memory (Bonin et al., 2014). The effect is not due to variations in mental imagery (Gelin et al., 2019), emotional arousal (Meinhardt et al., 2018), or threat (Leding, 2019a, 2019b). Hovhannisyan et al. (2021) developed a database of 1,000 object pictures, along with norms for visual and semantic properties. They then conducted two memory experiments where participants viewed pictures of objects, and were later tested on memory for those pictures, either with a visual recognition test (picture cue) or lexical recognition test (word cue). The objects were grouped into 29 categories—the animate categories were the most memorable. Studies of free recall often constrain some word properties to narrow ranges, examining the difference between discrete levels—for instance, high and low emotional arousal. Some studies, however, have let word properties vary, allowing for a variety of word properties to be considered in relation to memory within a less constrained study design. Madan (2021a) explored the relationship between 20 word properties and memorability. The objective was to juxtapose a broad spectrum of lexical, semantic, and affective properties of words to discern which attributes most significantly influence word memorability. Memorability was assessed in two datasets: the first encompassing 1,638 words presented to 147 young adults across 20 sessions; the second involving 532 words presented to 116 young adults. A plethora of word properties were considered, including the number of letters and syllables, frequency, age of acquisition, concreteness, semantic features, body-object interaction, arousal, valence, and more. The most compelling finding was the strong correlation between animacy and recall probability in both datasets; these findings demonstrate that animacy is a stronger predictor of word memorability than the properties typically considered (Rubin & Friendly, 1986; Nairne et al., 2013; Lau et al., 2018; Aka et al., 2021). Since this study, several databases of animacy ratings have been published (VanArsdall & Blunt, 2022; Jozwik et al., 2022; Félix et al., 2023; Westbury, 2023). Danger and usefulness ratings were sourced from an existing rating database; Heard et al. (2019) used the following instructions: Danger: Participants were asked to rate how dangerous a word’s referent is for human survival from 1 to 7 (1 = not at all dangerous, 7 = extremely dangerous). Usefulness: Participants were asked to rate how useful a word’s referent is for human survival from 1 to 7 (1 = not at all useful, 7 = extremely useful). (p. 11) Danger, usefulness, and size also exhibited strong correlations. These effects persisted even when controlling for relationships between word properties. For instance, while animacy and size are correlated, both

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independently predicted recall. These results align with other research emphasising the effects of animacy on memory, potentially due to attentional capture and the adaptive nature of memory for survival-relevant information. While animacy enhances memory for items, it simultaneously impairs memory for associations (Popp & Serra, 2016; Mah et al., 2023). Notably, this is convergent with each motivational domain, as discussed in earlier chapters.

10.5 Adaptive memory One view of the purpose of memory is to be useful to survival, from an evolutionary perspective (Nairne & Pandeirada, 2008, 2010; Nairne, 2010). From this view, the function of memory is to enhance fitness, focusing on the retention of information that is crucial for survival and reproduction. This viewpoint diverges from traditional memory research, which has a more agnostic view of encoding and retrieval as fundamental, basic processes that are part of cognition. This adaptive memory view provides an answer to why memory operates in the way it does. The survival-processing paradigm, described next, provides some support for this view. Here memory is enhanced when participants incidentally encode unrelated words while making ratings for relevance to a survival scenario—in comparison to other scenarios or rating tasks. The earlier discussed animacy findings also provide evidence of memory being attuned to fitness-relevant dimensions. Here we will explore these findings and others that provide convergent evidence for memory being more than just an abstracted set of cognitive processes.

Survival processing When trying to survive in the desert, some items are more relevant than others. ‘Sword’ may be more relevant—and memorable—than ‘flute,’ from a list of 30 items. But what about the overall proportion of items remembered? The basic premise of survival processing is that memory systems are tuned to remember information that is processed in terms of its survival relevance. This idea is rooted in evolutionary theory, suggesting that our memory systems have been shaped by natural selection to help us remember information that is crucial for survival. This is what Nairne et al. (2007) tested empirically. Participants were assigned to one of three rating conditions, followed by a short distractor task, and then free recall. In the survival rating task, participants were instructed: In this task, we would like you to imagine that you are stranded in the grasslands of a foreign land, without any basic survival materials. Over the next few months, you’ll need to find steady

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supplies of food and water and protect yourself from predators. We are going to show you a list of words, and we would like you to rate how relevant each of these words would be for you in this survival situation. Some of the words may be relevant and others may not—it’s up to you to decide. (p. 264) Alternatively, a second group of participants were given a moving rating task: In this task, we would like you to imagine that you are planning to move to a new home in a foreign land. Over the next few months, you’ll need to locate and purchase a new home and transport your belongings. We are going to show you a list of words, and we would like you to rate how relevant each of these words would be for you in accomplishing this task. Some of the words may be relevant and others may not—it’s up to you to decide. (p. 264) The third group was given a pleasantness rating task. Across four experiments, the survival-processing instruction consistently resulted in greater memory recall. In a later experiment, Nairne et al. (2008, Exp. 2) further demonstrated the survival-processing advantage in a within-subject design, alternating between blocks with the survival instruction and an alternate vacation instruction: In this task, we would like you to imagine that you are enjoying an extended vacation at a fancy resort with all your basic needs taken care of. Over the next few months, you’ll want to find different activities to pass the time and maximise your enjoyment of the vacation. Please rate how relevant each of these words would be for you in this vacation situation. Some of the words may be relevant and others may not—it’s up to you to decide. (p. 179) The results of Nairne et al. (2008, Exp. 2) have since been directly replicated as part of a large-scale replication project (Open Science Collaboration, 2015). The key finding from this study, and many others, is that participants typically remember more words that were processed in the survival context compared to the control conditions. This effect has been replicated across various types of materials (words or pictures) and different types of tests (free recall or recognition) (Nairne et al., 2007, 2008; Nairne, Cogdill, & Lehman, 2017; Kang et al., 2008; Otgaar et al., 2010; Burns et al., 2011). It has also been shown to be robust against other well-established memory effects, such as the depth-of-processing effect (Nairne et al., 2008; Kang et al., 2008; Bell et al., 2013, 2015; Dewhurst et al., 2017; Meinhardt et al., 2018, 2020). In a meta-analysis of 90 experiments using this procedure, 49 using betweengroup designs, and 41 using within-subjects designs, it was concluded that

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survival-processing effects tend to be medium to large (d = 0.57 and d = 0.89, respectively) (Scofield et al., 2018). In one set of follow-up studies, Soderstrom and McCabe (2011) replicated the original survival-processing effect using the same instructions as in the original study and stated earlier, but also included four comparison groups: (1) survival instructions, but the word ‘grasslands’ was changed to city and ‘predators’ to ‘attackers’ (replicating Weinstein et al., 2008); (2) the previous city change, but ‘predators’ to ‘zombies;’ (3) the original grasslands instruction but also zombies; and (4) pleasantness rating. Recall did not differ between the four survival instructions, suggesting the effect is not due to ‘ancestral priorities,’ but is more general to emphasis on survival. Survival relevance have also been demonstrated with virtual reality environments (Wang, Zhang, et al., 2023). Though survival-processing studies typically use words that are not specifically relevant to survival, Bonin et al. (2023) published a ratings database including several survival-relevant dimensions. MIN RE

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These findings suggest that our memory systems may be particularly sensitive to survival-relevant information, providing support for an evolutionary perspective on memory. However, the exact mechanisms underlying the survival-processing effect are still a topic of on-going research. Some researchers suggest that it might be due to the richness of the encoding process (i.e., survival processing encourages more elaborate and interconnected thinking), while others propose that it might be due to a specific “survival advantage” in memory.

Motivational goals Kleinginna and Kleinginna (1981) compiled 102 statements defining motivation. Many of these definitions highlight some common characteristics of motivation. It directs behaviour towards certain goals or outcomes over others. Motivation guides behaviour based on needs, incentives, or past consequences. The studies of survival processing and relevance of stimuli danger and usefulness also converge with this. It is generally agreed that there are two primary orientations of behaviour in response to stimuli or goals. Approach motivation refers to the drive or inclination to move towards a desired object, goal, or outcome. It is often associated with positive emotions, rewards, or fulfilling needs. When an

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individual is motivated by approach factors, they are drawn to engage with, seek out, or pursue something that is perceived as pleasurable or beneficial. This can include seeking social interactions, pursuing career goals, or engaging in hobbies that bring joy. Avoidance motivation, on the other hand, refers to the drive or inclination to move away from an undesired object, threat, or outcome. It is often associated with negative emotions, punishments, or potential harm. When an individual is motivated by avoidance factors, they are driven to disengage from, evade, or prevent something that is perceived as painful, threatening, or detrimental. This can include avoiding conflict, staying away from dangerous situations, or refraining from actions that might lead to failure or embarrassment. Approach and avoidance motivations are not mutually exclusive; they often interact and can be present simultaneously. The balance between these two motivations can shape an individual’s behaviour, decision-making, and emotional experiences. For example, a person might be motivated to approach a new job opportunity due to the potential rewards (approach motivation) but might also have concerns about the challenges or risks involved (avoidance motivation). The consideration of approach and avoidance motivation most closely aligns with studies of reward on memory. Some studies have described the procedure as examining effects of reward or shock motivation on memory (Weiner & Walker, 1966; Murty et al., 2011, 2012; Murty & Adcock, 2014; Bauch et al., 2014). Moreover, findings of U-shaped reward-value effects and extreme-outcome rule also fit with a view of motivation on memory (Madan & Spetch, 2012; Madan et al., 2014; Madan, Ludvig, & Spetch, 2019; Ludvig et al., 2014a). Studies of emotional memory have also ascribed motivation as being more pertinent than valence (Gable & Harmon-Jones, 2010a, 2010b; Harmon-Jones et al., 2013; Kaplan et al., 2012). Even otherwise, judgements of approach or avoidance are sometimes used as an incidental encoding task in studies of emotional memory (Kensinger et al., 2007a; Payne et al., 2008; Waring et al., 2010; Madan et al., 2020). Aesthetics is another domain that highlights the overlap between different motivational domains. Lee et al. (2023) examined the relationship between aesthetic judgements and self-reference effect (SRE). Paintings that received extreme aesthetic judgments, i.e, the most and least liked, were remembered comparably to the SRE. However, there aesthetic-memory relationship was U-shaped, rather than gradually increasing—providing additional parallels to emotional valence and reward salience. Indeed, others have investigated the relationship between aesthetics and emotion and reward processes (Berlyne, 1970; Nadal et al., 2010; Forsythe et al., 2011; Mas-Herrero et al., 2012; Marin et al., 2016). Murty and Adcock (2017) proposed that—in addition to orientation—a second dimension is also necessary: learning. This learning dimension, varying from interrogative to imperative, also influences what networks of brain regions are involved. Interrogative states are focused on active information gathering, engaging the ventral tegmental area (VTA) and dopamine systems.

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Imperative states, in contrast, are focused on immediate goals, engaging the amygdala and norepinephrine systems. One hypothesised difference in behaviour associated with these states is that relationships and the broader context are prioritised in interrogative states, whereas a more goal-directed focus on salient items is present in imperative states. While most studies have focused on only one of emotion, reward, self, or motor actions, some studies have included more than one in the same study. For instance, pairs of motivational approaches—emotion and reward (Wittmann et al., 2008; Shigemune et al., 2010; Padmala et al., 2019), emotion and self (Sakaki et al., 2011; Gutchess & Kensinger, 2018; Daley et al., 2020a, 2020b), and reward and self (Northoff & Hayes, 2011; Yankouskaya et al., 2020; Sui et al., 2023). For instance, some studies have suggested that viewing beautiful faces is rewarding (Aharon et al., 2001; O’Doherty et al., 2003; Tsukiura & Cabeza, 2008). Very few—but still some—studies have intermixed even more approaches in the same study (Yankouskaya et al., 2022). Some theoretical papers have proposed frameworks linking two or more of these motivational domains (Cardinal et al., 2002; Pessoa, 2009; Lang & Bradley, 2010; Chiew & Braver, 2011; Northoff & Hayes, 2011; Kensinger & Gutchess, 2017; Kim, 2022). The aforementioned SIMON framework and broader discussions of motivated cognition provide an approach for integrating all four discussed motivational domains (Madan, 2013, 2017b). Additionally, in grounded cognition, the situated action cycle also integrates all four of these motivational domains (Barsalou, 2020).

Food as motivation and memorandum In some studies, food is used as a reward outcome (Hare et al., 2011; Lim et al., 2011; Polanía et al., 2015; de Water et al., 2017; Duif et al., 2020; Watson et al., 2021)—refer back to Section 7.4 (p. 218). Food rewards are somewhat unique in that most other rewards are secondary reinforcers (e.g, points, money) or are otherwise less contextually desired (e.g., viewing erotic pictures in a lab study). Indeed, motivation for food—that is, satiation—can be varied by having participants fast for a period and participate in the study at a particular time of day. Food pictures have also been used in studies of emotion (Plassmann et al., 2008; Talmi et al., 2013; Montagrin et al., 2021). Staats and Hammond (1972) auditorily presented participants with a list of food and non-food words. One of the word lists used was: BLACK, PANCAKES, ROAST BEEF, SECOND, BACON, SQUARE, ANVIL, FRENCH FRIES, ICE CREAM, IRONY. Half of the participants were asked not to eat breakfast or lunch. The experimental session always occurred in the early afternoon. Salivation was measured by having a cotton swab under the participant’s tongue, replaced on each trial. Both food-deprived and nondeprived participants had low and comparable amounts of salivation for the non-food words. The non-deprived participants had more salivation for the food words; this effect was much stronger for the food-deprived participants.

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Blechert et al. (2014) developed a database—food-pics—for conducting food-related research. The database contains 568 food images and 315 nonfood images, including detailed visual characteristics (colour, size, brightness, contrast, complexity), subjective ratings (valence, arousal, palatability, desire to eat), and nutritional information (calories, macronutrients). Example pictures are shown in Figure 10.7. Several food types were rated as more palatable and desirable: (1) high calorie more than low calorie foods; (2) sweet more than savoury; and (3) whole foods more than processed foods. Ratings were collected from a large sample (N = 1, 988), allowing for individual difference analyses. Vegetarians rated meat as less palatable/desirable than non-vegetarians. Hunger positively correlated with desire to eat ratings. This database was later extended (Blechert et al., 2019), adding 328 new food pictures, expanding the cross-cultural applicability by including more foods from Middle Eastern, Asian, and other cuisines—bringing the total to 896 food pictures. Visual characteristics and subjective ratings are also updated.

FIGURE 10.7: Examples of food pictures and relevant characteristics. Reprinted from Blechert et al. (2014).

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Other studies have shown that food pictures capture attention (Mohanty et al., 2008; Piech et al., 2010; Radel & Clément-Guillotin, 2012; Montagrin et al., 2021; Watson et al., 2021). Moreover, food pictures when hungry elicit food craving-related brain activity (LaBar et al., 2001; Pelchat et al., 2004; Beaver et al., 2006; Uher et al., 2006; Blechert et al., 2016). These results demonstrate that automatic semantic processing of food stimuli can elicit a physiological response, providing convergence with the automatic emotional psychophysiological (e.g., skin conductance and heart rate) and motor simulations (e.g., TMS pulse threshold and EMG) discussed in earlier chapters. Talmi et al. (2013) framed their study as investigating emotional memory, but used food stimuli. To control for stimulus properties, emotionality was manipulated through hunger vs. satiation. Hungry participants recalled more food pictures than non-food pictures, whereas sated participants recalled both equally. This interaction suggests that hunger enhances memory for food pictures. Hungry participants were slower in a dual task to discriminate tones when viewing food vs. non-food pictures, indicating that food pictures captured attentional resources. The results suggest that hunger leads to prioritised processing of food images, increasing memory availability during retrieval. These results have since been replicated and extended (Montagrin et al., 2021). Memory for food has practical relevance as well. The ability to remember what and when food was last consumed can influence future eating decisions. For example, if someone remembers having a large, balanced breakfast, they may choose a lighter lunch. Conversely, a lack of memory regarding food intake might lead to unnecessary snacking or overeating at the next meal. Better memory for food consumption is associated with less food intake—the sensory experience of the meal contributes to the feeling of fullness and satiety (Robinson et al., 2013). Remembering what and how long ago food was last eaten is important for appetite regulation (Garbinsky et al., 2014; Seitz et al., 2021; Stevenson et al., 2022). By being mindful and aware of what has been consumed, individuals can make more informed and controlled choices about what to eat next. Memory can also influence the type of food chosen. If an individual remembers a positive experience with a healthy meal, they may be more inclined to choose similar options in the future. Conversely, negative memories associated with particular foods might lead to avoidance. The connection between memory and food consumption is not just a topic of basic research, but has broader implications. By recognising the role that memory plays in our eating behaviours, we can develop strategies and interventions that promote healthy eating patterns, support weight management, and enhance overall well-being.

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End of chapter wrap-up Summary Considering the overarching effects of motivation might offer a richer perspective than isolating individual influences of emotion, reward, selfrelevance, and motor processing. Across these domains, patterns emerge— such as attentional capture, higher rates of false memories, and impairments in contextual memory binding. The underpinning thread tying these together is motivational salience. This notion suggests that experiences which leave a significant mark are the ones that etch deeper into our memory. The locus coeruleus is a central region to motivational systems, and it is notably affected in the early stages of Alzheimer’s disease progression. Our understanding of memory is further nuanced when we consider various biases in its availability. From serial position effects to the extreme-outcome rule, these biases coalesce under the overarching concept of the availability heuristic—providing a mechanism for past experiences to drive future decisions. An evolutionary standpoint suggests that our memory systems have evolved to prioritise information relevant for survival. This perspective is supported by enhanced memory for animate stimuli and the survival-processing advantage. Such findings bring coherence to the possibility of shared mechanisms across the motivational domains discussed in previous chapters. By challenging valueneutral interpretations of memory function, we shine a light on adaptive memory’s emphasis on the utility of survival. Drawing parallels between emotional, rewarding, self-relevant, and motor-related processes, we can gain more insight into the mechanisms that are the basis for memory itself.

Reminder cues

Quick quiz 1. According to the hedonistic perspective, which type of experiences are we likely to remember the most? (a) Experiences that are particularly pleasurable or painful. (b) Experiences that align with our long-term goals. (c) Experiences that have relevance to our survival. (d) Experiences that are intellectually stimulating.

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2. The student studying for an important exam is exhibiting a form of sustained, goal-directed behaviour. What role does the locus coeruleus (LC) play in this scenario? (a) The LC plays no role in this scenario, as it is primarily involved in immediate, rather than long-term, responses. (b) The LC helps maintain the student’s motivation and focus, potentially through the regulation of norepinephrine levels. (c) The LC decreases the student’s motivation over time, leading to the need for breaks and changes in study material. (d) The LC triggers a stress response in the student, making the studying process uncomfortable and difficult. 3. Which of the following concepts is NOT related to a generalised view of the availability heuristic? (a) The cocktail-party effect, where self-related items are prioritised and more readily processed. (b) The extreme-outcome rule, where extremity in reward value leads to better memory availability. (c) Context reinstatement, where memory performance is enhanced if the same context present at encoding is also present at retrieval. (d) Recall bias, often observed in contexts like medical adherence where individuals may not accurately recall their behaviours. 4. Two cognitive scientists, Sally and Robert, are having a debate about the primary factors that influence word memorability. Sally maintains that the frequency of use and length of a word are the most crucial determinants. Conversely, Robert argues that the semantic meaning is more important. Who has a stronger case? (a) Sally, because words that are used more frequently are easier to remember. (b) Robert, because words that represent objects that are useful to us are more memorable. (c) Sally, because words that are used frequently can be retrieved more readily. (d) Robert, because words representing objects we can easily interact with are best remembered.

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5. Which statement is the most accurate characterisation of survival processing? (a) The effectiveness of survival processing is specific to evolutionarily relevant environmental contexts. (b) The effectiveness of survival processing is heavily influenced by the presence of a threat, such as predators or attackers. (c) Survival-processing effects are not necessarily tied to ancestral priorities, but rather to a general emphasis on survival, regardless of context. (d) Survival processing is effective, but less so than ratings of pleasantness as an incidental encoding task.

Thought questions ▶ Why is the survival-processing procedure so effective? How could you design a study to test your hypothesis? ▶ Do you agree that the indicated memory biases can be grouped as instances of the availability heuristic? Is there still value in considering them as distinct? ▶ What benefits are there for examining the brain regions that are common to different motivational domains?

Further reading ▶ Nairne, J. S., VanArsdall, J. E., Pandeirada, J. N. S., Cogdill, M., & LeBreton, J. M. (2013). Adaptive memory: The mnemonic value of animacy. Psychological Science, 24(10), 2099–2105. doi: 10.1177/0956797613480803 ▶ Hovhannisyan, M., Clarke, A., Geib, B. R., Cicchinelli, R., Monge, Z., Worth, T., …& Davis, S. W. (2021). The visual and semantic features that predict object memory: Concept property norms for 1,000 object images. Memory & Cognition, 49(4), 712–731. doi: 10.3758/s13421-02001130-5 ▶ Sherry, D. F., & Schacter, D. L. (1987). The evolution of multiple memory systems. Psychological Review, 94(4), 439–454. doi: 10.1037/0033-295x.94.4.439

Part IV

Deliberate strategies

Chapter 11 Strategies for deliberate memorisation

I will give you a valuable hint. When a man is making a speech and you are to follow him don’t jot down notes to speak from, jot down pictures. It is awkward and embarrassing to have to keep referring to notes; and besides it breaks up your speech and makes it ragged and non-coherent; but you can tear up your pictures as soon as you have made them–they will stay fresh and strong in your memory in the order and sequence in which you scratched them down. And many will admire to see what a good memory you are furnished with, when perhaps your memory is not any better than mine. – Mark Twain (1914)

If I could remember the names of all those particles, I’d be a botanist. — Enrico Fermi (from Lederman, 1963)

Until this point, we have focused on how motivational factors have bottom-up influences on attention and memory. Students are taught for over a thousand hours of instruction over a university degree, but rarely are they taught how to remember information effectively. Some universities have introductory ‘study skills’ courses, but these are a rarity and still may not be evidence based. In contrast, there have been hundreds of books over the years providing memory improvement training or advice (Loisette, 1898; Lorayne & Lucas, 1974; Buzan, 1986; Hagwood, 2006; Dellis, 2018). There is a fundamental gap here—conventional educational curriculum does not help people with the practical skills of long-term memorisation, a gap that self-help books of varying repute attempt to fill. 323

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When people are asked to look at a picture with the intention of remembering it, they look at it differently. That is, intentions matter when we process information. This was convincingly demonstrated in an early eyetracking study by Yarbus (1967). Here, visual search behaviour differs when people are asked to try and remember aspects of the picture, compared to free viewing or alternative instructions. This is illustrated in Figure 11.1 and has also been replicated more recently (DeAngelus & Pelz, 2009). As an aside—it is worth marvelling at the fact that Yarbus was able to measure eye movements nearly 80 years ago—at the time, the technology available was quite limited compared to today’s standards. Yarbus’ eyetracking technique involved attaching a mirror with a suction cup to the subject’s cornea of the participant’s eyes. This device, known as the “Yarbus lens,” was carefully placed so as not to obstruct the subject’s vision. The lens had a tiny mirror or a marker that moved with the eye as it shifted its gaze. The subject was seated in front of a display, such as a painting or an image, and instructed to look at it. A light source was directed at the subject’s eye, reflecting off the mirror or marker on the Yarbus lens. This reflection was then projected onto a screen or captured by a camera. By analysing the position of the reflection, Yarbus was able to determine the subject’s gaze direction and infer the sequence of eye movements, allowing him to study how people visually perceive and process images. This method of measuring eye movements was developed by Yarbus himself (Yarbus, 1967). Yarbus’ pioneering research has had a lasting impact on our understanding of visual perception and information processing, and his methods laid the foundation for modern eye-tracking technology. When not yet taught evidence-based memory strategies, students tend to re-read textbooks and re-write notes (Gruneberg, 1973; Karpicke et al., 2009; McCabe et al., 2013; de la Peña et al., 2021). However, after being taught these strategies, students will shift to using them, particularly retrieval practice. Learning more about these learning strategies, both their history and how they work, will be the focus of this chapter. Memory strategies have also been used as a component of cognitive rehabilitation (Patten, 1972; Wilson, 2009; Hampstead et al., 2014; Gopi, Wilding, & Madan, 2022). However, as this topic is outside of the focus of the current chapter, these references are only mentioned for potential further reference for those interested.

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FIGURE 11.1: Visualisation of eye movement data when viewing a scene, based on Yarbus (1967). Lower panels show eye movement data for a single participant under different viewing instructions, each based on three-minute recordings. (A) Unexpected Visitors painting by Ilya Repin (c. 1888). (B) Labelled sections of the painting. Adapted from Yarbus (1967) and Archibald (2008).

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11.1 Repetition, repetition Re-reading a text has been shown to improve recall relative to only a single reading (Arnold, 1942; Ausubel & Youssef, 1965; Rothkopf, 1968; Barnett & Seefeldt, 1989). Re-reading also led to better test performance than notetaking or summarising. This sets the foundation for a number of further questions—how many study sessions, how much time between sessions, and what should be done in these sessions?

Spacing and interleaving When you are studying a topic for a later exam, or otherwise long-term retention, spacing is a must. If you intend to study for three hours, you could study the material when for three hours in the week it was taught—weeks in advance of the exam. Alternatively, you could wait and study the material just in the days before the exam. Both of these options are considered ‘massed practice,’ as all of the studying is done in a short, concentrated period. Or, you could spend the same amount of time and spend one hour per week, spacing out your effort, but still spending the same three hours in total. The research is clear that spacing is superior. The difference between these two is illustrated in Figure 11.2A.

A

Space Mass

B

Interleave Block

FIGURE 11.2: Example of study scheduling involved in spacing and interleaving. Adapted from Weinstein et al. (2018). Spacing has been independently discovered several times (Ebbinghaus, 1885; Spitzer, 1939; Pimsleur, 1967; Landauer & Bjork, 1978) and continued to be studied over the decades (Jost, 1897; Melton, 1970; Glenberg, 1979; Zechmeister & Shaughnessy, 1980; Dempster, 1989; Bahrick et al., 1993; Kang, 2016). Figure 11.3 shows an illustrative memory performance based on repeated presentations each week for up to five weeks.

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FIGURE 11.3: Simulated memory recall performance with weekly spaced practice. Repeated practice leads to slower (shallower) forgetting over time. Cepeda et al. (2006) reviewed 317 experiments across 184 articles and comprehensively examined how the spacing between study sessions and interval to final-test related to performance. A subsequent study by Cepeda et al. (2008) implemented these principles, using two sessions that were separated by 0, 1, 2, 4, 7, 11, 14, 21, 35, 70, or 105 days, with a test delay of 7, 35, 70, or 350 days. As such, this study involved 26 groups with over 1,300 participants. Achieving the best performance on the test was dependent on the ratio of the spacing interval and test delay. A short spacing interval of just one day was best for the seven-day test delay. In contrast, a 21-day study interval led to the best performance for the 70-day test delay. If multiple study sessions are used, Kang et al. (2014) demonstrated that the interval between study sessions should be increasing, rather than equally spaced (also see Küpper-Tetzel et al., 2014; Van Hoof et al., 2021a; Madan, 2023b). Developing relatively independently of the main literature, Woźniak et al. (1995) proposed a mathematical model to optimise item-wise presentation of information, particularly with language learning in mind (also see Woźniak & Gorzelańczyk, 1994; Tabibian et al., 2019). The modelling results also support the empirical finding that study sessions should be increasingly spaced out. Spacing is a key feature of many online-learning platforms (Kim et al., 2019; Hanson & Brown, 2020; Tabibian et al., 2019; Eglington & Pavlik, 2020).

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Interleaving is a second key scheduling-based learning strategy. If you are studying multiple topics, or a broad topic that has distinct components within it, you should similarly space out your studying. For instance, let’s refer back to the earlier example of three hours of studying. If there are three topics, you should not do one hour per week, you should cover all three topics in each study session. These two approaches are referred to as blocked and interleaved practice, respectively, illustrated in Figure 11.2B. As long as there are multiple study sessions, there is inherently a level of interleaving between studying and not-studying, but likely also between studying of different topics. However, at a more granular level, interleaving is assumed to be focused on the scheduling within study sessions. First, many studies have demonstrated that, despite poorer self estimates of learning, interleaved practice leads to better performance than blocked practice (Taylor & Rohrer, 2010; Rohrer et al., 2020). Birnbaum et al. (2013) proposed that the benefits gained by interleaving are due to the contrast provided by alternating between topics, highlighting the differences between topics (also see Rohrer, 2012; Sana et al., 2017). Indeed, some studies have observed that novice learners struggle with interleaving if they do not have sufficient semantic knowledge to recognise the categorised being alternated between (Hatala et al., 2003; Shah et al., 2016; Monteiro et al., 2017; Yan & Sana, 2019). Depending on the implementation considerations, spacing can be done using automated technologies such as scheduled emails or educational mobile apps (Kerfoot et al., 2007; Blazek et al., 2016; Smeds et al., 2016). Other studies have also investigated a variety of additional aspects of interleaving (Hausman & Kornell, 2014; Rozenshtein et al., 2016; Carvalho & Goldstone, 2017; Sana et al., 2017; Van Hoof et al., 2022). Spacing is not just for study sessions—it also applies to our entertainment consumption. When describing the opposite of spacing, we usually think of ‘cramming,’ but it also is binging a TV show. Horvath et al. (2017) examined memory and enjoyment of television shows that were binge watched or watched daily or weekly. Spaced, rather than binged, watching was associated with more perceived enjoyment and better memory for the events. That said, binge watching can be associated with advanced planning considerations of time use (Lu et al., 2023). Similar findings were also observed for watching pre-recorded online lectures (also see Miyamoto et al., 2015). Relatedly, it is recommended to watch videos at normal speed, as memory can be negatively affected if watched at a faster pace (Song et al., 2018; Murphy, Hoover, et al., 2020; Nordmann et al., 2022). Some studies do show benefits of watching with increased playback speed if re-watching to review the content (Murphy, Hoover, et al., 2020).

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Retrieval practice If the goal is to perform well on a knowledge test (i.e., summative evaluation)— ensuring that the correct information comes to mind and can be produced— then practising retrieving that information is the best way to prepare. In other words, doing practice tests will lead to better performance on the ‘real’ test, in comparison to if you merely re-studied the material. This is also referred to as the testing effect, and more generally as the practice effect. The practice effect is any improvement related to practice or repetition, whereas retrieval practice and the testing effect refer to that practice/repetition being specifically ‘testing.’ For instance, even with no repetitions, participants will have better recall over successive lists due to ‘learning-to-learn’ practice effects where they become more familiar with the procedure (Dallett, 1963). So ubiquitous is the practice effect that the absence of it has been considered as a potential sign of cognitive decline (e.g., due to dementia) as this improvement relative to previous assessments is expected and needs to be adjusted for (Wechsler, 1981; Hawkins & Sayward, 1994; Iverson & Green, 2001; Smith, 2002; Wilson et al., 2009). As noted earlier with respect to aging (Section 4.1, p. 101), one of the causes of slower agerelated declines in memory performance in longitudinal samples—as opposed to cross-sectional—is due to repeated testing. Retrieval practice is often more constrained to the to-be-learned content and is conventionally considered specific to remembering facts (as opposed to procedural skills). Roediger and Karpicke (2006) contrasted study—study with study—for retention of concepts from a short text. When tested after just a five-minute delay, both groups did quite well, but there was better memory for the study—study group, 81% vs. 75%. However, after two days, the study—test group performed better, 68% vs. 54%, as well as after a oneweek delay, 56% vs. 42%. MIN RE

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In a more nuanced demonstration, Karpicke and Roediger (2008) had participants learn English words and their Swahili translations over several blocks. They included four learning conditions. In the first group, participants repeatedly studied and tested on the 40 pairs for eight blocks of the experiment. In the second group, the same procedure as the first was used, but if the test was answered correctly in the previous block, the translation pair was no longer presented during study. That is, the number of times the pair was re-presented decreased over the eight blocks, but the pair was still tested. In the third group, the opposite modification was made—pairs were

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re-studied each block, but no longer tested if they were previously responded to correctly. The fourth group had both the study and test removed if the pair had previously been responded to correctly. Demonstrating quite convincing results, on a final test that occurred one-week later, performance was at 80% for the first two groups. The third group recalled only 36% of the pairs; the fourth group only 33%. That is, those who were repeatedly tested remembered the material, those that only had to answer correctly once, did not. Karpicke and Blunt (2011) compared retrieval practice to another strategy, concept mapping, where people make a ‘mind map’ diagram of associated concepts. Single study and repeated study control groups were also included. Retrieval practice led to superior performance on several methods of assessment. These findings have since been replicated as part of a large-scale replication initiative (Camerer et al., 2018). Both multiple-choice and short answer practice tests have been found to be effective (Smith & Karpicke, 2013). Demonstrating further flexibility, Smith et al. (2013) showed that retrieval practice benefits occur even with covert (i.e, silent) retrieval. Later studies have compared performance to other strategies and tested further variations of the strategy (Szpunar et al., 2008; Butler & Roediger, 2008; Smith et al., 2016; Ferreira et al., 2019; Pan & Sana, 2021). Several meta-analyses have examined the literature, consistently finding strong evidence for the use of retrieval practice: Rowland (2014): g = 0.50; Adesope et al. (2017): multiple choice, g = 0.70, short answer, g = 0.48. Two further meta-analyses in classroom settings are described shortly (Sotola & Crede, 2021; Yang et al., 2021). The notion of studying this way is not new, having been demonstrated periodically over at least a hundred years (Abbott, 1909; Gates, 1917; Birnbaum & Eichner, 1971; Carrier & Pashler, 1992). In a comparison of repeated recall vs. single recall, Hanawalt (1937) demonstrated consistent memory decay for the single recall condition, whereas repeated recall led to near-zero decay over a two-month interval. The more recent work by Karpicke and Roediger, as well as efforts to communicate the strategy to educators (Wickline & Spektor, 2011; Agarwal et al., 2012, 2021; Khanna, 2015; Davis, 2017; Van Hoof & Doyle, 2018), have facilitated the broader uptake of this strategy. Moreover, the strength and reliability of the results has facilitated in communicating evidence of the strategy across fields so that those studying other disciplines can also be taught about it (Lyle & Crawford, 2011; Davis, 2013; Larsen et al., 2015; Yang et al., 2019; Van Hoof et al., 2021b). Ideally, retrieval practice is an activity that learners will engage in on their own. One approach for enforcing retrieval practice, from the perspective of the teacher, is to have low-stakes quizzes (Davis, 2013; Thomas et al., 2020). For instance, students may be expected to read the textbook chapter in advance of the lecture and you begin with a short quiz at the start of class, worth only a small amount relative to the final course mark—perhaps even dropping the lowest quiz marks (e.g., average of best 10 out of 12 quizzes). These quizzes would only be for the first 5–10 minutes of the lecture session, but would provide motivation for students to attempt to read the material

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in advance, be prepared to be examined on it, and to retrieve this knowledge from memory. When more substantive assessments occur every several months, performance should improve due to these low-stakes quizzes. Two recent metaanalyses evaluated the effects of quizzes on real classroom performance and found moderate effects: Sotola and Crede (2021): d = 0.42 across 52 studies; Yang et al. (2021): g = 0.50 across 222 studies. Retrieval practice can also be implemented through classroom activities, especially those that are game-like (Morris & Fritz, 2002; Stavnezer & Lom, 2019; Whitt & Haselgrove, 2023). Reviews have suggested that the benefits of both spacing and retrieval practice appear to be related to hastening the shift of memory dependence from the hippocampus to prefrontal regions (Antony et al., 2017; Van Hoof et al., 2021a). Some limitations of retrieval practice do exist. While the strategy is useful for memorisation, benefits are more limited if the assessment requires knowledge transfer or critical thinking (Brunyé et al., 2020; Endres et al., 2020; Barenberg et al., 2021; van Peppen et al., 2021). However, this may also be a constraint introduced by the specific test questions used, with higher-order knowledge questions being more beneficial to learning (Agarwal, 2019).

Not all difficulties are desirable The benefits provided by retrieval practice, spacing, and interleaving have led them to be described as desirable difficulties (Bjork, 1994), as students/participants tend to find that they make the experience of learning feel more difficult (Jacoby et al., 2008; Karpicke & Blunt, 2011; Deslauriers et al., 2019). While true, this description is sometimes incorrectly used as a mechanism. More generally, some studies have shown that text that is more difficult to read (i.e., reading disfluency)—either due to font use (DiemandYauman et al., 2011) or sentence structure (O’Brien & Myers, 1985)—is better remembered. This could similarly be due to requiring more effort, eliciting a deeper level of processing than the control condition. For further context, a number of comprehensive reviews describe these learning strategies in detail (Dunlosky et al., 2013; Weinstein et al., 2018; Madan, 2023b). Based on this evidence of reading disfluency, Banham et al. (2018) developed a computer font, Sans Forgetica, that was intended to be difficult to read. Adapted from the popular sans-serif font Helvetica, the intention was that the increased reading difficulty would result in making the content more memorable. Though the font was developed by a team of academics and graphic designers, even winning awards, a press release was made and the font distributed prior to any published research studies (RMIT, 2018). Subsequent studies by other research groups have evaluated it and found no positive effects on memory, though it was successful in causing reading disfluency (Geller et al., 2020; Taylor et al., 2020). As such, this can also be considered as evidence that the notion of desirable difficulties itself should not be viewed as a mechanism for supporting learning, while not taking away from the findings supporting retrieval practice, spacing, and interleaving themselves.

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Metacognitive judgements An important concept highlighted here is that metacognitive judgements of learning and actual performance are relatively independent. That is, even if students feel like they will remember something better in one situation than another, this may not be the case. This is a key point here, with the notion of desirable difficulties, as well as in other contexts, such as in relation to emotional events (as described in Section 6.3, p. 179). One implication of this metacognitive discrepancy is when students fill out teaching evaluations, they may criticise pedagogical practices that are evidence-based and done for their benefit. Rewards/positive affective states can also bias evaluations, such as by providing cookies to students (Hessler et al., 2018). More generally, student evaluations of teaching are biased by a variety of factors, including instructor gender and attractiveness (Ambady & Rosenthal, 1993; Wolbring & Riordan, 2016; Adams et al., 2022; Clayson, 2022). Including rigorous inclusion criteria, Uttl et al. (2017) conducted a meta-analysis of 97 studies across 51 articles and found only very weak relationships between student evaluations and learning. More generally, it is well-known that people with just a little topic knowledge overestimate their abilities—the Dunning-Kruger effect (Kruger & Dunning, 1999; Dunning, 2011). Here, however, the overestimation is simply a ‘boost,’ which perhaps could be explained by a difference in perspective of who the participants and researchers considered the ratings being relative to. What people consider to be the main ‘take home’ message from the Dunning-Kruger effect is actually the result of Rozenblit and Keil (2002), a strong overconfidence with a small amount of knowledge that diminishes with experience before increasing in estimated ability aligned with true expertise (also see Sanchez & Dunning, 2018). This could be viewed as a DunningKruger effect on the Dunning-Kruger effect. Even then, the specific curve and names commonly attributed to stages of this curve, e.g., Mount Stupid, are not from Rozenblit and Keil (2002) either. The closest original source to the well-known curve is from an online comic (Weinersmith, 2011). This overall effect, in the form it is well-known, is shown in Figure 11.4. While the details have changed, the problem is not new: there are records of similar overconfident opinions dating back to the 4th century BC, in feedback Apelles of Kos received on a painting he had been working on (Pliny the Elder, 79 AD, Book 35, Ch. 36). As the story goes, a cobbler noticed a flaw in the depiction of a sandal in Apelles’ painting and pointed it out. The artist, appreciating the constructive criticism, corrected the mistake. Emboldened by this, the shoemaker began to critique other aspects of the painting. Apelles, however, rebuked him saying, “Ne supra crepidam sutor iudicaret,” which translates to “Let the cobbler not judge above the sandal.” This phrase has since been used to caution against overstepping one’s knowledge or expertise.

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Confidence

High

Low Novice

Competence

Expert

FIGURE 11.4: The well-known curve of the relationship between confidence and experience. However, this is not what is shown by the studies by Kruger and Dunning (1999). Overestimations in ability have been demonstrated across numerous domains, as demonstrated by 65% of Americans who think they have higher intelligence than the average person (Heck et al., 2018). Watching a fourminute video made novices more confident that they could land a plane safely (Jordan et al., 2022). This video was described as “100% useless” by a trained pilot. Across multiple measures, Roy and Liersch (2013) found that people tended to rank their driving ability in the 70th percentile. Even when considering that people may have different subjective criteria when making their estimations, e.g., what makes a ‘best driver,’ participants thought they were better drivers than most. 12% of men think they could win a point off Serena Williams (YouGov, 2019), one of the greatest tennis players of all time. Overestimation biases are pervasive across many other domains as well (Glenberg & Epstein, 1987; Park & Santos-Pinto, 2010; Jansen et al., 2021).

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11.2 Content-specific mnemonics Some mnemonics are tailored to the to-be-remembered content. In contrast, scaffold mnemonics—discussed in the next section—require pre-existing memorisation of a structure that can then be applied to any content. You likely already know that making an acronym or story can help you remember information—this is considered a scaffold mnemonic technique. In primary school, many learn the acronym ROY G. BIV as a shorthand for memorising the order of colours in the rainbow: red, orange, yellow, green, blue, indigo, and violet. Alternatively, the mnemonic could be a sentence using the same first letters. In the UK, this same information has been taught to children with the mnemonic “Richard Of York Gave Battle In Vain.” MIN RE

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Later, in secondary school, mnemonics are commonly used in maths for teaching the trigonometric identities. To remember that sine is the ratio of the opposite side (in a right-angle triangle) to the hypotenuse, cosine is the ratio of adjacent to hypotenuse, and tangent is the ratio between the opposite and adjacent sides, the mnemonic SOH-CAH-TOA is used. Returning to the sentence approach, this can be taught as “Some Old Hags Can’t Always Hide Their Old Age” (many other variants are also used). Many other mnemonics have been used for use with school and university students to learn a variety of topics, including biology, history, geography, music, statistics, and time management (Jackson & Anderson, 1988; Evans, 2007; Scott & Compton, 2007; Parkinson, 2008; Stalder & Olson, 2011; Mocko et al., 2017). Acronymbased mnemonics are even used in public health initiatives, such as for recognising the signs of stroke. In the UK, the acronym FAST is used: Face (“Has their face fallen on one side? Can they smile?”), Arms (“Can they raise both arms and keep them there”), Speech (“Is their speech slurred?”), and Time (“To call 999 if you see any single one of these signs”). The use of mnemonics extends to more advanced topics as well (Pick, 1860, 1861, 1888; Gruneberg, 1973; Pinkofsky & Reeves, 1998). Returning to a stroke mnemonic again, but from the perspective of management, BRAIN ATTACK is sometimes taught to nurses working on an acute stroke unit: Blood pressure, Respiration, Airway, Imaging, Normoglycaemia, Aspirin, Temperature, Thrombolysis, Assess…, Continence, Keep up to date…(Rowat et al., 2009; Evans, 2010). Mnemonics are quite popular with healthcare professionals (McKissock, 2014; El Hussein & Jakubec, 2015; Bates, 2018). Mnemonics are also used in firefighter training (Gleason, 1991; Thorburn et al.,

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2000; Hardison & Gray, 2021), such as the wildfire safety acronym “LACES” for: Lookouts, Awareness, Communications, Escape routes, and Safety zones. Some mnemonics include taboo words mixed in—likely to enhance memorability—such as the mnemonics for remembering the names and functions of the 12 cranial nerves. Tamer (i.e., non-taboo) variants of the mnemonics also exist, such as: “Ooh, Ooh, Ooh To Touch And Feel Very Good Velvet. Such Heaven!” As before, the first letter of each word corresponds to the first letter of the name, here of the corresponding cranial nerve, in order: olfactory, optic, oculomotor, trochlear, trigeminal, abducens, facial, vestibulocochlear, glossopharyngeal, vagus, spinal accessory, and hypoglossal. A second mnemonic is used to convey the function of nerve: sensory (‘S’), motor (‘M’), or both (‘B’): “Some Say Marry Money But My Brother Says Big Brains Matter More.” For convenience, see Figure 11.5 for an illustration of the cranial nerves. These examples are a type called acrostic mnemonics, where a sentence is created where each word’s first letter represents the information to remember.

FIGURE 11.5: Cranial nerves and their function.

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Mental images, though more commonly used in scaffold mnemonics, can also be useful when learning foreign languages. Atkinson (1975) developed the keyword method, where a word that has some similarities to the pronunciation of the translated word is integrated into a mental image along with the main word of interest. Here are two examples from Atkinson (1975): The Spanish word for duck is pato (pronounced something like “pot-o”). Using the English word pot as the keyword, one could image a duck hiding under an overturned flower pot with its webbed feet and tufted tail sticking out below. In Russian the word zvonók means bell. Its pronunciation is somewhat like “zvahn-oak,” with emphasis on the last syllable, and it contains a sound that resembles the English word oak. Employing the English word oak as the keyword, one could imagine something like an oak with little brass bells for acorns, or an oak in a belfry, or perhaps an oak growing beneath a giant bell jar. (p. 822) Using the keyword method, participants learned vocabulary much better than those in the control group. At the end of a three-day learning procedure, participants in the keyword group recalled 72% of the words, with 46% for the control group. A surprise delayed test was also conducted after six weeks, here 43% for the keyword group and 28% for the control group. TrouttErvin (1990) demonstrated that the keyword method also works with other knowledge domains, such as medical terminology.

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11.3 Scaffold mnemonics Unlike content-specific mnemonics, scaffold mnemonics involve associating the to-be-remembered information with a previously stored structure that is used to provide a ‘scaffold’ for memorising the content (Worthen & Hunt, 2011). Though not a required part of the definition of this approach, these approaches tend to use imagery as a key component (Twain, 1914; Post, 1932; Higbee, 1979; Hutton, 1987).

Imagery Information that is more readily associated with imagery is remembered better than more abstract concepts, as discussed in the section about dualcoding theory (Section 9.1, p. 265). With the goal of learning associations, several studies have shown that imagining scenes that involve the two objects interacting is referred to as interactive imagery (Bower, 1970; Wollen & Lowry, 1971; Straub & Granaas, 1992). Often the use of bizarre imagery is recommended, as bizarre images are better remembered than more mundane imagery (Paivio, 1969; Wollen et al., 1972; McDaniel & Einstein, 1986; Zoller et al., 1989; Mercer, 1996; Parmar & Shaw, 2018). Toyota (2002) found, however, that this bizarreness effect was selective, only providing benefits to those with good imagery ability; there was no difference in recall of bizarre and common imagery sentences in those with poor imagery ability. However, overall memory performance was also much poorer in those with poor imagery ability. Even early on, individual imagery ability was understood as being linked to memory for imageable information (Paivio, 1969; Marks, 1973). In a US Navy training manual, bizarre images were used to simultaneously teach Morse code and the NATO alphabet (e.g., charlie [•−•− ], hotel [••••], romeo [•−•], india [••], sierra [•••]) (Ainsworth, 1979, pp. 45–51). As we recommend the use of imagery mnemonics, it is important that there are different types of imagery abilities (Betts, 1909; Sheehan, 1967; McAvinue & Robertson, 2008; Madan & Singhal, 2015). Moreover, there is variability in imagery ability, particularly considering aphantasia (Section 4.3, p. 108). In medieval times, bizarre images were often used to help with memorising verses of the New Testament. Ars Memorandi per Figuras Evangelistarum (von Rosenheim & Brandt, 1502) depicts the core ideas of the four gospels of the evangelists—Matthew, Mark, Luke, and John—through 15-block reproduced images. One of these images is shown as Figure 11.6. Each of them is represented by central iconography: Matthew is depicted as an angel, symbolising the humanity of Christ and his incarnation; Mark is depicted as a winged lion, representing the royal authority of Christ; Luke is represented by a winged ox, symbolising the themes of sacrifice and service in his gospel; John is depicted as an eagle, symbolising his focus on the divine nature of Christ and lofty theological concepts. Each individual image has several items integrated within the image scene, each numbered to correspond to the gospel chapter

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and a brief summary printed on the accompanying pages of text. From a rough translation of the medieval Latin, the numbered items on this page refer to the following events: (7) Jesus heals the Caanite woman and a man with a speech impediment; (8) Jesus feeds thousands with seven loaves of bread and a few fish; (9) Jesus casts a demon out of a boy; (10) Jesus teaches about humility; (11) Jesus’ triumphal entry into Jerusalem on a donkey; (12) Jesus tells of the Parable of the Tenants. This book, and others like it, demonstrates that bizarre imagery has been used to aid with memory, even well before the cognitive mechanisms of memory have been formally understood. These works have been discussed in many academic works as having an important role in the rise of mnemonics (Jaeger, 1983; Tamm et al., 2020). Remembering scripture continues to be useful for mnemonics (Hartzell et al., 2016; Frost & Hill, 2020).

FIGURE 11.6: Imagery used for remembering events from the gospel. (A) Second image for the Gospel of Mark, adapted from von Rosenheim and Brandt (1502). (B) Fourth image for the Gospel of Luke, from c. 1470 version.

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Peg method One approach for remembering items in a specific order is to form mental images associating the items as interacting with those from a fixed list of items, that serve as pegs for keeping the order. The most common list used with this mnemonic strategy begins with one—BUN, two—SHOE, and three—TREE. The full list is shown in Figure 11.7. To remember that PENCIL was the first item, the participant should imagine a pencil inside a hotdog bun. If the second item was POTATO, the participant may imagine a potato sticking out of a shoe, or maybe a small plastic shoe sticking out of a potato, like the popular children’s toy. This strategy is motivated by the conceptual-peg hypothesis (Lambert & Paivio, 1956; Paivio, 1969), whereby recall of a list of words is supported by association with a set of ‘peg’ words. The use of a consistent list of pegs may also aid in association formation in a manner similar to how H.M. was able to anchor new information to existing facts (see Section 4.5, p. 117).

Number

Peg

Zero

Hero

One

Bun

Two

Shoe

Three

Tree

Four

Door

Five

Hive

Six

Sticks

Seven

Heaven

Eight

Gates

Nine

Wine

Ten

Hen

FIGURE 11.7: Typical items used in the peg mnemonic.

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Bugelski et al. (1968) compared list memory for participants using this peg method with two control conditions, one involving rhyming and one without any specific instructions. Additionally, all groups were given an initial baseline list to recall prior to being provided a strategy (where applicable). Those in the control groups recalled around 6–7 of the 10 words presented, but those using the pegmethod performed near perfectly. At least, this was the case when words were presented with 8 seconds between items. Presentation rate was also varied in the study, with all groups performing poorly when there was only 2 seconds between items—recalling approximately 5 words. Here it was likely that there was insufficient time to engage in mental imagery. Several other studies have since further tested the peg method and found it to be quite beneficial for list recall (Bugelski, 1968; Bower & Reitman, 1972; Roediger, 1980a). A recent study used the peg method with children, using the rainbow mnemonic as the pegs (Ramlow & Little, 2020). The pre-school children, aged 4–5, were able to perform better on the memory test when provided with the mnemonic.

Method of loci Though still a scaffold mnemonic, the method of loci is of sufficient importance to be featured in its own section. The strategy itself is quite simple: imagine an environment you are familiar with, such as your home or workplace. When given a list of information to remember—a speech or grocery list, or list of unrelated words or sequence of playing cards—imagine walking through that environment and placing the items, or cues that can remind you of them, down along a path. To recall the list, in order, you imagine the environment again and walk along that same path, picking up the items as you go. MIN RE

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To provide a detailed example of the method of loci, consider the apartment shown in Figure 11.8A. A variety of distinct locations (i.e., loci) can be identified within it, as shown with the 35 numbers in Figure 11.8B. Here the loci sequence was determined using a clockwise path between and within rooms. The first loci is in front of a painting in the foyer, followed by loci 3–8 in the living room (on a sofa or chair [2,6,8], by a lamp [3], in front of the TV [4], near plants [5,7]). Loci were also added throughout the kitchen, on the eating table (9), on a side table (10), on the counter (11,13), oven (12), or in the sections of the cabinet/pantry (14–16). This process is continued

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FIGURE 11.8: Apartment floorplan and 35 enumerated distinct loci. throughout the hallway, office, bathroom, and bedroom. Loci can be assigned with a higher density, e.g., different shelves in the pantry or bookshelf, both on the oven and in the stove, etc. There are two major reasons that the the method of loci is a prominent mnemonic in the literature: it has ancient antecedents and it is effective. Simonides of Ceos is usually described as the first to be recorded using a version of the method of loci, a Greek poet in around 500 BC (Yates, 1966, pp. 1–2). Simonides was attending a banquet and at some point was told that someone was waiting for him outside. He left the banquet hall and very shortly after, the hall collapsed, killing everyone. Unfortunately the bodies were injured too badly to be identified. Simonides was able to remember where

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people were as he passed them when he had exited the building, allowing relatives to bury the dead. Cicero, a later user of the memory strategy himself, retold that Simonides began to teach others of this memory strategy: He inferred that persons desiring to train this faculty (of memory) must select places and form mental images of the things they wish to remember and store those images in the places, so that the order of the places will preserve the order of the things, and the images of the things will denote the things themselves, and we shall employ the places and images respectively as a wax writing-tablet and the letters written on it. (Cicero, 51 BC, ll. 351–354) The history of the method of loci does not end there, sometimes alternatively referred to as “memory palace” or “memory journey.” The memory strategy was later further taught and spread by Jesuit priest Matteo Ricci in the 1500s (Yates, 1964; Spence, 1984; Manuel, 2000). The method of loci was taught to schoolchildren, however, this was stopped in 1584 by the church as the use of bizarre and contrived imagery was thought to be unholy and was in fact rooted in pagan teachings (Yates, 1964, 1966; Patten, 1990; Brown, 2007; Madan, 2014a). This is somewhat ironic, as just prior to this decision, the strategy had been used to improve memory for bible teachings— as discussed earlier in this section, such as in Figure 11.6. Sherlock Holmes is also described as having used the method of loci in A Study in Scarlet (Doyle, 1887), as well as recent television and movie depictions. More recently, commonalities have been discussed between the method of loci and analogous strategies that predate Simonides (Kelly, 2016, 2019). Australian Aboriginal songlines associated to-be-remembered items with parts of the landscape. Recall through reciting a song or dance is cued by the landscape once again and encodes navigational information. A recent comparison of the ‘conventional’ method of loci and the Australian Aboriginal demonstrated comparable performance for the two groups, both superior to an untrained comparison group (Reser et al., 2021), with nominally better performance for the Australian Aboriginal version. In another instance, West African Luba people made memory boards (“lukasa”) where beads, varying in size and colour, are embedded within a small wooden board (Reefe, 1977; Roberts & Roberts, 1996). Here, different items are associated with each bead—each serving as a loci. A large number of studies have demonstrated the method of loci’s effectiveness with a variety of content (Ross & Lawrence, 1968; Massen et al., 2009; Qureshi et al., 2014; Sousa et al., 2021), and the strategy is even used by world-class mnemonists (Maguire, Valentine, et al., 2003; Raz et al., 2009; Foer, 2011; Dresler et al., 2017)—this will be discussed further in the next chapter. The strategy has also been demonstrated to be useful with older

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adults, offsetting age-related memory declines (Yesavage & Rose, 1983, 1984; Anschutz et al., 1985, 1987; Kliegl et al., 1990; Verhaeghen & Marcoen, 1996). While the method of loci is generally thought to require extensive experience—and performance does improve with practice—even minimal instruction with the method of loci does yield enhanced memory recall compared to an uninstructed control group (Legge et al., 2012) Additionally, modern technologies have allowed for the use of virtual environments, resulting in all participants being able to readily use the same environments (Legge et al., 2012; Caplan, Legge, et al., 2019). In the last few years, many research groups have been studying the method of loci using virtual environments (Hagström & Winman, 2018; Reggente et al., 2018; Krokos et al., 2019). A meta-analysis analysed the results of 13 studies of the method of loci (Twomey & Kroneisen, 2021), indicating a reliable medium effect size (g = 0.65). Current research has been testing the method further, such as demonstrating that the method of loci and animacy can have additive benefits (Blunt & VanArsdall, 2021). Another study compared the method of loci to survival processing (Kroneisen & Makerud, 2017). The two encoding tasks performed comparably for high-imageability words, but the method of loci was superior for low-imageability words—this may be due to effects of imagery on the association as a whole, in-line with the conceptual-peg hypothesis (Paivio, 1969; also see Madan et al., 2010). Another well-developed memory strategy called the phonetic code or Major system is described in Section 12.5 (p. 396).

Seductive details In 2008, McCabe and Castel published where participants were given summaries of psychology research studies, for instance, ‘Playing Videogames Benefits Attention.’ The findings were either accompanied by a neuroimaging picture, a bar graph, or only explained in text. Each summary was approximately 300 words in length and included errors in scientific reasoning. After each article, participants were asked to rate the article on several statements, from strongly agree to strongly disagree. One such statement was: “The scientific reasoning in the article made sense.” Across several experiments, ratings of study believability were higher when articles were accompanied by brain images than comparison conditions. The findings were interpreted as brain images providing more of a physical representation of the results than only a more abstract cognitive interpretation. This initial study was discussed widely and became relatively wellknown within the field. Some follow-up work has provided converging evidence, examining different types of brain images (Keehner et al., 2011) or neuroscience-related explanations influenced judgements (Weisberg et al., 2008; Fernandez-Duque et al., 2015). However, other studies did not replicate these findings (Gruber & Dickerson, 2012; Hook & Farah, 2013; Schweitzer et al., 2013; Rhodes et al., 2014). In particular, Michael et al. (2013) ran

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ten experiments with nearly 2,000 participants and were not able to replicate the original results. These findings, along with further discussions (Farah & Hook, 2013), suggest that this bias due to brain images is not as pronounced as initially suggested by the results of McCabe and Castel (2008). Though this is only partially relevant to discussions of memory, non-replications of initial findings tend to be not as discussed and some may only know of the following work. As such, here I decided to include these findings to provide a more comprehensive view of the field and its findings.

The myth of ‘learning styles’ When discussing evidence-based learning strategies, I would be negligent to not also comment on learning styles. Many students, parents, and educators believe that people have visual, auditory, or kinesthetic learning styles and learn best when taught in alignment with this style. Nancekivell et al. (2020) presented the idea clearly in a recent survey study: Some people report that they have a learning style or one superior way of learning information. For example, some people report that they learn best through looking such as when looking at charts or diagrams; other people report that they learn best through listening such as when listening to a teacher or podcast; and other people report that they learn best through doing such as when creating chemical models or solving wooden puzzles. (p. 223) Unfortunately, learning styles is a myth. Unlike learning strategies—such as spacing, retrieval practice, and the method of loci—learning styles are not supported by evidence-based research. Much to the contrary, an overwhelming amount of research indicates that learning styles are not related to academic performance (Coffield et al., 2004; Pashler et al., 2008; Nancekivell et al., 2020; Rogowsky et al., 2020). Learning styles are still taught in a variety of disciplines (Newton & Salvi, 2020; Newton et al., 2021; Hanson et al., 2021)— please pass this on to your colleagues outside of psychology so they do not continue to endorse these views in their educational practices. Newton and Salvi (2020) report a systematic review of 37 studies conducted between 2009 and 2020, including a total of over 15,000 educators, reporting 89.1% believed in learning styles—with no evidence of any decline in recent years. Even when teachers use evidence-based learning strategies, they typically do not teach about them explicitly (Granström et al., 2023). As you go forward, try and do this in your own practices—students need to be taught how to learn, not just what to learn.

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While we are discussing learning myths, Macnamara and Burgoyne (2023) conducted a systematic review and meta-analysis of the growth mindset intervention; across 63 studies, the effect does not generalise. Briefly, the intervention involves teaching individuals about the malleability of the brain and the potential for personal development and growth. Participants are encouraged to view challenges as opportunities for learning and growth, rather than as threats or measures of their inherent worth. Many studies have over-generalised the extent of the intervention—here, evidence suggests that the intervention does not have any meaningful effect. However, if implemented specifically for students that are academically struggling, there can be improvements (Yeager & Dweck, 2012).

11.4 Understanding and information relevance One criticism sometimes levied against the strategies described thus far is that they prioritise verbatim and rote-like memorisation, rather than true understanding. For example, even if complex visual mnemonics are used to remember a short story word-for-word, that does not necessitate that the underlying moral of the story was learned. Analogously, being able to remember a list of words does not mean that any of them are understood. From an educational perspective this is well accepted, with ‘remembering’ (originally, ‘knowledge’) viewed as the most basic level in Bloom’s taxonomy, described as being able to recall facts and basic concepts (Bloom et al., 1956; Krathwohl, 2002; Mayer, 2002). This is then followed by ‘understanding’ (originally, ‘comprehension’)—the ability to explain ideas or concepts. The subsequent categories in increasing depth of mastery or cognitive complexity are ‘apply,’ ‘analyse,’ ‘evaluate,’ and ‘create.’ The taxonomy is typically shown as a pyramid, as shown in Figure 9.1. Here the focus is particularly on the difference between understanding and merely remembering. Feynman provides an excellent example of this in Surely You’re Joking, Mr. Feynman (1985): For example, there was a book that started out with four pictures: first there was a wind-up toy; then there was an automobile; then there was a boy riding a bicycle; then there was something else. And underneath each picture it said, “What makes it go?” I thought, “I know what it is: They’re going to talk about mechanics, how the springs work inside the toy; about chemistry, how the engine of the automobile works; and biology, about how the muscles work.” It was the kind of thing my father would have talked about: “What makes it go? Everything goes because the sun is shining.” And then we would have fun discussing it: “No, the toy goes because the spring is wound up,” I would say.

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Memories that matter “How did the spring get wound up?” he would ask. “I wound it up.” “And how did you get moving?” “From eating.” “And food grows only because the sun is shining. So it’s because the sun is shining that all these things are moving.” That would get the concept across that motion is simply the transformation of the sun’s power. I turned the page. The answer was, for the wind-up toy, “Energy makes it go.” And for the boy on the bicycle, “Energy makes it go.” For everything, “Energy makes it go.” Now that doesn’t mean anything. Suppose it’s “Wakalixes.” That’s the general principle: “Wakalixes makes it go.” There’s no knowledge coming in. The child doesn’t learn anything; it’s just a word! What they should have done is to look at the wind-up toy, see that there are springs inside, learn about springs, learn about wheels, and never mind “energy.” Later on, when the children know something about how the toy actually works, they can discuss the more general principles of energy. It’s also not even true that “energy makes it go,” because if it stops, you could say, “energy makes it stop” just as well. What they’re talking about is concentrated energy being transformed into more dilute forms, which is a very subtle aspect of energy. Energy is neither increased nor decreased in these examples; it’s just changed from one form to another. And when the things stop, the energy is changed into heat, into general chaos. But that’s the way all the books were: They said things that were useless, mixed-up, ambiguous, confusing, and partially incorrect. How anybody can learn science from these books, I don’t know, because it’s not science. (pp. 297–298)

N.B. While Feynman was a Nobel prize-winning physicist, he has also explicitly and proudly described himself committing highly sexist behaviour in his very same book. More nuanced commentary has been discussed by others (Brynjarsdóttir, 2018; Behmard, 2019; McNeill, 2019), but I could not in good conscience credit his insights without also his other attributes.

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Albert Einstein had a similar criticism of memorisation without understanding (from Frank, 1947), and of being selective in what is worth remembering: I don’t burden my memory with such facts that I can easily find in any textbook. It is not so very important for a person to learn facts. For that he does not really need a college. He can learn them from books. The value of an education in a liberal arts college is not the learning of many facts but the training of the mind to think something that cannot be learned from textbooks. (p. 185) Along similar lines, Francis Bacon is quoted as saying (Herrmann & Chaffin, 1988): “feats can be performed with it [mnemonic techniques] that are marvelous and prodigious, but nevertheless it is barren thing for human uses. It is not well contrived for providing assistance to the memory in serious business and affairs” (p. 167). MIN RE

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Decades prior, Sherlock Holmes also made a critique about the lack of importance in memorising ‘irrelevant’ facts (Doyle, 1887), again in A Study in Scarlet (also see Section 3.3, p. 89). Upon Dr. Watson explaining to Sherlock that the planets revolve around the sun, Sherlock claims that the information is irrelevant and that he will do his best to forget these facts: “Now that I do know it I shall do my best to forget it.” “To forget it!” “You see,” he explained, “I consider that a man’s brain originally is like a little empty attic, and you have to stock it with such furniture as you choose. A fool takes in all the lumber of every sort that he comes across, so that the knowledge which might be useful to him gets crowded out, or at best is jumbled up with a lot of other things, so that he has difficulty laying his hands upon it. Now the skillful workman is very careful indeed as to what he takes into his brain-attic. He will have nothing but the tools which may help him in doing his work, but of these he has a large assortment, and all in the most perfect order. It is a mistake to think that that little room has elastic walls and can distend to any extent. Depend upon it there comes a time when for every addition of knowledge

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Memories that matter you forget something that you knew before. It is of the highest importance, therefore, not to have useless facts elbowing out the useful ones.” “But the Solar System!” [Dr. Watson] protested. “What of the deuce is it to me?” he interrupted impatiently: “you say that we go round the sun. If we went round the moon it would not make a pennyworth of difference to me or to my work.” (p. 19)

Of a similar view, Fadiman (1955): “A good memory is one trained to forget the trivial” (p. 36). While this distinction between memory and understanding has been relatively understudied in the cognitive psychology literature, it has been discussed sporadically over the several decades (Brown et al., 1982; Kember, 1996; Entwistle & Entwistle, 2003; Lin et al., 2015). For instance, Kember (1996) discusses the limitations of traditional approaches to learning, which often prioritise surface-level memorisation over deeper understanding. Students who adopt a surface approach tend to see assignments and readings as the end in itself, i.e., studying for the test. In these cases, students focus on reproducing surface-level aspects of the task, such as specific words or diagrams verbatim, rather than engaging with the material in a more meaningful way. This approach is detrimental to students’ long-term learning and critical thinking abilities, as it prioritises short-term results over deep understanding and intellectual curiosity. Some studies have examined memory in a way that content understanding could be manipulated. As an example, read the following passage from Bransford and Johnson (1972): The procedure is actually quite simple. First you arrange things into different groups. Of course, one pile may be sufficient depending on how much there is to do. If you have to go somewhere else due to lack of facilities that is the next step, otherwise you are pretty well set. It is important not to overdo things. That is, it is better to do too few things at once than too many. In the short run this may not seem important but complications can easily arise. A mistake can be expensive as well. At first the whole procedure will seem complicated. Soon, however, it will become just another facet of life. It is difficult to foresee any end to the necessity for this task in the immediate future, but then one never can tell. After the procedure is completed one arranges the materials into different groups again. Then they can be put into their appropriate places. Eventually they will be used once more and the whole cycle will then have to be repeated. However, that is part of life. (p. 722)

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In this experiment, Bransford and Johnson (1972, Exp. 2) presented this passage to three groups of participants. One group was given no title to the passage, as it is presented here; another group was given the title after reading the passage; and the last group was given the title before the passage. The groups with no title and title after both poor ratings of comprehension and mean number of ideas recalled. Those with the title, however, had significantly higher comprehension and recall. The title here is “washing clothes.” Here is another example from this paper: A newspaper is better than a magazine. A seashore is a better place than the street. At first it is better to run than to walk. You may have to try several times. It takes some skill but it’s easy to learn. Even young children can enjoy it. Once successful, complications are minimal. Birds seldom get too close. Rain, however, soaks in very fast. Too many people doing the same thing can also cause problems. One needs lots of room. If there are no complications, it can be very peaceful. A rock will serve as an anchor. If things break loose from it, however, you will not get a second chance. (p. 722) This passage was from the materials of Exp. 4, with the title of “making and flying a kite.” These findings demonstrate that activation of semantic context can facilitate comprehension and recall. Dooling and Lachman (1971) also investigated comprehension and memory, here by comparing: (1) random words, (2) random phrases, and (3) coherent prose, as well as (4) a relevant or irrelevant title. Several other studies have since followed up with this work (Bransford & Johnson, 1973; Smith & Swinney, 1992; Long & Spooner, 2010).

11.5 Gamification The best videogames are often described as creating memorable experiences. What if we could adapt the underlying principles that make games memorable for use with deliberate remembering? This is the goal of gamification. Gamification can be described as “the use of game mechanics and experience design to digitally engage and motivate people to achieve their goals” (Burke, 2014, p. 6). The term ‘gamification’ is relatively recent, being coined in 2002 by game developer Nick Pelling. The widespread adoption into apps did not occur until the 2010s, but the principles of gamification came far earlier (Zichermann & Cunningham, 2011; Hon, 2022). Companies have been putting toys in food packages from as early as 1912, such as Cracker Jack. Other common examples of gamification include earning points for frequent flying or shopping. Gamification is generally aligned with making the activity more similar to operant conditioning, providing frequent small rewards and allowing you to easily track your progress. Social components are also often present, such as a

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leaderboard, to encourage competition. These principles are most developed in videogames, particularly with the notion of achievements, which have been developed and discussed by both academics and videogame developers (Falstein, 2004; Blair, 2011). However, the principles are far from being contained only within videogames, especially in our contemporary society. If your favourite coffee shop gives you a ‘star’ or other small reward with each purchase, later allowing you to exchange them for a free item (but also having them expire if you refrain from purchases for too long), then this is an excellent example of gamification. Though not using the term, Pizza Hut (in Canada and the USA) has been running a gamification-based promotion for over three decades, in cooperation with primary schools. In this “Book It!” programme, children are incentivised to read books and awarded free pizzas. MIN RE

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Within a learning scenario, gamification relies on a combination of both episodic memory and operant conditioning. While the focus of gamificationenhanced learning is to enhance conscious recall, part of the benefits are accrued through intertwining reward anticipation processes with this deliberate learning. Gamification can help improve intrinsic motivation to engage in a learning activity, though does not necessarily guarantee quality of that engagement is adequate (Domínguez et al., 2013; Jagoda, 2020). Ideally gamification is used with tasks that can be broken into clear subtasks that can be objectively assessed—a multiple-choice question or a selfreport of ‘complete’ can be suitable, but the completion of open-ended thought questions are less so. Competition with peers, such as by including a leaderboard of performance relative to peers, can also be an effective approach (Festinger, 1954; Garcia et al., 2013; Amo et al., 2020; Höllig et al., 2020). Receiving ‘badges’ for accomplishing tasks or milestones is also typical (Bowen & Thomas, 2014; Hurst, 2015; Kidwell et al., 2016; Sheffler et al., 2020). Using second-language learning as an example, here the system keeps track of what information you have previously been provided with. It can then intermix new and repeated trials using a combination of spacing and retrieval practice, awarding you points for correct responses. Your cumulative score and recent progress are also likely visible to others you know. Duolingo is one platform that takes advantage of these principles (Rachels & RockinsonSzapkiw, 2018; Loewen et al., 2019; Lotze, 2020; Shortt et al., 2021). Gamification of learning a second language or technical terms is generally quite effective using commonly available websites (Karjo & Andreani, 2018; Hanson & Brown, 2020; Lu et al., 2021). Using specialised software, gamification can

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facilitate learning to play musical instruments (Graham & Schofield, 2018; Havre et al., 2018; Claussen, 2020). Gamification of learning is far from the only domain they are being used in. Any focus of behavioural change can be ‘gamified,’ with health being a particular focus (McCallum, 2012; Lister et al., 2014; Johnson et al., 2016; Koivisto & Hamari, 2019). If you have used a fitness app that gives you points or badges for being active, shows a leaderboard with your friends, or gives you nudges to complete at least a specified number of additional steps within the next ten minutes, it has been gamified. Many common to-do list apps have also integrated gamification principles (Cassells & O’Broin, 2019; Martín-García & Marín, 2020). Within higher education, gamification—particularly in the form of card or board games—has been particularly embraced within medical education, referred to in this literature as “serious games.” Several systematic reviews have recently provided an overview of the use of serious games in medical education (Abdulmajed et al., 2015; Gorbanev et al., 2018; Gentry et al., 2019), as well as developed theoretical frameworks that highlight the critical elements of game design in this context (Olszewski & Wolbrink, 2017; Rutledge et al., 2018). One such serious game has been designed to improve knowledge retention related to neonatal resuscitation training, cleverly named “RETAIN” (Cutumisu et al., 2019). Other games have been developed to improve knowledge and skill development across specialties within healthcare professionals (Tsoy et al., 2019; Cooper et al., 2019; Garrison et al., 2021). Some conventional board games are also designed to incidentally have players learn real-world knowledge, such as Wingspan (West, 2019). Edwards et al. (2021) outlined eight key questions that should be considered when developing a new gamification: (1) What are the educational goals? (2) Who is the intended audience? (3) What mechanics will work best? (4) What format do you want to use? (5) How will your learners interact with the game? (6) How do I refine my game to make sure it works? (7) How professional should my final game production be? (8) How do I measure the success of a game? See Edwards et al. (2023) for additional elaboration on each of these questions. The questions were developed based on existing guidance on curriculum development (Sweet & Palazzi, 2015).

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End of chapter wrap-up Summary Conventional education often falls short in teaching effective, long-term memorisation methods. Motivation and intention play crucial roles in memory and information processing. Memory strategies such as repetition, spacing, and interleaving enhance recall, while retrieval practice prepares for knowledgebased tests but may have limitations when knowledge transfer or critical thinking are required. These are generally considered desirable difficulties— they are learning strategies that initially seem challenging but ultimately enhance memory and learning. However, not all difficulties, like reading disfluency, are beneficial. Students’ perceptions of their learning and their actual performance often diverge, a discrepancy with significant implications. Mnemonics and bizarre imagery serve as effective memory aids, particularly the peg method and the method of loci. The myth of learning styles, the idea that people learn best when taught in alignment with their supposed learning style, lacks supporting evidence. Understanding information goes beyond simply remembering it. Bloom’s taxonomy provides a framework for this differentiation. Gamification, the application of game-design elements in non-game contexts, can improve intrinsic motivation and enhance learning and memory. Examples of gamification abound in various contexts, such as second-language learning and learning to play musical instruments. Enhancing memory and understanding requires a combination of effective evidencebased strategies and leveraging innovative techniques like gamification. By understanding these principles, we can better design educational experiences that promote not just memorisation, but deep, lasting learning.

Reminder cues

Quick quiz 1. Which of the following statements is true about retrieval practice? (a) It is considered specific to remembering facts. (b) It is more effective when paired with concept mapping. (c) It is more effective with overt retrieval. (d) It is less effective when information is re-presented.

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2. Which of the following is a limitation of using acronyms as a mnemonic? (a) Acronyms can be too complex and difficult to remember. (b) Acronyms are not effective for remembering sequences of information. (c) Acronyms are only useful for short-term memory tasks. (d) Acronyms are not suitable for use in educational settings. 3. Which of the following is NOT a characteristic of scaffold mnemonics? (a) Require pre-existing memorisation of a structure. (b) Can be applied to any content. (c) Tailored to the to-be-remembered content. (d) Requires significant initial effort to learn the structure. 4. What are some effective strategies for deepening one’s understanding of a complex topic or concept? (a) Reading the information multiple times. (b) Highlighting important information. (c) Summarising the information in your own words. (d) Engaging in discussions and asking questions. 5. Why are gamification principles thought to enhance learning? (a) They provide frequent small rewards that positively reinforce behaviour. (b) They allow learners to track their progress and receive feedback. (c) They increase intrinsic motivation to engage in learning activities. (d) All of the above.

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Thought questions ▶ The method of loci is a complex memory strategy. What are some features that likely contribute to its effectiveness? ▶ Discuss how alexithymia, anhedonia, and aphantasia relate to individual differences in memory abilities. ▶ Given the long history of memory systems and techniques, is it possible to develop an approach that can be considered wholly new and original? Bonus Points: Look into Fellows (1888) and the court case of LarroweLoisette v. O’Loughlin from 1898 and its implications to current intellectual property law. Consider the perspective that “Loisette could no more claim ownership of his memory system than a math teacher could claim ownership of calculus” (Long, 2020, p. 133).

Further reading ▶ Weinstein, Y., Madan, C. R., & Sumeracki, M. A. (2018). Teaching the science of learning. Cognitive Research: Principles and Implications, 3(1), 2. doi: 10.1186/s41235-017-0087-y ▶ Bellezza, F. S. (1981). Mnemonic devices: Classification, characteristics, and criteria. Review of Educational Research, 51(2), 247–275. doi: 10.3102/00346543051002247 ▶ Twain, M. (1914). How to make history dates stick. Harper’s Monthly Magazine, 130(775), 3–15.

Chapter 12 Memory expertise across domains

Chess provides a striking example of how knowledge can influence perception. When a novice and a master look at a position, there is a profound difference in their experience. The master sees the power of the pieces: he immediately knows which squares the bishop attacks; no conscious thought is required. More complicated matters can also be perceptual. A master can immediately perceive that a square is weak, a bishop is bad, a pawn is backward, and a queen is pinned. He can perceive all this in one or two seconds of scanning the board, while the novice has only taken in the fact that chess is being played on the board rather than checkers. […] A master cannot see the bishop on e3 as a chunk of dead wood, any more than you can look at your best friend’s face and see a meaningless matrix of colors and shapes. The master once saw the board like this, but now there is no going back (unless there is some unfortunate neurological event). The best a master can do to understand a novice’s perspective is to look at a board on which the pieces have been haphazardly placed, without any regard for chess rules or chess strategy. — Stuart Rachels (2008)

Our prior experiences shape what we remember and how we see the world. If you are an avid bird-watcher and the study then presents you with pictures of birds, the expert would demonstrate better recognition performance than a novice (Peeck & Zwarts, 1983; Wing et al., 2022). Similar results have been shown with car (Herzmann & Curran, 2011) and literary experts (Zeitz, 1994). Medical doctors can remember clinical cases better than novices (Patel et al., 1986), and electronics technicians can expertly remember circuit diagrams (Egan & Schwartz, 1979). The extent of expertise may be surprising—expert hikers can recognise previously seen mountain scenes better than novices (Kawamura et al., 2007). Experts in strategy, from chess to basketball, can 355

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recall domain-specific structured information better than novices, but have no advantage when information is unstructured (Chase & Simon, 1973; Frey & Adesman, 1976; Allard et al., 1980; Starkes & Deakin, 1985). While memory is critical for everyone, some professions and hobbies are particularly reliant on specific aspects of memory and have been studied as such. In many cases this is semantic knowledge, learned and practised over the course of many years—such as with taxi drivers and chess masters, though also true of hobbies such as bird watchers or car experts. In other cases, memory mastery is demonstrated through rapid learning of temporary information, such as with waiters and actors. Sharing many attributes with these last jobs, there are true memory champions—those that participate in regulated memory competitions. Some jobs require a mix of both semantic knowledge and learning strategies, such as healthcare professionals. The emphasis here is not on the development of expertise, other works have discussed that sufficiently (Dreyfus & Dreyfus, 1986; Ericsson & Charness, 1994; Hambrick et al., 2014; Higgins et al., 2021). Rather, this chapter is about exploring how different domains of expertise are associated with semantic knowledge, and in some cases, topic-specific strategies for remembering episodic content. There are many domains of expertise, but chess has come to be the priority for research in psychology, as described by Simon and Chase (1973, p. 394): “As genetics needs its model organisms, its Drosophila and Neurospora, so psychology needs standard task environments around which knowledge and understanding can cumulate. Chess has proved to be an excellent model environment for this purpose.” This literature grew from the foundation of de Groot (1946) and continued into a major domain of expertise research (Binet, 1894; Charness, 1992; Gobet & Charness, 2006; Franklin et al., 2020). Gobet (1998) evaluated four theories of expertise in relation to chess players. Each theory proposes a different explanation for how experts are able to remember game positions. Each theory provides a basis for expertise: (1) experts use knowledge of patterns to group pieces into chunks; (2) experts use a search process to retrieve information from memory; (3) experts have larger working-memory capacity due to knowledge; (4) experts use templates or mental representations to aid in recall. Each theory provides some support for observed behavioural effects.

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12.1 Structured knowledge Though it may not have been apparent at the beginning of this chapter—be it actor or bird watcher, taxi driver or chess grandmaster—the underlying memory feats are not so different. Understanding of underlying knowledge structures, through the use of chunking and schemas, allow for the more holistic comprehension of information relative to novices that can only process items as their most simplest components.

Who is an expert? In most cases, experts participating in research studies were already experts. In some cases, expertise is distinguished by a self-report measure of domainspecific experience; ideally it is validated, such as using an objective knowledge test—further discussed as tests of knowledge later in this chapter. Other times the criterion of expertise can be externally corroborated, such as for expertise associated with occupations—taxi drivers, actors, and healthcare professionals. By way of holding these jobs, the participant is a demonstrated domain expert. In other cases, experts are recruited from community groups associated with the topic of interest, such as from bird-watching groups or wine clubs. In a few studies, however, expertise is developed in the study itself, through training procedures provided to the participants (either pre/post or between groups). Like many things, expertise is multifaceted and nuanced. In many cases, becoming an expert is associated with a high degree of domainspecific knowledge, true of taxi drivers, chess players, and radiologists. In addition to this knowledge, however, there is often a degree of strategy and ‘knowing what to look for,’ otherwise referred to as schemas, pattern recognition, or knowledge representations. These aspects are more about how the information is processed, and as such, rote memorisation of knowledge—or access to externalised knowledge (e.g., via the internet)—is not equivalent to true expertise. Nonetheless, here we will discuss the relevance of memory/knowledge to the everyday feats of those who are domain experts, though this is only a facet of their expertise. Several key approaches have been developed to study expertise, referred to as knowledge elicitation—Olson and Biolsi (1991) and Hoffman et al. (1995) provide overviews of these various approaches, but here we will discuss some of the main ones. Figure 12.1 shows a summary of these methods. The think-aloud approach involves having experts articulate their thought processes while they perform a task (Ericsson & Simon, 1984; Chi, 1997; Ericsson, 2006). By providing a narration of their thought processes, researchers can ‘listen in’ and gain insights into the cognitive processes and strategies the expert employs. The method is often used in problem-solving and planning tasks where it is useful to understand the steps that the expert considers and works through. In this approach, individuals are instructed to

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Knowledge elicitation method

Outcome representation

Observing expertise within familiar tasks Task analysis Observation Simulated familiar tasks

Strategies

Interviews Unstructured Structured (e.g., probe questions or test cases) Contrived tasks Memory recall Think aloud Sorting and rating tasks Mental map/graph generation

Key concepts and vocabulary

Associations between concepts

FIGURE 12.1: Overview of procedures used for expertise knowledge elicitation and the associated representations obtained. verbalise their thoughts, assumptions, and considerations, effectively ‘thinking aloud.’ The approach does have its limits though, as talking while performing a task might influence the critical cognitive processes involved (Chi et al., 1994; Ericsson & Simon, 1998; Burt et al., 2022). In some cases, the critical cognitive process may be automatic and a conscious account may be epiphenomenal (de Groot, 1946; Kiesel et al., 2009). A variety of studies have demonstrated that domain-specific expertise is associated with qualitative differences in knowledge representations (Tanaka et al., 2002; Coderre et al., 2008; Ivy et al., 2021). One approach for assessing knowledge representations is to use a sorting task, such as asking doctors to create a hierarchical diagram where different diagnoses are grouped together (Cain et al., 1998; Coderre et al., 2008). Structured interviews and diaries can also provide insight into knowledge representations, for instance to understand computer programming expertise (Campbell et al., 1992). As an example, one interview question in this study was: “When you know there’s a problem, but you aren’t sure exactly what is causing it, how do you go about finding it?” Collecting richer data from expertise behaviour is also informative, such as eye movements for visual search and brain imaging of the regional activations that underlie the cognitive processes. Comparing visual search patterns between domain experts and novices can provide insight into how experts process visual cues differently due to their accumulated experience. The most well-known examples where this has been demonstrated are with chess

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grandmasters (Charness et al., 2001; Reingold et al., 2001), but also extend to sports (Mann et al., 2007; Klostermann & Moeinirad, 2019) and arts training (Nodine et al., 1993). Driving experience also changes eye movements— experienced drivers focus more on the road and further ahead, their eye movements distributed more widely across the driving scene (Mourant & Rockwell, 1972; Chapman & Underwood, 1998; Nabatilan et al., 2013; Robbins & Chapman, 2019). Brain-imaging studies have been used to investigate chess expertise (Atherton et al., 2003; Bilalić et al., 2010; Krawczyk et al., 2011), as well as other domains (Gauthier et al., 2000; Milton et al., 2007; Bilalić et al., 2016; Martens et al., 2018; Meshulam et al., 2021). Further examples of expertise-related brain-imaging findings are discussed throughout this chapter. Though not a focus here, physics expertise has been one of the prominent focuses as the literature has developed (Larkin et al., 1980; Chi et al., 1981).

Lexicons of knowledge Expertise in any given domain is often accompanied by a deep and nuanced understanding of the subject matter. A hallmark of expertise is a rich, topic-related vocabulary. This specialised vocabulary allows experts to communicate complex ideas efficiently, differentiate between subtle variations, and express themselves with precision. More than just communicating nuanced concepts, an extensive vocabulary facilitates cognitive processes—including categorisation, memory retrieval, and problem solving. For instance, medical terminology is a rich topic unto itself (Fleming, 1994; Chabner, 2012; Taylor, 2017; Fremgen & Frucht, 2019). A medical professional might use a term like “encephalitis”—where encephal- means brain and itis means inflammation. While these terms are common language for them, they can be complex or unfamiliar to those outside the medical field. A wine connoisseur might have a diverse lexicon to describe the taste, aroma, and appearance of wines (Lehrer, 1975, 1983; Brochet & Dubourdieu, 2001; Langlois et al., 2011; Koenig et al., 2020). They might use terms unfamiliar to a causal drinker, like “tannic”—referring to the dry, puckering taste from tannins in wines—or “buttery”—describing a creamy texture often found in wines like Chardonnay. Some topics are associated with knowledge, but are also relatively common to everyday interactions (Rozenblit & Keil, 2002). For instance, how does a key press on a computer keyboard work, or even a key turn within a cylinder lock? Many may not realise the extent of specialised vocabulary and nuance associated with some of these topics. With computer keyboards as a starting point, there are communities of mechanical keyboard enthusiasts that view this as a hobby. Initially you might just think of the ‘key caps’ and changing them to be different colours, but these can come in different profiles (i.e, curvature of the keys, which also differ across rows of the keyboard), types of plastic, and manufacturing processes (e.g., ‘doubleshot’). This is then compounded by variations in the components of a

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keyboard that are less visible, such as the switches that are just below the cap that determine if a key is pressed or not. These key switches, which consist of upper and lower housings, a stem, crosspoint, and a spring, work together to register a keypress when the user applies sufficient actuation force—as shown in Figure 12.2A. The stem connects the switch to the keycap, while the switch is held in place by being mounted to a plate. Switches are comprised of several parts that can be modified, such as adding more lubrication, changing the spring, and adding rubber dampeners (‘o-rings,’ which themselves can vary in thickness, hardness, material, and colour). As the user presses down on the keycap, the spring within the switch provides resistance, determining the actuation force required for the keypress. If sufficient force is provided, the key is pressed down and contact is made between the two portions of the crosspoint, this connection then sends a signal to the printed circuit board (PCB), which in turn communicates with the computer. A variety of switches are made, designed to either provide a more ‘tactile’ feedback when the key counts as being pressed, be more audibly ‘clicky,’ or move ‘linear’ with less tactile or auditory feedback, or vary in the amount of force required to register as a key press. Larger keys like the spacebar and enter key use stabilisers to maintain a level keypress and prevent wobbling. I suspect that most reading this book have experience with computer keyboards and may even use them for several hours in a day at times, but were not aware of the vast nuance and vocabulary that can be associated with them, unlike the more readily apparent expertise associated with some other hobbies, such as bird watching and wine tasting. MIN RE

DER CU E

Transitioning from the topic of mechanical keyboard ‘keys’ to another domain, the terminology and mechanics of a key and door lock are also surprising and complex, despite being a frequently used device. The knob is the portion easily gripped and turned, housing an intricate mechanism, the cylinder. The lock cylinder houses the springs, driver pins (top), and key pins (bottom)—as shown in Figure 12.2B. When the correct key is inserted, the key pins are lifted to align with the shear line, a boundary separating the driver and key pins. At the same time, the driver pins are pushed above the shear line by the springs, which provide tension to hold the pins in place. The unique pattern of cuts in a key is the bitting, where each pin aligns with a depth of cut—set to an increment or step of depth number. The root depth, the distance from the bottom of the key blade to the deepest part of the cuts, determines the height at which the bottom pins need to be lifted. If master

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FIGURE 12.2: Internal structure of (A) keyboards and (B) lock key cylinders. pins are present between the top and bottom pins, the lock can work with multiple keys, creating a master key system. In typical locks, the driver pins are of a consistent length, with only the key (and master pins) varying in length to match the key bitting. In high-security locks, the driver pins may also be designed to vary in length to increase resistance to lock picking. Once the pins are aligned with the shear line, the cylinder rotates, allowing the lock to open. As discussed in Section 4.1 (p. 102), there are many topics of expertise that we have knowledge about—though not all of them stay with us over time. For example, children may know more about dinosaur names and species than their parents do. As one fun fact—there is less time separating us from the Tyrannosaurus rex than the T. rex from the Stegosaurus. The T. rex lived during the Late Cretaceous period, approximately 68 million years ago; however the Stegosaurus lived during the Late Jurassic period, around 150 million years ago.

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Returning to the DRM procedure, Castel, McCabe, et al. (2007) found more intrusions in a list of animal names based on names of football teamsrelated animals (e.g., DOLPHINS, BRONCOS, FALCONS), in relation to knowledge of football. Knowledge-based intrusions have also been found in relation to other domains of expertise (Arkes & Freedman, 1984; Baird, 2003; Mehta et al., 2011). As a further example of a similar task, consider if a participant was given the following list of 12 animals and asked to categorise them into two groups: RAVEN, PANTHER, RAM, PELICAN, HAWK, RAPTOR, BULL, HORNET, BUCK, FALCON, LION, EAGLE While most would categorise these animals based on if they can fly or not, an American sports buff may instead group them based on if they are the name/animal for a football (NFL) or basketball (NBA) team. Here the first three and last three animals are NFL football teams; the middle six animal names are NBA basketball teams. The language of expertise is quite nuanced and complex. Most studies of expertise compare experts to novices, but a few studies compare different groups of experts—showing how different training backgrounds can end up in the same place, but with different knowledge representations. An excellent example of this was demonstrated by Boehler et al. (2016). The focus of this paper is how two different medical professionals approach a complex medical procedure. Briefly, the procedure involves diagnosing and treating problems in the bile duct or pancreas, such as to remove gallstones or take biopsy samples. This procedure is performed regularly by both the surgeons and gastroenterologists participating in the study. Using structured cognitive task interviews, the researchers found that differences in professional training led gastroenterologists to use a more rational and theory-based approach, whereas surgeons used a more practical approach based on physical and technical processing. It was also found that the two types of medical professionals had different emphases on stages of the procedure when describing the procedure protocol (Canopy et al., 2015). This work highlights that different training paradigms and experiences can serve as sufficient prior knowledge, but still lead to different knowledge representations. Comparable studies have also been conducted with other pairings of expertise. For example, Gilmore and Green (1988) examined planning involved in different programming languages, BASIC and Pascal, which are based on different design philosophies in syntax and structure.

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12.2 Perceptual identification Some other instances of extensive semantic knowledge are particularly associated with perceptual expertise. Two hobbies of this type are bird watchers and car experts, though this also applies to less visually reliant topics, such as bird call or wine tasting expertise.

Visual expertise Visual expertise is a form of perceptual expertise that involves the ability to quickly and accurately process and identify visual stimuli within a specific domain of knowledge. This form of expertise is often associated with hobbies or professions that require a keen eye for detail, such as bird watching, car enthusiasts, and art connoisseurs. Some studies have demonstrated the specificity of expertise, having two sets of visual stimuli and groups of experts with the associated expertise. This has been primarily done with studies of bird and car experts (Gauthier et al., 2000; Xu, 2005), but also with other domains—such as bird and mineral experts (Martens et al., 2018). In EEG studies, measures of event-related potentials (ERPs) have been used to show that experts quickly and automatically process visual information related to their domain of expertise. This has been shown across several domains, including birds (Tanaka & Curran, 2001), dogs (Tanaka & Curran, 2001), cars (Herzmann & Curran, 2011), as well as fingerprints (Busey & Vanderkolk, 2005). In particular, the N170—a negative deflection occurring approximately 170 ms after stimulus presentation—is stronger for stimuli related to a person’s domain of expertise. More generally, the N170 is typically associated with face-related processing (Bötzel et al., 1995; Bentin et al., 1996; Rossion & Jacques, 2008; Kuefner et al., 2010). With accumulated experience there is a shift from featural to configural processing; in other words, experts rely more on the spatial relationships between features rather than the features themselves. Expertise in a specific domain, such as bird watching, comes from the accumulation of knowledge and experience over time. Individuals with extensive experience in a particular field possess a rich semantic knowledge, which enables them to identify and distinguish between different aspects of their domain with ease. In the case of bird watching, experienced birders can readily identify various species of birds by observing their physical characteristics—such as size, shape, colour patterns, and distinctive markings—as well as calls, songs, and behaviours. Van Gulick et al. (2016, Exp. 3) provided some evidence of this, with expert birders performing much better than novices on both visual and semantic bird-domain tests. The activity of bird watching traces its history to Florence Merriam (1889, 1896), a pioneering female scientist. Merriam was an advocate for observing birds in their natural habitats, rather than hunting them and collecting them for private collections. This approach, which was revolutionary

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at the time, promoted ethical bird watching practices and contributed to a deeper understanding of avian behaviour. Her passion led her to develop innovative bird-watching guides and fostered a new appreciation for birds and their habitats, encouraging readers to become active participants in their conservation. As a woman in a male-dominated field, Merriam’s groundbreaking work pushed boundaries and set a new standard for ornithological study, solidifying her legacy as a pioneer in both bird watching and women’s contributions to science. An expert birder can identify a mallard (Anas platyrhynchos) by its distinctive physical characteristics, such as the male’s bright green head, white ring around the base of the neck, chestnut-brown breast, mottled brown body and wings, and long, flat, orange-coloured bill with a black tip. Female mallards have a brown head and body with a lighter underside and similar bill colouring. When distinguishing other ducks from mallards, a birder would notice that American black ducks have a darker overall plumage, with a less prominent white neck ring compared to male mallards. Mottled ducks, on the other hand, have a rounder head and a shorter, thicker bill than mallards, despite their similar mottled brown plumage. Lastly, gadwalls are slightly smaller and more slender than mallards, with a sloping forehead and a mottled grey and white plumage that contrasts with the mallard’s predominantly brown colouration. There are limits to domain-specific expertise. While bird experts have better ability to identify birds using colour and spatial frequency information (Hagen et al., 2014, 2016), they are comparable to novices when only given motion cues (Hagen et al., 2021). In another domain, art experts view paintings differently than novices, focusing on different features (Augustin & Leder, 2006; Pihko et al., 2011; Pang et al., 2013; Koide et al., 2015; Francuz et al., 2018). However, here experts do not have better recognition memory than novices (Vogt & Magnussen, 2005, 2007a), though there was better memory for features within the paintings (Vogt & Magnussen, 2007a). Poor domain-specific memory has also been shown with some medical specialists, where recognition memory is often worse for images associated with their professional expertise than general picture categories such as faces and scenes (Myles-Worsley et al., 1988; Evans et al., 2011). In these cases, it can generally be argued that expertise is associated with relevant aspects within the domain-specific category of expertise, not with all content within that category uniformly. For instance, it may not be necessary for a doctor to remember which mammogram they have and have not seen, as long as they know where to look to categorise it diagnostically. Memory was better for images that had abnormalities in them (Myles-Worsley et al., 1988; Evans et al., 2011; Schill et al., 2021). To systematically evaluate expertise in different domains, Gauthier and colleagues developed the Vanderbilt Expertise Test (VET) and later the Semantic Vanderbilt Expertise Test (SVET). The VET is a measure of object recognition and categorisation, designed to assess an individual’s ability to

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identify and differentiate between objects within a specific category (McGugin, Richler, et al., 2012). The test involves presenting participants with a series of pictures from a particular category, such as birds or cars, and asking them to identify which they have seen previously. The VET includes variations tailored to different domains, including cars, butterflies, wading birds, mushrooms, leaves, and motorcycles. The SVET, on the other hand, is designed to be a more direct assessment of semantic memory for a particular category of objects. Here participants are presented with three names of domain-related items and need to select which is ‘made up.’ The SVET includes variations for cars, planes, transformers, dinosaurs, shoes, birds, leaves, and mushrooms (Van Gulick et al., 2016). Plant identification, much like bird identification, requires a certain level of expertise to accurately recognise and differentiate between various species. Knowledge of nature and botany is crucial when foraging or simply appreciating the natural world. Expert naturalists consider various factors when identifying plants, such as location, season, smell, habitat, and subtle anatomical details. Apps have been developed to aid in plant identification using some of these characteristics, but often rely on only a coarse photo and maybe GPS location data (Tawadrous et al., 2020; Otter et al., 2021; Schmidt et al., 2022). These apps can be great in fostering interest in nature and in some cases even gamify the interactions. Unfortunately, apps can provide people with a false confidence in their abilities, perhaps mistaking hemlock—a highly toxic plant—for a more mundane and edible one, such as cilantro or parsley. A beginner naturalist can differentiate between the toxic hemlock and the edible cilantro by focusing on their most prominent distinguishing characteristics. Hemlock leaves are finely divided, fern-like, and emit a musty odour when crushed, while cilantro leaves are lobed and release a strong, aromatic scent when crushed. Additionally, hemlock’s small, white flowers are arranged in umbrella-shaped clusters, whereas cilantro’s flowers form more compact, flat-topped clusters. In the pursuit of understanding perceptual expertise, researchers have often turned to controlled laboratory settings where the learning experience and exposure to specific stimuli can be closely monitored. One such approach involves the use of novel, complex objects such as greebles (Gauthier & Tarr, 1997). Greebles are computer-generated, three-dimensional objects and were specifically designed for studies on visual recognition and categorisation. They possess a certain level of complexity and uniqueness, yet share a common structure, making them ideal for studying the development of perceptual expertise. Pictures of example greebles are shown in Figure 12.3. Studies involving greebles have provided valuable insights into the neural mechanisms underlying perceptual expertise. For instance, it has been observed that expertise in recognising greebles is associated with activation in a portion of the fusiform cortex, which overlaps with the face-selective region known as the fusiform face area (FFA) (Gauthier et al., 1999).

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Interestingly, similar fusiform regions are also activated in bird and car experts when viewing pictures associated with their domain of expertise. These groups also show face-selective activation in relation to their domain-specific expertise, suggesting that the mechanisms involved in face recognition may also play a role in other forms of visual perceptual expertise (Gauthier et al., 2000). Some degree of dissociation can still be conducted, for instance, in distinguishing car- and plane-related expertise (McGugin, Gatenby, et al., 2012). Providing some evidence towards specificity, two individuals who have acquired prosopagnosia were able to acquire expertise for greebles comparable to age-matched controls (Rezlescu et al., 2014). One of the individuals developed prosopagnosia due to stroke-related lesions to the right occipitotemporal cortex and hippocampus, the other due to resection of the right amygdala and hippocampus to control epilepsy. Also refer back to discussion of cortical specialisation, including in relation to Pokemon characters, introduced in Section 5.2 (p. 133). Studying the expertise of radiologists can provide further insight into memory in a professional context (Carmody et al., 1981; Lesgold et al., 1988; Crowley et al., 2003; Drew et al., 2013; Samei & Krupinski, 2018). Radiologists must access their extensive knowledge, encompassing human anatomy, the manifestations of disease processes, and the diverse appearances of various conditions across different imaging modalities. This process engages both semantic and episodic memory. For instance, the recognition of a rare condition in an image might be facilitated by the recollection of a similar case encountered years prior, a function of episodic memory, intertwined with the factual knowledge about the condition, a function of semantic memory. Sunday et al. (2017) developed a standardised test, the Vanderbilt Chest Radiograph Test, that requires participants to identify lung nodules on x-ray images. They found that performance in novices correlated with performance on an unrelated object configuration test with greeblelike stimuli. Schill et al. (2021) focused more on studying performance in radiologists themselves. Participants were shown images of mammograms and had to make two separate judgements—is the image abnormal, and have they seen it previously? Their study used a continuous recognition procedure, where some images were repeated within the trial sequence. Experts were better at identifying abnormal images and were particularly good at recognising previously seen images that had been abnormal. The researchers explain this effect as being related to distinctiveness, where the abnormal images stand out in memory due to the atypicality. While we are all experts in recognising faces, some people have an extraordinary ability to recognise faces and are referred to as super recognisers (Russell et al., 2009; Bate et al., 2021). The perceptual expertise associated with super recognisers is still domain-specific, limited to the recognition of faces. One test used to assess the range of face recognition abilities, the Oxford Face Matching Test (Stantic et al., 2022), has been shown to be sensitive to deficits—e.g., developmental prosopagnosia, as well as super recognisers.

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FIGURE 12.3: Examples of stimuli requiring perceptual expertise. Those shown in the same category are similar, but an expert would be able to distinguish them in, for instance, an old/new recognition test. For comparison, stimuli from another category are also shown. The first row shows birds, adapted from Duyck et al. (2021). The second row shows chess boards, adapted from Bilalić et al. (2010). The third row shows greebles, adapted from Gauthier and Tarr (1997).

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One domain of perceptual expertise not often considered, but perhaps even more impressive for it, is chicken sexing. When a chicken is only days old, it can be difficult to determine the sex of the baby chick—but not for experts, who “can sex chicks at over 98% accuracy at a rate of 1,000 chicks per hour spending less than a half second viewing the [relevant] region” (Biederman & Shiffrar, 1987, p. 640). In their study, Biederman and Shiffrar (1987) used 18 pictures of difficult cases. A sample of five experts achieved 72% accuracy. In a group of naive participants, initial accuracy was 61%. They were then given a one-page guide made by the researchers that described a simple perceptual rule that could be used to determine the sex—accuracy here rose to 84%. The experts reported that they had never been provided with a simplified diagram and only learned ‘on the job’ with feedback. Records from one hatchery in the 1960s reported that sexers were paid 1¢ for each correctly sexed bird, but charged 35¢ for each error. Visual expertise is not limited to humans—and impressive feats have been demonstrated by non-human animals. For example, Wu et al. (2013) trained honeybees to discriminate between Impressionist paintings by Monet and Cubist paintings by Picasso. The paintings were presented to the bees as pictures in a tunnel, with the reward of sugar water for choosing the correct painting. To prevent side preferences, the rewarded picture was presented on both the the right and left sides in random order. Critically, after sufficient learning has occurred in sessions comprised of only training trials, later sessions included unrewarded test trials interleaved with the still-rewarded training trials. These unrewarded test trials were included to ensure that the bees were making decisions based on visual cues rather than some way of detecting sugar water chemically; in these trials, neither painting was rewarded with sugar water. Between-groups counterbalancing was used to ensure that each group of bees had an equal chance of being trained with either Monet or Picasso paintings. This helped to control for any potential biases that might have affected their performance, and the paper reports four experiments. Similar discrimination tasks of different artistic styles have also been done with mice and pigeons, often also with Picasso and Monet paintings (Watanabe et al., 1995; Watanabe, 2017). Possibly even more impressive, however, are medical diagnosis classification studies conducted with pigeons (Columba livia), such as the detection of cancer in histopathological sample images (Levenson et al., 2015) and cardiac disease in cardiology perfusion images (Navarro et al., 2020).

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Auditory expertise Expertise with auditory perception—sounds—is another domain where existing knowledge and memory impact perception (Chartrand et al., 2008). Musical expertise is the most obvious example of specialised auditory perception. Musicians, through years of training and practice, develop a refined ability to perceive and interpret complex auditory stimuli. This expertise extends beyond the ability to distinguish between different musical notes or chords. Musicians also demonstrate superior skills in identifying the timbre of different instruments and detecting errors in pitch (e.g., perfect pitch) or rhythm (Pitt, 1994; McAdams et al., 1995; Chartrand & Belin, 2006). There are some limits to this, however—Stradivarius violins are viewed as the most finely crafted. However, when blindfolded and asked to judge which violin they prefer, expert violinists preferred the modern violins, not the Stradivarius (Fritz et al., 2012). Some criticisms followed this initial study, particularly in relation to the environment being a hotel room rather than a concert hall— these were addressed in a follow-up study that came to similar results (Fritz et al., 2017). These findings suggest that the reputation of Stradivarius is not associated with better sound quality. Some of the domains of expertise discussed with respect to visual expertise may also have auditory expertise. For instance, birders develop a keen sense of auditory perception related to bird calls. This expertise allows them to identify different species of birds based on their unique calls, songs, and other vocalisations (Sibley, 2002; Constantine, 2006; Oliver et al., 2018). Car enthusiasts and mechanics often develop an expertise in identifying issues with car engines based on the sounds they produce (Humphreys et al., 2009). A knocking sound might indicate a problem with the engine’s rod bearings, while a high-pitched squeal could suggest a problem with the belts. This form of auditory expertise is crucial in diagnosing and fixing mechanical issues. Language expertise is another domain where auditory perception plays a crucial role. Mastery of a language involves not only understanding vocabulary and grammar but also the ability to perceive and interpret subtle variations in speech sounds, intonation, and rhythm (Kim et al., 1997). Bilinguals and multilinguals, for instance, demonstrate a heightened ability to distinguish between similar speech sounds in different languages, a skill that is less developed in monolinguals (Sharifinik et al., 2021; Bsharat-Maalouf & Karawani, 2022).

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Chemical senses Identification-related expertise is not constrained to just visual and auditory modalities, but can be developed in other perceptual domains, such as the chemical senses of taste and smell. While researchers have done some studies of these senses, the emphasis had been on expertise-related changes in perceptual ability (Chollet et al., 2005), rather than on the co-occuring development of richer semantic representations reflected in flavour lexicons (Drake & Civille, 2003). Expertise here can exist in a variety of domains, including wine (Langlois et al., 2011; Croijmans et al., 2020; Koenig et al., 2020; Wang et al., 2021), beer (Meilgaard et al., 1979; Valentin et al., 2007), coffee (Croijmans & Majid, 2016; Carvalho & Spence, 2018), and perfume (Valentin et al., 2011; Veramendi et al., 2013; Allen et al., 2018). As an example, coffee experts have a larger lexicon of attributes associated with their topic of expertise, including colours, aroma (e.g., fruity, floral, nutty), taste (e.g., acidic, bitter, sweet), and texture (e.g., sticky, grainy, thick) (Hayakawa et al., 2010; Chambers et al., 2016; Batali et al., 2020). Moreover, sensory expertise here has been studied in association with specific categories of foods as well—such as cheese, mushrooms, meats, and chocolates (Drake et al., 2001; Drake et al., 2010; Maughan & Martini, 2012; Pelsmaeker et al., 2019; Chun et al., 2020). In research studies, experts displayed greater consistency in their assessments and employed a more sophisticated vocabulary compared to novices. This suggests that domain expertise correlates with a more refined and nuanced understanding. Moreover, our familiarity with different odours is associated with our preferences (Schloss et al., 2015). Where chess is the main topic of study for expertise, wine is definitely in the top five. While many study wine expertise because of their interest in the domain specifically, it has also served as a foundational model of expertise for cognitive science (Brochet & Dubourdieu, 2001; Parr, 2019; Spence, 2020). Of particular note is Adrienne Lehrer’s work on understanding the semantics of wine terminology and how it is used in conversation (Lehrer, 1975, 1983). In her book, Wine and Conversation (Lehrer, 1983), she thoroughly discusses wine as both a linguist and a wine enthusiast. The book spans three sections. First, delving into the semantics of wine words such as “dry” and “robust,” but also into more evaluative and metaphorical ones like “honest.” In the second section, Lehrer describes experiments designed to test whether people talking about wine actually use wine words in mutually consistent ways and to what extent they manage to communicate with them. The experiments, conducted with two groups of sophisticated but nonprofessional wine tasters, revealed little consensus on the meanings of wine words. The third section of the book is about the communicative functions of wine talk. Lehrer summarises a number of ways of classifying the uses of language. Wine sommeliers have been shown to not only have richer lexicons to describe flavours—demonstrating not only a more nuanced semantic representation and odour identification, but also better episodic memory in

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an old/new odour recognition test (Parr et al., 2002, 2004) and in recall of wine-related vocabulary (Hughson & Boakes, 2002, 2009). Some researchers have also worked to standardise the associated vocabulary, such as developing hierarchical representations of descriptive characteristics (Noble et al., 1984, 1987; Gawel, 1997; Gawel et al., 2000; Pickering & Demiglio, 2008)—see Figure 12.4. MIN RE

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An expert wine sommelier would be able to use their knowledge and rich vocabulary to expertly describe the differences between different wines. Here is an example, written with the consultation of a sommelier: Pinot Grigio and Sauvignon Blanc, two widely enjoyed white wines, each offer unique flavor experiences that are best appreciated when understood in greater depth. A Pinot Grigio presents a tasting journey that begins with the initial flavor impressions of crisp green apples and freshly sliced pears. This fruity opening is likened to the refreshing aura of a summer’s afternoon in a fruitful orchard. As the tasting experience develops, more complex elements subtly emerge, resembling nuances of blossoming honeysuckle or a mild smokiness akin to a warm pebble beach. The conclusion of the tasting experience is characterised by a smooth, slightly mineral aftertaste, reminiscent of a mountain stream gently washing over a warm stone bed. This wine’s refreshing nature and relative simplicity make it a fitting companion to light, summery dishes, such as grilled white fish served with a zesty citrus salsa or a simple chicken salad garnished with fresh herbs and creamy cheeses. Contrastingly, Sauvignon Blanc delivers a more intricate sensory experience. The initial taste sensation is a lively burst of green, herbaceous flavors, evocative of standing at the edge of a lush, dew-kissed meadow at dawn. This bright, fresh introduction evolves to reveal an underlying complexity that includes hints of ripe passion fruit and zesty grapefruit. In certain regional variations, a smoky flintiness can be discerned, adding an enigmatic layer to the flavor journey. The aftertaste of Sauvignon Blanc is distinctive, leaving a lingering, vibrant, mouth-watering acidity. This complex and charismatic flavor profile is suitably paired with rich and bold dishes, such as tangy goat cheese, mussels in a garlic-infused broth, or grilled asparagus tossed in a zesty lemon vinaigrette.

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Memories that matter Moving to reds, Cabernet Sauvignon and Malbec are both celebrated for their robust character, share common ground in their flavor profiles. Both wines offer a rich sensory experience characterised predominantly by dark fruit flavors—particularly black cherry and plum. However, as the tasting journey unfolds, the distinctions between the two wines become more pronounced. Cabernet Sauvignon, with its full-bodied and complex profile, introduces a layer of secondary flavors that hint at vanilla, leather, and tobacco, particularly when the wine has been oak-aged. Its robust tannins give it a hearty structure and a discernible astringency, offering a wine tasting experience that demands attention. On the other hand, Malbec, typically medium-bodied, presents a softer, more velvety texture. Its tannins, though present, are smoother than those of Cabernet Sauvignon. As the Malbec tasting experience evolves, it unveils unique earthy notes along with a hint of spice, like black pepper or licorice, distinguishing it from its Cabernet counterpart.

Similar expertise also exists in other domains, such as perfume. An expert perfume critic needs to have a rich sensory vocabulary and deep comprehension of the chemical senses, allowing them to discern and articulate the delicate nuances and evolution of a fragrance over time. Their knowledge extends beyond the sensory experience, delving into the interplay of fragrance components, the artistry of the perfumers, and the context of the perfume within the broader market and cultural trends. A perfume critic’s expertise lies in their ability to translate the complex, ephemeral nature of scent into vivid, understandable language, enabling others to appreciate the depth and artistry encapsulated in each bottle of perfume. Furthermore, expertise in some of these domains is not constrained to just the sensory experiences directly—for instance, coffee expertise includes a wealth of knowledge related to the preparation, such as immersion vs. percolation brewing, burr grinders with aftermarket burrs, and brew extraction profile.

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FIGURE 12.4: A section of the wine aroma wheel. Adapted from Noble et al. (1987).

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12.3 Schematic frameworks Expertise related to schemas are associated with an individual’s organisation of knowledge based on experience, used dynamically when presented with new experiences. People often rely on these mental frameworks, or schemas, to make sense of new information quickly. Some professions of memory experts particularly rely on their knowledge across sustained schemas, such as taxi drivers and chess grandmasters. Admittedly, expertise in domains of perceptual expertise do rely on schemas as well—these are not mutually exclusive categories.

London taxi drivers Maguire et al. (2000) examined the hippocampal structure in London taxi drivers and based on the well-established role of the hippocampus in navigation behaviour. The taxi drivers were all right-handed men, aged 32—62, and their brain structure was compared to a sample of 50 righthanded men who were not taxi drivers, as a ‘control’ group. The size of the hippocampus as a whole did not differ between the groups. However, differences were found when the hippocampus was segmented along the longaxis, into anterior, body, and posterior sections (also see Section 5.4, p. 146). Here the posterior hippocampus was relatively larger for the taxi drivers than the control participants, whereas the anterior hippocampus was relatively smaller for the taxi drivers. Moreover, the magnitude of these volumetric differences was related to the number of years of taxi driving experience, ranging from 1.5 to 42 years (mean of 14 years). With the study published in 2000 and at least two drivers had around 40 years of taxi driving experience, they had been on the job since the 1960s. A requirement in being able to drive a taxi in London is that a comprehensive navigation-based exam, called The Knowledge, is part of the licensing process. The drivers in this study took between 10 months and 3.5 years to pass this exam, though some trained continuously while others practised part-time. The Knowledge involves memorising 320 routes between specified start and end points in Greater London, along with a route between these points, i.e., which way to turn at each intermediate intersection, as well as the reverse route. This further involves memorising critical details such as which are oneway roads and what points of interest are near the route taken. The first route listed, Run 1, is Manor House Station to Gibson Square. The training material provides a more extensive and representative list of the points of interest, and their locations—this route has over 50 points of interest listed as examples. Only so much of the routes can be learned with a map and notebook; practice also necessitates actually travelling between the points. The Knowledge was first introduced in 1865 and the black taxi cabs are considered one of the iconic features of the city of London. For further insights into how taxi drivers study for the assessments, see Griesbauer et al. (2022).

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In a subsequent study, Maguire, Woollett, and Spiers (2006) compared London taxi drivers and bus drivers. Only taxi drivers had the relative regional hippocampal volumetric changes, despite the two groups being matched for years of driving experience. Moreover, the taxi drivers performed worse on a neuropsychological assessment involving remembering complex visual representations, perhaps suggesting that maintaining their vast navigational knowledge makes it more difficult to learn new spatial representations. In a subsequent study, it was found that taxi drivers were better than non-taxi drivers at learning to navigate a new area, but worse when the new area had to be integrated with London knowledge (Woollett & Maguire, 2010). Some research has also been done with a taxi driver who is also a patient with bilateral hippocampal damage (Maguire, Nannery, & Spiers, 2006). The patient in this study was 65-years-old at the time of the research and had spent 37 years as a London taxi driver, but had stopped for the two years prior to the research study. He had stopped taxi driving due to the onset of an illness that caused memory deficits and later progressed to involve seizures as well. The symptoms and progression are being managed with a drug treatment, but MRIs indicate relatively localised hipppocampal damage, but intact surrounding medial temporal lobe corticies (e.g., entorhinal, perirhinal, parahippocampal). Memory for landmarks was observed to be intact, but the patient tended to use the main artery roads more than the healthy comparison taxi drivers and thus also took longer routes between destinations. The patient became lost when not on main artery roads, which—when combined with other measures from the study—suggested that gist navigational information was able to be used independent of the hippocampus, but more detailed spatial representations were hippocampal dependent. A recent study examined regional hippocampal structure within the general population, particularly to see if the relative volumetric changes observed with the London taxi drivers were apparent continuously in relation to navigation ability (Weisberg et al., 2019). In a sample of 90 young adults, this was not borne out, with the interpretation suggesting that this effect may only occur with particularly extensive navigation expertise (also see Maguire, Spiers, et al., 2003; Van Petten, 2004; Weisberg & Ekstrom, 2021). However, a relationship has been observed between regional hippocampal volume and selfreported use of cognitive map-based navigational strategies in young adults (Brunec et al., 2019), perhaps indicating that the mechanism underlying this structural difference is more nuanced than initially considered. The results of these studies, and the training approach used for The Knowledge, dictate that expertise in this domain is likely not related to complex ‘online’ route planning, but rather is based on highly rehearsed and semanticised schema of the routes which can then be mixed-and-matched to complete a novel route. That is, taking a new passenger to their destination is less of a multi-step conscious recall and decision process and occurs more automatically based on previously memorised facts.

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Chess grandmasters Look at the chess board shown in Figure 12.5. What do you see?

FIGURE 12.5: The beginning moves of a game of chess. If you know the basics of chess, you might say that each player has taken a turn. White moved their fifth pawn (from the left) forward two positions; Black moved their third pawn (from the left) forward two. That would be it. Of the 20 possible opening moves, this is the most popular, occurring as the opening of approximately 42% of all chess games. (Twenty opening moves: each of the eight pawns can move forward one or two spaces [16 moves], each knight can move forward two spaces and left or right one [4 moves].) Black then moved their pawn to c5. This is the first set of moves in 17% of all chess games played by grandmasters (Watson, 2006). (This coordinate shorthand is well-established within the chess community.) Together, this opening is known as the Sicilian Defence—a name given to it by Jacob Henry Sarratt in 1813. A more experienced chess player would know that White always goes first. White moved their ‘king’s pawn’ to e4, to prevent Black from moving a pawn to d4—controlling the centre space. This move also frees White to begin to move their bishop or queen. In response, Black moved their ‘c-pawn’ to c5, which is known as the Sicilian Defense. This move aims to counter White’s central control and potentially allow Black to strike back later in the game.

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A chess grandmaster would further know that this is a dynamic opening that offers Black a wide range of options for countering White’s attacking plans. This opening is particularly popular at the highest levels of play, as it allows Black to seize the initiative and play for a win, rather than merely aiming to equalise the position. The Sicilian Defense’s main objective is to control central squares with Black’s pawns and pieces, while using the c5pawn to support the d6-pawn. This approach effectively challenges White’s control of the centre and hinders their ability to mount a successful king-side attack. One of the key reasons many grandmasters favour the Sicilian Defense is that it enables them to play aggressively and take the initiative, proactively dictating the course of the game instead of just reacting to White’s moves. The wealth of variations within the Sicilian Defense allows for diverse and creative play, making it difficult for opponents to predict and prepare against. Some of the most popular and well-respected variations include the Najdorf, Dragon, and Scheveningen. These variation names correspond to the opening if several other moves are followed exactly (2. Nf3 d6, 3. d4 cxd4, 4. Nxd4 Nf6, 5. Nc3). These would then differentiate based on Black’s response—a6 (Najdorf), g6 (Dragon), or e6 (Scheveningen). Even though there are only 20 possible opening moves, there are three billion possible ways the first four moves of the game could be played. MIN RE

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Chess grandmasters have been one of the earliest and most well-studied ‘memory expert’ populations (Binet, 1894; Cleveland, 1907; Djakow et al., 1927), likely due to the reliance on both semantic memory (schemas) and episodic memory (current state of the game; e.g., playing against many players concurrently [simultaneous exhibition; ‘simul’ or blindfolded chess]). It has been demonstrated that they can rapidly memorise a chess board mid-way through a game. However, they tend to perform as poorly as novices if the board positions are ‘random’ and could not have been achieved through valid play—a difference that the novices are not sensitive to (Chase & Simon, 1973; Frey & Adesman, 1976; Gobet & Simon, 1996b, 1996a; Gobet & Waters, 2003; Kiesel et al., 2009; Gong et al., 2015). This is likely related to the use of schemas and automatic judgements, rather than deliberately memorised plays. Rachels (2008) described a natural occurrence of this: Once, when I was giving a thirty-five-board simul, I noticed at one board that a piece had been moved to a different square while I was concentrating on other games. My opponent

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Memories that matter immediately apologised and put the piece back, blaming the error on his small child, who was watching. This was not a matter of ‘memorization’—I do not have a trick memory—the position just didn’t make sense with the piece misplaced. (p. 216)

Some grandmasters have accomplished even more impressive feats, for instance, “[Henry Nelson Pillsbury] played blindfold chess against twelve opponents, while also playing blindfold checkers on four boards and blindfold [cards] at several tables—he memorised the cards after a short look at them” (Schulz, 2017). In 1947, Najdorf played 45 boards of blindfolded chess concurrently: Held in the luxurious Prestes Maia Gallery, the display started around 8 PM on Friday, January 24, and finished around 7:25 PM the next day—23.5 hours later. The players sat in a horseshoelike pattern, with Najdorf seated in another room hearing his opponents’ moves and calling out his own via microphones. […] Many writers have commented on Najdorf’s gracious behavior during the event. He permitted new players to replace anyone who got tired or had to leave before a game was finished; so a total of 83 adversaries participated on the 45 boards. Once, he suggested that a player take back a bad blunder and substitute a new move, and on another occasion he insisted that a player not give up because he still had a good position (‘if you are tired, find a replacement’). José Pinto Costa, a 15-year-old opponent of Najdorf’s […] recalled fifty years later that a few times players would have the wrong position after ‘thinking with their hands’ and Najdorf would correct the position and allow the game to go on. Despite these indulgences, Najdorf finished with a score of 39 wins, 2 losses, 4 draws, an impressive 91.1 percent. (Hearst & Knott, 2009, p. 95) It is worth acknowledging that, in some cases, deliberate knowledge may be accessed only automatically and unconsciously. Rachels (2008) describes: In studying a position, a master may quickly understand that there are three viable possibilities for the player on move. But how his brain has determined this, he has no idea. And even when he is deliberating among the viable options, there is typically little inner dialogue. (p. 214) Similar perspectives have been put forth by Binet (1894), de Groot (1946), and Dreyfus (2014). Montero (2019) challenges this view, suggesting that even in one-minute-per-player chess games, players engage in conscious thought and

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deliberation. She distinguishes between automatic skills (such as riding a bike) and consciously controlled skills (such as solving a math problem), arguing that chess playing involves both types of skills. While some aspects of chess playing may become automatic with practice (such as recognising patterns), other aspects require conscious control (such as planning ahead). Chess masters train for many years, including deliberate memorisation of well-established openings and matches. Through this they develop a precise vocabulary for different sequences of moves, and complex board arrangements are not being memorised as a large number of object—location associations, but rather as holistic board schemas, reducing the amount of effort required. In some ways this is similar to reproducing a word in a foreign language script; for instance, try reading the text in Figure 12.6A.

A

ृित

B 𐑕𐑲𐑒𐑪𐑤𐑩𐑡𐑦

FIGURE 12.6: A word in a foreign script. (A) The Hindi word for ‘memory;’ (B) the word ‘psychology’ in English, but printed in Shavian script. ‘Memory’ in Shavian is 𐑥𐑧𐑥𐑼𐑦. Depending on your prior experiences, this word is either indescribably difficult to reproduce after a few minutes, or requires nearly no effort at all. In both cases, this ability to group ‘pieces’ of information based on previous training is known as ‘chunking’ (as briefly described in Section 3.1, p. 67). A less extreme example would be remembering a non-word letter string (e.g., GHLOAND) rather than an actual word. However, the use of a foreign script as an example is more apt to help appreciate the complexity of remembering a ‘pattern’ without having the requisite vocabulary. Even an English word written in an unconventional script would be incomprehensible–as in Figure 12.6B. While anyone reading this book is familiar with the 26-letter Roman/Latin alphabet used in English, its suitability has often been questioned due to its imperfect representation of English phonetics. This discrepancy has led to the development of an alternative: the Shavian alphabet (Shaw, 1962, p. 151). Based on criteria set out by Bernard Shaw and developed by Ronald Kingsley Read, this alphabet features a 1:1 correspondence between letters and phonemes, a stark contrast to the often ambiguous phonetic representation of the Roman/Latin alphabet. With its 48 letters, Shavian alphabet’s primary goal is to accurately represent the sounds of English (i.e., phonemes). Letters are in pairs based on mirroring (similar to how ‘d’ and ‘b’ relate in the Roman alphabet), reducing the number of new shapes to learn to make it more intuitive; however, this mirroring

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concept may pose challenges for some individuals with dyslexia. Though this alphabet has not become mainstream, it demonstrates that even native English speakers without experience with the script can find it unreadable— despite being designed to be more true to English pronunciation. As discussed in the last chapter, the relationship between memorisation and understanding is a complex one. Though chess involves multi-step decisions and interaction with another player, the ‘planning’ is typically based on past matches and established patterns of movements—in other words, schemas. These schemas help players recognise key positions, evaluate the strength of various moves, and develop plans for their next steps. By drawing on their knowledge of typical pawn structures, opening principles, tactical motifs, and endgame strategies, players can make informed decisions without having to calculate every possible outcome. World-renown grandmaster Garry Kasparov (2008) proclaimed: Players, even club amateurs, dedicate hours to studying and memorising the lines of their preferred openings. This knowledge is invaluable, but it can also be a trap. Many make the mistake of believing that if they know what a famous grandmaster played in this exact position back in 1962, they don’t have to think for themselves…Rote memorisation, however prodigious, is useless without understanding. At some point, he’ll reach the end of his memory’s rope and be without a pre-made fix in a position he doesn’t really understand. (p. 143) Fischer was known for his disdain for excessive memorisation of chess openings. He believed that relying too heavily on memorisation also could inhibit a player’s creativity and ability to think critically during a game. One approach for reducing the reliance of chess performance on memorisation is to use a variation of the rules where the order of pieces in the back row is randomised, with a few constraints. Based on these constraints, there are 960 legal starting positions. This variation was invented by Bobby Fischer in 1996 and is referred to as Fischer random chess or Chess960. (Prior to this variation, a less constrained variation known as shuffle chess had already existed.) Further variations to the chess composition, board size, and other rules are known as fairy chess, including the addition of new chess pieces based on variations or combinations of the main chess piece movement types—leapers (knight), riders (rook, bishop, queen), and hoppers (no conventional example, can only move if jumping over another piece) (Dawson, 1928; Dickins, 1969). An example of a combined piece is the amazon, a compound of the queen and knight; there are dozens of other possible pieces based on these movement types and distances. Some computer games have instantiated ways to play fairy chess, such as Chess Evolved Online. Alternatively, another variation on chess can enhance the reliance on schemas but also temporary memorisation: blindfolded chess. Here chess moves are said aloud and the chess expert is blindfolded. They must

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maintain a mental representation of the board in their mind, along with the the problem solving that is always requisite in chess (Binet, 1894; Saariluoma & Kalakoski, 1998; Campitelli & Gobet, 2005; Hearst & Knott, 2009). Technological developments have begun to change the game. Chess artificial intelligence can plan many steps ahead of humans, with much more formalised estimates of the value of different potential future states than a human grandmaster would consider (Madan, 2020b). The advent of Deep Blue’s victory over Garry Kasparov in 1997 marked a significant turning point in the realm of artificial intelligence (AI) and its application to strategic games (Hsu, 2002). The triumph of AI over human intelligence in the game of chess, a game long considered a pinnacle of strategic and cognitive prowess, sparked a shift in focus towards a more complex and elusive target: the ancient Chinese game of Go. With simple rules but intricate strategies, Go has long been considered a challenging frontier for AI planning. The game’s complexity arises from its vast search space, which far exceeds that of chess, making traditional brute-force search strategies used in chess AI, such as those employed by Deep Blue, impractical (Silver et al., 2016). In 2016, Google’s AlphaGo defeated the world champion Go player Lee Sedol in a five-game match. This victory was a testament to the power of modern AI techniques—and also led Lee Sedol to retire from the game (Madan, 2020b). The shift from chess to Go in AI research reflects a broader trend in cognitive science and AI: the move away from schema-based planning towards more flexible and adaptive strategies. While chess can be effectively played using a set of predefined schemas or plans, Go requires a more flexible approach due to its complexity and the vast number of potential board configurations (Silver et al., 2016, 2017, 2018). Despite the core rules of chess having existed for thousands of years, the presence of strong AI opponents has pushed human players to adapt their playing styles and strategies (Nielsen, 2019). In this way, AI has not only demonstrated its own prowess but has also fostered growth and improvement among human chess players. In contrast to chess and Go, some games truly have simple planning demands—for instance, tic-tac-toe (Spitz & Winters, 1977). Sala and Gobet (2017) conducted a meta-analysis across a range of expertise domains—including chess, music, medicine, and sports—examining expert memory performance. The studies used different types of materials respective to the domain of expertise, such as recalling chess positions or musical pieces. The results showed that experts had a significant advantage over novices in recalling domain-specific material (d = 1.31). However, there was also a significant advantage in recalling domain-specific random stimuli (d = 0.45). One possibility is that experts are better at finding patterns in the random stimuli, based on their existing knowledge. Alternatively, it could be due to more general processes, such as improved working-memory capacity or attentional control.

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Other domains of schema-based, rapid planning A number of studies with different groups of medical professions have also demonstrated that expertise is associated with faster access to schema knowledge (Lesgold et al., 1988; van de Wiel et al., 2000). Determining a diagnosis involves combining episodic memory of a particular case with semantic knowledge of different possible differential diagnoses to form a problem representation (Bowen, 2006; Cutrer et al., 2013). Within this literature a key concept is “semantic qualifiers”—different dimensions that help characterise a person’s symptoms (Bordage, 2007). These serve as a scaffold for characterising a particular case with respect to existing semantic knowledge and communication of precise concepts using nuanced vocabulary. As an example, temporal qualifiers can distinguish early vs. late onset of a medical condition such as Alzheimer’s disease. Spatial qualifiers can provide information about the location of a condition, such as frontal vs. temporal lobe epilepsy. Quantitative qualifiers can offer insight into the severity or extent of neuropsychological symptoms or deficits, such as mild vs. severe cognitive impairment. Causal qualifiers can distinguish genetic vs. acquired neurological disorders. Procedural qualifiers are used to denote the methods employed in neuropsychological assessment or intervention, such as pharmacological vs. behavioural treatment for mental disorders. These demonstrate how semantic knowledge and schemas are embedded within medical professions. Computer programming also is a domain of expertise associated with knowledge schemas (Gilmore & Green, 1988; Meshulam et al., 2021). This can also be explored by observing how experienced programmers approach using unfamiliar programming languages (Scholtz & Wiedenbeck, 1993). Planning is also relevant to other domains of expertise. Generally, many domains of expertise are associated with larger working-memory chunks, then facilitating more comprehensive memory and understanding (Chiesi et al., 1979; Spilich et al., 1979). Skilled rock climbers are better able to identify and enact action sequences related to climbing, including remember sequences of holds (Boschker et al., 2002; Pezzulo et al., 2010; Whitaker et al., 2020; Rucińska, 2021). Professional videogame e-sports players need to memorise flexible plans of strategies, based on both prior experiences and reacting to their opponent (McCrea, 2009; Weber & Mateas, 2009; Thompson et al., 2014; Kowalczyk et al., 2018; Madan, 2020b). Board games can also have complex rules that need to be memorised. Some forms of expertise are likely to be over-looked; for instance, similar to random chess arrangements with chess grandmasters, experienced sports players can readily recognise and remember structured play, but perform comparable to novices when game situations are unstructured (Chiesi et al., 1979; Allard et al., 1980; Starkes & Deakin, 1985).

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12.4 Verbatim recall A number of professions require the memorisation of specific information verbatim—when all the world is a stage. All of these examples can be thought of as rehearsed performances. From complex motor movements in videogames to spoken phrases by actors and magicians. In a shorter term and constantly changing, waiters also need to have verbatim recall of restaurant orders.

Complex motor actions Solving a Rubik’s cube is another domain of expertise, relying on memorisation of preplanned action sequences. Experts who can solve a Rubik’s cube in tens of seconds rely on similarly structured schemas. While these solutions are fast, they nonetheless rely on many more turns than are minimally necessary (Korf, 1999; Madan, 2020b). Specifically, popular speedcube approaches generally rely on planning to complete intermediate goals and identifying sets of pieces to swap to achieve these goals. Intermediate goals include making a white cross and completing the first two layers. These piece swaps are done using memorised algorithms of around ten turns each, requiring between 78 to 119 algorithms (for the Friedrich/CFOP method), depending on the specific variant used. More efficient algorithms have been devised such that any valid configuration can be solved in no more than 52 moves (Thistlewaite, 1981), but these require memorisation of longer sequences of movements (i.e., fewer intermediate states to be evaluated), making it impractical for humans. While this may seem efficient, it has been shown computationally that any Rubik’s cube can be solved in 20 moves or less (Rokicki et al., 2010). A range of other domains of expertise are also heavily reliant on the conscious recall of sequences of complex motor actions—including dance choreography (Longstaff, 1998; Jean et al., 2001; Stevens, 2017; Stevens et al., 2019), stenography (Seashore & Bennett, 1948; Ito et al., 2015), and fighting videogames (such as Street Fighter and Mortal Kombat) (Mattiassi, 2019). In this context, videogame expertise is typically thought of as motor skill experience, either faster reaction times or learning of complex combinations of movements. Street Fighter 6 (2023) includes a ‘modern’ control scheme to make the game more approachable to casual gamers, but also includes mini-games to help them master these combo techniques—like Hado Pizza. Additionally, video games are also associated with rich vernacular—names and attributes of game characters and locations within the world and historical events—content stored as semantic knowledge (Baba, 1993). This aspect of video game knowledge is comparable to other fictional works, such as Star Trek or Lord of the Rings (Neisser & Hupcey, 1974; Means & Voss, 1985; Long & Prat, 2002; Louwerse & Benesh, 2012; Troyer & Kutas, 2020).

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Performances Other professions also rely on precise recall with less constraints on encoding, such as performers. For example, actors and waiters quickly store specified material for later verbatim recall. Actors need to know their lines verbatim, but rote memorisation is not the most effective strategy. Instead, a combination of enactment, perspective taking, and embodiment yields better recall rates than direct memorisation (Noice, 1996; Noice & Noice, 1997; Noice & Noice, 2006). In some ways, this is not dissimilar to the difference between memorisation and understanding discussed in the previous chapter. The practices of actors are discussed from a cognitive psychology perspective in impressive detail in The Nature of Expertise in Professional Acting: A Cognitive View (Noice & Noice, 1997). The strategies used by actors can also be beneficial to others, such as for older adults (Noice et al., 1999). DER CU MIN E RE

Experienced waiters are able to remember food orders with less study time than those without training (Ericsson & Polson, 1988b). That said, using a notepad or digital ordering device is an option and, in some cases, can communicate the order directly to the kitchen. Some restaurants and guidebooks, however, recommend memorisation of orders— viewed as benefitting both customer satisfaction and tipping (Bennett, 1983; Bekinschtein et al., 2008; Seiter & Weger, 2020). There is mixed evidence of memorised orders resulting in higher tips, but delivering incorrect dishes after memorised orders was viewed as particularly problematic (Seiter & Weger, 2020). Expert memory here is not confined to just the menu items, but also includes ingredients, appearance, and typical order combinations (Rose, 2001). Discussed in these studies is one waiter who demonstrated a truly exceptional memory (Ericsson & Polson, 1988b). The strategy used by this individual relied on remembering categories to structure the order information, as well as acronym mnemonics. For instance, the salad dressings for a table of four could be remembered as “BOOT” corresponding to “blue cheese (B), oil and vinegar (O), oil and vinegar (O), thousand island (T).” In a subsequent article, Ericsson and Polson (1988a) describe this strategy in more detail, including an interview transcript describing specific examples. At its core, it relies on a combination of schemas and content-specific mnemonics. Other studies have also observed the use of schemas and chunking in order taking, albeit with less complex mnemonic strategies (Bennett, 1983; Stevens, 1993; Huet & Mariné, 1997; Rose, 2001; Bekinschtein et al., 2008).

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Beach (1993) studied the memory strategies used by bartenders across a variety of experience levels: from novice to advanced student, advanced student to recent graduate (of bartending school), and finally from recent graduate to professional bartender. In earlier stages, memory operations are occupied with memorising recipes, but this later shifts using cues to remember recipe knowledge, and last to memorising customers’ names and preferred drinks—as well as current events. With increasing experience, the focus shifts as requisite stages become more reliant on semantic knowledge. On discussing the relevance of memory as a pianist, Browning (1987) said: Memorizing is an issue with everybody because we have to play from memory. And I don’t care what anybody says, every performer, no matter how secure, always thinks about the possibility of memory slips. […] You’re not likely to have problems with memory if you can sit in a chair or lie in bed and go through the entire work, no matter how complicated, and call it out in your mind. I really don’t feel I’m ready to play a work in public until I can do this. (p. 32) Other studies of memorisation by musicians provide strategies and reflections on the role of expertise in musical performances (O’Brien, 1943; Ross, 1964; Pressley et al., 1982; Reubart, 1985; Hallam, 1997; Chaffin & Imreh, 1997; Williamon, 1999, 2000; Chaffin et al., 2009). Many performances by magicians can be attributed to feats of memory. For instance, a straightforward trick would be for a magician to present the audience with a deck of cards that appears randomly ordered. The magician then asks an audience member to choose a card and then instantly knows what card was chosen. We will assume that the magician was able to subtly glance at the preceding or subsequent card in the deck and that the deck was not shuffled, it only appeared randomly ordered. There are several prespecified sequences of cards that are designed to work in different tricks (Galasso, 1593; Pinchbeck, 1805; Stebbins, 1884; Aronson, 1999; Tamariz, 2004; Aragón, 2017), for instance, sequences that lead to specific poker hands when dealt out. These sequences are referred to as ‘memorised deck stacks.’ Alternatively, bizarre imagery and memory strategies can be used to readily remember cards in naturalistic sequences—with applications in card games such as bridge, as well as magician performances (Onika, 2012; Hampton, 2013; Trustman & Trustman, 2017). A random sequence of 52 cards is incredibly unique. Mathematically, there are 52! (52 factorial) possible sequences of cards, corresponding to 8 × 1067 combinations. If you were to create a new unique sequence of 52 cards every second, it would take 2.54 × 1060 years to go through all the combinations. That’s more than the current age of the universe—13.8 billion years.

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While on the topic, ‘counting cards’ is also a feat of memory—and has been a topic of some studies (Keren & Wagenaar, 1985; Speelman et al., 2015). Though it is viewed in a negative light, card counting is a blackjack strategy that shifts odds away from the casino. While there are basic strategies related to what cards are known on the table, card counting involves keeping track of the relative odds across hands by assigning point values to different sets of cards. The ‘high-low’ count assigns a value of +1 to cards 2—6, 0 to cards 7—9, and −1 for 10, ace, and the face cards (jack, queen, king). The count starts at 0 when all decks are complete, since there are an equal number of high and low cards in the deck. When a card is seen, the running count is updated by adding its assigned value to the count so far. If multiple decks are in play, the ‘true count’ is the running count divided by the number of decks. Based on the current true count, a player should adjust their behaviour as the likelihood of the next card possibly resulting in a bust changes. Though there are several card counting systems, they all rely on this heuristic-based approach to make the odds easier to estimate, rather than having to maintain verbatim recall of large sequences of cards. These strategies have the most impact if blackjack is being played from a single deck. When using multiple decks, casinos can also reduce the edge provided by counting by reshuffling the decks before they are fully played out. The statistical analyses that have been applied to card counting—and made available to an interested reader—are impressive in their own right (Griffin, 1996; Bollman, 2021). If it is done individually (rather than collaboratively with other players) and without any technological aids, counting cards is merely a heuristic for tracking relative odds and is not illegal. Other topics of verbatim knowledge can be more general, such as knowledge for significant public events (Meeter et al., 2005; Janssen et al., 2008; LePort et al., 2012, 2017) and current political figures (Anson, 2018; O’Shea et al., 2022).

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Knowledge tests From hobbies and professions to more common knowledge, we all have some verbatim knowledge that serves as expertise. In other cases, expertise may be remembering specific verbatim information that needs to be recalled when a relevant situation arises. One example of this is the Konami code, first used in 1986 but has pervaded through dozens of games since. As a reminder, thus sequence of button presses is: Ȅ Ȅ ȁ ȁ Ȃ ȃ Ȃ ȃ B A. In the 1980s, several books of videogame strategies had been published (Kubey, 1982; Sullivan, 1982). Pac-Man in particular was a focus, with dedicated books suggesting movement patterns to memorise (Penguin, 1982; Uston, 1981). Penguin (1982) reads: “Once you memorise the pattern, you’ll be able to relax (many people are seen yawning during the first screen)” (p. 8). The initial portion of this path is shown in Figure 12.7.

FIGURE 12.7: Initial optimised pattern for Pac-Man. Letters A—D denote intermediate points along the route. Adapted from Penguin (1982).

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Even the computer keyboard shortcuts for copying and pasting are a verbatim recalled form of expert knowledge. Extending from this, the use of complex functions has become the foundation for competitions, such as the Microsoft Excel World Championship (Stern, 2021; du Soleil & Jelen, 2022). Topic knowledge can also be expertise; many studies have examined academic subjects (Chi et al., 1981; Nuthall, 2000; Brandt et al., 2005; Custers & ten Cate, 2011). Similarly, practical skills—languages and cooking recipes (Bahrick, 1984; Bier et al., 2011; Hargreaves et al., 2012)—and popular culture trivia—songs, TV, and sports (Chi & Koeske, 1983; Means & Voss, 1985; Toth et al., 2011; Hartman et al., 2022)—are also domains of expertise. Studies of knowledge retention over decades has provided insights into how knowledge is structured (Beatty et al., 1997; Skotko et al., 2008; Bier et al., 2011). Verhoeven et al. (2002) reported an analysis of knowledge acquisition across a six-year medical degree, across over 3,000 participants and 20 years. Each year, each student is assessed four times on an exam that tests for graduate-level knowledge—thus, each student is assessed in this format 24 times over their training. Performance is scored as Correct − Incorrect, with students also allowed the option of “I don’t know” for no penalty. At the end of year 1, students score 10%; by the end of year 6, they score 60%. This largescale evaluation demonstrates the incremental acquisition of medical expertise. All of our life we acquire factual knowledge, particularly through formal education, but also through extended training and experience more generally. Tests have been developed to measure the acquisition of knowledge, to evaluate an individual’s abilities within these domains (Asher & Sciarrino, 1974; Roth et al., 2005; Custers, 2010). Some domains of knowledge are acquired as needed later in life, such as general medical knowledge related to allergies or diseases that may affect those around us. Some other domains are related to topics already discussed earlier in the chapter—chess, coffee, wine. However, knowledge is much broader than that, including sports, baking, and other topics. To provide an overview of the diverse domains, Table 12.1 provides examples of questions from a variety of knowledge tests; answers on p. 399. Knowledge tests often also include other question types not featured here, such as true/false statements, matching, and fill-in-the-blank responses. It may seem like all tests are knowledge tests—but this is not the case. Admittedly, all tests require some prior knowledge, such as the language that the test is written in and an understanding of the underlying assumptions (see p. 458). However, some tests are intended to evaluate the presented information and rather are assessments of reasoning and fluid intelligence abilities—like in some IQ test problems (e.g., Raven’s Progressive Matrices); this is known as cognitive reflection. The initial cognitive reflection test only included three numerical-based problems, e.g., “A bat and a ball cost $1.10 in total. The bat costs $1.00 more than the ball. How much does the ball cost?” (Frederick, 2005). Others have since developed additional questions as well as generalised the test to other domains (Toplak et al., 2014; Sirota et al., 2020).

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TABLE 12.1: Knowledge in Diverse Domains (KIDD) 12-item test. 1. In which opening is it possible for White to get the largest pawn front (connected pawns on the fourth rank)? (a) Marshall (b) Cochrane (c) Grunfeld (d) King’s Gambit (from Van Der Maas & Wagenmakers, 2005) 2. Which of the following aromas characterizes Cabernet Sauvignon? (a) Violet, raspberry, pepper, spices, leather (b) Cherry, plums, spices (c) Red berries, pepper, green, dark chocolate, tobacco (d) Green pepper, strawberry, raspberry, blackcurrant, bramble, wood (e) Do not know (from Koenig et al., 2020) 3. What is the proper way to age coffee with the intention to improve quality? (a) By grinding the roasted coffee and keeping it in an open jar for several weeks, allowing it to breathe (b) By keeping roasted coffee beans in the fridge (c) Drying the coffee berries for an extended time period (d) Keeping the unroasted coffee under controlled conditions for several months to years (e) By only using coffee beans from very old coffee trees (from Croijmans & Majid, 2016) 4. A frail 70-year-old with early Alzheimer’s disease and mild dementia complains of chronic pain. Physical examination is rather unremarkable. X-rays of the lumbar spine show mild changes consistent with osteoarthritis. In consultation, the radiologist suggests that the x-ray findings are minimal and may not account for the pain. The most accurate evidence of the existence of pain and its intensity is: (a) The nurse’s report (b) The patient’s report (c) Physical examination findings (d) X-ray evidence of osteoarthritis (from Lee et al., 2004)

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5. What is another term for a severe allergic reaction? (a) Urticaria (b) Anaphylaxis (c) Atopic dermatitis (d) Adrenaline (from Hahn et al., 2017) 6. People sometimes write notes to themselves as reminders. How effective is this technique for Alzheimer’s disease patients? (a) It can never be used because reading and comprehension are too severely impaired. (b) It may be useful for the mildly demented patient. (c) It is a crutch which may contribute to further decline. (d) It may produce permanent gains in memory. (from Dieckmann et al., 1988) 7. Two metal balls are the same size but one weighs twice as much as the other. The balls are dropped from the roof of a single-storey building at the same instant. The time it takes the balls to reach the ground below will be: (a) about half as long for the heavier ball as for the lighter one. (b) about half as long for the lighter ball as for the heavier one. (c) about the same for both balls. (d) considerably less for the heavier ball, but not necessarily half as long. (e) considerably less for the lighter ball, but not necessarily half as long. (from Hestenes et al., 1992) 8. Which political party is more conservative when it comes to healthcare policy? (a) Democratic Party (b) Republican Party (c) They are about the same (from Anson, 2018)

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9. It is good strategy in tennis to: (a) force opponent out of position. (b) drive all balls to opponent’s backhand side. (c) try to rattle opponent during play. (d) play balls to opponent’s baseline. (e) chop all balls. (from Hewitt, 1937) 10. Which best describes the flight of a good [badminton] smash? (a) High arc that drops near opponent’s end line. (b) Straight line parallel to the floor. (c) Flight directly downward toward the opponent’s end line. (d) Flight directly downward into the opponent’s fore court. (from Hennis, 1956) 11. Which one of the following conditions is most likely to result in a dull crust color on Danish pastry? (a) Not enough dusting flour (b) Underproofing (c) Low egg content (d) Old dough (from Knauft, 1949) 12. How long will an apple tree bear fruit if properly cared for? (a) 5–10 years (b) 10–15 years (c) 15–20 years (d) 20–25 years (e) 25–30 years (from Grigg, 1948)

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12.5 Memory champions While we began with discussing strategies that people can generally use and then the notable feats of memory demonstrated by groups of individuals, we will now focus on the exceptional accomplishments of the few that have taken these strategies to their maximum. For those who are at the limit of memory retention in recorded history, how do they do it? In this section, we will focus on those that are using deliberate memory strategies; this is in contrast to individuals who have natural exhibited impressive memory abilities. Pliny the Elder (79 AD, Book 7, Ch. 24) highlighted impressive feats of memory from over two millennia ago, such as that of King Cyrus, who reigned around 500 BC, and was reputed to have remembered the names of all the soldiers in his army. More contemporaneously, there have been recordings of numerous individuals with impressive natural memory abilities (Binet, 1894; Weinland, 1948; Luria, 1968; Brown & Deffenbacher, 1975; Wilding & Valentine, 1997). Some may have used strategies, but it can be somewhat unclear to determine given the limited records available. Other instances of exceptional natural memory, e.g., HSAM, were discussed in Section 4.4 (p. 111). Ericsson et al. (1980) trained an undergraduate student, S.F., an avid runner with average memory abilities, to have impressive memory abilities. Over 20 months (230 hours of laboratory time), S.F. went from being able to remember sequences of 7 digits to 79. Over time, S.F. developed a chunking strategy, associating sets of 3–4 digit sequences with other information. The majority of S.F.’s associations were with running times or ages. Chunking would only explain a span of approximately 28 digits; this was superceded by a second development, S.F. using a hierarchical retrieval structure (also see Chase & Ericsson, 1981, 1982). Later a second participant who was also a runner, D.D., was added to the Skilled Memory Project and when given the same strategy readily also achieved large memory spans (Chase & Ericsson, 1982). Decades later, a follow-up was done—with D.D. (Dario Donatelli) as a co-author (Yoon et al., 2018). D.D. had reached a span of 68 digits after 286 hours of training, increasing to 106 digits in 1985 after around 800 hours when the project ended. After 30 years without training, D.D.’s digit span fell to ten digits. However, after three days of testing, he was able to increase to 19 digits—which was more than many famous mnemonists. While all of these accomplishments are impressive, much longer digit spans are possible. Ericsson et al. (2017) reports experiments done with Feng Wang, who won the World Memory Championship by recalling 300 digits presented at one digit/s.

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World Memory Championship Outside of memory feats accomplished within laboratory studies, there is the World Memory Championship. Here people compete and train to remember all that they can from their own motivation, not for a research study. This event, established in 1991 by Tony Buzan and Raymond Keene, represents the pinnacle of competitive memory sports. Competitors from around the world participate in ten memory challenges, ranging from memorising decks of cards and long lists of binary digits to recalling historical dates and faces with associated names (World Memory Sports Council, 2019). Some challenges have multiple variations in the rules, for instance one hour to remember all the shuffled playing cards you can, or having only 5 minutes. Competitors employ a range of mnemonic techniques to achieve extraordinary feats of memory. The method of loci—discussed in the previous chapter—is a frequently used strategy (Raz et al., 2009; Maguire, Valentine, et al., 2003; Dresler et al., 2017; Wagner et al., 2021). To briefly give more context to the challenges, I will summarise three of them using details from the official competitor’s handbook (World Memory Sports Council, 2019). Some have different durations for different competition levels—here I will use the lengths for the world competition. In Speed Numbers, competitors are presented with rows of 40 digits of random numbers. Competitors have 5 minutes to memorise as many rows as they can, then 15 minutes for written recall. A correct row is worth 40 points. For each row, if there is one mistake, the competitor receives 20 points; if there are two or more mistakes, zero points. The current record is 616 digits. In Random Cards, competitors memorise the sequence of as many shuffled 52 playing card decks as they can in 60 minutes. After a short delay (5–15 minutes), they have 120 minutes to provide a written recall. The current record is 2,530 cards (just over 48 decks). In Random Words, competitors memorise as many words as they can in 15 minutes, then written recall for 30 minutes. Considerations are made to use common words, avoiding words that have different American and British spellings, and are culturally specific. The current record is 335 words. Despite all of the limitations of human memory discussed—the reconstructive nature of memory and countless related biases—amazing feats of memory are possible. Wilding and Valentine (1994) studied some participants from the first World Memory Championship. Some participants had naturally good memory, whereas others were more reliant on strategies for their performance. Examining performance across a variety of memory tasks (Wilding & Valentine, 1994, 2006), natural memorisers were generally good across all tasks. However, those using strategies were better at tasks more amenable to strategy use—faces, names, and words—but performed relatively worse on other tests—such as remembering stories, spatial information, and snowflakes.

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Maguire, Valentine, et al. (2003) investigated the brains and memory techniques of individuals who had achieved superior memory performance in the World Memory Championships. Using fMRI, they compared the brain activity of ten memory champions with ten participants who had normal memory. All participants were presented with sequences of stimuli: threedigit numbers, faces, and snowflakes, intermixed. Memory differences between groups were most pronounced for the digits, and least so for the snowflakes, which are much more difficult to uniquely identify. The memory champions activated a different network of brain regions compared to controls, including the right posterior hippocampus. This is consistent with the idea that memory strategies rely on spatial memory techniques. More recent studies have examined memory champions and novices across several-week intervals with training, to further characterise the brain networks associated with memory champions (Mallow et al., 2015; Dresler et al., 2017; Wagner et al., 2021). Joshua Foer, a science journalist by profession, first encountered the world of competitive memory training when he was covering the USA Memory Championship—publishing a long featured article in Natural Geographic in (2007). Fascinated by the astounding memory feats he witnessed, Foer decided to dive headfirst into this intriguing world. Guided by the expert memory athlete, Ed Cooke, and after a year of rigorous training, Foer decided to put his skills to the test. He entered the USA Memory Championship, the very competition he had covered as a journalist just a year prior. Competing against seasoned memory athletes, Foer was the underdog. To the surprise of many, including himself, Foer emerged as the champion, setting a new USA record in the process. He later detailed his journey in a book (Foer, 2011), showing that we have the potential to be memory champions if we dedicate ourselves to the requisite training.

Memorising pi Memorising digits of pi has long been a memory challenge—with world records kept for the past decades. In 1981, Rajan Mahadevan was the record holder, reciting 31,811 digits of pi (Thompson et al., 1991, 1993). This record was later superceded by Hideaki Tomoyori in 1987, reciting 40,000 digits (Takahashi et al., 2006). These are far beyond typical memory span and verbatim recall. Akira Haraguchi was able to recite 111,700 digits of pi in 2006, though, unfortunately, this was not recognised by Guinness World Records (Hooper, 2018). While this is definitely a remarkable accomplishment, it is not something that was done through sheer force and focus. Rather, Akira developed a narrative-based memory strategy, where digits correspond to characters in the Japanese alphabet. Several others have demonstrated notable abilities in memorising digits of pi and have been studied for this (Raz et al., 2009; Yin et al., 2015).

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With memorising specific information, such as the digits of pi, others may have already come up with strategies that are optimised for that information (Cukier, 1999). One strategy for memorising long numbers is to remember a phrase where the length of each word represents the number (with ten letters representing the digit zero). Words with more than ten letters are considered a two-digit set of numbers. This memorisation strategy is called pilish. There are many phrases or poems that can be used to memorise the first few dozen digits of pi, in many languages. The most popular such phrase is: “How I need a drink, alcoholic in nature, after the heavy lectures involving quantum mechanics” (15 digits). Particularly impressive, Keith (1996) wrote a short story called Cadaeic Cadenza that uses this approach and if memorised would cover the first 3,835 digits of pi and incorporates adaptations of classic literature, including The Raven by Edgar Allan Poe, Jabberwocky by Lewis Carroll, and The Love Song of J. Alfred Prufrock by T. S. Eliot. The first words are: One, A Poem: A Raven Midnights so dreary, tired and weary, Silently pondering volumes extolling all by-now obsolete lore. This excerpt represents 3.1415926535897932384, the first 20 digits of pi. Keith (2010) later wrote a book, Not A Wake, that spans the first 10,000 digits. MIN RE

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Other, more succinct, approaches for remembering pi also exist. For instance, Benjamin (2000) suggests using a phonetic code, where specific consonant sounds correspond to each digit. The consonants associated with each digit are shown in Table 12.2. Vowels are then added to create words, but are not themselves associated with any numerical value. The consonants h, w, and y are also not associated with numbers and can be used as ‘fillers’ when making words. Benjamin (2000) provides a mnemonic for memorising the phonetic code, “Tony Marloshkovips.” This table only includes example words that represent one digit each, but single words can represent multiple digits. A few examples are “rain” for 42, “cheese” for 60, “meteor” for 314, “remember” for 43394. The number 2024 can be encoded into multiple words including “nice winner,” “noise anywhere,” “unseen war,” and “nissan air.” Some websites can help with generating words for provided numbers. Note that the strategy is based on the consonant sounds, not the spelling. “Action” would be 762, not 712 (instead

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TABLE 12.2: Phonetic code and example words for the Major system. Digit Consonants Example Words 1 t, th, d head, wet, idea, hit 2 n knew, wing, wine, honey 3 m home, yummy, mow, wham 4 r rye, row, air, aware 5 l hill, yellow, wheel, wily 6 sh, ch, j hush, chew, wash, shy 7 k, hard c, hard g hug, cow, awake, egg 8 f, ph, gh, v wife, eve, phew, hive 9 p, b bow, web, pie, whip 0 s, z, soft c sew, hazy, icy, eyes

use “acting”); “missle” would be 305, not 3005 (instead use “Mrs. L” [300-5], “muses hall” [300-5], or “miss sell” [30-05]). This approach had been described previously and is intended to be more general memorisation strategy (Lorayne & Lucas, 1974). Some adapt the strategy to assign a peg word for each number between 0 and 99, or even 999, and then form them into sequences of pictures. Here this strategy is used to encode the first 60 digits of pi in three sentences (Benjamin, 2000) and can even reach 100 digits with an additional two sentences (Benjamin, 2015): My turtle Pancho will, my love, pick up my new mover, Ginger. (24 digits) My movie monkey plays in a favorite bucket. (17 digits) Ship my puppy Michael to Sullivan’s backrubber. (19 digits) A really open music video cheers Jenny F. Jones. (18 digits) Have a baby fish knife so Marvin will marinate the goose chick. (22 digits) (p. 200) This phonetic code method is the “Major system.” While the method is named after Major Beniowski (1841, 1845), there were earlier versions of the system (Grey, 1799; Beniowski, 1841; Pick, 1861, 1888; Post, 1932; Gardner, 1956), including a version by Lewis Carroll (Weaver, 1956). Pick (1861, 1888) dated a similar system back to Stanislaus Mink von Winkelman (1648). Though many consider memorising pi to hundreds or thousands of digits to be a worthwhile feat, NASA (2016) found that 16 digits is sufficient: It turns out that our calculated circumference of the 25 billion mile diameter circle would be wrong by 1.5 inches. Think about that. We have a circle more than 78 billion miles around, and our calculation of that distance would be off by perhaps less than the length of your little finger. 39 digits of pi is sufficient to calculate the circumference of the visible universe to within the diameter of one hydrogen atom.

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End of chapter wrap-up Summary Countless topics of expertise exist, and many allow experts to perform feats of memory that seem extraordinary to the novice. Expertise is associated with complex knowledge representations, where information is highly structured, allowing experts to recognise patterns and process information as chunks. Many domains of expertise are associated with perceptual knowledge, from bird watching to radiographers. Not all perceptual knowledge is visual, however; wine knowledge in particular is associated with many fields of study, and a nuanced vocabulary. Schemas are also central to the development of expertise. Chess is particularly well known as a domain of expertise that requires flexible planning. Variations of chess, such as fairy chess and blindfolded chess, can increase the emphasis on episodic memory demands, relative to the traditional rules. Some domains of expertise involve verbatim recall, from videogames to acting. Beyond these memory feats embedded with professions and hobbies, memory competitions themselves also exist. Some require rapid memorisation of randomised decks of cards, while others relate to memorising pi to thousands of decimal places. This chapter highlights the use of memory in numerous contexts, revealing how strategies, training, and deliberate practice can push the boundaries of our memory capabilities.

Reminder cues

Quick quiz 1. What is the concept of “chunking” and how does it contribute to the development of expertise? (a) Chunking is the process of breaking down complex information into simpler components to facilitate novice learning. (b) Chunking is the process of grouping related pieces of information together, aiding in memory recall and knowledge representation. (c) Chunking is the method of separating information into distinct, non-related segments to prevent memory overload. (d) Chunking is the term used to describe the process of repeating information over and over to aid memory retention.

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2. Alex, a seasoned birdwatcher, and his nephew, Jamie, a novice in bird watching, are out by a lake. A bird swiftly crosses their path and perches on a distant tree. Alex is able to identify it as a red-winged blackbird based on the specific tree it perched on. Jamie, who also saw the bird at the exact same moment, is still flipping through his field guide trying to identify it. What could be the most likely reason for Alex’s ability to identify the bird more quickly than Jamie? (a) Alex has a more comprehensive list of bird names in his memory. (b) Alex has previously seen the bird on an earlier day, so he had time to think about it earlier. (c) Alex has developed better eyesight over the years. (d) Alex has deeper familiarity with the habitat preferences and habits of birds. 3. In blindfolded chess, players must mentally maintain the positions of all pieces without seeing the board. Which type of memory is least crucial for success in this variant of the game? (a) Episodic memory to recall the sequence of moves that have taken place during the game. (b) Semantic memory to understand the rules and possible moves of each piece, and to use schemas developed from past games to evaluate current situations. (c) Procedural memory to recall the actions used to move the pieces in the game so far. (d) All of the above are equally important. 4. Olivia, an upcoming actor, has just landed a role in a play with lengthy monologues. Which of the following approaches might Olivia consider to effectively prepare for her monologues? (a) Memorise each word in the monologue individually. (b) Break down the monologue into meaningful chunks and weave a mental narrative to link these chunks. (c) Write down the monologue repeatedly to etch it into her memory. (d) Improvise on the stage, basing her monologues on the general theme of the play.

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5. Based on the discussion of pilish, how could this technique be adapted or modified to aid memory in other contexts? (a) It could be used to remember people’s names by associating them with specific word lengths. (b) It could be used to remember historical dates by associating them with word lengths. (c) It could be used to remember a shopping list by writing a story where the length of each word represents an item. (d) It could not be adapted for other contexts; it is only useful for remembering pi.

Thought questions ▶ Consider the concept of “chunking” and how it is used in various domains of expertise. Can you think of an area in your own life where you might be using chunking without realising it? ▶ How do the mnemonic skills demonstrated by taxi drivers and chess grandmasters compare? ▶ Given the discussion about memory in expertise, what insights have you gained about the potential of human memory? How do these examples challenge any preconceptions or assumptions you had about the limits of memory? Do these examples inspire you to think differently about your own memory abilities or the ways you could potentially enhance your memory?

Further reading ▶ Van Gulick, A. E., McGugin, R. W., & Gauthier, I. (2016). Measuring nonvisual knowledge about object categories: The Semantic Vanderbilt Expertise Test. Behavior Research Methods, 48(3), 1178–1196. doi: 10.3758/s13428-015-0637-5 ▶ Lehrer, A. (1975). Talking about wine. Language, 51(4), 901–923. doi: 10.2307/412700 ▶ Chi, M. T., De Leeuw, N., Chiu, M.-H., & Lavancher, C. (1994). Eliciting self-explanations improves understanding. Cognitive Science, 18(3), 439–477. doi: 10.1207/s15516709cog1803_3

The answers for the knowledge test questions are: 1. d; 2. c; 3. d; 4. b; 5. b; 6. b; 7. c; 8. b; 9. a; 10. d; 11. b; 12. b.

Chapter 13 Extended mind, expanded memory

…mnemonic systems are typically not particularly helpful in remembering the sort of information which one requires in everyday life. They are, of course, excellent for learning the strings of unrelated words which are so close to the hearts of experimental psychologists, but I must confess that if I need to remember a shopping list, I do not imagine strings of sausages festooned from my chandeliers and bunches of bananas sprouting from my wardrobe. I simply write it down. — Alan D. Baddeley (1976)

While memory is generally thought of just as what we have in our head, it is only a fraction of the knowledge we have access to. Most of us make to-do lists, a form of external reminder, on a daily basis. We also make notes in a calendar of upcoming events and store contact information for our friends and colleagues in our phones. We also rely on external information, using ‘map’ mobile apps to assist us in driving to a destination and Wikipedia to look up facts. All of these are external memory aids that are integrated into the fabric of our daily lives. To additionally reflect on the previous chapter, while memorised maps may still be beneficial to London taxi drivers, the necessity of this memory feat has decreased drastically in the last few decades. Restaurant waiters previously have benefitted from memory strategies, though notepads have always been available. However, a small digital pad can now readily send the order straight to the kitchen without the waiter needing to walk the order over, potentially improving efficiency. Clark and Chalmers (1998) championed the view of the extended mind. Though they make many points and present the arguments from a more philosophical perspective than a psychological one, one of their examples is particularly relevant: consider two individuals, Otto and Inga, who are both walking to attend an event at a museum from relatively nearby. Inga knows the directions to the museum and is able to walk there, taking a path that 401

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she remembers from previous experiences. Otto has Alzheimer’s disease and regularly uses a notebook to help him remember things. In advance of leaving home, he wrote down the directions and follows them to arrive at the museum. While Inga was able to rely on her internally stored memories, Otto used his external notebook, as he does regularly. Here Otto is using the notebook as an extension of himself storing information as needed. This view makes a strong case that a notebook can be used to compensate for memory deficits, but this view can be extended to use external aids to have better-than-normal memory abilities. However, this view of including external aids as part of one’s memory is far from generally agreed on (Clark, 2008; Michaelian, 2012). Nonetheless, the use of external aids does bear on the role of memory on everyday life, regardless of how concepts are themselves defined. This view of extending cognition to the world around us, incorporating tools, objects, and even other people into our cognitive systems, is known as active externalism (Clark & Chalmers, 1998; Dartnall, 2007; Carter et al., 2014; Carter & Palermos, 2015). This philosophical view challenges the traditional view of memory as a purely internal process, stored and retrieved within the confines of our brain. It suggests that our memory can be distributed across our environment, with external objects and tools serving as extensions of our cognitive processes. This is not to say that our brains are not crucial in the process of memory. Rather, it is to acknowledge that our brains often work in conjunction with the external world to remember and process information. Consider, for instance, the simple act of making a shopping list. When we jot down items on a piece of paper or a digital note, we are effectively offloading some of our memory onto an external object. The list then becomes a part of our cognitive system, aiding us in remembering what we need to buy. This is active externalism in action. Active externalism also extends to our interactions with other people. When we engage in a conversation, we are not just exchanging information; we are also shaping and influencing each other’s thoughts and memories. In a sense, the other person becomes a part of our cognitive process, helping us to remember, understand, and process information. This is referred to as transactive memory. In the digital age, active externalism takes on even more relevance. Digital tools and platforms, from search engines to social media, have become integral parts of our cognitive processes. They help us remember, learn, and understand information in ways that would not be possible with our brains alone. All of these dimensions will be explored throughout this chapter.

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13.1 Daily external aids External memory aids are often used in daily life (Harris, 1980; IntonsPeterson & Fournier, 1986; Schönpflug, 1986; Schryer & Ross, 2013). Some studies have found that older adults use them more frequently than young adults (Schryer & Ross, 2013). Some studies surveyed participants about both internal and external aids, finding that even though the method of loci—an internal aid—is undeniably an effective memory strategy, it is often not what people use for their daily reminders (Harris, 1980; Intons-Peterson & Fournier, 1986; Park et al., 1990). In the study conducted by Park et al. (1990), a sample of memory psychologists was also included. Even these individuals reported using the same strategies as non-experts, suggesting that even though experts recognise the benefits of more involved memory strategies, ease of use is considered sufficiently important. As such, the method of loci ranked near last in frequency of use, with peg lists as the very least used strategy. Making notes or lists and using other physical reminders, such as a calendar, were the most commonly used and most recommended. If a notepad and calendar can help us think and plan, are they part of our minds? Some external aids have been used for hundreds of years, such as notes and calendars (Harris, 1980; Hertel, 1993; Eddy, 2018), however, technology has greatly changed how we rely on memory. Though they may seem ubiquitous now, recent technologies have rapidly changed what we need to remember: photos, GPS-based navigation, and mobile internet. There is no shortage of commercial memory aids, particularly for prospective memory—such as alarm clocks and egg timers (Herrmann & Petro, 1990; Finley et al., 2018).

Diaries and notes Notes and diaries are the most common and easiest to use form of external aids and can further provide insights into autobiographical memory—as discussed in Chapter 8. Diaries can be useful for recording recent experiences—though often represent highlights, rather than verbatim records. They are also useful in helping mentally process events, serving as an emotion regulation strategy. Digital systems have also been developed for storing personal databases of people’s event memory. Initial work was conducted by computer science researchers, with the goal of modelling efficient memory processes with database structures and attempting to automatically capture relevant data (Jones, 1986; Lansdale & Edmonds, 1992; Lamming et al., 1994; Rhodes, 1997; Crabtree & Rhodes, 1998). Lamming and Flynn (1994) developed Forget-MeNot, a pioneering system that used sensors and portable devices to track a user’s interactions with people, objects, and locations, creating a personal history that could be easily searched and retrieved. The system was designed to assist users in recalling information by providing context-based reminders and indexing daily activities. Later studies were done to develop and evaluate the use of these technological aids for patients with acquired brain injury

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(Wilson et al., 1997, 1999; Jamieson et al., 2017). Training with external memory aids can increase use in patients with memory difficulties (Lanzi et al., 2019; McGoldrick et al., 2021; Gopi, Wilding, & Madan, 2022). Moreover, they can even provide insights into the past, particularly for personal accounts of historical events, such as the diaries of Anne Frank (1947) and Napoleon (Johnston, 1910). As an example, Napolean’s diary provides insight into his perspective of the 1800 ‘Plot of the rue Saint-Nicaise’ assassination attempt: I was so drowsy that I fell asleep in the coach. I was asleep when the explosion took place; and I recollect when I woke experiencing a sensation as if the vehicle had been raised up, and was passing through a great body of water. The contrivers of this were a man named St. Regent, Imolan, and some others. They got a cart and barrel resembling that with which water is supplied through the streets of Paris, with this exception, that the barrel was put crossways. This he had filled with gunpowder, and placed it nearly in the turning of the street through which I was to pass. Possibly my coachman may have assisted by driving furiously round the corner, as he was drunk and not afraid of anything. He was so far gone that he thought the report of the explosion was that of a salute fired in honour of my visit to the theatre. (Johnston, 1910, p. 147) Unlike most other topics discussed in this chapter, diaries involve externalising our own memories—in this way, memories can be shared with others. Looking further back, diaries and notes have also provided great insights into the lives and minds of Marco Polo, Leonardo da Vinci, and Charles Darwin. In some cases, retroactive reflections allow us to see ideas before they were formally understood, such as early observations of Neptune by Galileo in 1613, well before it was formally discovered in 1846 (Kowal & Drake, 1980).

Other physical reminders Tying a string to a finger is a traditional and simple external aid used for memory enhancement. This physical cue serves as a tangible reminder, prompting individuals to recall a specific task or event they intended to remember. The tactile sensation of the string on the finger, combined with the visual cue, creates a strong sensory association that effectively triggers recollection, even in the absence of more sophisticated memory tools. External aids have often been used for reminders of future intentions, i.e., prospective memory. While more of the literature has focused on their use in memory rehabilitation (Harris & Sunderland, 1981; Gross et al., 2012), they have become common in everyday life.

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Commemorative coins, keychains, and memorabilia are examples of external aids that capture memories and significant moments in a tangible form. These items act as symbolic representations of experiences, milestones, or historical events, allowing people to connect with their past or shared cultural heritage. The emotional and sentimental value attached to these keepsakes can strengthen the process of recollection, serving as powerful reminders of the moments they represent. Furthermore, these mementos can be shared or passed down through generations, preserving memories and stories for future generations to cherish and appreciate. In addition to the interview study asking about memories for Lincoln’s assassination (Section 6.1, p. 159), Colegrove (1899) conducted a broad questionnaire of people’s memories, asking about the participants’ early memories, memory strategies, meta-cognition, and emotional memories. This early exploration of memory was quite a substantial work: A large number of devices are given for keeping appointments. Females change rings, insert paper under a ring, pin paper on dress, etc. There are other favorite mechanical devices. Chairs are turned over, and other furniture disarranged. A middle aged man hid his hat to remind him of an appointment. Next morning he hunted up another hat, but did not recall why the one usually worn was gone. One associates appointments with the hands of the clock at the hour fixed. Not a few find it necessary to repeat the appointment again and again. Others are aided by a memorandum. (p. 251) The VR videogame Zed (2019) takes a more artistic approach to this same topic. Here you play as an aging artist suffering from dementia, trying to piece together fragments of memories to create a final work of art as a gift for your granddaughter. The game involves solving puzzles to reconstruct memories of the past and provides an immersive VR experience. The game raises awareness about dementia and the significance of memories in shaping one’s identity, relationships, and personal history.

Tattoos Tattoos can also be used as reminders of past events, but are far less ephemeral. If you have not thought about the relationship that tattoos can have to memory and identity, you likely have not watched the movie Memento (2000). Briefly, the main character has amnesia and uses a combination of tattoos and photos as external aids to allow him to remember recent events. Clark discussed Memento in a follow-up to his earlier article on the extended mind (Clark, 2010).

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Interview studies have found that motivations for getting tattoos are often associated with one’s identity, experiences, and actions (Dey & Das, 2017; Sundberg & Kjellman, 2018; Alter-Muri, 2020; Atli et al., 2022). For instance, these may be associated with relationships—interpersonal (e.g., close friend or partner), group affiliation (e.g., football team)—or to commemorate important life accomplishments. Tattoos are often used as a reminder of an important personal experience, thus serving as a means to bring autobiographical memory into a physical form (Velliquette et al., 2006; Steadman et al., 2019). MIN RE

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13.2 Veridical recordings, but also highlight reels Memories are reconstructions. Diaries are less flawed, partially due to the shorter interval between the event and the externalised recording. However, in the digital age, we have access to even more veridical forms of recording— photos and videos. Photographs and videos provide a more objective record of our experiences, capturing moments in time with a level of detail that our memories cannot retain. However, it is crucial to acknowledge that these recordings, while more accurate than our internal recollections, still offer a biased perspective. They capture a particular frame of a designated moment, not a representative window into daily life. They are closer to being objective than any memory reconstruction, but they are not a typical experience. The bias in these recordings becomes more apparent when we consider shared versions of recorded experiences. The photos and videos we choose to share, whether in physical photo albums or on social media platforms, are often carefully curated highlights of our lives. They capture smiles and achievements, but rarely the tantrums, the exhaustion, or the mundane moments that constitute a significant part of our lived experiences. Consider a photo album of a family holiday. The photos might show smiling faces, beautiful landscapes, and exciting activities. They do not show the effort it took to get the little one to stay still for the photo, the hours spent in transit, or the exhaustion at the end of the day. These recordings, therefore, while veridical in one sense, still present a biased window into what was experienced.

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This pattern of selective sharing continues and is amplified on social media platforms. Here, individuals often present an idealised version of their lives, sharing carefully selected and sometimes even edited photos and videos. This creates a skewed representation of reality, a highlight reel. Despite these biases, these veridical recordings form a significant part of our objective autobiographical memory. They serve as external memory aids, helping us remember our past experiences with a level of detail that our internal memory systems might not retain. However, it is crucial to remember that while these recordings can enhance our memory, they do not replace the richness and complexity of our lived experiences.

Photos Photos serve as a unique intersection between our personal memories and objective reality. They offer a snapshot of a moment in time, frozen and preserved in a way that our natural memories cannot achieve. Moreover, photos can be curated and shared with others (van Dijck, 2008). On the one hand, photographs provide a veridical record of our experiences. They capture a moment as it was, free from the distortions and biases that often colour our memories. In this sense, they can serve as an external memory aid, providing a reference point that can help us recall details that might otherwise fade over time (Chalfen, 1998; Whittaker et al., 2010). On the other hand, photos are not just passive records of our experiences. The act of taking a photo is an active process that involves making decisions about what to include and what to leave out. This selective framing can influence how we remember an event. For instance, we might remember a holiday as being more enjoyable than it actually was because we chose to take photos of the fun moments and not the stressful ones. Moreover, reviewing photos can shape our memories. Each time we look at a photo, we are not just recalling a memory, but reconstructing it. In the digital age, the use of photographs as memory aids has become even more prevalent, since 91% of adults regularly carry a device that can take photos (Finley et al., 2018). With smart phones, we have the ability to take and store thousands of photos, allowing us to document our lives in unprecedented detail. However, this abundance of photos can also lead to a kind of memory overload, where the sheer volume of images makes it harder to recall specific details. Ads from Kodak in the 1940s and 1950s featured slogans focused on the ability of photos to serve as reminders, but also to preferentially highlight specific aspects: “Make your memories last forever.” “It’s always summer in snapshots.” “Snapshots keep your happiest times.” “Snapshots remember—when you forget.” “How to get rid of unwanted relatives.”

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Henkel (2014) investigated the impact of photographing objects on memory. Two studies were conducted in which participants were taken on a guided tour of an art museum and were instructed to either observe or photograph certain objects, using a within-subjects design. Results revealed a photo-taking-impairment effect—fewer objects that were photographed were remembered than those that were only observed. Experiment 2 divided the photo-taking condition into photographing the whole object (as in Experiment 1) and photographing zoomed in on a specific feature. Here memory was comparable for the zoomed condition than just observing. The findings suggest that there are key differences between human memory and the camera’s ‘memory.’ The act of photographing an object as a whole may lead people to rely on the external device of the camera to remember for them, resulting in a decrease in memory performance. The act of taking photos may also be considered as dividing one’s attention, leaving less resources available for incidental encoding. On the other hand, when individuals actively and physically zoom in on a specific feature of the object, their focused attention allows for better subsequent memory accuracy. Other studies have provided convergent evidence (Koutstaal et al., 1999; Nunes et al., 2009). MIN RE

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In another series of studies, Barasch et al. (2017) examined the effects of volitional photo taking on memory for visual and auditory aspects of experiences. Those that were allowed to freely take photographs during an experience had better recognition of what they saw, but less recognition of what they heard, compared to those who could not take any photographs. This effect was also observed when participants only took mental photos, ruling out the necessity of interacting with an actual camera as causing this shift in attention (also see Diehl et al., 2016). Interestingly, participants who used a camera during their experience even had better recognition of nonphotographed aspects compared to participants without a camera.

Other recording devices Beginning in the 2000s, a timelapsed video recording device called SenseCam played a pivotal role in autobiographical memory research. The device hangs around the neck using a lanyard and automatically takes photos if triggered by changes to an environmental sensor—monitoring lighting, heat, temperature, microphone—or otherwise every 30 seconds (Hodges et al., 2006). Berry et al. (2007) conducted a preliminary study with a patient with memory

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impairments. Within the duration of the study, after an interval of three months there was no recall for autobiographical events with no aids, but this rose to over 70% when cued with images from the SenseCam. Later research has continued to explore the SenseCam as a memory rehabilitation aid (Nguyen et al., 2009; Hodges et al., 2011; Doherty et al., 2011; Dubourg et al., 2016; Silva et al., 2017). Some studies have further used the SenseCam with young and older adult samples to characterise everyday memory that can be objectively assessed (Mair et al., 2017). Providing another approach for event veracity, some studies have used staged events (Mair et al., 2018). A similar device for recording periodic sound samples has also been used to create objective recordings of autobiographical events: Electronically Activated Recorder or EAR (Mehl et al., 2001; Mehl & Holleran, 2007). This device records 30-second samples once every 12 minutes for 2–4 days. Mehl (2017) provides an overview of research conducted with the EAR and uses it to conduct naturalistic research. Wank et al. (2020) used the EAR with over 100 older adults and recorded real-world conversations over a four-day period. The conversations were then scored for use of semantic and episodic details in real-world sharing of autobiographical memories, following the wellestablished Autobiographical Interview protocol (Levine et al., 2002). This work helps characterise how people use autobiographical memory in their own lives, rather than more laboratory-based interviews. Lifelogging, the practice of continuously recording one’s daily experiences using digital devices, is a frontier of autobiographical memory and veridical recordings. By creating a detailed digital archive of our lives, lifelogging has the potential to augment human memory, but is not without its challenges. These devices do more than just capture images; they also record video, GPS, and sensor data, creating a rich reproduction of our life experiences. The SenseCam in particular has been shown to be a useful tool for lifelogging (Doherty et al., 2011; Bolanos et al., 2017; Mair et al., 2017). Some additionally record audio, although this increases the degree of consent issues that need to be carefully considered. The practice of lifelogging brings with it a host of privacy and ethical concerns, from the recording of others to the potential misuse of intimate lifelogs (Price et al., 2017). Technology can also be used to improve memory for everyday adults in older adults. In a novel intervention, Martin et al. (2022) developed a smartphone app—HippoCamera—to allow older adult participants to record and replay personally meaningful events. These brief but detail-rich cues improved memory at assessments with 2-week and 10-week periods, as well as 3-months after not using the app. Brain activity was also examined in the study, finding that app-associated re-experiencing increased mnemonic discrimination. This project demonstrates a promising use of technology to enhance memory and improve quality of life. De Leo et al. (2011) also explored the use of smart phones as a tool to aid memory, here for use with patients with Alzheimer’s disease. Here researchers gave smart phones loaded with a custom application designed

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to support autobiographical memory recall to patients with Alzheimer’s disease. The application included features such as reminders for appointments and medication schedules, as well as prompts for recalling specific events or memories. Participants were also able to record audio notes and take photos using the smart phone. Recall was assessed before and after using the smart-phone application for six weeks, showing an improvement due to the intervention. Some patients may have difficulty learning how to use the technology and may become frustrated if they are unable to operate it correctly. Overall, this study suggests that smart phones can be an effective external aid for supporting autobiographical memory in patients with memory deficits (also see Wade & Troy, 2001; Woodberry et al., 2015). Modern technology can be re-purposed in ways that can create meaningful new possibilities. A particularly innovative solution is to use Google Street View data, readily and publicly available in a limited form (with a computerconnected stationary bicycle), to allow dementia patients to visit places they remember—very literally taking a trip down memory lane (Hafizi, 2019). The original developers called the approach “BikeAround” and designed it to serve as a type of reminiscence therapy. Figure 13.1 shows an illustration of the equipment setup. The ‘visit’ is done remotely and safely from a care home, with no worry of getting lost. Though it is only a view from the street, it can be done in the past—the camera data is periodically collected and there is an option to rewind to an earlier state. I am from Canada and can see the house I grew up in from as far back as 2009, with views from 2012, 2014, and 2015 also accessible—even though I now live in the UK.

FIGURE 13.1: BikeAround equipment setup.

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13.3 Remembering how instead of what Notes, photos, videos—all of these are artifacts of our own experiences, things we make ourselves. They can be shared with others too though. This is much more often the case, where semantic knowledge exists in the world and we want to learn it. At the very least, this applies to the modern education system— even this book itself. But, modern technology has been changing the script. Do you need to remember a recipe if you can look up a video online? Is there enough reason for a London taxi driver to learn The Knowledge when GPS navigation systems are readily available? Should schools be teaching topics like world history and the sciences? All of these sorts of information can be looked up when needed, so why learn the what as long as you know how to find it. Reliance on the internet as part of our memory is now included as part of the concept of transactive memory (Sparrow et al., 2011; Ward, 2013; Ferguson et al., 2015; Risko et al., 2016). If you do not know a fact, you look it up. Even if you cannot recognise a song, you can have your phone identify it for you (Wang, 2006). This term ‘transactive memory’ arose from Wegner (1987), who defined the term as “a set of individual memory systems in combination with the communication that takes place between individuals” (p. 186; also see Wegner et al., 1985, 1991; Sutton et al., 2010; Hirst & Echterhoff, 2012; Liao et al., 2015). Originally, transactive memory has been used to refer to memory shared within a group, ‘collaborative remembering,’ such as autobiographical memories discussed at a high school reunion (Barnier et al., 2008), the distributed expertise associated with a working team (Michinov et al., 2008; Meade et al., 2009; Liao et al., 2015), or even experimental lists of objects where each partner in a couple has been assigned to remember items belonging to a specified category (Wegner et al., 1991). Comprehensive reviews of the transactive memory literature have highlighted the breadth of study designs used to study the concept—as well as the ill-defined and heterogeneous nature of the transactive memory system (Peltokorpi, 2008; Ren & Argote, 2011). MIN RE

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Sparrow et al. (2011) was a key study in examining how the internet relates to cognitive processing, and memory specifically. The researchers conducted four experiments to investigate the effects of the internet on memory. Experiment 1 had participants complete trivia questions interleaved with a modified Stroop test using internet-related words, functioning as a semantic priming manipulation. Sparrow et al. (2011) includes a heterogeneous set of studies and this one was not particularly of interest from my own perspective.

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Experiment 2 used trivia questions, but focused on a between-groups instructed-memory manipulation—akin to directed forgetting. The results here were not particularly definitive. Experiment 3 was within-subjects manipulation of trivia answers being stored in the computer, or not. Participants knew they would need the answers again later, so if it was erased from the computer, they would need to rely on their own memory. Participants’ memory for the trivia answers was better— in a recognition test—when they thought it would not be accessible from the computer. There were three conditions, however: stored, erased, and stored in a specific computer folder. For this last condition, if they had been told where it was saved, they had to identify where, a sort of source-memory test—though here memory was not different from otherwise stored. Experiment 4 was of particular interest, and is discussed in much more detail in the paper than the preceding three experiments. Here participants had a similar procedure to Experiment 3’s last condition, but were tested for recall of trivia answers. Afterwards they had to judge where the trivia was saved. Results showed that people had better memory for where to find the information than for the information itself. This was the most related to the broader notion of a shift in our memory strategies with the advent of the internet. Instead of remembering the information itself, we are now remembering where to find the information. It underscores how our memory systems adapt to new technologies and the changing information landscape. As we continue to navigate this digital age, it is crucial to understand these shifts and their implications for our cognitive processes. Camerer et al. (2018) conducted a replication of many psychology papers published in Science and Nature. This included Experiment 1 of Sparrow et al. (2011), and it did not replicate. Hesselmann (2020) also failed to replicate this experiment. However, in my view, Experiment 4 is the most interesting and has relatively strong results. In our daily lives, the reliance on digital aids extends beyond mere factual information. Many of us no longer bother to memorise phone numbers or addresses, relying instead on our devices to store and retrieve this information. Even personal details—such as friends’ birthdays—are often outsourced to digital tools. Social networking sites readily provide this information and even provide reminders. While this might seem convenient, it also means that we are entrusting important aspects of our personal relationships to these platforms. Moreover, we are increasingly relying on digital calendars and reminders to manage our time and tasks. These tools can be incredibly useful, helping us to stay organised and remember important dates and deadlines. However, this reliance on external aids also means that we are less in control of this information; if our devices fail or are lost, we lose access. Of course, the internet also includes information we were never aware of. Hinnosaar et al. (2023) examined the influence of Wikipedia articles on tourist travel. Through a randomised field experiment, the researchers improved the Wikipedia pages for some Spanish cities in 2014. For these pages, they added

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tourist-relevant information and images. They then examined tourist travel statistics between 2010 and 2015. The study found that these improvements led to a 9% increase in hotel stays in the cities where the Wikipedia page was enhanced; increases were particularly evident where pages were previously incomplete. This study shows that how we rely on external sources can influence our behaviour. The issue becomes particularly problematic when we consider the varying reliability of online information sources. For instance, while Wikipedia can be a great resource for quick information, the quality and accuracy of its content can sometimes be questionable. As a user-generated platform it is not immune to errors or biases, even though there are measures in place to moderate the information. While digital aids can enhance our memory and cognitive capabilities, it is crucial to use them judiciously and critically.

Arguments for and against using external aids This reliance on digital memory has both benefits and drawbacks. On the positive side, it frees up cognitive resources—referred to as cognitive offloading (Schönpflug, 1986; Risko & Gilbert, 2016; Storm et al., 2017, 2022; Carter, 2018; Fisher et al., 2022). With external memory, we can store and retrieve vast amounts of information. Moreover, using external stores sill requires some minimal internal representation of the external information (Schönpflug, 1986, 1988). However, there are also downsides. Some argue that this reliance on external resources can lead to a decline in our memory abilities over time (Carr, 2011; Marder & Marom, 2022). This is not a new view. In Phaedrus, Plato (360 BC, 275a) recounts a conversation where Socrates cautions Phaedrus against being too dependent on written texts: Trust in writing will make them remember things by relying on marks made by others, from outside themselves, not on their own inner resources, and so writing will make the things they have learnt disappear from their minds. [Writing] is a potion for jogging the memory, not for remembering. You provide your students with the appearance of intelligence, not real intelligence. Because your students will be widely read, though without any contact with a teacher, they will seem to be men of wide knowledge, when they will usually be ignorant.

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In contemporary times, thousands of years later, not much has changed. Marder (2017) laments: Those of us who teach undergraduate and graduate students daily confront the fact that our students often do not remember what they learn in class or read, even if they get almost perfect scores on their exams. Our students have seemingly moved storage from their brains to their phones or tablets. What is more, they are completely convinced that because they can, in principle, access the world’s knowledge with a few key strokes, there is little reason for them to remember what they studied the previous semester, or read last month. (p. 1) And, even more recently, “you cannot reason with understanding or knowledge that you do not know exists, even if your phone knows it” (Marder & Marom, 2022, p. 145). A similar point was also made by Asimov (1958) regarding the societal loss of basic thinking abilities due to increasing technological advances. On the other side of the argument, a quote often attributed to Albert Einstein states, “Never memorise something that you can look up.” However, a more thorough examination of Einstein’s words reveals a different sentiment. When asked about not knowing the speed of sound for the Edison Test, Einstein responded that he did not “carry such information in my mind since it is readily available in books” (New York Times, 1921). This statement underscores his belief in the importance of understanding over rote memorisation, and that some facts are not neccesary to be memorised. While there may be fears about the impact of external memory on learning and memory—why teach students historical facts and specific numbers that they are unlikely to need beyond the course exam—external aids are part of daily life. Instead of limiting people with tradition, we need to study and understand how these external memory stores change behaviour and find ways to work with these changes. The historical diaries we discussed earlier—Napoleon, Galileo, and Anne Frank—provide records of events and experiences prior to our lives, emphasising the sociocultural role of memory—of understanding our history. Banned books, often those that are particularly effective at being thoughtprovoking, are still being banned in some parts of the world. This highlights the power of memory and the written word, and the lengths to which some will go to control it. The adage “history is written by the victor” underscores this power dynamic inherent in memory and history. As is being increasingly highlighted in modern times, through initiatives to ‘decolonise the curriculum,’ the narratives of the marginalised have often been suppressed, and only now are efforts being made to redress these imbalances.

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13.4 Memory in a digital society Many contemporary memory aids are digital. Our daily lives now revolve around smart phones and computers, but these now also serve us as technological external memory aids. Moreover, our use of these devices is continuously increasing (Finley et al., 2018). The internet, in particular, is changing how we remember (Hoskins, 2009; Brockmeier, 2010; Carr, 2011; Clowes, 2013; Ward, 2013; Poundstone, 2016). With the easy access of the internet, this reliance on external memory goes further—allowing us to ‘remember’ information that we never knew in the first place (Barr et al., 2015; Ferguson et al., 2015; Risko et al., 2016; Storm et al., 2017). The internet now serves as an extension of our mind. Human memory has been constant over the ages, but the society around us is more fluid. In today’s digital society, how we access information and share our experiences is changing—“google” was added to the dictionary as a verb in 2006 (The Motley Fool, 2006), “instagram” was added in 2018 (Merriam-Webster, 2018). People no longer have dictionaries and volumes of encyclopedias in their living rooms, family photo albums have been replaced by memory cards. Even then, in ancient times past, literacy was not as common as it is today. Memories of facts and past events used to only be conveyed by conversation, experiences were more ephemeral and were not able to be recorded verbatim. Such a world is nearly unfathomable now, but really it is the current circumstances that have changed our relationship with externalised information rather drastically and suddenly. This has implications for both our episodic and semantic memory. Episodically, we are less likely to remember specific details of events or experiences because we know we can revisit them through digital photos, videos, or social media posts. Semantically, we are less likely to remember factual information because we know we can look it up online at any moment. With diaries and photos, you decide what events get canonised in external memory, to be reflected upon as desired. With encyclopedias and reputable resources, we trust that the facts we look up are correct. But, with the internet as a whole, you are open to the views of many either in a (semi) democratised form, such as Wikipedia, or the views of the specific websites’ author.

Digital preservation While the internet is growing at a rapid rate, information is also being lost at an unimaginable rate—known as link rot (Woodyard, 2003; Markwell & Brooks, 2003; Zittrain, 2021). In some cases these are more personal memories, websites that we used to send short messages to friends or share our favourite songs have come and gone. When artists first started making digital art, it was truly ephemeral as there was not yet a save function—though some works were saved through photos of the screen (Haeger, 1985). In some ways, this is not a new problem. For hundreds of years, historians and archivists have been

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recovering and preserving manuscripts from ages long past (Echard, 2000; Landrus, 2018; Hagen & Soliman, 2018). That said, it is far easier to purchase a book printed decades ago than it is to retrieve data stored on a floppy disk. Several organisations have stepped in to preserve our past as we have transitioned into the Information Age, such as Project Gutenberg and Internet Archive (Gomes et al., 2021). However, the technical issues associated with long-term data preservation are substantial (Hedstrom, 1997; Rickards et al., 2020; Antoniazzi, 2021), let alone issues related to the shifting cultural views (Rosenzweig, 2003). As you can see, long-term preservation of digital information is difficult. Some companies have built hardware that can write DVD or BlueRay compatible discs to rock-like material discs, called M-DISC (or Millennial Disc), estimated to be able to last for a thousand years. But, will we continue to have compatible disc readers and support the requisite file formats for similarly long periods of time? Paper, paintings, and other ‘analog’ approaches have worked well so far, despite issues with later, further reproduction. We have long since passed the stage of copying text being an arduous task for scribes, but photocopying and scanning are not lossless reproductions, noise gets introduced and quality is reduced. As technology advances, it will be crucial for archivists and preservationists to anticipate and adapt to potential challenges in maintaining compatibility and accessibility to historical records. Separate from the loss of data is the preservation of data in an everchanging world. There are instances when content—such as a TV show or movie—was publicly available, but can no longer be accessed or found. This is referred to as “lost media.” This is usually because the content was shared in a pre-digital age and long-term preservation was not yet viewed as an important consideration—most instances of this are from the 1960s and 1970s. Doctor Who, a long-running British TV series, has been particularly affected by lost media. The show first premiered in 1963 and has since become a cultural phenomenon. However, during the early years of the show, it was common practice for the BBC to erase tapes or reuse them for other broadcasts— videotapes were expensive and archiving was not a priority. This has led to numerous early episodes being lost or partially lost. Over the years, dedicated fans and researchers have made substantial efforts to recover lost episodes. As of 2023, 97 out of the 253 episodes from the show’s first six seasons (1963–1969) were still missing. The BBC has made an effort to reconstruct and release missing episodes through various means (Molesworth, 2010). One approach is to use surviving audio tracks, often recorded by fans during the original broadcasts, combined with still images, photographs, or animation to provide a visual representation of the lost content. These reconstructions have been well-received by fans and offer a way to experience the missing episodes despite the absence of the original footage (Hills & Garde-Hansen, 2017). There is still hope that more episodes may be recovered—copies were sold to foreign broadcasters and some recoveries are from archives of these TV stations in Canada, Nigeria, and Hong Kong. This search for lost episodes serves as a

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reminder of the significance of archiving and the need for effective long-term digital preservation strategies in an ever-changing world. Another recently found piece of lost media is an episode of Sesame Street from 1976. This episode, number 847, featured the Wicked Witch of the West from The Wizard of Oz. After originally airing on television, this episode was not well received by parents and was deemed unsuitable to be re-aired. As with Doctor Who, consumer recording devices were not common and this was a period when master recordings were not always saved, so for decades it was unknown if there was any trace of this episode remaining—save for a few still images that had been archived. In 2019, however, Sesame Street provided an archive of all episodes for archiving to the US Library of Congress, though only to be viewed in person. Later that year, a copy of the episode circulated online, after remaining unavailable to the public for over four decades. The preservation of data not only ensures that historical records are maintained, but also that valuable cultural artifacts and stories continue to be accessible and enjoyed by future generations. Our contemporary online streaming platforms provide solutions, but also new problems. These platforms improve accessibility of old films and TV shows, but also can decide to remove titles with little notice. In some cases this is due to licensing agreements that expire, but this even occurs from the company owning the property—typically as a means to reduce on-going expenses and royalties (Chan, 2023). More troubling, however, is that historical films can be edited and only streamed as a modified version, without any disclaimer saying otherwise. In mild versions, this has occurred several times recently where the ending of TV shows has been retroactively edited to better fit with other works in the same overall setting (Lussier, 2021; Chilton, 2023). More controversially, the 1971 Oscar winning film, The French Connection, has been edited as a form of censorship (Klein, 2023). This 2023 modification removed racial slurs that were obviously slurs even in 1971, but only now have been removed—with no formal acknowledgment that the change even occurred (also see Alexander, 2020). Some initiatives for digital preservation have come from unexpected places. In 2020, Reporters Without Borders launched The Uncensored Library, a virtual library containing censored and banned journalistic work from around the world. This Uncensored Library, however, exists as a Minecraft server. By using Minecraft’s in-game book mechanics, The Uncensored Library makes suppressed articles accessible to millions of users in countries where press freedom is restricted. The virtual library embodies the idea of digital preservation by ensuring that these valuable resources are accessible and not lost to censorship. The significance of this initiative is further emphasised by the deteriorating political landscape in Western countries like the US and UK, where classic books are increasingly subjected to censorship based on contemporary perspectives regarding race, sexual identity, and colonialism.

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Though the issue of lost media is important, it is also crucial to recognise and avoid perpetuating past mistakes in our digital preservation efforts. A notable example is the widespread use of the “Lenna” image in computer science for evaluating signal processing and image compression algorithms. This standard test image is derived from a cropped version of a 1972 Playboy centrefold, raising concerns about perpetuating sexist and inappropriate content in a professional context (Munson, 1996; Editorial, 2017; Wirth & Nikitenko, 2011). By acknowledging such issues, we can work towards creating a more inclusive and ethical environment in digital preservation and technological advancements. Unlike books and video recordings, the internet and other modern digital media—such as videogames—are living works, continually updated. Accessing previous versions of web content can be difficult—as an example, when writing this book there were several instances where supplementary information was intended to be available through a researcher’s website that are no longer available. More generally, when viewing videogames as works of art to be shared and experienced (where content is continually updated), it can easily become impossible to re-experience them in their original form. This can lead to a nostalgia for how the media used to be (Whalen & Taylor, 2008; Murphy, 2013; Sloan, 2015; Makai, 2018; Harris, 2020; Robinson & Bowman, 2022; Williams & Tobin, 2022), and for instance, the impossibility of being able to share an online videogame with your child in the way it was when you first experienced it. From a thorough analysis of 1,500 videogames, 86.7% of classic videogames released in the United States between 1960 and 2009 are no longer commercially available (Salvador, 2023). This does not include unofficial archival methods such as emulation. Compared to studies of other creative mediums, the availability rate of pre-2010 videogames (13%) is similar to the commercial availability of pre-World War II audio recordings (10% or less) or silent-era American films (14%). Not to belabour the point, but I personally find it quite amazing both what we have been able to preserve and share as memories, and what we have not yet managed. We can have photos from many decades ago—film (analog) photography can be scanned and digital photos can be readily saved and shown to others. A talk that I gave nearly a decade ago that was live streamed is still available online. Even with single-player games, it is increasingly becoming required to be online so the game can ‘check in’ with a server run by the publisher as a form of anti-piracy protection—and can also impede game performance (Taylor, 2018; Gallagher, 2021). Once these servers are shut down, the game becomes permanently inaccessible. Sometimes this occurs just a few years after the initial game release. This balance of ownership and ability to share experiences is increasingly relevant with the increasing reliance on digital technologies, rather than analog ones (Finley, 2013; Kubesch & Wicker, 2015; Karthik et al., 2020).

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Older console games, however, can be playable through emulation. There are some aspects of the experience lost still, the inherent graphical limitations create particular artifacts in the visual associated with old cathode-ray tube (CRT) televisions that are not reproduced by modern monitors (e.g., pixel softness and scan lines). These differences can contribute to a mismatch between how you remember the retro game graphics looking when attempting to reproduce them with modern hardware, decreasing the feeling of nostalgia. Highlighting the nostalgia of videogames from yesteryear, “DOS Memories Project” collects over 2,800 PC computer games released between 1980 and 2003 (Internet Archive, 2013). The Internet Archive has also made the games playable online via the internet browser, further facilitating the accessibility of these games for years to come (https://archive.org/details/softwarelibrary _msdos_games). In announcing this project, Scott (2019) said: What makes the collection more than just a pile of old, nowplayable games, is how it has to take head-on the problems of software preservation and history. Having an old executable and a scanned copy of the manual represents only the first few steps. […] They were released, sold some amount of copies, and then disappeared off the shelves, if not everyone’s memories. A related initative, eXoDOS, has collected and packaged over 7,200 DOS games so that they can be played on your local machine (www.retro-exo.com/ exodos.html). Lendino (2022) provides a narrative overview of how these games and associated technologies developed (also see Hansen, 2016; Etchells, 2019). Figure 13.2 highlights some of my favourite DOS games. Nostalgia is closely tied to our memories for past experiences. The word comes from the Greek words “nostos” and “algos,” for the concepts of returning and pain, respectively. It is first used as a medical diagnosis for unwellness associated with homesickness (Hofer, 1688). It can be challenging to separate our personal experiences from the context of the present, but popular culture seems to have embraced nostalgia for several reasons. Firstly, the rise of social media has made it easier for people to connect with each other and share memories of the past, creating a sense of nostalgia among those who look back on their childhoods and adolescence with fondness (MacDonald, 2015; Chopra-Gant, 2016; Finley et al., 2018; Stone et al., 2022). Secondly, the current political and social climate is often perceived as negative and divisive, leading some to seek comfort and familiarity in the past (Andris et al., 2015; Taylor et al., 2017; Rollwage et al., 2019; Chiew et al., 2022; Jost et al., 2022). Moreover, the increasing availability of streaming services allows people to easily access old movies and TV shows, offering the opportunity to revisit their favourite childhood classics (Murphy, 2013; Makai, 2018; Pallister, 2019; Liboriussen, 2023). This accessibility has contributed to the growing focus on nostalgia in today’s culture.

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FIGURE 13.2: Screenshots from a selection of DOS games. (A) The Secret of Monkey Island (1990). (B) Lemmings (1991). (C) Solar Winds (1993). (D) One Must Fall 2097 (1994). (E) Commander Keen (1990). (F) Prince of Persia (1989). (G) Wolfenstein 3D (1992). (H) Warcraft II (1995).

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Unfortunately, this chapter likely will not age as well as the rest of this book, due to the focus on modern technology. Memory studies from five to six decades ago, or even a hundred years ago, are still very relevant to our current understanding. However, the proliferation of the internet and later of smart phones has changed how we interact with technology on a daily basis, and how accessible knowledge has become. While websites like Facebook and Instagram have become quite pervasive in daily life, many of the principles underlying the studies discussed in other chapters—even if not the studies themselves—use procedures that are relatively ubiquitous and could have been done comparably well decades ago. Even during the course of writing this book, societal views on using Facebook have changed. I can only guess how perspectives on memory and digital technology may change in the next five to ten years—but we can look to fictional depictions of futuristic memory technologies. The interactions between memory and our current digital society, particularly the internet, are quite complex. On the one hand, the internet makes a wealth of facts and knowledge readily available, and does not need to be remembered. Automated notifications from social media can be a godsend—it can be hard to keep track of birthdays and even know of important events to congratulate others on, as in Figure 13.3. On the other hand, to use technology we are required to remember specific, self-generated bits of information verbatim, along with associated context—passwords. We are encouraged to have different passwords for different websites, particularly for ones such as email and bank accounts, as well as for the computer and mobile devices themselves. Moreover, we are also often encouraged, if not required, to periodically change these passwords every few months or once a year. Reminders from social media are not always good though. For instance, reminders of birthdays or shared experiences with someone who has since passed away can be difficult to deal with. Grieving after a death is a difficult process, even after many years. An involuntary reminder from a ‘well meaning’ social media website can prevent adequate coping and moving on. Persistence on the internet after having passed can form a memorial or a digital immortality (Stokes, 2012; Walter, 2015). A more advanced view of this is portrayed in the episode of Black Mirror entitled “Be Right Back” (2013; Season 2 Episode 1). In this episode, a digital version of a loved one is reconstructed based on their social media data, supplemented with provided personal photos and recordings. Here a dead loved one is first able to respond to messages over an instant messenger, then talk over the phone, and finally is re-made with a physical body. Though this last step is clearly fictional, it is still shown that the reconstruction is limited. He cannot tell any stories that have not already been told and cannot feel genuine emotions. He is hollow. The first portion of this—developing an AI chatbot that can respond to messages, referred to as a thanabot—has recently become a reality (Henrickson, 2023). The instance that received the most press was Barbeau (2021), who lost his fiancee Jessica Pereira to a rare liver disease several years ago. Featured in a

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news article, Joshua describes how he used a website called Project December to build a chatbot of Jessica based on her social media posts and emails (Fagone, 2021). In an earlier instance, Eugenia Kuyda was devastated when her friend Roman Mazurenko died in a hit-and-run accident in November 2015. She decided to create a memorial bot for Mazurenko using the thousands of text messages they had exchanged over the years (Newton, 2016). The bot is able to hold text conversations and answer questions in Mazurenko’s voice and helped Eugenia to grieve. As argued by researchers working in this field, as technologies evolve, so do the ways that we grieve a loved one (Elder, 2020; Sisto, 2020; Krueger & Osler, 2022; Xygkou et al., 2023; Henrickson, 2023). The interplay between memory and the changing technologies of our society raise thought-provoking questions about the evolving nature of human connection and remembrance. As we continue to explore the potential of these technologies, it’s essential to balance the opportunities they offer with the ethical concerns they present, ensuring we honour the authentic essence of individuals’ memories and experiences.

FIGURE 13.3: Facebook reminders. Credit: Safely Endangered Comics, by Chris McCoy.

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Many websites on the internet have stated that the capacity of human memory is around 2.5 petabytes—equivalent to 2.5 million gigabytes. This estimation is based on a scientific study (Bartol et al., 2015), corresponding to bits of information represented by neural synapses. However, this is often then converted into quantities of books, photos, songs, and movies. There is no basis to assume that the brain stores data in a similar format to computer data files. For instance, pictures can be stored in different formats, involving data compression or not. Some of these formats take advantage of variations in luminance and colour that correspond to human perception, such as variation in luminance being much more salient than colour saturation, and biases in spatial frequency sensitivity, but these then also differ in their corresponding file size. Moreover, pictures can be stored based on arrays of pixels (i.e., raster) or based on relationships between points (i.e., vector). Each has their benefits in practical use for different types of pictures, such as photos vs. logos, but also in how efficiently they store data. Moreover, humans can readily process object segmentation and know which portions of the picture represent a composite object, like a car or building, and distinguish these from background properties. ‘Groups’ or ‘layers’ are not represented in typical picture formats, but are available in some that are used by graphics designers. Nonetheless, our understanding of semantic knowledge is intrinsic to our ability to remember information, but is not a property of computer data files.

Information reliability With information much more available and abundant, it is harder to discern fact from fiction. For a time, photographs and audio recordings provided a means to document events without room for interpretation or biases, but current technology now allows for such evidence to be generated and modified without a blemish to signify a change has been made (Wade et al., 2002; Rajanala et al., 2018; Murphy & Flynn, 2021; Johnson et al., 2023). The world has become increasingly interconnected, but one’s ability to distinguish expertise and knowledge from ‘fake news’ and bias has become more challenging (Madan, 2024). When it comes to a given topic, everyone has a voice, but not all are equally worth hearing (see also Hills, 2019). It may seem like non-experts are becoming overconfident in their expertise, from the Dunning-Kruger effect (Section 11.1, p. 332) to the democratisation of communication afforded by the internet and our modern “death of expertise” (Nichols, 2014, 2017; Hills, 2019). Now people can look online for health advice, but this often leads to greater negative affect and anxiety (Hardey, 1999; Jungmann et al., 2020). When people are warned that external information may not be reliable, they can better notice manipulated information (Karanian et al., 2020; Pereira et al., 2022). While the topic of misinformation has become more important than ever, it is not as new as you might think. In the late 1990s in Canada, a public service announcement (PSA) began airing on TV, describing the House Hippo. The

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ad begins with a narration describing the House Hippo, showing it foraging for crumbs, drinking from a dripping tap, and nesting in a glove. The PSA’s looks realistic and was designed to challenge viewers to think critically about what they see in the media (Concerned Children’s Advertisers, 1999): It’s nighttime in a kitchen just like yours. All is quiet. Or is it? The North American House Hippo is found throughout Canada and the Eastern United States. House Hippos are very timid creatures and are rarely seen, but they will defend their territory if provoked. They come out at night to search for food, water, and materials for their nests. The favorite foods of the House Hippo are chips, raisins, and the crumbs from peanut butter on toast. They build their nests in bedroom closets, using lost mittens, dryer lint, and bits of string. The nests have to be very soft and warm. House Hippos sleep about 16 hours a day. The advertisement concluded with a message emphasising the importance of questioning and verifying information: That looked really real, but you knew it couldn’t be true, didn’t you? That’s why it’s good to think about what you’re watching on TV and ask questions, kind of like you just did. Think about what you see on the news, or when you’re reading books, and even if you’re playing video games. These messages are still true and necessary today, nearly 30 years later. In the age of information and misinformation, the democratization of communication has been a double-edged sword. On the one hand, it has made information more accessible and easier to disseminate, breaking down barriers and enabling a global exchange of ideas. On the other hand, it has made it increasingly difficult to distinguish between well-founded information and illconstructed perspectives. The sheer volume of information available, coupled with the lack of effective gatekeeping mechanisms, has created a fertile ground for misinformation to flourish. This has been further exacerbated by the rise of social media platforms, which allow for rapid dissemination of information, irrespective of its veracity. The result is a complex information landscape where truth and falsehood are often intertwined, making it challenging for individuals to navigate and make informed decisions. DER CU MIN E RE

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As discussed, there are many benefits to externalising our memory, but the internet also has provided another important difference from our own memory—we are not in charge of it. If you researched a topic and made your own notes on it, then you would be confident that the content is comprehensive and correct. While the notion of misinformation is timely, it is also not new. For instance, Neisser (2008) had commented: “Whenever newspapers turn up, it is wise to bear in mind that not everything they say is true” (p. 82). Further cementing the omnipresence of misinformation as an issue, one of the most well-known myths in society is that spinach is a good source of iron. Ask anyone “what is spinach a good source of?” and they will answer “iron.” This has been common knowledge for generations now. While a few articles have been published on this error (Hamblin, 1981; Sutton, 2010; Rekdal, 2014), none have been as detailed in tracing the error and its correction as Mielewczik and Moll (2016), which is where I am principally drawing a timeline from and is far more thorough. The source of this error itself is a mixture of facts and fiction. Many sources describe this error as being due to a decimal/transcription mistake occurring around 1850—1880, but it appears that errors also occurred in assumptions made about the use of fresh or dry weights of vegetables when conducting chemical analyses. This finding that spinach is a good source of iron was then highly popularised from 1900 to 1940s in newspapers worldwide. This view was further shared through comics and animated films featuring Popeye in the 1920s to 1940s. Articles drawing attention to the over-estimation error began to circulate in the 1950s, however, even many decades later the myth is still generally accepted (also see Byun & Spaide, 2021). In a recent study of pharmacy students (Jasińska-Stroschein et al., 2019), this myth was the most falsely accepted of those included in the survey—only 13.4% correctly identified it as a myth. Another common myth is the belief that carrots improve eyesight. This belief originated as propaganda by the UK government during World War II, when people were encouraged to grow carrots to supplement rations and help with night blindness (Stolarczyk & Janick, 2011; Byun & Spaide, 2021). This was done both to help prevent enemy bombing runs when lights were turned off, and to hide the development of their new radar technology from the enemy. Over time, this propaganda has held, and the message that carrots are good for your eyes became common belief that they improve eyesight. While carrots are a good source of beta-carotene, which the body uses to produce more Vitamin A—a nutrient essential for good vision (Smith et al., 1999)—there are better sources of Vitamin A in contemporary times, such as eggs, fish, cheese, and butter. Despite this, the myth persists, and it is time for us to move on from war-time propaganda and revise our understanding of nutrition. As we transition from the realm of food myths to the world of gaming, it’s interesting to note the power of misinformation and how it can shape our understanding and beliefs. Just as the myths about spinach and carrots have persisted for decades, so too has a particular myth in the gaming world. Another example is the well-known bug in the computer game Civilization,

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known as “nuclear Gandhi.” For this I will quote the game designer, Sid Meier, from his recent memoir: all of the leaders were given a score from 1 to 12 across a number of variables, and Gandhi’s military aggressiveness was placed at 1, as would be expected. A different piece of code, however, called for an automatic two-point drop in military aggressiveness whenever a country adopted democracy, which would theoretically have put Gandhi at a score of negative 1. But since negative numbers were impossible in this type of calculation, an overflow error caused the value to wrap around to the top of the number list, giving him a score of 255. Thus, the moment India became democratic, Gandhi would turn into a vicious warmonger and begin nuking everyone in range. […] But it’s not the countless callbacks and references that make the nuclear Gandhi story so funny to me. It’s the fact that none of it is true. The overflow error never happened at all. […] Dedicated fans will be quick to point out that Gandhi’s preference for nuclear weapons over other forms of warfare was set to 12 in Civilization V, as revealed by the game’s lead designer, Jon Shafer. But that was nineteen years after the original release, and Jon was only leaning in to the existing amusement over Gandhi using nuclear weapons at all. His was the first game in the series to codify it as an Easter Egg for fans, and he had never heard of the 255-overflow story when Civ V was released in 2010. (Meier, 2020, pp. 261—266) Given the availability of misinformation, being able to assess information reliability is ever-increasingly important, particularly related to health topics. Cameron et al. (2013) assessed how different message formats of facts and myths influenced participants’ knowledge and recall accuracy. Participants were randomly assigned to view one of four influenza-related messages: (1) CDC control, (2) Facts only, (3) Myth and Fact, and (4) Myth, Fact, and Refutations. An example of these stimuli is shown in Figure 13.4. The CDC control condition was based on existing practices, including myths and facts, but were generally more verbose than the corresponding experimental condition; moreover, the myth and fact were not always closely matched. Knowledge was measured using true/false items at pre- and post-test, while recall accuracy was assessed using specific items at post-test. Results showed that all participants’ knowledge scores increased; however, recall was the best for those that received the myth, fact, and refutation. The study also highlighted the concerns regarding the repetition of false information, even if

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it is repeated to discredit that information. Previous research suggested that some—particularly older adults—misremember myths as facts. The findings have significant implications for health education materials. While presenting both facts and myths may be appealing, caution should be exercised.

FIGURE 13.4: Example health messages from Cameron et al. (2013). The clearest example of belief in a false memory in the general public is the Mandela effect, and misremembered facts that go with it. The term was coined by paranormal consultant Fiona Broome, and it characterises a collective misremembering of specific facts or events by a large group of people. The term was inspired by the widespread false memory of the death of Nelson Mandela in prison during the 1980s, despite the fact that he lived until 2013. One of the most famous examples of the Mandela effect is the misremembering of the title of the popular children’s book series, “The Berenstain Bears.” Many people recall the title as “The Berenstein Bears,” with an E instead of an A in the last syllable. This widespread misremembering has led to numerous debates and theories, including some that delve into the realms of parallel universes and quantum physics. The phenomenon also highlights the role of collective memory in shaping our understanding of the world. Collective memory refers to the shared pool of memories, knowledge, and information of a social group that is significantly associated with the group’s identity. The Mandela Eefect demonstrates how collective memory can diverge from factual reality, creating a shared but inaccurate recollection of events. Since it was first developed, there has been some academic discussion of the effect (Spinney, 2017; French, 2018; Prasad & Bainbridge, 2022). Most notably, Prasad and Bainbridge (2022) conducted a series of studies on the Mandela effect, using pictures that were selected to be likely to evoke it. In

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Experiment 1, participants completed a forced-choice recognition task on 40 popular culture images. Seven images showed the criteria of the effect: low identification accuracy, a specific false memory shared across participants, high familiarity and confidence despite poor accuracy. These seven images corresponded to C-3PO, Fruit of the Loom logo, Curious George, Pikachu, the Monopoly man, Tom (of Tom & Jerry), and the Volkswagen logo. Image variations for each of these are shown in the paper. (Experiment 2 was less relevant.) Experiment 3 quantified the real-world visual experience of the Mandela effect images by scraping Google Images. Results showed high variation in exposure to the canonical vs. Mandela version across images. This suggests there may not be a consistent perceptual cause for the false memories. Experiment 4 used an online drawing task to test whether the Mandela effect occurs in free recall. Around half of the drawings contained the specific Mandela error, showing that the false memory also arises in recall. Overall, the study provides evidence that certain images elicit consistent, specific false memories across people. Given modern advances in technology, information reliability is increasingly coming into question. As an example, given sufficient samples of an individual’s speech, it is possible to construct new phrases. As a more extreme scenario that has recently been undertaken, a fake news broadcast has been created based on the possibility that Apollo 11 had ended in disaster (Panetta et al., 2020). This project used a speech for then-President Nixon that had been prepared at the time (Safire, 1969), in combination with advanced AI-based computational methods to construct a ‘deepfake’ video of Nixon delivering the speech. While this video was simulated and refined over several months, the underlying technology will only become more convincing and less time consuming as it is improved. The use of deepfake videos in memory studies is already beginning (Murphy, Ching, et al., 2023). Fake photos are technically much less difficult to construct than faked videos and have circulated for over a decade now. As an example, in 2011 a photo began to circulate of Albert Einstein riding a bicycle away from a test nuclear bomb explosion, as shown in Figure 13.5. In reality, this photo was a composite of two photos—one taken of Einstein riding a bicycle in Santa Barbara in 1933 and another from a desert nuclear test site in Nevada, 1962. Manipulated photos and videos have only become more prevalent as technology has made them easier to modify, opening the door to not only misinformation, but also false memories for personal events. Wade et al. (2002) showed participants an altered photo of a childhood event that never happened: 50% of the participants ‘remembered’ these fictitious events after repeated viewings of the manipulated photos, demonstrating how convincing they could be. Though 20 years have passed since this study, another group of researchers has recently replicated and extended the findings of Wade et al. (2002) to a different event (Johnson et al., 2023). These studies bear some commonalities to the Loftus and Pickrell (1995) lost-in-mall study discussed in Section 2.3 (p. 43), which also replicated (Murphy, Dawson, et al., 2023).

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FIGURE 13.5: Photos components used for the fake composite photo of Albert Einstein riding away from a nuclear bomb explosion. While the potential for manipulated images and videos to induce false memories is a concerning consequence of technological advancement, far more new opportunities are provided. In some cases, modern technology has also created new instances for memorising. When using complex computer programs, such as a 3D modelling application, memorising shortcut keys is an essential skill that can significantly improve efficiency and productivity. Mastering these shortcuts enables users to swiftly navigate through the software, access frequently used tools, and execute commands with ease, reducing the need to search through menus or toolbars. By committing these shortcuts to memory, users can optimise their workflow, allowing them to focus on the creative aspects of their projects and more fluidly turning their ideas into a reality.

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Passwords and security questions Passwords are an oddity of our daily lives. While they are self-generated, they are sometimes constrained by absurd restrictions (e.g., at least one uppercase and lowercase letter, number, and symbol, of at least eight characters, and not the same as you’ve used in your past ten passwords or one year)—we need to recall them sometimes more than a dozen times a day, particularly if using a laptop or office computer. Society expects us to have numerous unique passwords, some of which may be shared with family or housemates. Password managers can be used to alleviate the burden of remembering all these passwords, serving as digital memory aids. Before I began as a researcher, I worked as a website designer and programmer. Sometimes clients would tell me their website hosting passwords so I could test website development (rather than make a separate account). Often I noticed that passwords were the name of their child or an important date, reflecting the typically autobiographical nature of password creation. Security questions, often used as a backup for password use, also tap into autobiographical memory. They typically ask for information individually unique to us; Table 13.1 provides a list of common security questions I compiled from several websites. TABLE 13.1: Twenty often used security questions 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 13. 14. 15. 16. 17. 18. 19. 20.

What is your mother’s maiden name? What is your father’s middle name? What is your library card number? What was the name of your best friend as a teenager? What was the name of your first pet? What was the first dish you learned to cook? What was the first film you saw in the cinema? Where did you go the first time you flew on an airplane? What is the name of your favourite school teacher? What is your dream job? What is your favourite children’s book? What was the model of your first motorised vehicle? Who was your favourite film star or character in school? Who was your favourite singer or band in school? In what city did your parents meet? What was the name of your first manager? What is the name of the street where you grew up? What is the name of the first beach you visited? What was the first album that you purchased? What is the name of your favourite sports team?

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Some, however, opt for more creative answers. For instance, “Lincoln bacon Jordan” might be the answer to a security question. These are not random words, but rather keywords representing a specific scene from a favourite movie, The Island (2005). This scene occurs approximately eight minutes into the film, and the words serve as a unique and individualised mnemonic device. There is typically no constraint that the security question is a sensible answer to the question, though this does make it more difficult to remember the correct answer. Alternatively, some set their password or security question to a list of names of objects that are near their computer. These sequences of words are relatively strong (i.e., difficult to guess by brute force), but also are memorable and can easily be cued by reminders. Ideally, passwords can be used that are related to autobiographical memory and individual preferences (Zviran & Haga, 1993; Rabkin, 2008; Das et al., 2012; Bonneau et al., 2015; Woo et al., 2016). Some of these facts would also be known to others—such as where you grew up, your first pet, and some of your favourite things (Schechter et al., 2009; Moallem, 2011; Podd et al., 1996). Your mother’s maiden name is not a secret, especially with the ubiquity of social media—it has been a ‘secret question’ used in banking for more than a century (Hayden, 1906). Passwords can also be set to be phrases of positive self-affirmation (Li et al., 2022). Some examples of this could be: “IamStr0ng2023!”, “AcHi3veGr8tness!”, and “Bel13ve1nMyself!”. This method, while seemingly unconventional, offers a multitude of benefits. The frequency with which we enter passwords throughout our day means that these affirmations are regularly reinforced, subtly ingraining these positive messages into our consciousness. This aligns with principles of positive psychology, which suggest that such affirmations can bolster self-esteem and overall mood. Moreover, they serve as constant reminders of our ambitions, thereby fostering motivation. From a security perspective, these passwords, being unique and personal, are less susceptible to common password attacks. Their personal significance also makes them memorable, reducing the likelihood of forgetting them. Apart from being a generally ingenious idea, it’s also what Serena Williams (2015) does: Back in 2008, when I was competing in the US Open, I would keep little “matchbooks,” where I’d write affirmations to myself and read them during matches. It worked pretty well. But before long I found an even better way to inspire myself: I started using affirmations as the passwords to my phone and my computer. (No, I’m not going to tell you what my current affirmation is!) You should try it. You’ll be surprised how many times a day you log in and have an opportunity to trigger the positivity. I love that I can use technology that way. (p. 88)

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13.5 Fictional future technologies The notion of using advanced, future technology to hasten learning is almost a staple within society. A clear indication of this from over a century ago is the ‘futuristic’ postcard illustration shown in Figure 13.6. This illustration shows a classroom setting where books are being fed into a machine, that then ‘uploads’ that information into the students’ minds. This can be presumed to be largely semantic knowledge, e.g., facts about science and society, as would be expected to be the focus of a school curriculum, however, other fictional settings have suggested similar processes for other types of information.

FIGURE 13.6: Postcard illustrating a futuristic classroom as part of the series En L’An 2000 (translated to ‘In the Year 2000’), as imagined in 1910 by Villemard. Potential future memory technologies that have been featured in fiction can generally be divided into three categories: (1) downloading memories, (2) sharing memories, and (3) erasing memories. This section is not intended to be a comprehensive list of all fictional memory-related technologies that have been proposed, but is instead a selection to discuss, specifically, those where the technology is sufficiently described in their function and implications, providing some food for thought in possibilities and consequences.

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Downloading memories One of the most memorable phrases from The Matrix (1999) is “I know kung fu,” spoken as the protagonist just finishes having a variety of skills uploaded into his mind. Later in the movie, while in the matrix, Trinity makes a call and asks, “I need a pilot program for a B-212 helicopter.” Moments later, she is completely proficient. In these cases, the uploaded learning seems to be procedural and semantic knowledge. An introductory discussion of uploading information into one’s mind cannot be complete without mentioning Johnny Mnemonic (1995), also starring Keanu Reeves. Based on a short story of the same name by Gibson (1981), Johnny works as a data courier in a dystopian future, using his brain as a secure storage device to transport sensitive information between clients. Johnny has previously been implanted with a cybernetic “mnemonic storage device” that allows him to store vast amounts of data directly within his brain. The memory technology is not without its limitations, as storing too much data within the brain can lead to brain damage or even death. Additionally, his brain is effectively ‘partitioned’ to allow for the data storage, leaving less space for Johnny’s own personal memories; this lead to ethical implications of using such technology. MIN RE

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In the TV show Chuck (2007—2012), initially only semantic knowledge can be downloaded, but a revised technology allows for procedural skills to also be transferred. This technology also bears similarities with Johnny Mnemonic, where accessing these artificial memories has damaging effects to natural memories. In a later instance, similar memory-downloading technology is used to download a personality and identity into a person. Even more interesting are the instances where experiences are downloaded—thus corresponding to episodic memory. A well-known example of this is the movie Total Recall (1990, 2012), where a fictional company, “Rekall Inc.,” sells vacation experiences as implanted memories—as opposed to living the experiences that one may not be otherwise able to afford. This story was inspired by the short story “We can remember it for you wholesale” by Philip K. Dick (1966), but also includes many alternations. In the original story, this experience is described as an “extra-factual memory.” The process involves the use of advanced technology to manipulate the brain and plant detailed, vivid memories that feel as real as true experiences. The story provides examples of potential drawbacks and limitations, such as the possibility of uncovering suppressed memories and creating confusion between real and artificial experiences. The narrative raises questions about the nature

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of memory, identity, and the implications of altering one’s past, showcasing the ethical and psychological consequences of using such advanced technology. OtherLife (2017) also features a technology where people can pay for the experience of a vacation or adventure that they otherwise would not have time for. Some other movies have also featured downloading episodic memories, such as Oxygen (2021). Not all downloaded memories are beneficial though, as implanted memories can also be used to compress the experience of decades in prison to occur in just minutes—as featured in OtherLife (2017) and the Black Mirror episode “White Christmas” (2014; Season 2 Special). Admittedly, these instances could be considered as a special case of virtual reality where experiences are lived, but at an accelerated pace, unlike the earlier examples where memories of the past exist but were never ‘in the present’ for the client. As it will be a re-occurring feature in this section, Black Mirror is an anthology TV series set in a bleak near-future alternate timeline with innovative, fictional technologies that are focused on their societal implications.

Sharing memories While the previous section was focused on downloading ‘engineered’ experiences into one’s mind, sometimes downloaded experiences are those that have been recorded from another. More generally, some fictional works have also featured the possibility of sharing memories between individuals. This can be done by transferring experiences directly or recording experiences in a way that can easily be replayed and shown to others through a monitor. The opening cinematic to the videogame Remember Me (2013) provides some insight into different circumstances where this may be desirable, such as sharing episodic experiences between partners in a married couple to understand each other better, or to share experiences across generations. A similar technology also exists in Cyberpunk 2077 (2020), called “braindance” (also see Fisk et al., 1989). In some cases, memories can be read directly from the brain and then shared with others, such as in Brainstorm (1983) and Strange Days (1995). Another instance of this type of technology is the “Willow Grain” from the Black Mirror episode “The Entire History of You” (2011; Season 1 Episode 3)—though it is also referenced in a few other episodes in the series. This technology is a grain-sized device implanted behind the user’s ear. Using a complementary handheld “Pebble” remote, the user can replay memories as well as share them with others. In the episode, there were three instances where this was requested—at a security check when boarding a flight, during a job interview, and when reporting an incident to the police. The device is always recording and memories can be replayed and shown to others on a TV or computer, or just to one’s self directly through your vision. Having a Grain is shown to be socially expected, with it stated that being ‘Grain-less’ is very uncommon—apart from those involved in criminal activity. Some demonstrated uses of the device include reviewing comments from the

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interviewers during the aforementioned job interview, zooming in and lip reading a conversation between people at a distance, re-watching part of an argument, and even replaying a prior sexual experience while having sex. Even babies have the device implanted, allowing parents to replay their child’s experiences with the babysitter after returning home from a night out. While recorded experiences can be deleted, there are limitations and this could be viewed negatively when requested to share recordings—such as by airport security or job interviewers. While this technology would solve biases in eyewitness memory (see Section 2.3, p. 41) as it represents an objectively correct recording, it also would make it difficult to move on from arguments or someone who has passed away. The Black Mirror episode “Crocodile” (2017; Season 4 Episode 3) uses a related technology, set at an earlier point in the series’ alternate timeline. Here there is no implanted device and memories are described as subjective experiences, but using a toolbox-sized device with a TV screen called a “Recaller” memories can be displayed and is used when investigating crimes. Despite the subjective nature of these recollections, memories from a few witnesses can provide corroborative evidence. To help people recall the memories of interest, music or scents are used. Other movies feature similar fictional technologies. In Anon (2018), experiences are again recorded using an implant, but are stored in a central database. In addition to accessing your own recordings, they can also be accessed by police when investigating a crime. In this society, people sometimes pay hackers to erase recordings of humiliating or incriminating acts. A commonality across many of the examples presented here is the use of memory sharing as a means of mass surveillance and loss of privacy. Reminiscence (2021) involves technology where memory can be externalised and re-experienced; this is readily accessible to consumers through specialised establishments where people can schedule or have walk-in appointments. However, as in other movies, this technology can also be used forcefully as an interrogation technique. The Final Cut (2004) also has experiences recorded using an implant, but typically these are not accessed while people are living. Instead, the main character has the job being a ‘cutter,’ who creates edited highlight movies of a person’s life after they have passed away, to be played at their funeral. These movies are made to cast the recently deceased in a favourable light. This is a topic discussed in the film, as it is a questionable practice since it distorts the reality of how the person acted and hides their misdeeds. In some works, memories are used to create immersive virtual-reality environments that can then be experienced by others. Aniara (2018) takes this approach and involves using virtual-reality simulations of nature, such as a forest, as a means of reminding people of a natural environment and calming their emotions while they are living on a spaceship.

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Exploring these potential future technologies sheds light on the unique nature of memory. In some situations, it may be desirable to share our memories with someone close to foster a deeper sense of understanding— in some instances, there could be a market for memories to be bought and sold as packaged experiences. Of course, it is essential to recognise that some memories are too intimate and personal that they need to be kept private. While the transfer of memory between individuals may currently seem particularly implausible, there is some empirical precedence. Thompson and McConnell (1955) trained planaria (flatworms) to associate a bright light with an electric shock. First of all—demonstrating conditioning in an invertebrate. However, these planaria were subsequently cut in half—the species is naturally able to reproduce asexually through a similar process, referred to as transverse fission. Both of the resulting regenerated planaria maintained the conditioning learning, presumably through memory traces stored in RNA. McConnell et al. (1961) and McConnell (1962) took this a step further—grinding up trained planaria and feeding them to untrained planaria. There were some criticisms of this work, due to lack of additional control groups (Walker & Milton, 1966) and replication failures by other researchers (Hartry et al., 1964). However, in 1965, four independent research labs demonstrated evidence of RNA mediated memory transfer in rodents using transplantation of brain tissue (Babich et al., 1965; Jacobson et al., 1965; Jacobson, Fried, & Horowitz, 1966; Jacobson, Babich, et al., 1966; Fjerdingstad et al., 1965; Reiniš, 1965; Ungar & OcegueraNavarro, 1965; Chapouthier & Ungerer, 1970). Failures to replicate these findings and other controversies have continued (Byrne et al., 1966; Setlow, 1997; Morange, 2006). More recently, the original results regarding splitting a planaria have been replicated with modern methods (Shomrat & Levin, 2013).

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Erasing memories While the possibility of downloading new experiences or transferring previous experiences with others remain within the the realms of fiction, a third major type of fictional technology has found some support: erasing episodic memories. One example of this technology has been in Eternal Sunshine of the Spotless Mind (2004). In the film, a company called Lacuna Inc. specialises in targeted memory erasure. The process involves mapping the memories of a client, identifying specific memories to be deleted, and then erasing those memories through a controlled neural stimulation procedure. The clients wear a head-mounted device while unconscious, and the memories are methodically erased, working backward through the client’s history. As part of the procedure, clients are asked to gather all physical items and reminders associated with the person whose memories they wish to erase, including photographs, letters, gifts, and other personal belongings. Lacuna Inc. sends letters to the client’s friends and acquaintances, informing them about the memory erasure. The letter explains that the client has chosen to forget a specific individual and requests that the recipients of the letter refrain from mentioning the erased person to the client in the future. The film provides an insightful outlook into the relationship between love, loss, and the importance of memories in shaping one’s identity and personal growth. (The name of the film comes from a 1717 poem by Alexander Pope.) Another major example of this is Paycheck (2003), based on a short story of the same name—also by Philip K. Dick (1953). Here the main character is an electronics engineer, working on top-secret projects. To ensure that he cannot remember any of the details of the project and protect the employer’s intellectual property, he agrees that his memory will be erased for the period of employment. “We can remember it for you wholesale” (Dick, 1966) also includes some memory erasure, with the visit to the memory implantation company being erased from memory: “you will never remember seeing me or coming here; you won’t, in fact, even remember having heard of our existence.” Moreover, an episode of Black Mirror provides an example of futuristic memory technology, in “Men Against Fire” (2016; Season 3 Episode 5), though this is not the central technology for the narrative. Similar to the prior example, this involved erasing the explanation of the terms of an agreement after consent had been given. The TV show Citadel (2023) provides another similar instance of memory-erasing technology. Despite their differing circumstances, all of these instances can be viewed as erasing memories to alter the person’s beliefs about their life situation. Some studies have shown that targeted memory erasure can be a reality (Han et al., 2009; Josselyn et al., 2015). In this work, memories are identified within a rodent and then portions of the hippocampus and amygdala are ablated (i.e., damaged), resulting in the loss of the remembered memory association—such as previous learning of a context-related threat conditioning.

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A few other fictional technologies exist that do not readily fit in any of these categories. In the movie Inception (2010), memories can be implanted while someone is dreaming, but the process is very contrived. In the TV show Severance (2022), a chip is surgically implanted to allow for the separation of memories between personal and work life. The chip creates a barrier between the two sets of memories, so that the ‘severed’ employees cannot access their personal memories while at work, and they cannot access their work memories while at home. While these discussions of future fictional technologies are far from comprehensive, they illustrate the wealth of possibilities that can be explored when considering how (fictional) technologies can help us understand memory processes (Chapelle Wojciehowski, 2018; Seamon, 2015).

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End of chapter wrap-up Summary Our memories are not confined to our minds, but can be externalised and preserved in various forms. From physical reminders like tattoos and photo albums to digital aids like social media and cloud storage, we are constantly creating external memory stores. Physical reminders can serve as potent cues of our past experiences. These items can stimulate autobiographical memory, fostering a connection between our past and present selves and providing a tangible link to important life events. Photos are particularly interesting and complex, as they tread between being veridical recordings, but also biased through their selection and staging. They can also be shared with others, influencing our social interactions. The internet is even more complex, serving as a vast, collective external memory store that is continually growing and evolving. While it offers the promise of limitless memory preservation, it also presents challenges related to data permanence, obsolescence, and privacy. Memory technologies continue to be developed, and looking to fiction may provide insights into what might be possible tomorrow with downloading, sharing, and erasing memories. These speculative technologies provoke us to consider the implications of such technologies on our understanding of memory and identity.

Reminder cues

Quick quiz 1. Which of the following is a benefit of using a diary? (a) Recording recent experiences (b) Providing insights into the past (c) Serving as an emotion regulation strategy (d) All of the above

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2. If Maria decides to get a tattoo of a specific bird that symbolises a turning point in her life, which of the following statements is NOT true? (a) The tattoo serves as a permanent physical reminder of a significant event in Maria’s autobiographical memory. (b) The bird tattoo helps Maria to communicate her personal history to others, thereby sharing her autobiographical memory. (c) The tattoo, representing a symbolic experience, may influence how Maria reflects on and interprets her past, thus shaping her identity. (d) The tattoo decreases the authenticity of Maria’s memory as it replaces the actual experience with a physical symbol. 3. Which statement best describes the viewpoint of proponents of cognitive offloading in relation to the use of digital memory aids? (a) Digital memory aids should be avoided as they lead to a decline in our memory abilities. (b) Digital memory aids allow us to store and retrieve vast amounts of information. (c) Digital memory aids are only useful for storing trivial information. (d) Digital memory aids should be used sparingly to prevent overreliance. 4. Imagine you are a digital archivist in 2100, tasked with preserving a collection of digital art from the early 2000s. You discover that some of the art pieces were created using software that is no longer supported or accessible. This situation exemplifies which of the following challenges of memory preservation in the digital age? (a) The inherent fragility of digital data, which can be easily lost or corrupted due to technological glitches or system failures. (b) The evolving nature of digital platforms and the subsequent risk of obsolescence, making it difficult to access and interpret historical records. (c) The challenge of verifying the authenticity and originality of digital art pieces, given the ease of replication and manipulation in the digital realm. (d) The potential for digital memories to become impersonal and detached, as they lack the tangible and sensory qualities of physical artifacts.

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5. Which fictional future technology is closest to being a reality? (a) (b) (c) (d)

Downloading memories Sharing memories Erasing memories All are equally possible

Thought questions ▶ Throughout history, different cultures have developed unique practices or items that aid in memory. For example, indigenous Australian songlines or rosary beads reflect on cultural or historical practices in different societies. How do these memory aids reflect societal values, beliefs, or norms of that time and place? Moreover, consider how these traditional practices compare with contemporary memory aids like digital systems and physical reminders. Have the functions they serve changed over time? ▶ How much do you take photos or videos of your holidays? How often do you look back at these? How does their existence relate to your memory for those experiences? ▶ Imagine a situation where you would have liked to have a digital recording, but none was made. How might future technologies, such as continuous recording devices (e.g., Google Glass), have changed this situation? Reflect on the potential benefits and drawbacks of such technologies, particularly considering the balance between memory preservation, privacy, and data security. How might we navigate these complex issues in a future where digital recording could be omnipresent?

Further reading ▶ Michaelian, K. (2012). Is external memory memory? Biological memory and extended mind. Consciousness and Cognition, 21(3), 1154–1165. doi: 10.1016/j.concog.2012.04.008 ▶ Foley, M. A. (2020). Effects of photographic reviews on recollections of the personal past: A new perspective on benefits and costs. Review of General Psychology, 24(4), 369–381. doi: 10.1177/1089268020958686 ▶ Intons-Peterson, M. J., & Fournier, J. (1986). External and internal memory aids: When and how often do we use them? Journal of Experimental Psychology: General, 115(3), 267–280. doi: 10.1037/00963445.115.3.267

Part V

Conclusion

Chapter 14 Final thoughts

Memory is like a dog that lies down where it pleases. — Nooteboom (1980)

The thing about me is that I am not a theoretician. I don’t mean that I don’t know other people’s theories, I do read about others’ work. But I’m not someone who comes up with great cognitive questions and then sees how I could answer them. I am extremely empirically driven. My quality is that I am a very good observer. I would note a funny little quirk in a patient and would think, “Well, that’s interesting! Why did the patient do that?” and then try to figure how I could find out more about it and test it in a more scientific way. — Brenda Milner (from Xia, 2006)

The influences of memory are pervasive. While the organisation and structure of memory lays an important foundation for understanding memory, a functionalist approach to memory has generally been lacking. This view is not a novel development and the basis of this perspective has been strongly inspired by researchers, such as Neisser (1978, 1985b), Nilsson (1979; Nilsson et al., 1987), Nairne (2005, 2010), and Glenberg (1997), among others (Oakley, 1983; Bruce, 1985a; Sherry & Schacter, 1987; Klein et al., 2002; Klein, 2015; Howe & Otgaar, 2013; Schacter et al., 2012). These researchers have highlighted the necessity and on-going lack of literature examining a functional approach to memory, but here I sought to build upon this perspective and integrate it with the expansive research on emotions and self on memory, the moderate amount of research on reward influences on memory, and the relatively sparse findings on motoric processes and memory—broadly, the influences of motivational processes on memory. These topics only characterise half of the landscape of memories that matter, the instances where events 445

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are inherently more memorable. The other half is perhaps more relatable, instances where the explicit goal is to remember information for later retrieval. As with motivated memory, this can come in many forms. A variety of memory strategies, include internal techniques to structure information or improve retrieval accessibility, and external aids and reminders, where memory storage is augmented by an extended mind approach. The role of memory in today’s life is changing, however, as the dawn of the internet and modern technology has shifted the necessity and reliance on memory. Having reached this point in the book, you now know a lot about memory. Or, at the very least, have ready access to a volume of memory findings. The next step, however, is using this information in practice. There are many actionable ideas here, particularly in the chapter about memory strategies. What I will point out here is that some advice on writing has focused on making the writing memorable (Madan, 2015b; Gernsbacher, 2018).

14.1 Memory systems and taxonomy As we iteratively refine our collective understanding of memory, we must periodically forge new definitions of our key concepts. Supported by the last decades of memory findings, it is time to revisit the boundaries between the memory systems. Episodic and semantic memory systems are closely intertwined and not as distinct as traditionally presented (Tulving, 1983b, 1986). This is a challenge that has been increasingly discussed, from different lines of evidence (Renoult et al., 2019; Zeithamova & Bowman, 2020; Rubin, 2022). Moreover, the distinction between episodic memory and associative learning is also more nuanced (Öhman et al., 1975; O’Brien & Sutherland, 2007; Madan, 2020a), particularly given recent findings using procedures such as decisions from experience and transfer of valence (Dunsmoor et al., 2015; Starita et al., 2019; Palombo, Elizur, et al., 2021; Mason et al., 2024). In other procedures, such as maze navigation and reward learning, both episodic and associative learning are sometimes tenable, with people relying on a mixture of the two strategies (Iaria et al., 2003; Bayley et al., 2005; Madan, Fujiwara, et al., 2012; Nicholas et al., 2022). Beyond these findings, these issues have become the topic of discussion sporadically (Dunsmoor & Kroes, 2018; Madan, Ludvig, & Spetch, 2019; Freedberg et al., 2020), but have not yet formed into a cohesive movement within the field. Complicating matters further, increasing evidence shows that separate tests of episodic memory are generally uncorrelated (Cheke & Clayton, 2015; Bernstein et al., 2018; Patihis et al., 2018; Murphy, Loftus, et al., 2023). What distinguishes one memory system from another? Are these instances of a task relying on co-occurring mechanisms, or is it time to redraw the boundaries between memory systems? If a new definition is to be developed, the key features still need to be adequately evaluated and a critical comparison established showing how the new definition furthers our understanding.

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The memory taxonomy, as described in Section 3.1 (p. 57), is not the only existing approach for classifying memory—far from it. It is worth highlighting that Tulving’s own definition of episodic memory developed over time. Initially it did not involve any reference to consciousness, this was added decades later (Tulving, 1972, 1983b, 2002). Even now, definitions of measuring consciousness are unresolved at best (Sandberg et al., 2010; Hunt et al., 2022). Autobiographical memory is—by definition—narrative and autonoetic, whereas episodic memory is only weakly autonoetic (Montemayor, 2018). While I concede that my own view is contentious (Madan, 2020a, 2023a), it is time that we continue to develop our conceptualisation of the memory systems further. As such, here I propose that episodic memory represents memory related to a specific episode. Memories that additionally involve the conscious retrieval of the event (i.e., ecphory and autonoetic awareness) should be referred to as event memory, and considered a type of episodic memory. By the conventional definition, episodic memory intertwines remembering the specific source experience for an event with the more active process of mental time-travel. While others have suggested distinctions (Oakley, 1983; Fuhrman & Wyer, 1988; Dokic, 2014; Hopkins, 2014; Rubin & Umanath, 2015; Keven, 2016; Pan, 2022), these have not become mainstream. The notion of event memory and its properties has been increasingly discussed (Sant’Anna & Michaelian, 2018; Boyle, 2021; Ménager et al., 2022; Yates et al., 2023). Providing some inspiration for further consideration, Roediger, Marsh, and Lee (2002) provided an overview of these potential classifications. Tulving (2007) describes “256 different kinds of memory” in a follow-up, tongue-incheek response. Despite many of these ‘kinds’ being not useful for developing a new memory taxonomy, there are a few gems buried in the sand. MIN RE

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I will also note and acknowledge that I am now more appreciative of the relevance of consciousness to episodic memory than I was when writing “Rethinking the definition of episodic memory” (Madan, 2020a), particularly due to the subsequent work I have done with Daniela Palombo on narrative recall and phenomenological ratings (Wardell et al., 2021a, 2023; Dev et al., 2022), and with Myron Tsikandilakis on emotional states and consciousness (Tsikandilakis et al., 2021a, 2021b, 2024). Some of these revised views are reflected in Madan (2023a), where I made three specific propositions about the relationship between episodic memory and consciousness:

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(1) episodic memory is usually associated with conscious retrieval; (2) it is possible to have consciousness without episodic memory; and (3) episodic memory can be accessed without conscious retrieval. Prior to working on these papers, I had not been as considerate of how the views of established researchers of the past may also have shifted over time. More broadly, however, I think it is a must that we move towards acknowledging that non-human animals can have episodic recall and assess this using tests of memory that do not rely on assumptions of consciousness. Critically, these rely on objective tests that can be validly compared across species (Easton & Eacott, 2010; Antunes & Biala, 2012; Crystal, 2021; Barbosa & Castelo-Branco, 2022). This includes using objective tests in humans (Shettleworth, 2010, pp. 7–8; Vila et al., 2021; Guo et al., 2024) and focusing on functional similarity. Similar re-conceptualisations have been occurring with a shift from the use of ‘fear conditioning’ in studies with nonhuman animals to use of the term ‘threat conditioning’ (LeDoux, 2012, 2014). Others have also discussed the difficulties in attributing conscious states to describe behaviours in animals (Paul & Mendl, 2018; Belzung & Philippot, 2007; Anderson & Adolphs, 2014; Genewsky et al., 2018). A major challenge continues to be establishing a clear definition of consciousness (Birch et al., 2020; Browning & Birch, 2022; Hunt et al., 2022; Veit, 2023; Andrews, 2024). In future studies, we should increasingly use naturalistic methods, which can span a variety of procedures. This is not to say that these methods have not been used at all; as such, I will cite some prior work that has already considered these more naturalistic procedures and can serve as inspiration for future studies. The most practical way to study memory that is more naturalistic is to have participants watch videos and be followed by an incidental memory test (Boltz, 1992; Luna & Albuquerque, 2018; Dev et al., 2022). The Sherlock movie-watching fMRI study (Chen et al., 2017) and subsequent re-analyses of this data (Kim, Weber, et al., 2020; Heusser et al., 2021; Lee Masson & Isik, 2021) provide an excellent example of the benefits of naturalistic paradigms— as well as of open science (see Section 3.3, p. 89). Beyond this, studies using more immersive methods would be even less contrived and solve the ‘treachery’ problem, such as using live snakes or spiders, haunted houses, or virtual reality (Hekmat & Vanian, 1971; Feinstein et al., 2011; Andersen et al., 2020; Shin et al., 2021; Safi et al., 2024). A beneficial feature of these designs is that the veridical truth is objectively known and the encoding was incidental. Even better, studies can take advantage of truly naturally occurring events and test verifiable memory details (Wagenaar & Visser, 1979; Chapman & Underwood, 2000; Ford et al., 2018, 2021; Raw et al., 2023). Beyond this, more research in applied/educational settings will also be useful (Bergman et al., 2015; Blazek et al., 2016; Havre et al., 2018). Outside of the lab, a key function of memories is for them to be shared, but this is rarely true with experimental studies of memory. Consider the dynamics within a long-time married couple. Over the years, they have shared countless experiences, and these shared memories have woven a tapestry

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of stories that they can recount together, being able to finish each other’s stories (Wegner et al., 1985; Hirst & Manier, 2008; Harris et al., 2014). This is not merely a charming characteristic of long-term relationships but a manifestation of an integrated transactive memory system. This system, formed through years of shared experiences and memories, fosters a deep sense of connection and understanding between the couple. In a related vein, the manner in which memories are shared and reminisced upon plays a significant role in determining relationship satisfaction (Bradbury & Fincham, 1990; Halford et al., 2002; Catal & Fitzgerald, 2004; Alea & Vick, 2010; Philippe et al., 2013). The act of sharing memories, particularly those that are positive or meaningful, can serve as a powerful tool for maintaining and enhancing the quality of a relationship. This underscores the profound impact that the sharing of memories can have on our social interactions and personal relationships. Consider the following quote from Campbell (2008): Sharing memory is how we learn to remember, how we come to reconceive our pasts in memory, how we come to form a sense of self, and one of the primary ways in which we come to know others and form relationships with them, reforming our sense of self as we come repeatedly under the influence not only of our own pasts as understood by others but of the pasts of others. (p. 42) Moreover, research on how sharing memories can facilitate health and wellbeing is beneficial to society. Two examples of this are reminiscence therapy (Sambandham & Schirm, 1995; Simmons-Stern et al., 2010, 2012; Elliott & Gardner, 2018; Reschke-Hernández et al., 2020) and inter-generational sharing of interests and heritage more generally (Olick & Robbins, 1998; Krumhansl & Zupnick, 2013; Cubitt, 2019; Nicoll, 2022). Reminiscence therapy involves elderly recalling and sharing their past experiences, which has been shown to improve mood and cognitive function. On the other hand, inter-generational sharing involves the older generation passing down their experiences, traditions, and stories to the younger ones. This practice fosters a sense of continuity, identity, and understanding across generations. Both practices underscore the significant role that memory sharing plays in individual and societal health. I have focused more on objective measures of memory—such as recognition studies with definite correct responses—including old/new, source memory, or mnemonic similarity task procedures. However, as briefly discussed, many studies include qualitative judgements, such as asking for ‘remember’ vs. ‘know’ responses. These assessments of subjective remembering are valuable, but are complicated by their involvement of consciousness and qualia. These represent two distinct approaches for assessing memory quality (refer back to Section 3.2, p. 74). Nonetheless, the subjective experience of remembering is an intrinsic property of real-world remembering that warrants research, even if it is less compatible with the constraints of experimental

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research. To study these phenomenological characteristics of memory—such as confidence and vividness—using Likert-scale measures. Investigations of these characteristics are more often done with studies of autobiographical memories (Johnson et al., 1988; Mickley & Kensinger, 2009; Wardell et al., 2021a), but are also occasionally done with episodic memories in experimental settings (Cooper et al., 2019; Tibon et al., 2019). For recent discussions, see Boyle (2020) and Simons et al. (2022). A further aspect for consideration is the distinction between memory and perception—and the role of the hippocampus in both processes. It is established that the hippocampus is involved in functions more general than memory retrieval itself, such as pattern completion. This is further demonstrated by parallels between memory and imagination (see Sections 1.5, p. 19, and 4.3, p. 108). Recent findings indicate that the role of the hippocampus may be more general—and fundamental—yet, coordinating the flow of information to distinct cortical regions. More specifically, the hippocampus has been described as a switchboard for connectivity (LindeDomingo et al., 2019; Treder et al., 2021). Depending on how closely we intend to map cognitive functions to neurobiological structures, these recent findings are another challenge to our current understanding of ‘memory’ as a discrete cognitive function.

14.2 Neurobiology of cognition Shifting to neuroscience more directly, there is increasing support for the view that our current understanding of functional specialisation of regions is limited (Buzsáki, 2019, 2020; Cepelewicz, 2021; Pessoa et al., 2021). Specifically, brain regions are involved in more complex operations that less clearly map to distinct cognitive functions. This contemporary view within the broader neuroscience community is convergent with an existing philosophical perspective, known in the literature as ‘eliminative materialism’ and dating back to the 1980s (Churchland, 1981; Stich, 1985). This view argues that mental concepts such as ‘beliefs’ and ‘emotions’ will eventually be eliminated from scientific explanations because they will not correspond to the actual workings of the brain. This radical perspective has nonetheless provided us with an important critique of prominent views at the time, as well as our contemporary understanding. It suggests that our traditional categories of mental phenomena are not reflective of the underlying neural realities. Instead, the brain’s operations are more complex and less neatly divided than our cognitive language would suggest. This perspective has led to a re-evaluation of how we conceptualise brain function and has encouraged a more nuanced understanding that embraces the complexity and interconnectedness of neural processes. Critics of this view point out that while these concepts may not perfectly map onto neural processes, they still provide a useful framework for understanding and predicting human behaviour.

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Providing a potential path forward, current evidence suggests that the brain is comprised of structural and functional gradients, rather than more discrete and modular segmentations (Voorn et al., 2004; Margulies et al., 2016; Madan, 2021b; Sydnor et al., 2021). This can be thought of as analogous to treating data as continuous and not applying divisions in the data. It is well established that dividing data into two groups based on a median-split is detrimental (Cohen, 1983; Maxwell & Delaney, 1993; MacCallum et al., 2002; Royston et al., 2006); Cohen (1983) demonstrated that dichotomising a variable using a median split reduces statistical power comparably to discarding between 38% to 60% of the data. Moreover, Mesulam (1998) proposed a network-based theory of gradients of information flow—the hippocampus, amygdala, and related regions are viewed as the most ‘inner’ set, with surrounding concentric circles for heteromodal/association cortex regions, unimodal regions, and finally, primary sensory regions as each outer set. (However, this inner-most circle is described as ‘limbic,’ which I do not agree with as a categorisation—refer back to Section 5.4, p. 144.) Additionally, as highlighted in Section 5.4 (p. 145), the hippocampus should not be viewed as a unitary structure. This does not necessarily mean it should be sub-divided, at least along the long axis, but rather that converging evidence also indicates there are meaningful gradients within the hippocampus itself (Brunec et al., 2018; Przeździk et al., 2020; Vogel et al., 2020; Genon et al., 2021). The thalamus in particular is becoming increasingly appreciated and viewed as more central to cognition than just a relay station. While it is well understood that brain regions outside of the medial temporal lobe are important, there is also increasing evidence that the thalamus is critically affected by aging, both in terms of structure (Hughes et al., 2012; Madan, 2019; Choi et al., 2022; Yadav et al., 2024) and function (Fama & Sullivan, 2015; Hwang et al., 2017; Wolff & Vann, 2018; Yang et al., 2020; Zhou et al., 2021; Shine et al., 2023). A more nuanced understanding of the role of the thalamus may prove critical in the coming years. In this book I have primarily discussed memory as being the retrieval of information that was previously encoded. However, examining encoding and retrieval—as well as the intervening period—can provide further insights into what will be later remembered and how successful retrieval will be. I am approaching these topics only superficially, but that is not to say they have not been studied extensively, only that I chose to emphasise other facets of the literature. With respect to encoding, the dynamics of cognitive processing can be most readily studied using eye tracking, such as the early work done by Yarbus (1967). As attention can be biased, this also appears in the saccade patterns, and can be influenced my motivational factors (Kaakinen et al., 2011; Madan, Fujiwara, et al., 2017; Voss et al., 2017). Memory retrieval can also be examined through eye gaze behaviour (Hannula et al., 2010; Kafkas & Montaldi, 2011; Damiano & Walther, 2019; Qin et al., 2021; Kragel & Voss, 2022). The cognitive dynamics of both encoding

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and retrieval phases can also be examined more richly using additional approaches, such as investigating variations in regional oscillation activity in electrophysiological recordings. Klimesch (1999) provides a comprehensive review on the relationship between alpha and theta oscillations and memory performance. Recent works examining the brain activity from intracranial recordings have been particularly informative in associating regional brain function with behaviour (Kucewicz et al., 2019; Chen et al., 2021; Kragel et al., 2021; ter Wal et al., 2021). Contemporary work is also expanding our understanding of locus coeruleus function (Dahl et al., 2022). Further advances with brain stimulation methods can also provide substantial insight into the neural basis of memory. These stem from further studies with intracranial stimulation (Suthana et al., 2018), but also extend to the use of transcranial methods and individualisation of stimulation sites (Booth et al., 2022; Cash et al., 2022). Bracco et al. (2023) impressively combined both EEG and TMS to enhance both motor skill and word recall memory. The findings of Wang et al. (2014) are particularly striking—they demonstrated that non-invasive brain stimulation (rTMS) can be used to target and enhance the cortical-hippocampal networks involved in associative memory. Moreover, this is one of the rare instances where replication studies have obtained stronger effect sizes than the original study (Hermiller et al., 2019; Freedberg et al., 2019). MIN RE

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When briefly presenting visual stimuli, conscious perception can vary in relation to the brain oscillatory activity—this has specifically been demonstrated with the phase of oscillatory activity (Hanslmayr et al., 2007; Mathewson et al., 2009; Busch et al., 2009; Veniero et al., 2021). The phase of alpha oscillations can also be experimentally induced using a procedure known as ‘entrainment.’ Here visual cues are presented repeatedly at a consistent rate, creating an automatic expectation of when information is presented. The last stimuli in the sequence, however, is presented such that it aligns with that entrained expectation—or is out of phase with it (Mathewson et al., 2012; Zelano et al., 2016; Arshamian et al., 2018). Oscillatory phase, particularly of theta and gamma, has also been associated with memory retrieval (Hasselmo et al., 2002; Kerrén et al., 2018; Lin et al., 2019; Yoo et al., 2021). Other studies yet have shown associations between conscious perception, subsequent memory, and respiratory oscillations (Huijbers et al., 2014; Zelano et al., 2016; Kluger et al., 2021; Grund et al., 2022). Taken together, these findings provide insight, as well as highlight limitations, in our understanding of how physiology

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relates to cognition. However, methodological caveats are necessary. Advances have suggested that some previous findings described as oscillatory activity may instead be event-related aperiodic activity (Caplan et al., 2001; Whitten et al., 2011; Donoghue et al., 2020). This underscores the importance of careful methodological considerations in the study of brain oscillations and cognition. Other methodologies and analysis approaches also offer their own unique insights into memory processes, including conventional fMRI methods, computational modelling, and sleep research This is particularly true when employing thoughtful experimental procedures. For instance, requiring effortful memory search and elaboration can provide a deeper understanding of memory retrieval and consolidation (Ford et al., 2014; Ford & Kensinger, 2017). Similarly, examining differences in post-encoding restingstate connectivity can shed light on the neural mechanisms underlying memory formation (Tambini et al., 2010; Tambini & Davachi, 2013; van Kesteren et al., 2010). As for the intervening period between study and test, the most well-established approach is to consider literature on sleep and memory (Gais et al., 2006; Cunningham et al., 2022; Simon et al., 2022; Brodt et al., 2023). A growing methodological approach has been to collect a large amount of data from a handful of participants. This has been a recent movement within the fMRI literature, involving scanning the same set of participants across dozens of MRI sessions, focusing more on precision of measurement and depth of understanding of individual brain systems, rather than generalisability across the population (Poldrack et al., 2015; Gordon et al., 2017; Madan, 2022). Within a more memory-focused framework, this approach would begin with naturalistic stimuli or otherwise long presentation sequences, such as in the Sherlock study that has been previously described (Chen et al., 2017) and the continuous recognition task that spanned 40 fMRI sessions (Allen et al., 2022). The approach here bears commonalities to the introspective, longterm memory studies conducted by Ebbinghaus (1885), Linton (1982), and Wagenaar (1986, 1992). Related procedures that were not previously discussed include the Individual Brain Charting study (Pinho et al., 2018, 2020) and the single-participant study of 30 episodes of Doctor Who (Seeliger et al., 2019). For more context on the rationale for studying individual brains, see Finn et al. (2020) and Fedorenko (2021). Another frontier in memory research is the use of different sensory modalities. The literature is dominated by studies using visual or auditory stimuli, but there is a much more limited understanding of how we remember information processed with our chemical senses (Gordon, 1925; Engen & Ross, 1973; Herz & Engen, 1996; Croy et al., 2015). Some innovative studies have used odour stimuli to cue memories during (slow-wave) sleep, improving verbal memory recall relative to words associated with an alternate, uncued odour (Smith et al., 1992; Rasch et al., 2007; Schouten et al., 2017; Bar et al., 2020). This procedure is known as ‘targeted memory reactivation’ and is thought to relate to similar principles as context reinstatement, building on a foundation of animal studies (Hars & Hennevin, 1987; Bendor & Wilson, 2012). Much of

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this work is now done with humans (Hu et al., 2020). Odour test instruments have been developed and validated, such as Sniffin’ Sticks, which includes penlike odour dispensing devices for assessing odour identification, discrimination, and thresholds (Hummel et al., 1997, 2007)—though other tests have also been developed (Doty et al., 1984; McMahon & Scadding, 1996; Hummel et al., 2010). However, in studies investigating odour identification, thus relying on semantic memory, it has been suggested that some odours may vary in familiarity between cultures: Cultural differences and inadequate translation might prevent odour identification and thus limit the applicability of this olfactory test in the UK. Our initial study showed that in the tested population, the odour most commonly mistaken by subjects with normal olfactory function were apple (35%), turpentine (30%), lemon (30%), and cloves (26%). […] Also, some distractor descriptors may not be very familiar to a UK-based population, for example, sauerkraut or gummy bears. (Langstaff et al., 2021, p. 103) Studies of expertise have also provided insight into how pre-existing knowledge structures can relate to better having a richer vocabulary to understand chemical-based stimuli—as in the case of wine, beer, and perfumes (Meilgaard et al., 1979; Drake & Civille, 2003; Veramendi et al., 2013; Croijmans & Majid, 2016). Odours have also been demonstrated to be effective cues of autobiographical memory (Koppel & Rubin, 2016; Munawar et al., 2018). Beyond the scientific literature, Proust’s writing on melancholy after smelling a rose provided insight into the use of odours as memory cues—a phenomenon we are still far from sufficiently understanding. With respect to the neurobiology of cognition, we have primarily discussed a systems- and network-level view of how brain regions support learning and memory. However, it’s important to also consider another critical aspect—the molecular and cellular basis of memory (Rahwan, 1971; Morris, 2006; Kandel et al., 2014; Takeuchi et al., 2014; Marshall & Bredy, 2016; Gallistel, 2021). For instance, how are specific details of events encoded through protein synthesis and neuronal dendrites? Griffith and Mahler (1969) proposed that memory could be stored in DNA, including drawing a connection to the methylation of portions of DNA—what we now know as epigenetics. This view was relatively prescient, though also overly simplistic. Our understanding of this level of memory biology is still relatively limited (Aggleton & Morris, 2018; Arshavsky, 2022). More recent advances suggest that cells other than neurons, such as glia, also play a significant role in memory (Bains & Oliet, 2007; Adamsky et al., 2018; Kol et al., 2020; Craig & Witton, 2022; Chen et al., 2023). In some ways, non-neuronal brain cells—such as glia—are like the dark matter of the universe. They make up much of our brain matter, but we have a poor understanding of their role and specific characteristics.

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Another frontier within memory research is the use of computational models—a variety of approaches are used, focusing on different facets of memory (Longuet-Higgins et al., 1970; Kahana, 2020). For instance, some models are centred on recognition dynamics, e.g., drift diffusion (Ratcliff, 1978; Ratcliff et al., 2016; Harris & Hutcherson, 2021; Pirrone et al., 2022). Other models focus more on associating memory items (Anderson, 1970; Murdock, 1982; Pribram, 1986; Humphreys et al., 1989). Of notable interest, models based on holographic representations provide a high degree of both biological plausibility and computational efficiency (Longuet-Higgins, 1968a, 1968b; Gabor, 1968, 1969; Westlake, 1970; Cavanagh, 1976; Plate, 1995, 2003).

14.3 Technological innovations Studying memory has also been related to numerous technological challenges and advances. While many studies of the method of loci relied on people’s own familiar environments, as typically done, the use of virtual environments has allowed for standardisation in understanding how environment layouts may influence the benefits of this well-known memory strategy (Legge et al., 2012; Caplan, Legge, et al., 2019). MIN RE

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The use of virtual environments goes as far back as Aguirre et al. (1996), using Wolfenstein 3D—the first mainstream first-person-shooter game, itself released in 1992. In the decades since, videogames have been critical in the development of virtual environments in memory research—beginning from some of the pioneering 3D games, such as Doom (Maguire, Frith, et al., 1998), Quake (King et al., 2002, 2004; Frey et al., 2007; Cushman et al., 2008; Lövdén et al., 2012), Half-Life (Legge et al., 2012; Caplan, Legge, et al., 2019), and Duke Nukem (Maguire, Burgess, et al., 1998; Spiers et al., 2001). Apart from first-person-shooter games, car racing games (Need for Speed) have similarly been used for their virtual environments (Calhoun et al., 2005; Sagi et al., 2012; Hofstetter et al., 2013). Contemporary VR studies typically use Unreal Engine or Unity (Starrett et al., 2021; Alsbury-Nealy et al., 2022; Safi et al., 2024), though there are other options still, such as Skyrim (Liu & Chen, 2022). To increase immersion, some studies used motorised treadmills to control movement within the virtual environment (Lövdén et al., 2012; Starrett et al., 2021). Comparably, some studies have even been done with rodents using a styrofoam ball as an omni-directional treadmill (Hölscher et

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FIGURE 14.1: Photo and schematic of a rodent navigating a virtual environment.

FIGURE 14.2: Screenshots from “Cliffwood Village” virtual environment built by Kobayashi (2023) in Unreal Engine 5.

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al., 2005; Harvey et al., 2009; Youngstrom & Strowbridge, 2012; Kaupert et al., 2017), as shown in Figure 14.1. Ball movement is tracked using a mounted optical mouse, in many ways functioning as an over-sized trackball mouse. As technology continues to advance, larger and more realistic virtual environments have become both easier to develop and more realistic (Kobayashi, 2023)—see Figure 14.2. More contemporary advances are supported by embracing citizen science (particularly Sea Hero Quest) (Coutrot et al., 2018; Coughlan et al., 2019; West et al., 2023), an increasing emphasis on naturalistic paradigms (Finn, 2021; Jääskeläinen et al., 2021; Dev et al., 2022), and the availability of online recruitment platforms (Buhrmester et al., 2018; Sassenberg & Ditrich, 2019; Newman et al., 2021; Gopi, Zhang, & Madan, 2022; Douglas et al., 2023). Beyond these, innovations in data acquisition are also changing what is possible. New developments in brain imaging and stimulation have provided new possibilities. For instance, a device for measuring magnetoencephalography (MEG) using sensors within the mouth has been recently developed (Tierney et al., 2021). There is also evidence that functional near-infrared spectroscopy (fNIRS) may have facilitatory effects in stimulating frontal regions (Waight et al., 2023). Research over the last two decades has conclusively shown that exposure to blue light affects the circadian rhythm, most often emitted by computer and smart-phone LCD screens (Gehring & Rosbash, 2003; Bues et al., 2012; Oh et al., 2015). While this is generally a consideration to be mindful of, it can be used strategically, such as using blue light in cars to improve night-time driving (Taillard et al., 2012) or otherwise to improve alertness (Beaven & Ekström, 2013). Building on these findings, pulsing blue light at different frequencies has been shown to have neurobiological specificity, such as particularly affecting hippocampus or amygdala responsiveness (Vandewalle et al., 2009, 2010; Lin et al., 2021). Additionally, collection of eye-tracking and heart-rate data has traditionally required additional dedicated hardware. While not bespoke to a specific study, these equipment are costly and not suitable in all settings, such as with online, at-home data collection. However, in the last few years, approaches have been developed whereby webcam hardware, which are practically a ubiquitous computer component now, can be used to obtain eye-tracking and heart-rate measures (Papoutsaki et al., 2016; Madan, Harrison, & Mathewson, 2018; Yang & Krajbich, 2021). In an altogether different setting, methods have been developed and validated for estimating eye-tracking data using MR signal variations from the voxels corresponding to the eyeballs and optic nerve, allowing for new opportunities for deriving more measures from existing fMRI data (LaConte et al., 2006; Son et al., 2020; Frey et al., 2021).

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14.4 Assumptions and generalisations When we assess memory experimentally, as researchers we choose which stimuli to present as the to-be-remembered memoranda. When studying words, we should consider how language abilities may influence memory performance. With English words, an individual with low proficiency in English may only be able to encode the stimuli relatively shallowly, remembering a series of shapes rather than being able to consider the meaning of the word or use more advanced strategies like constructing a narrative from a list of words. I remember in one of my first studies a participant was describing one of the words they could not remember by gesturing a ‘cross’ with their finger—intending to communicate to me that it had the letter ‘t’ in it. Even with image stimuli, we need to consider the relative familiarity of objects or own-race bias in face recognition. This is particularly important when using neuropsychological tests that assess individual ability. In the Weschler Memory Scale, Walker et al. (2010) report lower scores for patients from culturally and linguistically diverse backgrounds (abbreviated as ‘CALD’) than those of English-speaking background, suggesting English language proficiency is the critical factor. Other studies of normed memory tests across cultures have arrived at converging conclusions (Low et al., 2012; Regal, 2017). Similar issues have been noted in other neuropsychological tests as well (Carstairs et al., 2006; Boone et al., 2007; Berry et al., 2019), even after mitigating considerations, such as back translation and the use of professional interpreters (Walker et al., 2009; Veliu & Leathem, 2016; Franzen et al., 2021). Task design considerations are not the only challenges to study generalisability. Neuroimaging and psychophysiological studies have also had biases in their data collection that need to be acknowledged. Recent commentaries have highlighted that due to a variety of reasons, study participants are not ethnically diverse (Moran-Thomas, 2020; Choy et al., 2022; Kwasa et al., 2023; Webb et al., 2022; Ricard et al., 2023). Factors contributing to these biases include race-related differences in hair type (affecting EEG measurement), skin colour/reflectance (affecting pulse oximetry and fNIRS measurement), and skin conductance. Additionally, a history of negative life experiences, related to racial discrimination, influences individual psychophysiological responses to threatening stimuli in experimental settings (Berger & Sarnyai, 2014; Harnett et al., 2019). Software for classifying emotional facial expressions also have been shown to have racial biases (Klare et al., 2012; Sham et al., 2023). While the title and cover present this book as being about memory, in some ways that is its second, or even third focus. If the focus was solely on memory, as you might expect in comparison to some other books, you may have been irritated by the relative depth of discussion allocated to attention, decision making, and expertise. A better characterisation of what you have read may be ‘notes from dozens of conversations with Chris,’ though these notes have a bias in capturing me at my most eloquent, coherent, and opinionated. If I do

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have a conversation with you in person, that caveat may be important, as I know I easily go into tangents. No chapter here is more meandering and broad as this one. In continuing with a much more expansive commentary that spans well beyond the memory literature, it is valuable to evaluate the assumptions that underlie much of psychology. For instance, when it is not clearly stated otherwise in the title or abstract, a study was likely conducted in a Western country and likely with undergraduate students or young adults as participants, but is ascribed as being general to all people. This issue of generalisation is summarised best by the description of most studies as being from WEIRD populations (Henrich et al., 2010a, 2010b; Rad et al., 2018; IJzerman et al., 2020). In this context, WEIRD is an acronym for Western, Education, Industrialised, Rich, and Democratic. More recently, this depiction of bias in the literature has been revisited from the perspective of biological anthropology, with the criticism re-cast as being related to whiteness to avoid erasing other ethnicities that are otherwise also living in Western regions (Clancy & Davis, 2019). Others have also re-framed the point to emphasise that a greater portion of the world is non-Western, instead using the terms Majority and Minority World (Alam, 2008). Independent of the terms used, we need to be considerate of how we categorise countries and people (Khan et al., 2022). To be more inclusive in our research, we should further be considerate about social identities, such as gender diversity, and how they can relate to cognitive processes (Tripp & Munson, 2021). Adequate diversity in participant recruitment involves many intersectional demographics which have direct implications to the reproducibility and generalisability of study findings (IJzerman et al., 2020; Dotson & Duarte, 2020; Grill et al., 2022). MIN RE

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This issue of generalisation is not only applicable to human studies, as research with other species has also been biased. Within the animal research literature, this bias has been framed as the acronym STRANGE: Social background, Trappability and self-selection, Rearing history, Acclimation and habituation, Natural changes in responsiveness, Genetic make-up, and Experience (Webster & Rutz, 2020). To provide some examples of these biases, animal research has tended to rely on a few model organisms, such as fruit flies and rodents, where many species have been far less studied. Even within a designated species, individuals that are more likely to end up in the test sample have selection biases, such as those that are easier to work with and more willing to follow experimental procedures. The size of the social group

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that an animal is housed in can also have an effect on behavioural tasks— perhaps not surprising when considered in relation to how these factors may relate to inter-individual behavioural variation with humans. Convergent with this view, Fischer et al. (2023) found that more research is done on bird species that are generally viewed as more aesthetically pleasing, and that are more accessible relative to university campuses. We also need to think more about how we can apply findings from behavioural science to society (Hallsworth, 2023). Some of these are relatively straightforward, particularly those related to the memory strategies covered in Chapter 11—learning a foreign language would benefit from spacing, retrieval practice, and gamification (Roediger & Karpicke, 2006; Cepeda et al., 2006; Rachels & Rockinson-Szapkiw, 2018; Shortt et al., 2021). Some specific important applications that memory research can improve are medication adherence (Boron et al., 2013; Hargis & Castel, 2018), eyewitness memory (Wells et al., 1998, 2020; Odinot et al., 2013; Luna & Albuquerque, 2018), and interpersonal relationships and empathy (Ross & Sicoly, 1979; Bradbury & Fincham, 1990; Halford et al., 2002; Alea & Vick, 2010). By delving deeper into the intricacies of memory, we can devise more effective strategies for ensuring people adhere to their medication prescriptions, accurately assess memory in legal cases, and foster a more compassionate and understanding society.

14.5 Here be dragons Despite these on-going vibrant topics of research, there is much we do not yet know. In old maps, prior to the circumnavigation of the Earth, dragons were drawn at the edges of what had been explored. Some of these boundaries of current human knowledge have already been identified in this chapter, such as the need for an updated taxonomy of memory systems and our relatively limited understanding of the neurobiology of cognition. Yet, these dragons are not to be feared, but to be embraced. They represent the frontiers of our knowledge, the areas where there is still much to learn and discover. As presented here, there are two paths to memorability. One is inherent salience due to emotion, reward, and other motivational factors; the other is deliberate and effortful, requiring strategies or aids. However, some work have been done to consider how information can be made memorable. Recommendations from these have been to connect to existing prior knowledge, include elements of unexpectedness or surprise, and try to evoke some emotion (Madan, 2015b; Sentell, 2016). A particular thought-provoking topic is the role of memory to the formation of beliefs and self-identity (Locke, 1690; Parfit, 1984; Kihlstrom et al., 2003; McAdams, 2008; Madan, 2024). One perspective on this is the construction of preference from memory, bringing us back to the preferencesas-memory framework (Weber & Johnson, 2013)—first discussed in Section 7.4

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(p. 224). Much of our beliefs are preferences, which are inherently derived from our past experiences. Even more generally, our views on different statements can be categorised into preferences, morals, and facts. Theriault et al. (2017) examined how people understand and represent these three types of statements. Facts are, by definition, reliant on semantic memory, but preferences and morals themselves are also reliant on information we have learned about the world, society, and our own past experiences. All of these are dependent on memory. To briefly highlight the difference between these three types of statements, here is an example of each, selected from those with high category agreement across participants. A fact is “In a full-term human pregnancy, babies spend nine months in a woman’s womb.” A moral statement is “Parents should be willing to make sacrifices for the benefit of their baby.” A preference statement is “Babies that are temperamental are aggravating to spend time around.” Though it is not often discussed in the cognitive science literature, memories are the basis for our beliefs (Kunst-Wilson & Zajonc, 1980; Morewedge et al., 2005; Sloman, 2022; Madan, 2024), but also memories are based on beliefs (Furlong, 1951; Rozeboom, 1965). For instance, if someone moves to a new city and visits a particular restaurant multiple times— consistently having enjoyable experiences—they will now view this restaurant positively and continue to visit. If the experiences were unfulfilling, their belief would be negative and they would avoid future meals there. Reciprocally, our beliefs influence what we remember. Beliefs can act as filters, improving availability of congruent information while potentially distorting or omitting incongruent details. For example, if someone firmly believes in the efficacy of a particular health remedy, they might more vividly remember instances where it appeared to work and forget or downplay instances where it failed. This would lead to confirmation bias—where individuals selectively recall memories that align with their existing beliefs, further entrenching those beliefs. As we have established, it is possible to have vivid memories with high confidence that are false (Neisser & Harsch, 1992; Talarico & Rubin, 2003; Sharot et al., 2004). One extension of this is the realm of conspiracy theories, and examining how memory supports one’s beliefs and sense of self that then is in-line with these theories. By definition, conspiracy theories are alternative explanations for events or situations that reject or challenge the officially or widely accepted narrative (Goertzel, 1994; Jolley et al., 2021; Fernbach & Bogard, 2023). They often involve the belief in hidden, malevolent forces orchestrating events behind the scenes. The propagation and belief in conspiracy theories can be attributed to various factors, including cognitive biases, socio-political context, and psychological predispositions (Douglas et al., 2019). However, the role of memory in the formation and perpetuation of conspiracy theories is a topic that has been relatively unexplored. Our memories are shaped by our social and cultural context, and, in turn, these memories shape our identity and understanding of the world (Madan, 2024).

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I really hope the ideas discussed in this book change how you think about memory. Here I have drawn from a variety of subfields within psychology, weaving a tapestry from fabrics of cognitivism, behaviourism, and constructivism, strands of naturalistic approaches, along with bundles from neuroimaging, neuropsychology, and comparative work. This represents my best attempt to comprehensively understand memory and how it matters. I am sure I have made statements that contradict established and on-going debates. I hope nothing was particularly egregious. In leading up to the completion of this book, I have had conversations about infantile amnesia, expertise, imagination, and consciousness. Prior to beginning this project, I had only a limited knowledge of these topics, but working on this book has led me to have much more enlightened understandings of these topics. By reading this book, hopefully you now do too. As this book comes to a close, I would like to share one of my favourite sayings: A couple of months in the laboratory can frequently save a couple of hours in the library. — Frank Westheimer (from Crampon, 1988) Understanding the intricacies of human memory goes beyond simply knowing facts from books and studies. It’s about unravelling the stories behind the facts—introspections from HSAM individuals and chess grandmasters— which give these facts context and meaning. It’s about appreciating the phenomenology of experiences—how our memories shape our understanding of the world and our place within it. Just like the intricate depictions of knights fighting with snails in the margins of medieval manuscripts (Randall, 1962; Camille, 1992), the memory literature is full of nuanced details and yet-to-be-understood discoveries. Keep exploring, delve into the stacks—find the snails! MIN RE

DER CU E

Again, I sincerely hope this book can satiate some of your interests in memory research and save you years of work in the lab with hours of fervent reading. If I meet you, I would love to hear about the aspects of this book that you enjoyed.

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End of chapter wrap-up Summary Memory is complex and multifaceted, playing a crucial role in our daily lives. Memory systems, including episodic and semantic memory, are intertwined. The boundaries between these systems are not rigid, and a reevaluation of these boundaries is necessary for a more accurate definition of episodic memory. Sharing memories has a profound impact on social interactions and personal relationships. Our understanding of the molecular and cellular basis of memory—and the relation of these to human cognition—is relatively limited. Technological innovations, including virtual environments and videogames, are increasingly used in memory research, along with new developments in brain imaging and stimulation. Assumptions and generalisations in memory research, such as the influence of language abilities on memory performance, need to be carefully considered. The findings from memory research have practical applications in society, such as learning a foreign language, improving medication adherence, and fostering a more compassionate society. The exploration of memory research can change how we think about memory, pushing the boundaries of our current knowledge and opening up new avenues for discovery.

Reminder cues

Quick quiz 1. What is a major challenge in studying memory in non-human animals? (a) Non-human animals do not have episodic recall. (b) Non-human animals cannot be tested using objective measures. (c) Non-human animals cannot express their consciousness, complicating the study of their episodic recall. (d) Non-human animals do not have memory systems similar to humans.

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2. How does the concept of gradients within the brain challenge traditional understandings of brain function? (a) It suggests that the brain can be divided into distinct regions with specific functions. (b) It proposes that the brain operates more like a network with information flowing along gradients. (c) It implies that the brain’s structure and function are static and unchanging. (d) It asserts that the brain’s functionality is entirely localised within specific regions. 3. Virtual reality (VR) has been used in a range of memory studies. Most studies used games based on a first-person perspective, though other types of games have also been used—such as a car racing game. Suppose a new memory research study uses a restaurant simulator instead. Which of these statements would be MOST sensible for a memory-related research question using this game? (a) Gradually increasing the number and complexity of recipes that the player has to remember. (b) Testing if participants have better accuracy for orders based on vegetarian vs. non-vegetarian dishes. (c) Comparing players’ performance in an order-taking waiter role vs. schema-learning chef role. (d) Evaluating if there are context effects in recipe retention if there is a separate training kitchen (encoding) than the one used for the restaurant (testing). 4. Dr. Gomez is a researcher studying memory in rats. She notices that some rats are easier to handle and more willing to perform the tasks she has set up. Over time, she includes more of these “cooperative” rats in her studies. What bias might Dr. Gomez be introducing into her research? (a) Dr. Gomez might be introducing a selection bias, part of the STRANGE set of biases. (b) Dr. Gomez might be inadvertently testing the rats’ acclimation to human contact, part of the CALD set of biases. (c) Dr. Gomez could be favouring rats that show higher cognitive abilities, making her findings not generalisable to all rats. (d) The rats’ behaviour could be influenced by time-of-day effects, biasing her results to circadian rhythm effects.

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5. When individuals integrate into a society with different cultural norms, their previous memories interact with new experiences, influencing the process of cultural assimilation and shaping their evolving identity. Which of the following statements is NOT accurate in describing this complex dynamic? (a) Previous memories can provide a unique perspective that enriches the understanding of new cultural norms, thus adding depth and complexity to their identity. (b) The process can lead to the formation of a multicultural identity that incorporates elements from both the original and new cultures. (c) The individual’s ability to adapt and assimilate is limited by their past experiences and memories, preventing any substantial changes in their identity. (d) Past memories and experiences can guide the individual’s adaptation process within the new culture, facilitating a transformative journey that continually enriches their identity.

Thought questions ▶ What is an interesting fact you learned from this book? Explain the idea clearly, as if to someone without a psychology background. ▶ What internal and external memory aids do you use? Did reading about them in this book change how you view them? ▶ What frontier in memory research, mentioned in this chapter, are you most excited about? Discuss specific recent studies and why the topic is exciting.

Online resources If you have not looked yet, online resources are available for each chapter: https://engra.me/books/memoriesthatmatter/resources/. These resources are primarily videos related to the concepts discussed in each chapter, intended to help make lectures more engaging or be suggested as optional supporting resources. While these are provided for every chapter, I only note their availability here and on pages xxv and 26.

Quiz answers

Chapter 1 (Introduction) 1. Question: As a language teacher, you understand the importance of memory in learning new vocabulary. Which of the following strategies would likely be the least effective in helping your students remember new words? Correct answer: (a) Ask students to list the new words along with their translations in their native language. Explanation: Just listing new words along with their translations is a form of rote learning, which is not as effective for long-term memory retention compared to more active learning strategies. This rote strategy does not take advantage of the reconstructive nature of memory or the power of schemas (understanding based on past experiences) discussed in the chapter. The other options involve creating associations, using the new words in context, and invoking surprise or emotions, all of which can help form stronger and more lasting memory traces. 2. Question: If we were to integrate the analogies of a treasure chest and a garbage can in describing memory, how might these work together? Correct answer: (c) Each memory is a treasure, stored in a vast beach of our minds. However, like a garbage can, the order of these treasures is stored in a disorganised pile. Explanation: This answer captures the essence of the reconstructive nature of memory discussed in the chapter. Each memory is valuable and unique (like a treasure), but the way they are stored is not orderly or linear (like a disorganised pile in a garbage can). When we recall a memory, we need to reconstruct it from these disorganised fragments, much like assembling a jigsaw puzzle. 3. Question: A friend who is studying for an exam tells you they wish their memory worked like a video camera so they could recall all the material verbatim. How could you respond based on your understanding from this section? Correct answer: (b) You suggest they use mnemonic strategies or other memory aids, noting that memory is not a verbatim recording but rather a reconstruction that can be influenced by various factors. 467

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Quiz answers Explanation: Memory is not a verbatim recording of our experiences, like a video camera. Instead, memory is a reconstructive process that can be influenced by various factors, including emotions, associations, and schemas. Mnemonic strategies and memory aids can leverage these influences to improve memory recall.

4. Question: Based on the analogy of a palaeontologist reconstructing a dinosaur, how might we expect a person’s memory of a recent vacation to change over time? Correct answer: (d) The memory might become less detailed or altered, as the person reconstructs the event based on their current knowledge and feelings. Explanation: The analogy of a palaeontologist reconstructing a dinosaur highlights the reconstructive nature of memory. Over time, details of a memory may fade, and the memory may be influenced by the person’s current knowledge, beliefs, and emotions. Just as a palaeontologist might fill in gaps in a dinosaur skeleton with educated guesses, a person might fill in gaps in their memory with plausible details based on their current understanding. 5. Question: You’re asked to imagine your perfect birthday party. Which type of memory is primarily used to construct this mental image? Correct answer: (c) Both episodic and semantic memory, as you’ll use personal memories and general knowledge to create a plausible scenario. Explanation: To imagine a perfect birthday party, you would likely draw from both episodic memory (personal memories of past birthday parties) and semantic memory (general knowledge about what a birthday party entails). These memories would be recombined in a new, imagined scenario–demonstrating the role of memory in imagination.

Chapter 2 (Function) 1. Question: What is the term for the basic unit of information being cognitively processed? Correct answer: (a) Chunk Explanation: In cognitive psychology, a chunk is the basic unit of information that our minds process. Chunks can be composed of several pieces of information, but are treated as a single unit in memory, which allows us to store and recall more information.

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2. Question: What is the significance of the ‘hero’s journey’ model in the context of memory for story narratives? Correct answer: (d) It provides a sequence for major events that can aid in memory. Explanation: The ‘hero’s journey’ is a common narrative structure that outlines a sequence of events in a story. This structure can serve as a schema, here a structured set of preconceived ideas in the reader’s mind. Schemas are cognitive structures that help us organise and interpret information, so they play a crucial role in memory and recall. When stories follow the ‘hero’s journey’ model, readers can anticipate upcoming events and relate the events to each other, which aids in memory recall. Furthermore, the story schema provided by the ‘hero’s journey’ model helps the reader to organise information about the narrative in a meaningful way, making it easier to remember the story. 3. Question: Suppose you are a detective interviewing a witness to a crime. Based on what you know about the reconstructive nature of memory and the influence of leading questions, which of the following approaches would be most appropriate? Correct answer: (c) Ask the witness to recall the event in their own words without interruption. Explanation: The reconstructive nature of memory means that our memories can be influenced by many factors, including the way questions are asked. Leading questions can introduce new information or suggest certain answers, which can alter the witness’s memory of the event. Asking the witness to recall the event in their own words without interruption minimises the influence of leading questions and allows for a more accurate account of the event. 4. Question: Why is verbatim recall important in medication adherence? Correct answer: (a) Patients need to remember to take their medication at the right times and dosages. Explanation: Verbatim recall is crucial in medication adherence because patients need to remember the specific details of their medication regimen, such as when to take their medication and how much to take. Errors in these details can lead to ineffective treatment or harmful side effects. 5. Question: How do memory availability findings relate to interventions aimed at reducing the perceived intensity of medical procedures? Correct answer: (c) Findings suggest that reducing the intensity at the peak and end of the experience can lead to lower remembered pain. Explanation: Memory availability findings show that our memory for an experience is particularly influenced by the peak intensity and the end

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Quiz answers of the experience, a phenomenon known as the peak-end rule. Therefore, interventions that aim to reduce the intensity of pain at these points can help to lower the patient’s remembered pain of the medical procedure.

Chapter 3 (Structure) 1. Question: You are watching a historical movie and recognise that the costumes and settings are accurate for the period it represents. This recognition primarily involves which type of memory? Correct answer: (d) Semantic memory Explanation: Recognising the accuracy of historical settings and costumes requires general knowledge about different historical periods, which is stored in semantic memory. Semantic memory is our memory for facts and general knowledge about the world. It doesn’t involve recalling specific personal experiences (which would be episodic memory), but rather, it involves understanding concepts and facts about the world around us. 2. Question: Consider a situation where you meet someone at a social event. You don’t remember their name, but you remember that they were wearing a red sweater and that you talked about a recent movie. According to the continuum model of recognition memory, how would you describe your memory strength for this encounter? Correct answer: (c) Somewhere in the middle of the continuum. Explanation: The continuum model of recognition memory suggests that memory strength can range from weak to strong. In this case, you have some specific details about the encounter (the red sweater, the conversation about the movie), but you’ve also forgotten a key piece of information (the person’s name). This suggests that your memory strength for this encounter is somewhere in the middle of the continuum. 3. Question: Dr. Lin is interested in examining memory for order of events. She asks participants to recount the events of a popular movie in the order they occurred. According to the text, what type of memory test is this researcher employing? Correct answer: (d) Serial recall Explanation: Recounting the events of a movie in the order they occurred involves serial recall, a type of memory test where participants are asked to recall items in the order they were presented. Serial recall is particularly concerned with the sequence of the information, not just the content of the information itself.

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4. Question: A researcher presents several items to a participant and then, later, asks them to pick out the items they’ve seen before from a larger set. Which term best describes this type of memory test? Correct answer: (c) Selection Explanation: This type of memory test is called a selection test. In a selection test, participants are shown a set of items and later asked to select the items they remember from a larger set. The larger set usually includes both the original items (targets) and additional items that were not presented before (distractors). 5. Question: What is the difference between primary and secondary distinctiveness? Correct answer: (b) Primary distinctiveness refers to the distinctiveness of a word within the local context of an experiment or a specific list, while secondary distinctiveness refers to distinctiveness relative to semantic knowledge and daily life as a context. Explanation: Primary distinctiveness refers to how an item stands out in the immediate context of an experiment or list, due to its unique features compared to other items in the same context. Secondary distinctiveness, on the other hand, refers to how an item stands out in the broader context of semantic knowledge and daily life. An item with secondary distinctiveness might not stand out within the specific context of a list or experiment, but it is distinctive when compared to the general knowledge or experiences of an individual.

Chapter 4 (Individuals) 1. Question: Which option best describes a problem with repeated administrations of the same cognitive assessment? Correct answer: (c) The cognitive assessment results become increasingly unreliable due to a potential practice effect leading to inflated performance. Explanation: Practice effects occur when individuals perform better on a test due to repeated exposure, rather than due to actual improvements in the cognitive abilities being tested. This can lead to inflated scores, making it difficult to accurately track changes in cognition over time. 2. Question: The concept of cognitive reserve in the context of aging refers to: Correct answer: (d) The accumulation of knowledge and skills over a lifetime, which counteracts cognitive decline. Explanation: Cognitive reserve refers to the resilience of the brain

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Quiz answers in the face of damage or aging. People with a high cognitive reserve, typically those who have engaged in intellectual activities and acquired a wealth of knowledge and skills throughout their life, may be able to compensate for brain aging or damage better than those with a lower cognitive reserve. This can delay the onset of cognitive decline or dementia.

3. Question: Considering the characteristics of aphantasia, which of the following statements is most accurate? Correct answer: (b) Aphantasia is associated with an inability to generate mental images, including associated emotional responses. Explanation: Aphantasia is a condition characterised by an inability to voluntarily visualise mental imagery. People with aphantasia have difficulty forming mental images or visualising scenarios, which can impact their emotional responses to situations as emotions are often linked to visual imagery. 4. Question: Alex has an exceptional ability to remember personal past events in great detail without using any specific memory techniques. However, he often feels overwhelmed by the constant recollection of past experiences and sees it as more of a burden than a gift. Which individual discussed in this section does Alex’s situation most closely resemble? Correct answer: (a) Jill Price Explanation: Jill Price, a woman with Highly Superior Autobiographical Memory (HSAM), can recall almost every day of her life in near perfect detail, much like Alex. While this ability might seem desirable, it can also be overwhelming, as every detail of every day is constantly accessible, which can be a burden. 5. Question: How did H.M.’s memory impairments affect his ability to acquire new semantic knowledge? Correct answer: (b) He could learn new semantic knowledge only if he could anchor it to existing information. Explanation: H.M.’s memory impairments were primarily in the domain of episodic memory, or memory for personal events. However, he could still acquire new semantic knowledge (facts and general knowledge) if he was able to relate it to something he already knew. This phenomenon is often seen in individuals with amnesia and demonstrates the distinction between episodic and semantic memory.

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Chapter 5 (Neurobiology) 1. Question: Which of the following acronyms represents the finding that older adults tend to have more frontal activations and less occipital involvement in memory tasks? Correct answer: (b) PASA Explanation: The PASA (Posterior-Anterior Shift in Aging) model describes the observation that older adults tend to show increased activation in frontal (i.e., anterior) brain areas and decreased activation in posterior areas during memory tasks. This shift is thought to reflect compensatory mechanisms in the aging brain. 2. Question: Given the example of adults who played Pokémon extensively as children showing differences in brain activity in a region of posterior fusiform cortex, why might the same type of cortical specialisation not be as pronounced in individuals who spent extensive amounts of time during their childhood playing chess or a musical instrument? Correct answer: (d) Chess and music are more reliant on schemas and planning, and less on visual expertise, which might not result in the same type of specialisation in the fusiform cortex as seen in Pokémon players. Explanation: Chess and music involve a different type of cognitive processing compared to Pokémon. While Pokémon involves a high level of visual expertise and recognition, chess and music are more dependent on strategic planning, problem-solving, and schemas. As a result, the type of cortical specialisation seen in the fusiform cortex in Pokémon players might not be as pronounced in individuals who extensively played chess or a musical instrument during their childhood. 3. Question: Which part of the medial temporal lobe is specialised for processing item-related information? Correct answer: (a) Perirhinal cortex Explanation: The perirhinal cortex is specialised for processing itemrelated information. This area plays a crucial role in object recognition and feelings of familiarity. 4. Question: What is the hippocampus necessary for when it comes to remembering episodes? Correct answer: (a) Integrating across what, where, and when Explanation: The hippocampus is necessary for information about what happened, where it happened, and when it happened. In particular, the hippocampus is necessary for integrating across these three aspects of episodic memories.

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5. Question: Which measures are most sensitive for assessing Alzheimer’s disease progression? Correct answer: (b) Neurobiological measures Explanation: Neurobiological measures are the most sensitive for assessing the progression of Alzheimer’s disease. These measures include brain-imaging techniques like MRI and PET scans, which can detect changes in brain structure and function before significant cognitive symptoms appear. These early detection methods can help in understanding the progression of the disease and in developing potential treatments.

Chapter 6 (Emotion) 1. Question: Consider a public event that you remember vividly. Which of the following additional statements would make it LESS LIKELY that your memory of this event is a flashbulb memory? Correct answer: (d) The event is often replayed in the media, but it didn’t have a significant personal impact on you. Explanation: Flashbulb memories are highly detailed, exceptionally vivid snapshots of the moment and circumstances in which a piece of surprising and consequential (or emotionally arousing) news was heard. They are usually associated with events that have a significant personal impact. If the event didn’t have a significant personal impact on you, it’s less likely that your memory of this event is a flashbulb memory. 2. Question: What is alexithymia? Correct answer: (b) A trait involving challenges in processing emotions. Explanation: Alexithymia is a personality construct characterised by the subclinical inability to identify and describe emotions experienced by oneself or others. Individuals with alexithymia have difficulties in processing their own emotions, which could influence their memory for emotional events. 3. Question: Which of the following is the main reason for emotional and neutral stimuli being matched for primary distinctiveness but still differing in secondary distinctiveness? Correct answer: (a) Emotional experiences are less frequent in everyday life. Explanation: Emotional experiences, compared to neutral experiences, are less frequent in everyday life. This contributes to their primary distinctiveness, or their initial novelty. However, emotional and neutral

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experiences can still differ in secondary distinctiveness, which refers to the relative distinctiveness of a memory in relation to other memories in one’s memory store. 4. Question: Consider a character in a novel who has just embarked on a long, uneventful journey. According to William James’ principle, how might this character perceive the duration of this journey and why? Correct answer: (b) The journey will seem long while it is happening, but short in retrospect due to a lack of notable experiences. Explanation: According to William James’ principle, a time filled with varied and interesting experiences seems short in passing but long as we look back. On the other hand, a tract of time empty of experiences seems long in passing but in retrospect short. Therefore, a long, uneventful journey will seem long while it is happening because there are no notable experiences to break up the monotony, but short in retrospect because there are few memorable moments to recall. 5. Question: Consider a person with high levels of narcissism in a romantic relationship. If their partner frequently gives both positive and negative feedback, which type of comments is the individual more likely to focus on and remember, based on their narcissistic traits? Correct answer: (b) The negative comments about their lack of empathy and consideration. Explanation: Narcissistic individuals tend to be hypersensitive to criticism and negative feedback. Their self-concept is usually inflated and they have a strong desire to maintain this image. Therefore, negative comments, which challenge their idealised self-image, are more likely to be remembered and focused upon.

Chapter 7 (Reward) 1. Question: What is one critique specific to studies that use reward cues as instructions during the study phase in the value prioritisation procedure? Correct answer: (b) Reward-memory effects may be primarily due to preferential attention or rehearsal of higher-value items. Explanation: In value prioritisation procedures, items associated with higher rewards may receive more attention or be rehearsed more frequently, which can enhance memory. However, this also means that the effects observed may not be due to the reward value per se, but rather to these attentional and rehearsal processes.

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2. Question: Consider a scenario where you repeatedly fail a particular level in a videogame because a specific enemy always manages to surprise you. Eventually, you begin to anticipate the enemy’s appearance and can counteract it effectively. Which attention process does this scenario best illustrate and why? Correct answer: (c) This scenario illustrates selection history because your repeated experiences with the enemy subtly guide your attention to anticipate its appearance. Explanation: The process of selection history refers to how past experiences shape our attention. The experiences we accumulate over time form a ‘history’ that informs and influences our future attentional selections. Without these past experiences, you wouldn’t have the necessary information to anticipate the enemy’s appearance. The selection history, therefore, is not just a record of what has happened, but also a predictive tool that aids your future attentional focus and response. 3. Question: What is the main driving force behind the hot-stove effect? Correct answer: (c) Sensitivity to early outcomes Explanation: The hot-stove effect refers to the tendency to avoid choices that have previously led to negative outcomes, even if they may be beneficial in the long run. This effect is largely driven by sensitivity to early outcomes, as individuals tend to be heavily influenced by the initial negative experiences. 4. Question: What is a ‘common currency’ of value in the context of reward-related outcomes? Correct answer: (d) A neural mechanism that generalises value across different stimuli. Explanation: A ‘common currency’ of value in the context of rewards refers to a neural mechanism that represents the value of different types of rewards in a unified way. This allows the brain to compare and make decisions about different types of rewards (for example, food vs. money) using the same scale. 5. Question: Tom, a Parkinson’s patient, started medication involving dopamine agonists. His family has noticed that he’s developed a tendency to gamble, which he never did before. What might this new behaviour suggest? Correct answer: (b) The dopamine agonist treatment might have led to problem gambling behaviour. Explanation: Studies have found that dopamine agonist treatment in Parkinson’s disease can lead to impulse control disorders, including problem gambling. This is because dopamine agonists stimulate

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dopamine receptors in the brain, which are involved in the reward system and can influence risk-taking behaviour.

Chapter 8 (Self) 1. Question: At a recent family dinner, Fred reminisces about reading a night-time story to his daughter every night when she was a child. What type of autobiographical memory would this be classified as? Correct answer: (b) Extended episodes Explanation: Extended episodes refer to continuous or recurring events. In this case, Fred’s memory of reading a night-time story to his daughter every night constitutes an extended episode because it’s a recurring event that happened over a long period of time. 2. Question: One interpretation for the reminiscence bump is the life script narrative, which suggests that autobiographical memories are centred around: Correct answer: (a) Culturally defined goals Explanation: The life script narrative interpretation of the reminiscence bump proposes that people remember life events that correspond to culturally defined life scripts or goals. These scripts define the expected or ideal life course in a given culture, and people tend to recall life events that align with these scripts, leading to the reminiscence bump. 3. Question: In the context of reminiscence therapy, which of the following is a primary benefit of using music to cue memories for patients with dementia? Correct answer: (c) Music can elicit positive emotions and improve social well-being. Explanation: Music has been found to be a powerful tool in evoking memories and emotions, especially in patients with dementia. It can elicit positive emotions, reduce agitation, and improve social interaction, thereby enhancing the social well-being of patients. While it doesn’t reverse the progression of dementia or regain lost cognitive abilities, it significantly improves the quality of life for these patients. 4. Question: Which of the following is NOT a common method used in the literature to study the self-reference effect? Correct answer: (d) Diaries Explanation: The self-reference effect is typically studied using methods such as trait adjectives, personal information, and ownership

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Quiz answers paradigms. Diaries, while a rich source of personal and autobiographical information, are not a common method used to specifically study the self-reference effect in the literature.

5. Question: In a classroom scenario, students were divided into groups for a project. After the project was completed, the students were asked to report their contribution. However, the sum of all students’ estimated contributions exceeded 100%. Which of the following strategies could be employed to attenuate the effect of an egocentric bias and the resulting overestimation? Correct answer: (a) Implement a peer-assessment component, where each student evaluates the contributions of their group mates. Explanation: Egocentric bias, where individuals tend to overestimate their contributions to a group project, can be attenuated by implementing a peer-assessment component. This allows students to evaluate the contributions of their group mates, which can provide a more balanced perspective on individual contributions and help reduce overestimations. It fosters an environment of shared understanding and mutual evaluation that can help to attenuate the effects of egocentric bias.

Chapter 9 (Motor) 1. Question: According to dual-coding theory, why are concrete words like CLOCK and PENCIL often remembered better than abstract words like JUSTICE and THEORY? Correct answer: (a) Concrete words can be mentally represented as both pictures and words, whereas abstract words can only be represented as words. Explanation: Dual-coding theory proposes that we have two cognitive subsystems, one specialised for the representation and processing of nonverbal objects/events (i.e., imagery), and the other specialised for dealing with language. According to this theory, concrete words are remembered better because they can be encoded into both subsystems, the verbal and the imagery system. Concrete words like CLOCK and PENCIL can be easily visualised, providing a pictorial representation in addition to a verbal one. On the other hand, abstract words like JUSTICE and THEORY are primarily encoded verbally as they are less easily visualised.

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2. Question: Imagine you are a researcher studying the motor attributes of different objects. You choose a wrench and a stapler for your study. Based on the text, how might the results of your study differ for these two objects in terms of graspability, moveability, ease of pantomime, and the number of possible actions? Correct answer: (c) The wrench would likely score higher in graspability, moveability, and the number of possible actions; the stapler might score higher in ease of pantomime. Explanation: A wrench is typically used for turning or tightening and has a high degree of graspability due to its handle, as well as a high degree of moveability because it is often used to manipulate other objects. It also allows for a range of actions, from tightening bolts to prying open lids, which may contribute to a higher score in terms of the number of possible actions. The stapler, on the other hand, has a single, specific use—to staple papers together. The action of stapling can be easily mimicked or pantomimed, which might lead to a higher score in ease of pantomime. However, due to its specific function and structure, it is not as versatile as the wrench in terms of the number of possible actions, graspability, or moveability. 3. Question: According to Gibson’s theory of affordances, what properties lead to an object being preferentially attended to? Correct answer: (d) The object must be a real object. Explanation: Gibson’s theory of affordances argues that we perceive and attend to objects based on what they afford us, meaning what actions they allow or facilitate. Importantly, these affordances arise from the physical properties of real objects and the potential for interaction between the perceiver and the object. Therefore, it is the ‘realness’ of an object, its tangible, physical presence in the world, that gives rise to affordances and influences our attention. 4. Question: How does the evidence of automatic motor simulations elicited by words and pictures challenge the traditional understanding of affordances? Correct answer: (c) It suggests that perception of affordances can also be influenced by symbolic representations and mental simulations, not just direct physical interactions. Explanation: Traditional understandings of affordances are rooted in the physical and tangible properties of objects. However, evidence of automatic motor simulations elicited by words and pictures challenges this view. It suggests that our brains are capable of simulating or imagining the actions associated with an object even when we are only presented with a symbolic representation of the object—such as a word or picture. This implies that our perception of affordances is not

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5. Question: During a study session, Lily decides to use drawing as her primary method of studying. She believes that this method will enhance her memory of the study material. Which statement best describes the cognitive processing involved in her study method? Correct answer: (b) Drawing will require more cognitive processing as it engages semantic processing to derive meaning from the material and motor processing to create the drawings. Explanation: Drawing as a study method involves multiple forms of cognitive processing. First, Lily would need to use semantic processing to understand the material she’s studying. Then, she’d need to use motor processing to translate that understanding into a visual representation through drawing. Because of this dual process, drawing can be considered a more active form of studying compared to passive methods such as reading or listening, thereby potentially leading to better memory retention.

Chapter 10 (Domain-general) 1. Question: According to the hedonistic perspective, which type of experiences are we likely to remember the most? Correct answer: (a) Experiences that are particularly pleasurable or painful. Explanation: The hedonistic perspective is driven by our inherent motivation to seek pleasure and avoid pain. Experiences that provide significant pleasure or inflict substantial pain tend to be more memorable because they strongly resonate with these basic motivations. This alignment with our primary drives makes these experiences more likely to leave a lasting imprint in our memory. 2. Question: The student studying for an important exam is exhibiting a form of sustained, goal-directed behaviour. What role does the locus coeruleus (LC) play in this scenario? Correct answer: (b) The LC helps maintain the student’s motivation and focus, potentially through the regulation of norepinephrine levels. Explanation: The locus coeruleus (LC), a small structure nestled within the brainstem, plays a key role in maintaining motivation and focus, particularly during sustained, goal-oriented activities like studying for an exam. This function of the LC may be linked to its regulation of norepinephrine levels, a neurotransmitter involved in attention and stress responses, thereby helping the student stay on task.

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3. Question: Which of the following concepts is NOT related to a generalised view of the availability heuristic? Correct answer: (d) Recall bias, often observed in contexts like medical adherence where individuals may not accurately recall their behaviours. Explanation: Recall bias, marked by systematic inaccuracies in memory retrieval, doesn’t fit with the general concept of the availability heuristic, a mental shortcut used to make judgements based on how easily information can be recalled. Unlike the availability heuristic, recall bias isn’t about the ease or vividness of recalling information; it pertains to distortions in the process of recalling past events. The other options, however, are consistent with the availability heuristic: they suggest that certain information—whether because it’s personally relevant, extreme, or linked to a specific context—tends to be more readily available in our memory, thereby influencing our judgements and decisions. 4. Question: Two cognitive scientists, Sally and Robert, are having a debate about the primary factors that influence word memorability. Sally maintains that the frequency of use and length of a word are the most crucial determinants. Conversely, Robert argues that the semantic meaning is more important. Who has a stronger case? Correct answer: (b) Robert, because words that represent objects that are useful to us are more memorable. Explanation: Robert’s argument hinges on the idea that the semantic meaning of words—including aspects like usefulness and danger, as well as animacy and size—plays a dominant role in their memorability. Words representing objects or ideas that bear relevance or utility to us tend to have high memorability. Therefore, Robert’s emphasis on semantic meaning, particularly usefulness, holds significant weight in this debate. 5. Question: Which statement is the most accurate characterisation of survival processing? Correct answer: (c) Survival-processing effects are not necessarily tied to ancestral priorities, but rather to a general emphasis on survival, regardless of context. Explanation: Survival processing refers to the memory advantage conferred to information when it’s considered in terms of its survival relevance. This effect isn’t limited to ancestral priorities or specific evolutionary contexts; rather, it’s tied to the general relevance of the information to survival. This suggests that our memory systems might be finely tuned to prioritise and retain information crucial to our survival, irrespective of the particular context or environment.

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Chapter 11 (Strategies) 1. Question: Which of the following statements is true about retrieval practice? Correct answer: (c) It is more effective with overt retrieval. Explanation: Retrieval practice, a method of studying that involves actively recalling information, benefits significantly from overt retrieval. This means that physically writing out or saying the answers helps reinforce the learning process more effectively than merely thinking about the answer (covert retrieval). While retrieval practice can be used for various types of learning, this active, overt recall appears to provide the most benefits. 2. Question: Which of the following is a limitation of using acronyms as a mnemonic? Correct answer: (a) Acronyms can be too complex and difficult to remember. Explanation: Acronyms, while useful mnemonic devices, can become overly complex when used to remember long sequences of information. When this happens, the acronym itself can become a challenging memory task, defeating its original purpose of simplifying the learning process. It’s important to remember that mnemonic strategies, including acronyms, should be manageable and support rather than hinder the learning process. 3. Question: Which of the following is NOT a characteristic of scaffold mnemonics? Correct answer: (c) Tailored to the to-be-remembered content. Explanation: Scaffold mnemonics, such as the method of loci or pegword method, involve a pre-existing structure that can be applied to any content. These techniques do require significant initial effort to learn the structure, but once mastered, they can be used flexibly across various types of content. However, the mnemonic structure itself is not tailored to the specific content that needs to be remembered, which is a key characteristic of scaffold mnemonics. 4. Question: What are some effective strategies for deepening one’s understanding of a complex topic or concept? Correct answer: (d) Engaging in discussions and asking questions. Explanation: Engaging in discussions and asking questions is a particularly effective way to deepen understanding of complex topics. This active approach promotes deeper cognitive processing, encourages different viewpoints, and allows for clarification of misunderstandings. While other strategies like reading, highlighting, and summarising

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information can also be beneficial, the interactive nature of discussions provides a more comprehensive exploration of the topic. 5. Question: Why are gamification principles thought to enhance learning? Correct answer: (d) All of the above. Explanation: Gamification enhances learning by incorporating elements traditionally associated with games into learning activities. This includes providing frequent small rewards that positively reinforce behaviour, allowing learners to track their progress and receive feedback, and increasing intrinsic motivation to engage in learning activities. By making learning more engaging and enjoyable, gamification principles can facilitate the learning process and enhance learning outcomes.

Chapter 12 (Expertise) 1. Question: What is the concept of “chunking” and how does it contribute to the development of expertise? Correct answer: (b) Chunking is the process of grouping related pieces of information together, aiding in memory recall and knowledge representation. Explanation: Chunking is a cognitive process that enables us to organise and group individual pieces of information into larger, meaningful wholes, thereby aiding in memory recall and knowledge representation. It’s a key element in expertise development, allowing experts to efficiently process and remember large amounts of information within their field of expertise by reducing cognitive load and making the retrieval process more efficient. 2. Question: Alex, a seasoned birdwatcher, and his nephew, Jamie, a novice in bird watching, are out by a lake. A bird swiftly crosses their path and perches on a distant tree. Alex is able to identify it as a redwinged blackbird based on the specific tree it perched on. Jamie, who also saw the bird at the exact same moment, is still flipping through his field guide trying to identify it. What could be the most likely reason for Alex’s ability to identify the bird more quickly than Jamie? Correct answer: (d) Alex has deeper familiarity with the habitat preferences and habits of birds. Explanation: Alex’s ability to identify the bird swiftly can be attributed to his developed expertise in birdwatching, particularly his deep knowledge of birds’ habits and habitat preferences. This knowledge, refined over years of experience, allows him to make quick identifications

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3. Question: In blindfolded chess, players must mentally maintain the positions of all pieces without seeing the board. Which type of memory is least crucial for success in this variant of the game? Correct answer: (c) Procedural memory to recall the actions used to move the pieces in the game so far. Explanation: In blindfolded chess, while all types of memory play a role, procedural memory—which involves remembering how to perform specific tasks—is less crucial. The actual physical actions involved in moving the chess pieces become less relevant, as the game unfolds mentally rather than on a tangible board, and the moves are verbally communicated rather than physically performed by the blindfolded player. Instead, success in this variant of the game hinges more heavily on episodic memory—to recall the sequence of moves—and semantic memory—to understand the rules and apply schemas developed from past games. 4. Question: Olivia, an upcoming actor, has just landed a role in a play with lengthy monologues. Which of the following approaches might Olivia consider to effectively prepare for her monologues? Correct answer: (b) Break down the monologue into meaningful chunks and weave a mental narrative to link these chunks. Explanation: Chunking, the process of breaking down information into meaningful pieces, is a highly effective strategy for memorising large volumes of information like a lengthy monologue. By breaking down the monologue into chunks and forming a narrative to connect these, Olivia can better understand and recall her lines, making her preparation more effective and efficient. 5. Question: Based on the discussion of pilish, how could this technique be adapted or modified to aid memory in other contexts? Correct answer: (b) It could be used to remember historical dates by associating them with word lengths. Explanation: Pilish—a method of using word lengths to represent the digits of pi—can be modified for other memory tasks. One prominent application could be remembering historical dates. By constructing sentences where each word’s length corresponds to the numbers in a specific date, one could transform an abstract sequence of digits into a memorable sentence. This adaptation of the pilish technique serves as a powerful tool to enhance memory in various contexts.

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Chapter 13 (External) 1. Question: Which of the following is a benefit of using a diary? Correct answer: (d) All of the above. Explanation: Keeping a diary offers multiple benefits. It serves as a record of recent experiences, aiding in the consolidation and recall of autobiographical memories. Furthermore, by providing a chronological account of events, a diary can offer valuable insights into the past, helping us understand patterns and transformations over time. Finally, writing in a diary can function as an emotion regulation strategy, allowing individuals to express, reflect upon, and manage their feelings effectively. 2. Question: If Maria decides to get a tattoo of a specific bird that symbolises a turning point in her life, which of the following statements is NOT true? Correct answer: (d) The tattoo decreases the authenticity of Maria’s memory as it replaces the actual experience with a physical symbol. Explanation: A tattoo, like Maria’s bird symbol, acts as a durable physical reminder. It’s a manifestation of a significant event or experience in Maria’s life, anchoring specific autobiographical memories. This physical symbol can facilitate recall as a reminder of these personal memories, thereby contributing to her personal narrative and identity. It can also communicate personal history to others, fostering a shared understanding of Maria’s experiences. Moreover, the symbolic representation can shape Maria’s self-reflection and interpretation of her past, thereby influencing her identity. However, the tattoo does not decrease the authenticity of Maria’s memory. Rather, it acts as a meaningful symbol that anchors and enhances her memory of the life-changing event. 3. Question: Which statement best describes the viewpoint of proponents of cognitive offloading in relation to the use of digital memory aids? Correct answer: (b) Digital memory aids allow us to store and retrieve vast amounts of information. Explanation: Proponents of cognitive offloading see digital memory aids as beneficial extensions of our cognitive capacity. These aids— ranging from simple note-taking apps to more complex memory augmentation devices—allow us to store and retrieve vast amounts of information that would be challenging to manage unaided. In this way, they increase the amount of information that we can effectively handle, thereby enhancing our cognitive performance.

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4. Question: Imagine you are a digital archivist in 2100, tasked with preserving a collection of digital art from the early 2000s. You discover that some of the art pieces were created using software that is no longer supported or accessible. This situation exemplifies which of the following challenges of memory preservation in the digital age? Correct answer: (b) The evolving nature of digital platforms and the subsequent risk of obsolescence, making it difficult to access and interpret historical records. Explanation: The scenario described highlights the challenge of digital obsolescence—the risk that technological advancements will render older platforms and formats inaccessible. As digital platforms evolve and new technologies replace older ones, accessing and interpreting historical records can become increasingly difficult. This is a significant issue in digital archiving and memory preservation, as it may lead to the loss or inaccessibility of valuable cultural and historical data. The rapid pace of technological change today exacerbates this issue, making digital obsolescence a timely concern in the modern era of memory preservation. 5. Question: Which fictional future technology is closest to being a reality? Correct answer: (c) Erasing memories Explanation: While all the technologies listed have been explored to some degree, the one closest to becoming a reality is the erasure of memories. Recent advancements in neuroscience and pharmacology have led to the development of techniques and drugs that can selectively disrupt the consolidation and reconsolidation of specific memories. However, these approaches are still in the experimental stage and are far from the comprehensive and precise memory erasure depicted in science fiction.

Chapter 14 (Conclusion) 1. Question: What is a major challenge in studying memory in non-human animals? Correct answer: (c) Non-human animals cannot express their consciousness, complicating the study of their episodic recall. Explanation: The study of memory in non-human animals poses unique challenges, one of which pertains to the examination of episodic recall. Episodic memory involves the conscious recall of personal experiences, which non-human animals cannot articulate. This makes it difficult to assess whether, and to what extent, animals possess episodic memory.

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2. Question: How does the concept of gradients within the brain challenge traditional understandings of brain function? Correct answer: (b) It proposes that the brain operates more like a network with information flowing along gradients. Explanation: The concept of gradients in the brain challenges and expands upon our current understanding of brain function. Two decades ago, the view was that the brain was composed of distinct regions with specific functions—this has progressed to a contemporary view that acknowledges that the brain operates as a network of modular components. The idea of gradients introduces an additional layer of complexity. Rather than having information confined to specific modules or networks, the gradient framework proposes that information flows along continuous gradients, transcending the boundaries of distinct network modules. This shift towards understanding the brain in terms of gradients marks a significant evolution in our comprehension of complex cognitive processes. 3. Question: Virtual reality (VR) has been used in a range of memory studies. Most studies used games based on a first-person perspective, though other types of games have also been used—such as a car racing game. Suppose a new memory research study uses a restaurant simulator instead. Which of these statements would be MOST sensible for a memory-related research question using this game? Correct answer: (a) Gradually increasing the number and complexity of recipes that the player has to remember. Explanation: A research study using a restaurant simulator game in the context of memory could reasonably focus on gradually increasing the complexity and number of recipes that the player has to remember. This approach would allow researchers to explore how memory capacity and recall accuracy are affected as the demand on memory increases. Such a setup could also provide insights into how individuals employ various memory strategies to handle increasing amounts of information. While the other options could be part of the study design, they don’t directly address memory-related aspects in as direct and fundamental a way as the selected option. For instance, testing accuracy for vegetarian vs. non-vegetarian dishes or comparing performance in different roles may not yield insights about memory mechanisms per se. Similarly, evaluating context effects could be an interesting aspect to explore, but it assumes a level of memory complexity that might be beyond the scope of an initial study.

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4. Question: Dr. Gomez is a researcher studying memory in rats. She notices that some rats are easier to handle and more willing to perform the tasks she has set up. Over time, she includes more of these “cooperative” rats in her studies. What bias might Dr. Gomez be introducing into her research? Correct answer: (a) Dr. Gomez might be introducing a selection bias, part of the STRANGE set of biases. Explanation: By choosing to include more “cooperative” rats in her studies, Dr. Gomez may inadvertently introduce a selection bias. This type of bias, which is part of the STRANGE set of biases, occurs when the sample is not representative of the population. In this case, the results of Dr. Gomez’s studies might not generalise to all rats, but only to those that are more cooperative. 5. Question: When individuals integrate into a society with different cultural norms, their previous memories interact with new experiences, influencing the process of cultural assimilation and shaping their evolving identity. Which of the following statements is NOT accurate in describing this complex dynamic? Correct answer: (c) The individual’s ability to adapt and assimilate is limited by their past experiences and memories, preventing any substantial changes in their identity. Explanation: The statement that an individual’s ability to adapt and assimilate is limited by their past experiences and memories contradicts the dynamic nature of identity formation in the context of cultural assimilation. Previous memories and new experiences interact, shaping the individual’s evolving identity in the new cultural context. This process does not necessarily limit the individual’s ability to change; rather, it contributes to the formation of a multifaceted identity that reflects both past experiences and new cultural influences.

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Index

A.J., see Price, Jill acetaminophen, 175 acid bath, 11 acquired brain injury, 404 active externalism, 402 actors, 384 ADNI, 103 adrenergic receptor, 175 aesthetics, 313 affective blindsight, 173 affordances, 281 Afghan Girl, 181 aging emotion valence, 193 external memory aids, 405 identity, 238 memory ability, 101 memory selectivity, 202 personality traits, 164 practice effects, 329 reward valence, 226 Air Transat 236, 158 alcohol, 79, 370 Alzheimer’s disease apathy, 302 APOE, 106 composite scores, 103 external memory aids, 402, 410 fiction, 117 hippocampal stiffness, 148 identity, 241 knowledge test, 388 locus coeruleus, 301 memory cases, 121 memory networks, 140 progression, 148 amnesia, 117 Ampelmännchen, 32 amygdala, 46, 172 volume, 299 amyloid-beta, 150 anachronism, 62 analogies, 10, 120 anatomy cranial nerves, see cranial nerves dissection guide, 140 anhedonia, 226, 301

animals 3D printed stimuli, 280 as stimuli, 305 consciousness, 448 expert discrimination, 368 food cache, 147, 220 hippocampus, 143 infantile amnesia, 240 memory, 448 memory capacity, 92 own-species bias, 92, 256 rewards, 213 STRANGE, 460 Aniston, Jennifer, 128 ant, 256 antagonistic pleiotropy, 106 apathy, 226, 301 Apelles of Kos, 332 aphantasia, 19, 109, 450 drawing, 283 APOE, 106 Apollo 11, 428 Apple, 36, 251 approach/avoidance motivation, 313 Aristotle, 81 artificial intelligence, 255 artwork, 313 associations, 81, 185, 273, 339 associative recognition, 83 Astley, Rick, 245 astrocytes, 106, 454 astronaut, 181 attention bottom-up, 183 history, 209 top-down, 324 attentional blink animacy, 306 emotion, 176 food, 316 procedure, 176 reward, 205 self, 250 attentional selection, 209 attic, 347 autism alexithymia, 172

635

636 memory abilities, 114 questionnaires, 258 self-reference effect, 258 theory of mind, 307 Autobiographical Memory Questionnaire, 163, 233 autobiographical memory, 113 aphantasia, 110 HippoCamera, 409 HSAM, 111 memory cues, 233 odour, 454 memory for self, 231 memory taxonomy, 59 mood induction, 167 neurobiology, 252 online security, 249 recording devices, 408 SDAM, 115 tattoos, 406 autonoetic awareness, 63 traumatic brain injury, 252 availability affordances, 281 context, 79 egocentric bias, 254 heuristic, 213, 303 nationalism, 257 availability bias, 48 Bacon, Francis, 347 Baddeley, Alan D., 78 baking, 388 banned books, 8, 417 Bartlett, Frederic, 29 baseball, 160 basketball, 362, 382 bat-and-ball question, 388 bats, 256 behavioural economics, 210 Berenstain Bears, The, 427 Berlin, 32 Berlin Wall, 160 Berry, Halle, 128 bibliometrics about the book, xxv SIMON, 298 BikeAround, 410 bile duct, 362 binging TV, 328 birds board game, 351 expertise, 363 food cache, 147, 220 hippocampus, 147 watching, 364 birth control pills, 175

Index Bitrex, 220 Black Mirror, 434 blackjack, 386 Blasey Ford, Christine, 236 Bloom’s taxonomy, 345 blue steak, 278 board game, 351 Book It, 350 Boston marathon, 160 boundary extension, 22 Braak staging, 148 brain activity animacy, 306 blue light, 457 DRM, 135 emotion, 172, 186 expertise, 359 guilt, 46 memory, 140, 141 memory champions, 394 motivation, 295 motor processing, 273 reward, 203, 207 seductive details, 343 self, 252 tools, 274 BRAIN ATTACK, 335 brain stimulation, 100, 452 brands cult, 251 logo, 36 bridge, 168 Broome, Fiona, 427 Brown, Joyce Ann, 40 bucket, 11 Burun, Noel, 117 Burun, Stella, 117 butcher on the bus, 79 butyric acid, 107 Cadaeic Cadenza, 395 caffeine, 100 Cameron, Jo, 173 Canadian music, 245 Capilano Suspension Bridge, 168 card games counting, 386 magic, 385 memorised deck, 385 Memory, 9 Carrillo, Franky, 41 Carroll, Lewis, 395, 396 carrots, 425 Carter, Kevin, 182 cascading reminiscence bump, 245 cellular memory, 454 censorship, 417

Index census, 12 Challenger explosion, 111, 160, 161 spacewalk, 181 cheese, 107, 370 chef, 210 chemical senses, 370 chess expertise, 376 knowledge test, 388 Chess960, 381 chicken sexing, 368 Child, Julia, 107 childhood amnesia, 236 chocolate, 107 choices, 209 Christmas tree, 120 chunking, 39, 67, 379 Cicero, 342 cilantro, 107, 365 Civilization, 426 clay forming, 283 Clemens, Samuel, see Twain, Mark climbing expertise, 382 Honnold, Alex, 173 cloze probability manipulability, 272 semantic, 83 Cochrane, Kent, 122 cocktail-party effect, 231, 250 coffee, 100, 370 cognitive control, 203 cognitive dynamics, 452 cognitive offloading, 413 cognitive reflection, 388 cognitive reserve, 105 cognitive style, 108 coins, 35 cold pressor test, 169 collaborative remembering, 411, 434, 449 colonoscopy, 51 commute time, 53 composite score, 103 computer keyboard, 360 computer programming, 138, 382 Concealed Information Test, 45 concept cells, 128 concept property norms, 268 concerts, 53 cone of experience, 266 confabulation, 23 confidence, 70, 180, 202 consciousness, 63, 66, 70, 141, 447, 449, 453 context, 77 binding impairment

637 animacy, 310 emotion, 186 motor, 273 reward, 205 butcher on the bus, 79 mood, 170 reinstatement, 77, 454 contraception, 175 cook, 210 Cooke, Ed, 394 Corkin, Suzanne, 118 counting cards, 386 cow, 11 Cracker Jack, 349 cranial nerves crafts, 266 mnemonics, 335 creativity, 83 credit assignment, 206 cresyl violet, 299 critical task, 92 Croatia war, 182 crossword puzzles, 119 Crowe, Russell, 92 CRT monitors, 419 CRUNCH, 133 cud, 11 cue-word technique, 233 cued recall, 83 Culham, Jody, 280 culturally and linguistically diverse backgrounds, 458 culture, 459 attention, 108 emotion, 177 knowledge, 388 neuropsychology, 458 odour, 454 own-race bias, 255 preferences, 247 reminiscence bump, 236 self-reference effect, 249 verbal probabilities, 211 curiosity, 220 cyanopsia, 107 Dalí, Salvador, 8 Darwin, Charles, 109, 404 data storage, 423 Dean, John, 14 decision by sampling, 212 decision making, 210 Deep Blue, 381 deepfake, 428 Deese-Roediger-McDermott see DRM delay discounting, 222

paradigm,

638 dementia, 247, 249 hippocampal stiffness, 148 Derryberry, HK, 113 description-experience gap, 210 desirable difficulties, 331 diagnostic error, 50 Dick, Philip K., 434 Dickens, Charles, 8 difference due to memory, 129 DiMaggio, Joe, 120 dinosaur expertise, 361 historical, 15 Neisser, 15 semantic knowledge, 102 directed forgetting, 70, 203 Disney, 417 distinctiveness, 94, 178 Dm, 129 Doctor Who, 417 fMRI, 453 dolphin, 149 Doom, 457 dopamine agonist, 208, 226 dorsal stream, 274 DOS games, 419 drawing, 36 driving eye movements, 359 overestimated ability, 333 taxi, 374 DRM brain activity, 135 emotion, 170, 177 expertise, 362 motivation, 303 procedure, 95 reward, 202, 206 self, 249 drugs emotion, 175 motivation, 302 reward, 208 dual-coding theory, 265, 337 dual-process theory, 70, 141 duck, 363 Dungeons & Dragons criticals, 216 time dilation, 190 Dunning-Kruger effect, 332 Duolingo gamification, 351 logo, 34 ecphory, 66, 448 EEG, 129, 452 racial bias, 458

Index EEM, 176 egocentric bias, 253 Watergate, 15 Einstein, Albert memorisation, 347, 414 misinformation, 428 ownership task, 251 electric shock, 218, 294, 313 electroencephalography, see EEG electrophysiological recordings, 46, 167, 452 eliminative materialism, 450 Eliot, T. S., 395 embodied cognition, 263 emotion regulation, 167, 193 emotion-induced blindness, 176 emotional blunting, 175 emotional enhancement of memory, see EEM emotional stability, 194, 242 emulation, 419 encoding, 68 encoding specificity principle, 77 endowment effect, 251 entrainment, 453 epilepsy, 117 episodic future thinking, 20, 50, 222 episodic memory, 447 episodic specificity induction, 224 erotic pictures, 166, 218 estimation strategy, 48 eugenics, 109 evaluative conditioning, 186 event memory, 448 event-related potentials, 363 eXoDOS, 419 expected value, 210 experimental confounds, 176, 458 expertise, 355 birds, 363 cars, 363 chess, 376 medical, 355, 366 memory, 392 overconfidence, 332 perceptual, 363 radiologist, 366 schemas, 374 taxi drivers, 374 external memory aids, 405 extra-factual memory, 434 extrastriate body area, 135 extreme-outcome rule, 213 eye movements, 452 expertise, 359 fMRI signal, 457 memory, 81, 324

Index Yarbus, 324 eyewitness memory, 41, 255, 460 Facebook aphantasia, 109 reminders, 421 faces N170, 363 self-related biases, 255 super recognisers, 366 fading affect bias, 193 fairy chess, 381 false alarm, 203 false memories, see DRM famous people, 119, 128 farming, 388 FAST, 334 FDNY, 162 Fermi, Enrico, 323 Feynman, Richard, 346 fiction amnesia, 120 Borges, Jorge Luis, 112 Funes the Memorious, 112 H.M., 120 life events, 239 Moore, Jeffery, 117 semantic memory, 87 Sherlock, 89, 342 technology, 432 file formats, 423 film preservation, 417 firefighter Amsterdam, 42 mnemonic, 335 Neural Bucket Brigade, 206 stress, 162 Fischer random chess, 381 Fischer, Bobby, 381 flashbulb memories, 43 floppy disk, 62, 416 Florida Praxis Imagery Questionnaire, 274 fluid intelligence, 388 flying a kite, 349 fMRI, 129, 203 localiser, 135 Foer, Joshua, 394 fonts, 331 food cache, 220 food colour, 278 football, 362 frames per second, 216 Frank, Anne, 404 free recall, 67 free solo climbing, 173

639 functional magnetic resonance imaging, see fMRI functional similarity, 448 fusiform face area, 133, 256, 366 Galileo, 404 Galton-Crovitz technique, 233 gambling, 226 gamification, 349, 365 Gandhi, 426 Gap, 34 garbage can, 11 Gauthier, Isabel, 365 gender identity, 179, 459 generalisability, 92 glassware, 35 glia, 454 Go, 381 gradients, 451 grandmother neurons, 128 greeble, 366 group projects, 253 growth mindset intervention, 345 Guilty Knowledge Test, 45 Guitar Hero, 351 Gump, Forrest, 239 H.M., 117 hair type, 458 haloperidol, 208 Haraguchi, Akira, 394 HAROLD, 133 Hawk, Tony, 80 heart rate, 46 hedonism, 290 Helvetica, 331 hemlock, 365 Hemsworth, Chris, 107 Henner, Marilu, 114 Heraclitus, 8 hero’s journey, 39 herpes simplex encephalitis, 122 highly superior autobiographical memory, see HSAM Hindi, 8, 379 HippoCamera, 409 hippocampus, 141, 143 animals, 147 APOE, 107 axes, 145 brain activity, 46 dentation, 148 emotion, 186 gradients, 451 reward, 203 semanticisation, 331 stiffness, 148

640 taxi drivers, 374 volume, 299 history, 8 history-based biases, 209 hits, 129 HK, 113 hoax, 34, 423 Holocaust, 235 Wilkomirski, 45 hometown, 249 Homo economicus, 290 Honnold, Alex, 173 Horse in Motion, 307 horses, 92 hot stove, 212 House Hippo, 424 HSAM, 111 hydrogen atom, 396 hyperthmesia, 111 IAPS, 166 history, 181 ice-cold water, 169 identity, 238 IKEA effect, 251 imagination, 19, 450 impulsivity, 225, 302 in-group bias, 255 incidental encoding, 76 indirect tests, 79 infantile amnesia, 236, 240 Information Age, 416 information format, 211 Innocence Project, 44 instance-based learning, 212 instruction manipulation NYPD/MGM, 184 washing clothes, 348 intellectual property law, 354 inter-generational sharing, 449 intergenerational sharing, 8 internet, 34, 411, 415 interrogative/imperative motivation, 314 interview, 41 intracranial electrodes, 452 Ishiguro, Kazuo, 8 isolation, 99 item recognition, 67 Jabberwocky, 395 James, William, 157, 190 Johnson, Lonni Sue, see L.S.J. judgement of learning, 180, 332 juice, 218 Kanwisher, Nancy, 133, 280 Kasparov, Garry, 381

Index key lock, 361 key switch, 360 keyboard, 360 kidnapping, 43 knowledge, see semantic knowledge elicitation, 357 Knowledge in Diverse Domains, 388 knowledge test, 87, 328 Alzheimer’s disease, 388 chess, 388 culture, 388 expertise, 387 fiction, 40 guilt, 45 trivia, 220 wine, 388 Kodak, 407 Konami code, 387 koniocellular pathway, 276 Korsakoff’s syndrome, 121 L.S.J., 120, 122 languages animacy, 305 expertise, 369 learning, 102, 460 gamification, 351 keyword method, 336 retrieval practice, 330 motor simulation, 271 proficiency, 458 programming, 362 savantism, 115 larger later, 222 Larrowe, Marcus Dwight, 354 lateral occipital complex, 135 Laws of Association, 81 lead exposure, 99 leading questions, 43 learned predictiveness effect, 295 learning pyramid, 266 learning styles, 344 learning to learn, 87, 329 Leeds United Football Club, 34 Lego, 251 Lenna, 418 Lethe, 7 levadopa, 208 levels of processing, 76 desirable difficulties, 331 drawing, 282 enactment, 264 manipulability, 272 self reference, 248 survival processing, 312 lie detection, 45 life-script narrative, 238

Index lifelogging, 409 limbic system, 144, 451 Lincoln, Abraham, 160 lingering biases, 209 Linton, Marigold, 234 lithotripsy, 51 Little Albert, 174 Livermore, Jesse, 199 lobster, 256 lock cylinder, 361 Locke, John, 116, 241 locus coeruleus, 299 Loisette, see Larrowe longitudinal, 101, 329 Lord of the Rings, 383 lost in the mall, 43 lost media, 417 low-stakes quizzes, 331 lukasa, 342 Luria’s S., 91, 109, 113, 115 M-DISC, 416 magnetic resonance elastography, see MRE imaging, see MRI magnocellular pathway, 276 Magritte, René, 278 Mahadevan, Rajan, 109 Major system, 396 mallard, 363 Mandela effect, 427 marriage, 14, 40, 253, 434, 449 Marvel Studios, 417 massed practice, 326 Matching Pairs, 9 McCandless II, Bruce, 181 McKinnon, Margaret (AT236), 158 McKinnon, Susie (SDAM), 115 median split, 451 medical Alzheimer’s disease, see Alzheimer’s disease colonoscopy, 51 diagnostic error, 50 education, 351 epilepsy, 117 expertise, 355, 362 gastroenterologist, 362 lithotripsy, 51 medication, see medication medication adherence, 48 Parkinson’s disease, see Parkinson’s disease peak-end rule, 51 radiologist, 366 terminology, 336, 359, 362 medical diagnosis, 368

641 medication adherence, 460 anxiety, 175 contraception, 175 emotion, 175 pain, 175 Parkinson’s disease, 208 schizophrenia, 208 medication adherence, 48 medieval times, 157 MEG, 457 Memento, 405 memorabilia, 405 memorised deck, 385 memory capacity, 91, 423 memory decay, 68 memory interview, 41 memory jars, 11 memory palace, 342 memory strength, 68, 203 memory theory of personal identity, see psychological continuity theory memory transfer, 436 MemTrax, 74 Mengs, Anton Raphael, 7 Merriam, Florence, 364 meta-analysis, xxiv β-adrenergic, 175 amygdala, 172 autobiographical recall, 168 chess, 381 dual-coding theory, 265 environmental context, 78 evaluative conditioning, 186 expertise, 381 growth mindset, 345 learning styles, 344 loneliness, 99 method of loci, 343 mood induction, 167 own-age bias, 255 own-race bias, 255 personality and life events, 242 personality—cognition, 100 quizzes, 331 retrieval practice, 330 self reference, 249 sleep, 99 student evaluations, 332 subsequent memory effect, 132 survival processing, 312 method of loci, 340, 393 metroprolol, 175 MGM Studios, 184 Microsoft Excel World Championship, 388

642 MID task, 207 Milner, Brenda, 118 Minecraft, 417 misses, 129 mistattribution of arousal, 169 mnemonic, 334 mnemonic similarity task, see MST Mnemosyne, 7 Molaison, Henry, see H.M. Monet, Claude honeybees, 368 vision, 107 monetary incentive delay, 207 monkey, 256 Monroe, Marilyn, 120 moon landing, 428 Morse code, 337 motivational salience, 292 motor chauvinist, 263 motor-evoked potential (MEP), 272 movie fictional memory technology, 432 hero’s journey, 39 horses, 92 Inside Out, 10 life events, 239 semantic order, 87 Sherlock, 89 two selfs, one body, 241 Mozart, 77 Mozilla, 109 MRE, 148 MST, 75 emotion, 187 reward, 221 multiband imaging, 207 multiple memory systems, 95, 204, 213, 247 museum, 402 music context, 77 preference, 245 myside bias, 254 myth carrots and eyesight, 425 growth mindset, 345 learning pyramid, 266 learning styles, 344 memory as a computer, 128 memory as a recording, 12 nuclear Gandhi, 426 spinach as source of iron, 425 mythology, 7, 21 N170, 363 Napoleon, 404 narcissism, 194

Index NASA, 396 National Geographic, 181 national narcissism, 257 NATO alphabet, 337 Natural Scenes Dataset, 74 naturalistic, 31, 448 nature, 52, 170 NBA, 362 Neeson, Liam, 92 Neptune, 404 neural alignment, 138 Neural Bucket Brigade, 206 neuromelanin, 299 NeuroSynth, 295 NFL, 36, 362 Nixon, Richard moon landing, 428 Watergate scandal, 14 norepinepherine, 299 Norse, 8 nostalgia, 34, 244, 418, 419 NYPD, 184 oddball, 94 Odin, 21 odour, 370, 454 operant conditioning, 350 order, 81, 339, 340 orientation motivation, 313 orienting task, 92 orienting/defensive responses, 167 overconfidence, 332 emotion, 180 expertise, 332 own-group bias, 255 own-race bias, 255, 458 ownership, 250 Oz, 417 pain, 157, 173 painting Dali, 8 Mnemosyne, 7 Monet, 368 Parnassus, 7 Picasso, 368 The Persistence of Memory, 8 The Treachery of Images, 278 Unexpected Visitors, 324 palaeontology, 15 pancreas, 362 parahippocampal place area, 133 paramedic, 170 Parkinson’s disease alexithymia, 172 apathy, 302

Index gambling, 225 medication, 208 parvocellular pathway, 276 PASA, 133 pattern completion, 144 pattern separation, 144 payola, 246 peak-end rule, 51 Peglau, Karl, 32 Pelling, Nick, 349 Pelmanism, 9 Pepsi, 34 perceptual expertise, 255 perceptual identification, 363 perfume, 370, 372, 454 personal semantics, 107, 232, 252 personality amnesia, 244 cognition, 100 personality trait, see trait, 248 pharmacological agents, 302 emotion, 175 reward, 208 phenomenological characteristics, 163 phenomenological measures, 450 phonetic code, 396 photojournalism, 182 physical health, 99 pi, 394 savantism, 115 Piaget, Jean, 43, 231, 240 Picasso, Pablo, 119 picture superiority effect, 91 pirate, 11 Pixar, 87 Pizza Hut, 350 planaria, 436 plane crash Amsterdam, 42 AT236, 158 Spantax, 182 plant, 365 Plato, 3, 413 Playboy, 418 Pliny the Elder Apelles of Kos, 332 cilantro, 107 King Cyrus, 392 PM-AT framework, 140 Poe, Edgar Allen, 395 points, 218 Pokémon, 138 Pollyanna principle, 193 positivity bias, 193 postcard, 432 posterior–anterior shift in aging, 133 Potter, Harry, 40, 87

643 practice effect, 329 praise, 218 prediction error, 208 preference, 80, 210, 303, 461 preferences, 107 premature closure, 50 presentation duration, 68 Price, Jill, 111, 239 primacy effect, 85 formative experiences, 244 prison, 434 programming, 138, 362, 382 propranolol, 175 prosopagnosia, 366 protein misfolding, 150 protein synthesis, 454 psychological continuity theory, 66, 116, 241 psychophysiology, 46, 167 PTSD, 158 public events, 236 pulse oximetry, 167, 458 pupil dilation emotion, 167 Pyrex, 35 Q-learning, 206 qualitative, 449 query theory, 212 questionnaire alexithymia, 172 autism, 258 autobiographical memory, 163, 233 delay discounting, 222 depression, 171 emotion, 168, 171 imagery, 109 memory beliefs, 13 memory strategies, 403, 405 O-LIFE, 301 subjective memory, 104 wine, 35 racial discrimination, 458 rainbow, 66 Raphael, 7 ravens, 21 Read, Ronald Kingsley, 380 reading disfluency, 331 recall, 67 recency effect, 85 receptor agonist, 175, 208 recognition, 67 recognition heuristic, 49 recollection, 70, 141 recorder, 10 Red Sox, 160, 257

644 Reeves, Keanu, 433 reinforcement learning, 206 relationship satisfaction, 14, 40, 434, 449 reliability, 180 reminiscence bump, 236 reminiscence therapy 3D printing, 280 BikeAround, 410 music, 247 societal health, 449 repeated presentations, 68 Repin, Ilya, 324 response bias, 203 resting-state fMRI, 140 retrieval dynamics, 88, 202 retrieval mode, 72 retrieval practice, 329 retrieval success, 129 retro games, 419 reward anticipation, 350 riddle, 59 risk preference, 210 RNA, 436 rock climbing, see climbing Rocksmith, 351 Ross, Blake, 109 Rossetti, Dante Gabriel, 7 ROY G. BIV, 334 Rubik’s cube, 383 rumination, 11 S., see Luria’s S. Sans Forgetica, 331 savantism, 115 scaffolding theory of aging and cognition, 133 schema, 19, 23, 39, 67, 380 schizophrenia, 208 Scoville, William, 118 scrub jay, 220 scuba, 78 SDAM, 115 Sea Hero Quest, 457 APOE, 107 seahorse, 144 security questions, 430 self identity, 53, 66, 241 self-reference effect, 248 semantic knowledge cortical specialisation, 133 dinosaur, 102 DRM, 95 expertise, 356 fictional technology, 433 H.M., 119 language, 102 learning science, 328

Index memory taxonomy, 58 objects, 268 semantic memory, 59, 135 semantic network, see knowledge semanticisation, 138 SenseCam, 409 serial position curve, 85, 202 serious games, 351 Sesame Street, 417 severely deficient autobiographical memory, see SDAM sexual assault, 236 sexual partners, 48 Shakespeare, William, 8 shared memories, 53 Shavian alphabet, 380 Shaw, Bernard, 380 sheep cattle grid, 65 face memory, 92 Shereshevsky, Solomon, see Luria’s S. Sherlock brain attic, 347 fMRI study, 89, 448 irrelevant facts, 347 method of loci, 342 shock, 218 shoemaker, 332 Sicilian Defence, 376 Signs.com, 36 Simonides of Ceos, 342 skeuomorphism, 62 skin color, 458 skin conductance response, 46, 167 skydiving, 170, 191 Skywalker, Luke, 239 slap, 157 sleep, 454 smaller sooner, 222 SME, 129 emotion, 186, 193 reward, 202 smell, 365 snacks, 332 Sniffin’ Sticks, 454 soap, 107 social anxiety, 258 social isolation, 53, 99 social pain, 175 socioemotional selectivity theory, 193 Socrates, 413 SOH-CAH-TOA, 334 solar system, 347 solitary confinement, 99 songlines, 342 space, 428 space shuttle, 161, 181

Index spaced practice, 326 Spanish, 102 species, 256 Sphinx, 59 spinach, 425 sports, 160, 257, 362 STAC, 133 Star Trek, 40, 383 Star Wars, 40 Starbucks, 36, 251 STRANGE, 460 Street Fighter, 383 stress, 99 stroke, 334, 335 student evaluations of teaching, 332 subjective cognitive decline biomarkers, 149 self report, 105 subjective memory complaints, 105 subsequent forgetting, 132 subsequent memory effects, see SME substitute tool-use, 277 Sudan famine, 182 sulpiride, 208 superagers, 116 surgeon, 362 survival processing, 249, 310 synesthesia, 114 taboo, 178 Tammet, Daniel, 114 targeted memory reactivation, 454 tau tangles, 148 Taxi (TV show), 114 taxi drivers, 374 taxonomy, 57, 447 teaching evaluation, 332 telephone handset, 62 temporoparietal junction, 132 test-retest reliability, 180 testing effect, 329 tetrahedral model, 92 Tetris amnesia, 81 monkeys, 138 thalamus, 451 thanabot, 422 The Hobbit, 19 The Knowledge, 374 The Matrix, 433 The War of the Ghosts, 15 Jill Price, 112 theory of mind, 307 therapy BikeAround, 410 music, 247 think aloud, 358

645 think—no-think, 70 Thinking About Life Experiences, 242 Thompson, Donald, 41 time dilation, 189 time-saving services, 53 Tolkien, J. R. R., 19, 40 topic space, 90, 177 total-time invariance, 68 traffic light, see Ampelmännchen trait aging stability, 164, 194, 242 alexithymia, 164, 172 anxiety, 164 depression, 171 emotion, 171 emotional stability, 194, 242 narcissism, 194, 242 phantasia, 108 schizotypy, 301 social anxiety, 258 trait adjective, 248 transactive memory, 402, 411 trauma, 160, 235 treachery, 278 treadmill, 457 treasure, 11 Trier social stress test, 169 trivia, 59, 220 tuning fork, 11 TV show, 114 Twain, Mark boating, 81 hot stove, 212 strategy, 323 typicality, 278 ultraviolet light, 107 Uncensored Library, 417 uncinate fasciculus, 252 understanding, 345 underwater, 78 Unexpected Visitors, 324 United States collective identity, 257 semantic information, 87 universe, 396 upload knowledge, 432 Urbach-Weithe disease, 173 US presidents, 87 utilitarianism, 290 vacation, 52, 232, 434 value prioritisation, 200 value-directed remembering, 200 vampire bats, 256 Vanderbilt Chest Radiograph Test, 366 ventral stream, 274

646 verbal probability phrases, 211 verbatim expertise, 383 recall, 46 recognition, 76 victors, 8 video playback speed, 328 videogame e-sports, 382 emotion regulation, 167 expertise, 383 fictional technology, 434 gamification, 349 Konami code, 387 library, 417 memories, 244 nostalgia, 418 Pac-Man, 387 virtual environment, 457 XCOM 2, 211 Villemard, 432 virtual reality context, 79 Mars, 79 method of loci, 343 objects, 280 technology, 448 videogame, 457 visual search, 359 visual word-form area, 135 vitamin B1 deficiency, 121 vividness, 160, 450 vocabulary, 9 vodka, 79 vomit, 107 von Restorff, 94

Index waiters, 384 Wakalixes, 346 washing clothes, 348 water, 404 Watergate scandal, 14 wax tablet, 12 weapon-focus effect, 183 Wearing, Clive, 122 WEIRD, 459 Weschler Memory Scale, 458 Wikipedia, 413 Wilkomirski, Binjamin, 45 Williams, Serena overconfidence, 333 password, 431 Wiltshire, Stephen, 114 wine aroma wheel, 371 knowledge test, 388 memory availability, 50 odour, 454 terminology, 359, 370 witch, 417 witness interview, 41 Wolfenstein 3D, 419, 457 word-frequency paradox, 93 world history, 257 World Memory Championship, 392 Yankees, 160, 257 Yarbus, Alfred L., 324 yohimbine, 175 zombies, 312