The Oxford Handbook of Emotion Dysregulation [Hardcover ed.] 0190689285, 9780190689285

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The Oxford Handbook of Emotion Dysregulation

Oxford Library of Psychology Area Editors: Clinical Psychology David H. Barlow Cognitive Neuroscience Kevin N. Ochsner and Stephen M. Kosslyn Cognitive Psychology Daniel Reisberg Counseling Psychology Elizabeth M. Altmaier and Jo-Ida C. Hansen Developmental Psychology Philip David Zelazo Health Psychology Howard S. Friedman History of Psychology David B. Baker Methods and Measurement Todd D. Little Neuropsychology Kenneth M. Adams Organizational Psychology Steve W. J. Kozlowski Personality and Social Psychology Kay Deaux and Mark Snyder

OXFORD

L I B R A RY

OF

PSYCHOLOGY

The Oxford Handbook of Emotion Dysregulation Edited by

Theodore P. Beauchaine Sheila E. Crowell

1 2020

1 Oxford University Press is a department of the University of Oxford. It furthers the University’s objective of excellence in research, scholarship, and education by publishing worldwide. Oxford is a registered trade mark of Oxford University Press in the UK and certain other countries. Published in the United States of America by Oxford University Press 198 Madison Avenue, New York, NY 10016, United States of America. © Oxford University Press 2020 All rights reserved. No part of this publication may be reproduced, stored in a retrieval system, or transmitted, in any form or by any means, without the prior permission in writing of Oxford University Press, or as expressly permitted by law, by license, or under terms agreed with the appropriate reproduction rights organization. Inquiries concerning reproduction outside the scope of the above should be sent to the Rights Department, Oxford University Press, at the address above. You must not circulate this work in any other form and you must impose this same condition on any acquirer. Library of Congress Cataloging-in-Publication Data Names: Beauchaine, Theodore P., editor. | Crowell, Sheila E. (Sheila Elizabeth), editor. Title: The Oxford handbook of emotion dysregulation / edited by Theodore P. Beauchaine, Sheila E. Crowell. Description: New York, NY : Oxford University Press, [2020] | Series: Oxford library of psychology | Includes bibliographical references and index. | Identifiers: LCCN 2019031334 (print) | LCCN 2019031335 (ebook) | ISBN 9780190689285 (hardback) | ISBN 9780190689308 (epub) | ISBN 9780190689292 Subjects: LCSH: Emotions—Handbooks, manuals, etc. | Psychology, Pathological— Handbooks, manuals, etc. | Affect (Psychology)—Handbooks, manuals, etc. Classification: LCC RC455.4.E46 O94 2020 (print) | LCC RC455.4.E46 (ebook) | DDC 616.89—dc23 LC record available at https://lccn.loc.gov/2019031334 LC ebook record available at https://lccn.loc.gov/2019031335 9 8 7 6 5 4 3 2 1 Printed by Integrated Books International, United States of America

C O N T R I B U TO R S

Molly Adrian, PhD Department of Psychiatry and Behavioral Sciences Seattle Children’s Hospital Kenneth J. D. Allen, AM Department of Psychology Harvard University Ananda B. Amstadter, PhD Virginia Institute for Psychiatric and Behavioral Genetics Virginia Commonwealth University Michael F. Armey, PhD Department of Psychiatry and Human Behavior Warren Alpert Medical School Brown University Rachel M. Atchley, PhD, MCR Center on Mindfulness and Integrative Health Intervention Development (C-MIIND) The University of Utah Theodore P. Beauchaine, PhD Department of Psychology The Ohio State University Lane Beckes, PhD College of Liberal Arts and Sciences Bradley University Spencer Bell, PhD Department of Physiology/Pharmacology Wake Forest University Health Sciences Ziv E. Bell, MA Department of Psychology The Ohio State University Michele Berk, PhD Psychiatry and Behavioral Sciences - Child and Adolescent Psychiatry and Child Development Stanford University Grace Binion, MS Department of Psychology University of Oregon

Patricia A. Brennan, PhD Department of Psychology Emory University April L. Brown, MPH Department of Psychology Emory University Mindy Brown, BS Department of Psychology The University of Utah Alexander L. Chapman, PhD, RPsych Department of Psychology Simon Fraser University Dante Cicchetti, PhD Institute of Child Development University of Minnesota Pamela M. Cole, PhD Department of Psychology The Pennsylvania State University Lindsey C. Conkey, PhD Department of Psychological and Brain Sciences University of Massachusetts Amherst Elisabeth Conradt, PhD Department of Psychology The University of Utah Geoffrey W. Corner, BS Department of Psychology University of Southern California Sheila E. Crowell, PhD Department of Psychology The University of Utah Katherine L. Dixon-Gordon, PhD Department of Psychological and Brain Sciences University of Massachusetts Amherst Anna R. Docherty, PhD University Neuropsychiatric Institute University of Utah Health Sciences Center Weston Layne Edwards, MA Department of Psychology Bradley University ix

S H O RT C O N T E N T S

About the Editors vii Contributors ix Table of Contents xiii Chapters 1–486 Index 487

v

A B O U T T H E E D I TO R S

Theodore P. Beauchaine, PhD, earned his undergraduate degree in ­psychology from Portland State University, and his PhD in clinical psychology, with a quantitative minor, from Stony Brook University. He completed his clinical internship at the University of California at San Diego School of Medicine. He is past recipient of both the American Psychological Association Distinguished Scientific Award for Early Career Contributions to Psychology and the American Psychological Association Mid-Career Award for Outstanding Contributions to Benefit Children, Youth, and Families. He has served on numerous editorial boards, and as Associate Editor for Development and Psychopathology and Psychophysiology. He served on the National Institute of Mental Health National Advisory Council Workgroup on Tasks and Measures for the Research Domain Criteria (RDoC). His research addresses neural underpinnings of and development of behavioral impulsivity, emotion dysregulation, and intentional self-injury in children, adolescents, and adults. Sheila E. Crowell earned her PhD in child clinical psychology from the University of Washington. She completed her clinical internship at Seattle Children’s Hospital through the University of Washington Psychology Internship Program. Dr. Crowell has expertise in emotion dysregulation across the lifespan, including infants, children, adolescents, and adults. Her work on emotion dysregulation extends across a number of diverse clinical populations, such as depression, substance use disorders, trauma, personality disorders, and self-injury. Dr. Crowell is also a licensed clinical psychologists with expertise in Dialectical Behavior Therapy (DBT), an evidence-based treatment for diagnoses characterized by emotion dysregulation. Dr. Crowell has served on study sections for the National Institutes of Health and as a reviewer or editorial board member for several journals. She has received funding for her research from the National Institutes of Mental Health and the American Foundation for Suicide Prevention. A primary goal of Dr. Crowell’s research is to prevent suicide and the development of psychopathology through enhanced identification of those at risk and early intervention.

vii

Margaret A. Fields-Olivieri Department of Psychology The Pennsylvania State University Courtney N. Forbes, MEd Department of Psychology The University of Toledo Brett Froeliger, PhD Department of Neuroscience Medical University of South Carolina Eric L. Garland, PhD, LCSW Center on Mindfulness and Integrative Health Intervention Development (C-MIIND) The University of Utah Kim L. Gratz, PhD Department of Psychology The University of Toledo James J. Gross, PhD Department of Psychology Stanford University Hunter Hahn, MA Department of Psychology The Ohio State University Nathaniel Haines, BA The Center for Cognitive and Brain Sciences The Ohio State University Greg Hajcak, PhD Department of Psychology Florida State University Lauren A. Haliczer, MA Department of Psychological and Brain Sciences University of Massachusetts Amherst Sophie Havighurst, PhD Department of Psychiatry The University of Melbourne Sage E. Hawn, BA Virginia Institute for Psychiatric and Behavioral Genetics Virginia Commonwealth University Nora H. Hope, PhD, RPsych Department of Psychology Simon Fraser University Sarah A. Horvath, MA Department of Psychology Ohio University Camelia E. Hostinar, PhD Department of Psychology University of California, Davis x Contributors

Hooria Jazaieri, PhD Kellogg School of Management Northwestern University Parisa R. Kaliush, BA Department of Psychology The University of Utah Niranjan S. Karnik, MD, PhD Department of Psychiatry Rush Medical College Erin A. Kaufman, BA Department of Psychology The University of Utah Christiane Kehoe, PhD Department of Psychiatry The University of Melbourne Patricia K. Kerig, PhD Department of Psychology The University of Utah Mona Khaled, MA Department of Psychology University of Southern California Joseph C. Leshin, BS Department of Psychology & Neuroscience The University of North Carolina at Chapel Hill Kristen A. Lindquist, PhD Department of Psychology & Neuroscience The University of North Carolina at Chapel Hill Christina Gamache Martin, PhD Department of Psychology University of Oregon Whitney I. Mattson, PhD Brain Development and Social Cognition Lab Nationwide Children’s Hospital Kateri McRae, PhD Department of Psychology University of Denver Michele A. Morningstar, PhD Brain Development and Social Cognition Lab Nationwide Children’s Hospital Eric E. Nelson, PhD Center for Biobehavioral Health Nationwide Children’s Hospital Emily Neuhaus, PhD Department of Psychology University of Washington

Jacqueline O’Brien, MS Department of Psychology University of Oregon Cassie Overstreet, MA Department of Psychology Virginia Commonwealth University Ruchika Shaurya Prakash, PhD Department of Psychology The Ohio State University Sarah E. Racine, PhD Department of Psychology McGill University K. Ashana Ramsook, MA Department of Psychology The Pennsylvania State University Lance M. Rappaport, PhD Virginia Institute for Psychiatric and Behavioral Genetics Virginia Commonwealth University Julia R. Richmond, MA Department of Psychology The University of Toledo Darby Saxbe, PhD Department of Psychology University of Southern California Heather T. Schatten, PhD Department of Psychiatry and Human Behavior Brown University Tiffany M. Shader, MA Department of Psychology The Ohio State University Brittany C. Speed, MA Department of Psychology Stony Brook University Sarah A. Stoycos, MA Department of Psychology University of Southern California

Ross A. Thompson, PhD Department of Psychology University of California, Davis Matthew T. Tull, PhD Department of Psychology The University of Toledo Andero Uusberg, PhD Department of Psychology University of Tartu Helen Uusberg, PhD Department of Psychology University of Tartu Robert D. Vlisides-Henry, BA Department of Psychology The University of Utah Gemma T. Wallace, BA Department of Psychiatry University of Utah School of Medicine Sara F. Waters, PhD Department of Human Development Washington State University, Vancouver Linnie E. Wheeless, JD Department of Psychology The University of Toledo Patrick Whitmoyer, MA Department of Psychology The Ohio State University Dominika A. Winiarski, PhD Department of Psychology Rush University Maureen Zalewski, PhD Department of Psychology University of Oregon Paree Zarolia, PhD Department of Psychology The University of Denver

Contributors

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TA B L E O F C O N T E N T S

1. Functionalist and Constructionist Perspectives on Emotion Dysregulation 1 Theodore P. Beauchaine and Nathaniel Haines 2. Emotions as Regulators of Motivated Behavior  13 Eric E. Nelson, Michele A. Morningstar, and Whitney I. Mattson 3. Emotions as Regulators of Social Behavior  27 Lane Beckes and Weston Layne Edwards 4. Cognition and Emotion in Emotion Dysregulation  39 Kateri McRae and Paree Zarolia 5. What Emotion Dysregulation Looks Like: Inferences from Behavioral Observations 53 K. Ashana Ramsook, Pamela M. Cole, and Margaret A. Fields-Olivieri 6. Emotion Dysregulation and Aging  69 Patrick Whitmoyer and Ruchika Shaurya Prakash 7. Emotion Generation, Regulation, and Dysregulation as Multilevel Transdiagnostic Constructs  85 Sheila E. Crowell, Robert D. Vlisides-Henry, and Parisa R. Kaliush 8. Development of Emotion Dysregulation in Developing Relationships  99 Ross A. Thompson and Sara F. Waters 9. Operant Reinforcement and Development of Emotion Dysregulation  115 Christina Gamache Martin, Maureen Zalewski, Grace Binion, and Jacqueline O’Brien 10. Cognitive Processes and Risk for Emotion Dysregulation  127 Hooria Jazaieri, Helen Uusberg, Andero Uusberg, and James J. Gross 11. Interpersonal Processes and the Development of Emotion Dysregulation 141 Sarah A. Stoycos, Geoffrey W. Corner, Mona Khaled, and Darby Saxbe 12. Respiratory Sinus Arrhythmia as a Transdiagnostic Biomarker of Emotion Dysregulation 153 Theodore P. Beauchaine and Ziv E. Bell 13. Event-Related Potentials and Emotion Dysregulation  167 Brittany C. Speed and Greg Hajcak 14. Neuroimaging of Emotion Dysregulation  183 Joseph C. Leshin and Kristen A. Lindquist 15. Behavioral and Molecular Genetics of Emotion Dysregulation  203 Lance M. Rappaport, Sage E. Hawn, Cassie Overstreet, and Ananda B. Amstadter xiii

16. Epigenetic Foundations of Emotion Dysregulation  221 Mindy Brown, Elisabeth Conradt, and Sheila E. Crowell 17. Emotion Dysregulation and Externalizing Spectrum Disorders  237 Tiffany M. Shader and Theodore P. Beauchaine 18. Emotion Dysregulation and Internalizing Spectrum Disorders  249 Camelia E. Hostinar and Dante Cicchetti 19. Emotion Dysregulation and Childhood Trauma  265 Patricia K. Kerig 20. Emotion Dysregulation in Autism Spectrum Disorder  283 Emily Neuhaus 21. Emotion Dysregulation and Psychosis Spectrum Disorders  299 Gemma T. Wallace and Anna R. Docherty 22. Emotion Dysregulation in Addiction  313 Eric L. Garland, Spencer Bell, Rachel M. Atchley, and Brett Froeliger 23. Emotion Dysregulation and Eating Disorders  327 Sarah E. Racine and Sarah A. Horvath 24. Emotion Dysregulation and Self-Inflicted Injury  345 Erin A. Kaufman and Sheila E. Crowell 25. Emotion Dysregulation and Borderline Personality Disorder  361 Katherine L. Dixon-Gordon, Lauren A. Haliczer, and Lindsey C. Conkey 26. Behavioral Assessment of Emotion Dysregulation  377 Molly Adrian and Michele Berk 27. Self-Report Assessment of Emotion Dysregulation  395 Kim L. Gratz, Courtney N. Forbes, Linnie E. Wheeless, Julia R. Richmond, and Matthew T. Tull 28. Assessment of Emotion Dysregulation Using Ecological Momentary Assessment 411 Heather T. Schatten, Kenneth J. D. Allen, and Michael F. Armey 29. Treating Emotion Dysregulation in Externalizing Disorders  427 Dominika A. Winiarski, April L. Brown, Niranjan S. Karnik, and Patricia A. Brennan 30. Treating Emotion Dysregulation in Internalizing Disorders  443 Christiane Kehoe and Sophie Havighurst 31. Dialectical Behavior Therapy and Treatment of Emotion Dysregulation 463 Alexander L. Chapman and Nora H. Hope 32. Future Directions in Research and Treatment of Emotion Dysregulation 477 Theodore P. Beauchaine, Hunter Hahn, and Sheila E. Crowell Index 487

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Table of Contents

CH A PTE R

1

Functionalist and Constructionist Perspectives on Emotion Dysregulation

Theodore P. Beauchaine and Nathaniel Haines

Abstract Two theoretical perspectives—functionalism and constructionism—predominate modern research on emotion. This introductory chapter describes these perspectives and offers points of convergence and divergence. It pays special attention to common misconceptions about functionalism and to strengths and limitations of each perspective. Functionalism, which draws in part from phylogenetic accounts of emotion and motivation, is limited by difficulties drawing inferences about human emotion from animal research, even though animal research is conducted using very precise methods of high spatial and temporal resolution. In contrast, constructionism is limited by difficulties falsifying its core propositions given reliance on research using functional magnetic resonance imaging, which has poor temporal resolution. These limitations notwithstanding, both functionalism and constructionism have much to offer current interpretations of and future research on emotion dysregulation. Thus, pitting the perspectives against one other is counterproductive. Keywords:  constructionism, emotion, emotion dysregulation, functionalism, psychopathology

Work on this chapter was supported by grant DE025980 from the National Institutes of Health, and by the National Institutes of Health Science of Behavior Change (SoBC) Common Fund.

Introduction

It is an honor and a privilege to coedit this Oxford Handbook, in which contributors describe diverse perspectives on emotion dysregulation. We were fortunate to receive contributions from internationally renowned experts in affective science, who together summarize contemporary approaches to and future directions in emotion dysregulation research. Chapters are grouped into six sections: (1) conceptual issues; (2) cognitive, behavioral, and social approaches; (3) neurobiological approaches; (4) psychopathology; (5) assessment and treatment; and (6) future directions. Collectively, these sections describe effects of emotion dysregulation on core ­aspects of human function across levels of analysis including genes, neural networks, electrophysiology, and behavior. During 3 years of planning and

editing this volume, Sheila Crowell and I (TPB) learned more about emotion dysregulation than we otherwise could have known, and we are indebted to a brilliant team of contributors. We hope readers find the diversity of topics useful in advancing their thinking about emotion dysregulation and its multiple determinants across the lifespan. In this chapter, we summarize functionalist and constructionist perspectives on emotion, which sets the stage for chapters to follow. Over the past two decades, emotion regulation has received burgeoning attention as a scientific construct, as evidenced by foundational articles, dedicated volumes, and extended scientific debate (e.g., Aldao, Nolen-Hoeksema, & Schweizer, 2010; Cole, Martin, & Dennis, 2004; Gross, 1998, 2014). Although emotion dysregulation has received more 1

circumscribed attention, it is of considerable interest to developmentalists, psychopathologists, and other invested parties (e.g., Beauchaine, 2015; Bradley et al., 2011; Gratz, Rosenthal, Tull, Lejuez, & Gunderson, 2006; Linehan, 1993). In this volume, we place primary emphasis on emotion dysregulation and how it compromises adaptive human functioning through its effects on initiating, maintaining, and modulating diverse human behaviors (cf. Campos, Mumme, Kermoian, & Campos, 1994; Thompson, 1990). Given our objective of conveying contemporary perspectives on emotion dysregulation, both emotion and emotion regulation must be discussed. However, they are not primary foci given widespread coverage in other sources. Interested readers are referred to excellent recent reviews (Aldao et al., 2010; Barrett, 2017a; Braunstein, Gross, & Ochsner, 2017; Gross, 2014; Gross & Barrett, 2011).

Variants of Functionalism

When defining emotion dysregulation, one must first consider what emotions are, and the day-to-day functions they serve and do not serve in both their ordinary and extreme forms. From this perspective, affect dysregulation cannot be defined by overt expressions of emotion without first specifying the contexts in which such expressions occur, then evaluating whether the emotion expressed and the intensity of its expression are context appropriate, inappropriate, or neutral vis-à-vis social and cultural norms. For example, intense expressions of anger toward others may be fully functional if the safety of one’s offspring is threatened, but similarly intense displays of anger interfere with adaptive behavior in most social and cultural contexts. Although often not considered, it is also important to note that in some situations expressions of anger are afunctional. Even moderately intense solitary displays of anger, for example, such as those elicited by frustration while driving, may serve no function or dysfunction whatsoever. Thus, whether particular displays of emotion are functional, dysfunctional, or afunctional, and whether they are regulated, dysregulated, or unregulated, depends in large part on ­eliciting contextual events, and match or mismatch between context and expressive intensity (e.g., Aldao, 2013). Furthermore, given two common uses of the term functionalism that partly but do not fully overlap (see immediately below), classifying emotions as functional or dysfunctional, regulated or dysregulated, is not as straightforward as it might first appear (e.g., Barrett, 2017b). 2

One common use of the term functionalism assumes evolutionary selection of at least some human emotions. Such accounts presume that broad classes of emotion evolved to motivate adaptive, survivalrelated functions including approach, avoidance, and social affiliation (e.g., Keltner & Gross, 1999). According to evolutionary functionalist perspectives, emotions that subserve these functions are preserved across species and experienced by all mammals, including humans, because they were selected in our environments of adaptation (e.g., Panksepp, 2011, 2016). For example, approach emotions (e.g., wanting, enthusiasm) elicit consummatory behaviors (e.g., foraging, food seeking); avoidance emotions (e.g., anxiety, fear) elicit precaution (e.g., passive avoidance, suppression of approach); and affiliative emotions (e.g., compassion, affection) elicit prosocial behaviors (e.g., group cohesion, pair bonding). Without emotions motivating approach, avoidance, and affiliative behaviors, likelihood of survival in our environments of adaptation would presumably have been lower. Evolutionary functionalist perspectives have a long history in animal, human, and comparative research on emotion and suggest that emotion and motivation are inextricable facets of human function, despite being separated in the history of behavioral science (see, e.g., Beauchaine & Zisner, 2017; Gray & McNaughton, 2000; Panksepp, 2011; Porges, 1997). An important corollary of this perspective is that humans sometimes behave at the behest of their emotions. Such is especially likely when ­environmental contingencies are extreme and pull strongly for survival-relevant actions (e.g., in situations of food deprivation, threats to physical safety to oneself or one’s kin). Strong emotional reactions to these situations motivate urgent behavioral responses that override ongoing activities (see, e.g., Corr, 2004). Notably, however, evolutionary functionalist accounts do not imply that all or even most emotional reactions are survival relevant. In fact, evolutionary theorists have long recognized that (1) over any ­extended period of time individual differences in  emotional and behavioral response tendencies confer probabilistic rather than deterministic effects on adaptive fitness, and (2) some behavioral response tendencies are coincidental byproducts of evolution—not direct outcomes of adaptive selection (Beauchaine, 1999; Buss, Haselton, Shackelford, Bleske, & Wakefield, 1998; Gould, 1991). In the latter case, such response tendencies have no bearing on

Functionalist and Constructionist Perspectives

adaptive fitness. Despite its name, evolutionary functionalism therefore does not imply that all or even most emotional experiences or expressions are functional, a point we return to in later sections (see “Points of Divergence and Convergence in Functionalism and Constructionism”). In a second common use of the term functionalism, experiences and expressions of emotions are linked to outcomes in our day-to-day lives, with limited if any consideration of our evolutionary ­ ­environments of adaptation (see Keltner & Gross, 1999). Among children, for example, emotionally complaisant, well-mannered behavior in the classroom is seen as functional and adaptive, whereas emotionally exuberant, impulsive behavior is seen as dysfunctional and maladaptive. Notably, however, exuberance and impulsivity were likely not maladaptive in our evolutionary environments of adaptation and may have conferred selective advantages in certain environmental niches (see Mead, Beauchaine, & Shannon, 2010). Thus, whether specific emotions and behaviors are functional or dysfunctional in our modern-day lives may have nothing to do with their phylogenetic adaptive value. Our intent here is to call readers’ attention to the important distinction between these two common uses of the term functionalism, the latter of which is especially prone to circular reasoning in definitions of adaptation. Given potential confusion brought about by ­different uses of the term functionalism, and given other issues described in foundational articles across the affective sciences (e.g., Campos et al., 1994; Cole et al., 2004; Keltner & Gross, 1999; Thompson, 1990), coeditor Sheila Crowell and I (TPB) encouraged authors to adopt a common definition of emotion dysregulation as “a pattern of emotional experience and/or expression that interferes with ­appropriate goal-directed behavior” (Beauchaine, 2015, p. 876, emphasis added; see also Cole, Hall, & Hajal, 2017). Here, we chose the word appropriate instead of adaptive to avoid teleological undertones. Teleological explanations are those that define phenomena based on specific purposes they serve, including assumptions that specific emotions either (1) evolved to serve highly specialized functions or (2) always serve an immediate function. As already noted, many displays of emotion are afunctional, and in Western culture, situations that require “appropriate” dampening of strong emotions are far removed from our evolutionary environments of adaptation. Moreover, testing evolutionary functions of emotions and emotion-subserving neural

circuitry is a difficult proposition (see Barrett, 2017b). These observations contributed to modern constructionist accounts of emotion, which eschew several assumptions of traditional functionalist theories, as described in the next section. A common although not universal assumption of evolutionary functionalism is that at least some emotions or subsets of emotions represent categories in nature. This notion follows from seemingly ­different classes of behavior—including approach, avoidance, and social affiliation—that specific emotions seem to support (see earlier; Beauchaine & Zisner, 2017; Gray & McNaughton, 2000; Panksepp, 2011; Panksepp & Watt, 2011). Furthermore, many evolutionary accounts presume that either rudiments of or fully formed approach, avoidance, and affiliative emotions (1) are present across mammalian species, (2) are experienced by human infants at birth, and (3) transcend human cultures (Ekman & Cordaro, 2011; Ekman & Friesen, 1971). These theories articulate phylogenetically old, subcortical neural networks that subserve basic emotions (see, e.g., Beauchaine, Neuhaus, Zalewski, Crowell, & Potapova, 2011; Panksepp, 2016). Full articulation of anatomical and functional characteristics of these subcortical structures is beyond the scope of this introductory chapter, but both are specified in extensive reviews of the animal and human literatures (e.g., Beauchaine et al., 2011; Ikemoto, Yang, & Tan, 2015; Koob & Volkow, 2010; Panksepp, 2016; Tovote, Fadok, & Lüthi, 2015). In brief, early work on subcortical neural circuits of ­approach and avoidance derived from studies of ­associative learning, motivation, and addiction in rodents and nonhuman primates. This work, including lesion studies, single cell recording experiments, and pharmacological manipulations, identified subcortical neural systems of appetitive and aversive motivation that are largely preserved across species. These systems include (1) the medial forebrain bundle—particularly projections from the ventral tegmental area to the nucleus accumbens— as integral to appetitive motivation and approach emotions (Sagvolden Johansen, Aase, & Russell, 2005; Schultz, 2002; Wise, 2004) and (2) the septohippocampal system—including the hippocampus and its afferent projections from the amygdala—as integral to aversive motivation and associated avoidance emotions (Corr, 2013; Gray & McNaughton, 2000; Strange, Witter, Lein, & Moser, 2014). Although general consensus exists regarding the primary roles these systems play in approach and Beauchaine and Haines

3

avoidance motivation and emotion (for reviews see Beauchaine, 2001; Beauchaine & Zisner, 2017), it is also well recognized that the systems interact structurally and functionally (e.g., Corr, 2013; Corr & McNaughton, 2016). For example, neurons in the nucleus accumbens (NAcc) respond to punishment as well as reward, and the amygdala responds to reward as well as punishment (e.g., Sauder, Derbidge, & Beauchaine, 2016; Schultz, 2016). Both are therefore intricately involved in associative learning. Moreover, the NAcc and the amygdala share interconnections via the paraventricular nucleus and the stria terminalis (e.g., Dong, Li, & Kirouac, 2017; Tovote et al., 2015). Thus, although the distinction between appetitive and aversive subcortical systems is useful heuristically, subcortical CNS networks of approach and avoidance interact complexly and are not functionally independent (see also Beauchaine & Constantino, 2017; Beyeler, 2016).

Implications for Emotion Regulation and Dysregulation

Functionalists often distinguish between bottomup, subcortically mediated emotion generation processes and top-down, cortically mediated emotion regulation processes (e.g., Beauchaine, 2015; Gross & Barrett, 2011). According to such perspectives, subcortical neural circuits that initiate strong emotional responses are modulated by cortical functions (see also Hare et al., 2008). This literature is voluminous and cannot be reviewed comprehensively, yet several findings are noteworthy. First, cortical structures, particularly in prefrontal and orbitofrontal regions, have long been implicated in executive function and self-regulation (see Beauchaine & Zisner, 2017; Etkin, Büchel, & Gross, 2015; Heatherton, 2011). Modern neuroimaging studies identify functional subdivisions of the prefrontal, anterior cingulate, and insular cortices as integral to effortful downregulation of negative affect (e.g., Tone, Garn, & Pine, 2016; Zilverstand, Parvaz, & Goldstein, 2017). In fact, volitional reappraisal of negative emotion elicits increased neural responding across a distributed network of frontal structures, including the dorsolateral, medial, and ventrolateral prefrontal cortices; the lateral orbitofrontal cortex; the inferior frontal gyrus (IFG); and the insular cortex (e.g., Goldin, McRae, Ramel, & ­ Gross, 2008). Second, subcortical structures reach volumetric and functional maturity many years before cortical neural structures (e.g., Brain Development Cooperative Group, 2012; Casey, Getz, & Galvan, 4

2008; Galvan et al., 2006). Differential neuromaturation of subcortical and cortical brain regions is a likely contributor to the impetuous, impulsive, and emotionally labile behaviors common to adolescence (e.g., Casey & Caudle, 2013). As prefrontal neuromaturation completes in early adulthood, self- and emotion regulation improve markedly. Notably, children and adolescents show stronger subcortical responses to incentives than adults, yet their prefrontal cortex responding is weaker and more diffuse (Macdonald, Goines, Novacek, & Walker, 2016). Furthermore, adolescents with impulse control problems show blunted frontal neuromaturation (De Brito et al., 2009). Finally, deficits in functional connectivity between cortical and subcortical structures are ­ observed in both impulse control and anxiety ­ disorders, which are characterized by excessive ­ ­approach- and avoidance-related emotions, respectively. For example, reduced functional connectivity between the anterior cingulate and dorsal striatum is observed among externalizing adolescents (e.g., Shannon, Sauder, Beauchaine, & GatzkeKopp, 2009), and reduced functional connectivity between the amygdala and the orbitofrontal cortex is associated with compulsive behavior and emotional lability (e.g., Churchwell, Morris, Heurtelou, & Kesner, 2009; Hilt, Hanson, & Pollak, 2011). Notably, although findings are complex and not fully consistent, several studies show improved cortical–subcortical connectivity following effective treatment for internalizing and externalizing disorders (for a recent review see Beauchaine, Zisner, & Hayden, 2019). Collectively, these findings lend support to the notion that emotion regulation is subserved by top-down cortical control over subcortical neural responding, and that disruptions in frontal cortical function and cortical–subcortical connectivity characterize emotion dysregulation (see also Beauchaine, Constantino, & Hayden, 2018).

Constructionism

An alternative to functionalist perspectives is constructionist theory. Constructionists assert that what humans perceive as discrete emotions are not encoded by specific brain regions, but rather constructed through learning processes that are highly individualized. According to this perspective, emotions and other experiential states, including perception and cognition, emerge from interactions among more primitive sensory and neural mechanisms, which humans interpret and categorize

Functionalist and Constructionist Perspectives

based on prior experience (see Barrett, 2009). Constructionist theory identifies core affective processes, including valence and arousal, which transcend multiple emotional states. Through repeated visceral pairings of these core affective processes with sensory and neural input elicited by our environments, we learn to associate instances of core affect with higher order, discrete representations of emotion such as happiness and sadness (e.g., Russell & Barrett, 1999). Neural mechanisms of core affective states are presumed to be present at birth, universal among humans, and supported by the same neural networks as other psychological processes and states, such as perception and decision making (see Duncan & Barrett, 2007). Constructionists make a clear distinction between core affective processes and emotions. Whereas core affective processes refer to general ­experiences of positivity–negativity (valence) and activation–deactivation (arousal), emotions are more specific experiential states, such as sadness, anger, fear, and shame (Ekman, 1992; Ekman & Cordaro, 2011). Thus, despite being experienced discretely, all emotions can be characterized along dimensions of valence and arousal (Barrett, 2016). According to constructionist theory, we rely on learning and memory from prior experience to infer the meaning of core affect in current situations. In this way, we construct context-dependent emotion representations (Barrett, 2017a). Of note, core ­affective processes, similar to basic emotions, can motivate behavioral response tendencies. For example, Pavlovian bias is a “hard-wired” tendency to approach positively valenced stimuli and avoid negatively valenced stimuli (Guitart-Masip et al., 2011). In some cases, Pavlovian bias is so strong that organisms cannot learn stimulus–response contingencies that require avoidance to attain reward (Hershberger, 1986). Constructionists have been critical of functionalist theories on a number of grounds. Although we cannot review all such critiques here, three especially important issues concern (1) teleological arguments concerning adaptive evolution of emotion, as outlined earlier (see “Variants of Functionalism”); (2) opposition to the notion that specific neural structures and networks subserve particular emotional states and functions; and (3) disagreement on the extent to which animal research on reward learning, fear learning, and motivation informs our understanding of human emotion. Although we agree that these points warrant consideration when evaluating functionalist theories, we argue that functionalism is often oversimplified and thus mis-

construed in critical discussions concerning its merits. This creates an artificial distinction between functionalist and constructionist views on emotion. We view functionalism and constructionism as largely compatible, so long as one avoids teleological misconceptions of evolution and acknowledges interactive complexities and functional dependencies of neural responding within and across subcortical and cortical networks. In sections to follow, we briefly outline our reasoning.

Implications for Emotion Dysregulation

Constructionist accounts now rival functionalist perspectives as explanatory theories of emotion, yet constructionists have written far less than functionalists about emotion dysregulation per se. This may be because constructionist approaches, including the theory of constructed emotion (TCE; Barrett, 2017a,  2017b; Lindquist, 2013), view emotions as emergent properties of complex neuro-architectures, which exhibit individualized affect-imbuing response patterns that are byproducts of unique learning histories. These learning histories produce cognitive–affective schemas, attributional biases, and stimulus–response associations that contribute collectively to emotional experience. From this standpoint, emotion dysregulation is emotion, because it arises through the same highly individualized neural processes and unique learning histories (see, e.g., Papa & Epstein, 2018). According to TCE, emotion dysregulation emerges at least in part from neural mechanisms of core affective processes (e.g., valence, arousal) and disruptions in situated conceptualization (Barrett, Wilson-Mendenhall, & Barsalou, 2013). Situated conceptualization refers to “the brain [as] a situated processing architecture, designed to process situations in the moment and to simulate non-present situations in thought” (Barsalou, 2016, p. 6). This includes evaluating what eliciting events represent, how to act upon those events, and the nature of core affective processes to expect. Barrett et al. (2013) suggest that emotion dysregulation could emerge from highly canalized, inflexible conceptualizations that are not situational. In turn, nonsituational conceptualizations could arise from disruptions to one or more among several processes, including memory retrieval, autonomic regulation, and attention, to name but a few. As reviewed by Barrett and Satpute (2013), many such deficits correlate with abnormalities in connectivity among intrinsic neural networks, including the salience network and the fronto-parietal network, as seen in diverse forms of Beauchaine and Haines

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psychopathology. Thus, disrupted connectivity plays a central role in both functionalist and constructionist theories of emotion dysregulation.

Points of Divergence and Convergence in Functionalism and Constructionism

As already noted, teleological explanations are those that define phenomena based on the specific purposes they serve. The notion that emotions were designed by evolution to serve specific, adaptive functions is therefore teleological (Barrett, 2017b). Basic emotion theory identifies approximately six discrete emotions (happiness, sadness, fear, surprise, anger, and disgust) that are shared across cultures, some of  which are documented in other mammals (Chevalier-Skolnikoff, 1973; Ekman & Friesen, 1971). A teleological explanation takes cross-species and cross-cultural expressions of affect as evidence that discrete emotions evolved to facilitate adaptive behaviors (e.g., fear evolved with the purpose of signaling organisms to danger). In other words, evolution by natural selection purposefully designed basic emotional states to preserve the organism. Here it is important to note that purposeful design has been explicitly eschewed as a mechanism of evolution since Darwin (1859) wrote On the Origin of Species. Thus, even though evolutionary psychologists have at times appealed to purposeful design, evolutionary biologists rejected the notion over a century ago (see Beauchaine, 1999; Buss et al., 1998; Gould, 1991). A more accepted approach among evolutionary theorists is to infer function from the consequences of emotions throughout ­evolutionary history (Wright, 1973). For example, we may infer that the function of fear is to alert an organism of immediate danger because fear in the face of danger creates conditions that are conducive to survival. By way of natural selection, the most likely consequence of an emotion is therefore the function of that emotion specifically in our environments of evolutionary adaptation (see Wright, 1973). Provided such inferences are supported by observable, biological mechanisms, they are not dubious philosophically (e.g., Barrett, 2017b; Neander, 1991). This Darwinian (1872) perspective is infused in contemporary thinking about emotion (see Keltner & Gross, 1999), despite terminology that sometimes leads to confusion. Indeed, even in biology, where most scientists decry language implying that evolution proceeds with goal-directed intention, some nevertheless use such language as a literary device (e.g., Hanke, 2004). 6

A second critique of functionalism concerns its  linking of emotional states to specific brain ­regions and networks. As outlined under “Variants of Functionalism,” for example, functionalist theories often link (1) appetitive emotions to neural responding in the medial forebrain bundle, including projections from the ventral tegmental area to the nucleus accumbens (Sagvolden et al., 2005; Schultz, 2002; Wise, 2004), and (2) aversive emotions to neural responding in the septo-hippocampal system, including the hippocampus and its afferent projections from the amygdala (Corr, 2013; Gray & McNaughton, 2000; Strange et al., 2014). According to such accounts, basic emotions are presumed to be initiated/generated by localized, phylogenetically old neural structures that are largely preserved across mammals and, in some cases, other vertebrates (Panksepp, 2011,  2016). As already noted, these conclusions are based on decades of extensive research with animals (rodents and nonhuman primates). This research includes localized lesion studies, pharmacological manipulations, and implanted electrode stimulation and recording experiments that are highly precise both spatially and temporally (e.g., Gray, 1982; Olds & Milner, 1954). Most studies of this nature cannot be conducted with humans for obvious ethical reasons. As a consequence, neural studies of human emotion rely primarily on functional magnetic resonance imaging (fMRI), which evolved more recently. When fMRI technology was first applied in emotion research, region-of-interest (ROI) and effective connectivity analyses predominated. Most early ROI and connectivity studies were deductive (top-down), with ROIs specified a priori based on theory. Early metaanalyses of these studies revealed modest evidence for emotion localization, consistent with animal research (e.g., Murphy, Nimmo-Smith, & Lawrence, 2003; Phan, Wager, Taylor, & Liberzon, 2002). More recently, inductive (bottom-up) approaches that capture coactivated neural circuitry have ascended to prominence in the fMRI literature. These approaches show that distributed patterns of neural activity account for more variance in basic emotions than specific brain regions (Celeghin, Diano, Bagnis, Viola, & Tamietto, 2017; Saarimäki et al., 2016). Such findings are sometimes cited as evidence against functionalism (Kober et al., 2008; Lindquist, Wager, Kober, Bliss-Moreau, & Barrett, 2012; Touroutoglou, Lindquist, Dickerson, & Barrett, 2015). It is important to note, however, that linking basic

Functionalist and Constructionist Perspectives

e­ motions to specific brain structures oversimplifies the functionalist perspective. In fact, functionalists have long recognized that multiple emotional states activate common brain regions (see, e.g., Gray & McNaughton, 2000), and that complex neural circuits and interacting cortical–subcortical networks generate and regulate affective responses (e.g., Beauchaine, 2015; Beauchaine & Zisner, 2017; Braunstein et al., 2017; Etkin et al., 2015; Goldin et al., 2008; Gray & McNaughton, 2000; Gross & Barrett, 2011). Indeed, functional deficiencies in cortical–subcortical connectivity characterize several psychiatric disorders for which emotion dysregulation plays a prominent role (see, e.g., Beauchaine, Constantino, et al., 2018; Shannon et al., 2009; Tone et al., 2016). It should also be noted that neural signals propagate across brain regions and networks at much faster rates than fMRI is capable of resolving. For example, reactivity to reward cues by midbrain ­dopamine neurons—as assessed via direct electrode placement in primates—peaks at about 0.2 seconds and returns to baseline at about 0.7 seconds (e.g.,  Lak, Stauffer, & Schultz, 2016). In contrast, the fMRI blood oxygen level–dependent (BOLD) signal peaks between 4 and 5 seconds poststimulus and returns to baseline after 10 seconds (e.g., Lohrenz, Kishida, & Montague, 2016). Thus, the BOLD signal is a sluggish indicator of neural responding and is not well suited for detecting rapidly propagating patterns of neural responding that ­originate in the subcortex and project to both cortical and other subcortical structures. Although modern imaging sequences provide whole-brain coverage of slices at well under 1-second resolution (e.g., Uğurbil et al., 2013), this does not circumvent sluggishness of the BOLD signal being measured. It is important to recognize this limitation when evaluating strengths and weaknesses of modern imaging techniques that characterize and correlate widely distributed patterns of BOLD coactivation with attentional and emotional processes (e.g., Yoo et al., 2018). It remains quite possible that among humans, at least some emotional states arise from patterns of neural reactivity that originate in the very subcortical structures identified in decades of animal research. As described earlier, several functionalist ­accounts suggest that vulnerability to emotion dysregulation occurs when rapid subcortical responses to eliciting events are not modulated effectively by cortical reactivity (e.g., Beauchaine, 2015; Casey & Caudle, 2013; Etkin et al., 2015).

In contrast, functionalist accounts suggest that regulated emotions should be associated with (1) subcortically generated responses to eliciting events that are (2) modulated by cortical responses via (3)  strong cortical–subcortical connectivity (e.g., Beauchaine, Constantino, et al., 2018; Beauchaine, Zisner, et al., 2018). If such is the case, we would expect to find distributed neural activity for any given instance of emotion due to the limited temporal resolution of fMRI. From this perspective, prominent functionalist accounts look much like contructionist ones—both assume that primaryprocess emotions (core affective states) that promote approach and avoidance behaviors are subserved by phylogenetically old structures (primarily subcortical structures), and that cortical networks interact with these subcortical networks to produce what we  consciously experience as emotional states (see Panksepp, 2011). Finally, the locationist basic emotion perspective of functionalism is only a single perspective—albeit a pervasive one in certain areas of research. Other functionalist perspectives focus on the dimensional nature of emotions and various contextual factors that influence our experience of affect (cf. Campos et al., 1994; Haines et al., 2019), similar to constructivist ideas. In sum, although language used to describe functionalist and constructivist theories is quite different, underlying ideas are more similar than some recent discourse in the literature suggests. A final critique concerns the utility of animal ­research for making inferences about human emotion. Because evolutionarily functionalism is a phylogenetic account of emotion, many functionalists assume that neural structures implicated in generating basic emotions among humans should overlap considerably (if not fully) with their vertebrate homologues. As noted earlier under “Variants of Functionalism,” such arguments are most persuasive when applied to subcortical regions that are structurally similar across species. Nevertheless, some constructivists have taken a strong stance against comparative research on emotion, noting that functionalist accounts often fail to specify mechanisms adequately, and that it cannot be assumed that emotions are experienced by animals in the same way as they are by humans (see Barrett, 2017b; LeDoux, 2012). Given (1) overwhelming structural differentiation of the human cortex, (2) the phenomenon of human consciousness, and (3) the role that language plays in Beauchaine and Haines

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shaping human experience of emotion, this critique also holds merit. Here again, however, prominent functionalists have made the same point. Indeed, Jaak Panksepp, who spearheaded functionalist emotion research with rodents, was very clear in describing qualitative differences between animal and human experiences of emotion: “Are the various affects—diverse feelings of positive and negative valences (‘good’ and ‘bad’ feelings in the vernacular)—identical across species? Of course not! Evolution persistently generates abundant differences, but always on top of ­conserved-homologous foundational principles at genetic, neural and primal psychological levels” (Panksepp, 2011, p. 1796). Our contention is that interspecies differences in emotion notwithstanding, basic animal research offers extensive insights into neural substrates and representations of emotion, as discussed in previous sections. Models of dopamine reward prediction error signaling in nonhuman primates provide one example (Schultz, Dayan, & Montague, 1997). These models capture moment-to-moment affective states among humans (Rutledge, Skandali, Dayan, & Dolan, 2014) and extend further to explain individual differences in mood states, including positive affectivity, irritability, and anhedonia (e.g., Eldar, Rutledge, Dolan, & Niv, 2016; Laakso et al., 2003; Zisner & Beauchaine, 2016). With continued development of computational models of emotion generation and regulation (e.g., Etkin et al., 2015), we expect that many more such examples will become realized in the near future.

Conclusions

In this chapter, we introduce functionalist and constructionist theories of emotion, discuss their implications for understanding emotion dysregulation, and consider points of divergence and convergence across perspectives. Although constructionist theories have gained remarkable traction in affect research and offer key insights into the complex individuality of emotion, we argue that functionalist perspectives still hold value, especially when they are not oversimplified. Functionalist perspectives derive from a long tradition of painstaking neuroscience research, including elegant experiments with animals using techniques of very high spatial and temporal resolution. Although such techniques are not available to those who test constructionist theories with humans, fMRI studies yield insights into the roles that widely distributed neural networks play in emotion and emotion dysregulation. 8

We look forward to research from both perspectives in upcoming years, and we hope this chapter provides a framework for readers as they digest the many interesting chapters to follow.

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D.  Cicchetti (Ed.), Developmental psychopathology, Vol. 2: Developmental neuroscience (3rd ed., pp. 523–556). Hoboken, NJ: Wiley. Touroutoglou, A., Lindquist, K. A., Dickerson, B. C., & Barrett, L. F. (2015). Intrinsic connectivity in the human brain does not reveal networks for “basic” emotions. Social Cognitive and Affective Neuroscience, 10, 1257–1265. Tovote, P., Fadok, J. P., & Lüthi, A. (2015). Neuronal circuits for fear and anxiety. Nature Reviews Neuroscience, 16, 317–331. Uğurbil, K., Xu, J., Auerbach, E.  J., Moeller, S., Vu, A.  T., Duarte-Carvajalino, J. M., . . . WU-Minn HCP Consortium. (2013). Pushing spatial and temporal resolution for functional and diffusion MRI in the Human Connectome Project. NeuroImage, 80, 80–104. Wise, R. A. (2004). Dopamine, learning and motivation. Nature Reviews Neuroscience, 5, 483–494.

Wright, L. (1973). Functions. Philosophical Review, 82, 139–168. Yoo, K., Rosenberg, M. D., Hsu, W.-T., Zhang, S., Li, C.-S. R., Scheinost, D., . . . Chun, M.  M. (2018). Connectome-based predictive modeling of attention: Comparing different functional connectivity features and prediction methods across datasets. NeuroImage, 167, 11–22. Zilverstand, A., Parvaz, M.  A., & Goldstein, R.  Z. (2017). Neuroimaging cognitive reappraisal in clinical populations to define neural targets for enhancing emotion regulation. A systematic review. NeuroImage, 151, 105–116. Zisner, A., & Beauchaine, T. P. (2016). Neural substrates of trait impulsivity, anhedonia, and irritability: Mechanisms of heterotypic comorbidity between externalizing disorders and unipolar depression. Development and Psychopathology, 28, 1179–1210.

Beauchaine and Haines

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CH A PT E R

2

Emotions as Regulators of Motivated Behavior

Eric E. Nelson, Michele A. Morningstar, and Whitney I. Mattson

Abstract Emotions, when viewed from the affective neuroscience perspective, arise from organized patterns of brain activity, which function to generate adaptive behavioral responses. Behavior that emerges from emotional brain engagement can almost always be characterized as motivated. Thus, emotion and motivation are highly interdependent concepts, particularly when it comes to behavioral expression. However, emotions do not always generate behavior, and behavioral outcomes of emotional engagement—that is, motivated behavior—are not always adaptive. The intersection and dissociation of emotion and motivation are reviewed in this chapter from an affective neuroscience perspective that is heavily influenced by the work of Jaak Panksepp. Keywords:  affect, neuroscience, psychopathology, bottom-up, translational

This chapter is dedicated to Jaak Panksepp (1943–2017), a mentor, scholar, and provocateur, who brought emotions into the brain and the animal spirit into humanity. Jaak was originally slated to write this chapter but his untimely death prevented completion. We have attempted to conjure his intellectual spirit in this writing.

Introduction

Emotions provide color and meaning to life. Major events such as birth and death are typically bookmarked with intense emotional involvement. Even more mundane daily encounters—such as anger directed at an inconsiderate driver, fear of the neighbor’s dog, happiness at seeing one’s family after work—are common punctuations to daily experiences. On a societal level, explorations of emotional experiences are important components of art, literature, and popular culture. All of these elements demonstrate the important role emotion plays in highlighting salient experiences of life. Although these features of emotion are clearly of existential importance, biological and psychological perspectives often ascribe a more functional role to emotion. Emotions serve to direct behavior, capture

attention, facilitate memory, and guide decision making (MacLeod, Mathews, & Tata, 1986; Cahill & McGaugh, 1998; Rolls, 1999; Panksepp & Biven, 2012; Damasio & Carvalho, 2013). From a mechanistic perspective, the similarity and consistency of emotional expression across individuals and species, common neural activation patterns, and similarities in contextual elicitors for a number of emotional experiences suggest that many emotions are conserved across evolution. Furthermore, these expressions serve important roles in fostering life-preserving behaviors, promoting reproductive success, and communicating with conspecifics (Darwin, 1872/2009; Ekman & Davidson, 1994; Rolls, 1999; Panksepp & Biven, 2012; Damasio & Carvalho, 2013). We view emotion largely from this latter perspective, and as such approach the topic of emotion 13

more from the standpoint of biological utility than experiential or constructivist perspectives (LeDoux, 2012; Barrett, 2016). Core aspects of emotion can be found in fundamental brain response patterns (Hamann, 2012; Panksepp & Biven, 2012). In both human and animal studies, emotional states such as desire and pleasure are associated consistently with activity in mesolimbic brain regions, particularly the ventral striatum and ventral prefrontal cortex (Kuhn & Gallinat, 2012; Berridge & Kringelbach, 2015). Recent neuroimaging research demonstrates that the distinctiveness of different emotional categories is not as clear as once assumed (Hamann, 2012; Lindquist, Wager, Kober, Bliss-Moreau, & Barrett, 2012). However, we believe that on balance, evidence supports core neural constituents for specific emotions. Specifically, these emotions are distinguishable at the neurobiological systems level (which include both anatomical and neurochemical components) and are shared across individuals and species (Berridge & Kringelbach, 2013; Panksepp, Lane, Solms, & Smith, 2017). However, we also agree with perspectives put forth in traditional cognitive neuroscience that the interaction between older brain regions and higher neocortical structures can generate complexities that are uniquely human (Panksepp et al., 2017). Additionally, we agree that emotional distinctions are not likely to emerge at the level of individual structures but rather in interactions of several regions across integrated circuits (Hamann, 2012). In this chapter, we consider the confluence of emotion and motivated behavior from a neuroscientific and biological perspective. Our overriding framework is that, from the standpoint of behavioral expression, behaviors that arise from emotion are motivated behavior (Beauchaine & Zisner, 2017). Behavior that emerges from emotional experience is energized, directed, and focused by the emotional brain systems engaged: for instance, withdrawal from threat is a behavior motivated by fear, the compulsive search for sex or drugs is behavior motivated by pleasure, and prolonged crying after losing a loved one is motivated by grief and sadness. Thus, motivated behavior and emotion are tightly coupled. However, they are not synonymous. There are important ways in which emotion can be dissociated from motivated behavior, and some of these differences may be particularly important for psychological health and psychopathology. We begin by defining key terms and concepts, then outline our theoretical perspective that emo14

tions and motivated behaviors evolved because they serve useful biological purposes. However, evolved biological utility is not always adaptive across ­modern-day contexts, or for all individuals. Next, we briefly discuss methodological approaches and current controversies, and close with important challenges for future research in this area.

Terms and Concepts

Much of the terminology used herein refers to common concepts in psychology and biology. Terms such as motivation and emotion refer to “states” that are generally understood but difficult to clearly define. Though some general aspects of these concepts are shared in the field, important differences in conceptualization can lead to misunderstandings among researchers. Therefore, we offer some level of definitional detail and provide examples for key concepts in the following sections.

Motivated Behavior

Motivated behaviors are focused and goal-directed. Importantly, however, not all “goal directed” behavior can be conceptualized as motivated behavior. Motivated behavior tends to be focused and highly prioritized in terms of neuronal resources (Bradley et al., 2003). Such behaviors typically involve movements that are rapid, are direct, and contain an element of urgency (Beatty, Cranley, Carnaby, & Janelle, 2016). For example, walking across the street is a behavior that is clearly goal oriented, but it does not necessarily meet our definition. In contrast, if this behavior was done rapidly to escape the cold or to retrieve one’s crying toddler, it would be considered motivated. Given that motivated behavior contains an element of urgency, it may be performed in favor of other potential behavioral lures or influences (such as cross-traffic or encounters with friends) in the environment.

Emotion

Emotion is a difficult and often contentious concept to define clearly. Although terms such as fear and anger are commonly used in the scientific literature and offer convenient shorthand, interpretations of such terms vary. Several theories have been proposed to explain the experience of emotion itself, referencing biological influences on physiological arousal (Scherer, 2009), cognitive labeling and contextual interpretation (Schacter & Singer, 1962; Reisenzein, 1983; Scherer, 2009; LeDoux, 2014; Barrett, 2016), and social learning processes (Fogel et al., 1992), among others (Barrett, 2016).

Emotions as Regul ators of Motivated Behavior

Whether such emotional concepts emerge from identical patterns of brain activation across individuals and species, require conscious experience, or are accompanied by universal expression are all important matters of debate (Ekman & Cordaro, 2011; Damasio & Carvalho, 2013; LeDoux, 2014; Barrett, 2016; Panksepp et al., 2017). Working from a neurobiological perspective, we consider emotions to be  coordinated patterns of activity in central and peripheral nervous systems, often accompanied by neuroendocrine activity (Panksepp & Biven, 2012). These coordinated patterns of physiological activity are accompanied by experiential states that, at least among humans, are similar across individuals. Neural substrates of emotion within the central ­nervous system include both subcortical (deep and evolutionarily preserved across species) and neocortical (the outer layer of the brain that is the largest and most elaborated among primates and humans) regions. This activity is typically transitory—lasting seconds to minutes—and is often accompanied by some form of behavioral expression (Ekman & Davidson, 1994). There are three important points to note about our conceptualization of emotion. First, a critical feature is coordinated activity of subcortical and cortical structures. This generates internal states that are both multifaceted and organized. Second, compilations of brain activity associated with specific emotions are recognizable patterns but are not rigid. Just as the color red has many variations that remain “red,” fear has many variations from prototypical that still remain fear. Third, behavioral expression is a common but not necessary feature of emotion, which is particularly important for the subsequent discussion.

Homeostasis

Homeostasis is an important concept in physiology, and one that has historical roots in biological studies of emotion and motivated behavior. Homeostasis is the active process of maintaining a steady state. For example, because maintaining constant levels of osmolarity is critical for life, many systems—both behavioral and physiological—function to maintain constant levels of fluidity and salinity within cells. These processes may translate to human behavior: for example, the imbalance of fluids may lead to a sensation of thirst, which motivates the search for liquids to ingest.

Learning and Memory

Learning refers to processes through which brain activation patterns and/or behavior change as a ­

c­ onsequence of past experience. Memory is stored by novel patterns of brain activity and connections, which can elicit novel experiences that result from that past experience.

Attention

Attention refers to active directing of sensory experience toward a specific domain, area, or sensory expectation.

Development

Development refers to regulated maturational changes in the brain, body, and behavior that occur between birth and adulthood. Notably, although maturational changes in the brain follow a preprogrammed timeline or ontogeny, environmental experience and behavior play a critical role in guiding this process. One mechanistic example of this interactive process is neuronal pruning, where intrinsic signals guide exuberant initial synapse connection and circuit formation, which is then refined by removal of connections that are underutilized (Stiles, 2008).

Social Behavior

Social behavior refers to behavior (both affiliative and/or agonistic) that is targeted toward or coordinated with a conspecific.

Theoretical Perspective Panksepp’s Framework

A basic premise of the Pankseppian model is that emotions are “kinds” in the universe. Emotions arise from distinctive patterns of brain activity, conserved in their basic form across evolution, that function to generate highly motivated and evolutionarily adaptive behaviors. Because of their adaptive value, these organized patterns became embedded in the genome and standard architecture of the  nervous system (Panksepp & Biven, 2012). Emotional kinds are brain systems organized primarily in subcortical structures in highly similar ways across both individuals and species. Panksepp identified seven basic emotional systems that he believed were physiologically distinctive and form the basis of all emotional experience: SEEKING, which generates search and consummatory behavior; RAGE, which provokes aggressive responses against conspecifics; FEAR, which is linked to withdrawal and avoidance behaviors; LUST, which generates mating behavior; CARE, which leads to nurturant behavior; PANIC-GRIEF, which is associated with social separation and loss; and PLAY, which is related to Nelson, Morningstar, and Mat tson

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affiliative exchange and promotes social cohesion and social learning (Panksepp & Biven, 2012). Each of these emerges from distinctive patterns of activity in subcortical brain systems and is present in similar form in most mammals. Some of these patterns are even evident to varying degrees in birds, amphibians, and reptiles (Maclean, 1990; Panksepp, 2011). For example, the SEEKING system is a neural network that ascends from the ventral tegmental area through the lateral hypothalamus and ventral striatum to the prefrontal cortex and consists primarily of dopaminergic fibers. The SEEKING system is associated with emotional states of wanting, excitement, and anticipation, and when engaged elicits motivated searches for elements needed for survival and procreation (Panksepp & Biven, 2012). An important feature of Panksepp’s model is that emotions can be experienced at a variety of “levels.” The most basic and hard-wired is the primary process level. At this level, basic emotional systems can be most clearly differentiated and are most conserved across evolution. Panksepp considered primary process the raw feelings of emotions and argued that many traditional animal-based affective neuroscientists generally adopt this perspective in delineating the neural basis of emotional experience (Cahill &  McGaugh, 1998; Moriceau, Raineki, Holman, Holman, & Sullivan, 2009; Orsini & Maren, 2012; Berridge & Kringelbach, 2013; Vanderschuren & Trezza, 2014; Panksepp et al., 2017). Although many brain-emotion researchers acknowledge a contribution of evolutionarily old ­subcortical systems to emotional experience, many argue that true affective experiences that humans consider “emotion” involve more complex cognitive processing. Such processing includes concepts such as consciousness, linguistic labeling, and sense of self (Rolls, 1999; LeDoux, 2012; Panksepp & Biven, 2012; Damasio & Carvalho, 2013; LeDoux, 2014; Barrett, 2016; Panksepp et al., 2017). Panksepp ­vehemently rejected this definition. However, he did argue that emotions consist of more than just core primary process states of intense activation. Panksepp argued that primary states generated at least two other levels of emotional experience. The secondary process emerges from the primary process as a function of learning. Consistent association of primary emotions with specific stimuli, classes of stimuli, or contexts can elicit partial activation of  primary process emotions, mixtures of primary emotions, and even novel combinations of primary processes with novel brain activation patterns. Finally, Panksepp referred to a tertiary level of emo16

tional experience, which can be construed as a meta-level of the primary process. This is frequently the level at which cognitive neuroscientists deal with emotion. The tertiary level involves engagement of representations of primary process experiences. According to Panksepp, secondary and tertiary process emotions would not exist without initial involvement of basic primary process states, but once they do appear they can function independently of primary process states. Panksepp and others argued that many psychiatric conditions are characterized by maladaptive emotional functioning at the secondary and tertiary process levels, in addition to the primary core levels (Panksepp, 2010; LeDoux & Pine, 2016). This perspective is taken throughout this volume, and is a core aspect of the contemporary emotion dysregulation construct (Beauchaine, 2015). In addition to the three levels of emotional experience, another important aspect of the Pankseppian model is bidirectional communication. By bidirectional communication, Panksepp referred to brain responses that were both bottom-up (in which ­primary process emotions influence behavior and cognitive activity) and top-down (in which tertiary level emotional experience affects primary process activity). Panksepp argued that activity in both directions is stronger in humans than in other mammals because so much more of the human brain is composed of neocortex. This results in a greater dissociation between behavior and primary process emotions in humans. For example, neocortical activity can inhibit and potentiate primary process emotions, and also subvert or redirect (i.e., regulate) behavioral outcomes following primary process engagement. In the present context, this is an important observation because it indicates a greater degree of dissociation between emotional engagement and behavior in humans than other animals. The ability to control behavioral expression and regulate emotional experience has become an important adaptive skill in the modern human environment. Although Panksepp’s model has been very influential, it has not been accepted universally. There are notable detractors and alternate interpretations of the neurobiology of emotion (Rolls, 1999; LeDoux, 2012; Damasio & Carvalho, 2013; Barrett, 2016; Panksepp et al., 2017). Indeed, aspects of the model, such as conscious experiential states of other species (Panksepp et al., 2017), are difficult to incorporate into standard scientific testing. However, because the model clearly incorporates mechanisms, brain function, and evolution into our discussion of

Emotions as Regul ators of Motivated Behavior

emotion more comprehensively than many other biological models, it is an important heuristic to which we appeal for the remainder of this chapter.

Adaptive Nature of Emotions and Motivated Behavior

When viewed from the perspective of biological utility, there are several specific roles for emotion in promoting adaptive responses in fluctuating environments. Motivated behaviors are important intermediaries for many of these functions. We highlight some of these specific functions in this section.

Homeostasis

Because life is only possible within relatively strict parameters, active adaptations to fluctuations— both internal and external to the organism—are built into many aspects of physiology. Some of these operate at cellular and subcellular levels, but organismwide emotional behavior also plays an important role. For example, dehydration inevitably results in a motivated seeking response for water. One of the simplest demonstrations that emotional responses can index biological needs was demonstrated in a series of experiments on temperature hedonics. Cabanac (1971) found that warm water baths of exactly the same temperature were rated as pleasant by those who were hypothermic but unpleasant by those who were hyperthermic, whereas the opposite was found for cool water baths. This simple experiment and many similar studies since demonstrated the functional feature of emotional systems in guiding behavior toward adaptive outcomes (Cabanac, 1979; Ramirez & Cabanac, 2003). Adaptive responding is also evident in experiments conducted by Curt Richter in the 1930s in which he demonstrated that plasma reductions in sodium induced by adrenalectomy induced a highly specific motivated appetite for salt in rats (Richter, 1976). More recent examples include induction of panic attacks among individuals following carbon dioxide buildup in the lungs (Pine et al., 1994), which presumably generates an energized search for consumable air. Panksepp viewed many of these homeostatic emotional responses as primary process behaviors, or ones that do not require learning and are not sculpted by environmental experiences.

Attention, Learning, and Memory

Several more recent studies of reward valuation and satiation in monkeys have focused on roles the amygdala and orbitofrontal cortex play in assigning value to stimuli with homeostatic importance

(Rolls, 1999; Izquierdo & Murray, 2010; Saez, Rigotti, Ostojic, Fusi, & Salzman, 2015; Saez, Saez, Paton, Lau, & Salzman, 2017). Although directly relevant for homeostatic regulation, Panksepp argued that many functions associated with these neural structures relate to secondary process emotions. In contrast, primary process states are linked with environmental stimuli in an associative manner (Panksepp & Biven, 2012). Much of the interindividual variance in emotional tendencies is evidenced at the secondary process level: unique fear responses by different individuals following specific traumatic events are examples of secondary emotions being generated via associational processes. These secondary emotional associations therefore play an important role in many psychiatric conditions (Qin et al., 2014). Because environments vary widely between individuals, the ability to flexibly apply basic emotional activation patterns to unique environmental events is an important adaptive feature of motivational ­systems. Therefore, an important characteristic of emotional and motivational systems is that they capture attention and facilitate memory formation. Affective neuroscience studies indicate that emotion can capture attention by biasing limited neuronal processing of sensory signals toward those associated with the emotional stimulus (Schettino, Keil, Porcu, & Muller, 2016; Hammerschmidt, Sennhenn-Reulen, & Schacht, 2017) via feedback mechanisms from the amygdala and possibly other regions to primary sensory areas (Pourtois, Schettino, & Vuilleumier, 2013). Thus, emotion may amplify relevant sensory responses and filter irrelevant sensory responses via associative regions including the amygdala and striatum. Emotion also acts as a “bottom up” means of facilitating acquisition of new behaviors and applying established response patterns to novel stimuli. Emotional facilitation of learning is a well-established phenomenon that applies to both appetitive and aversive events and affects conditional, instrumental, and social learning (Reisberg & Hertl, 2004). From the standpoint of biological adaptation, both the capturing of attention and learning are a means of employing motivated behavior in a maximally flexible manner across a number of different stimuli and contexts that may vary substantially across ­individuals.

Social Behavior

In social interactions, basic emotions direct motivated behavior in adaptive ways. For animals that live in social groups, emotion modulation plays an Nelson, Morningstar, and Mat tson

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important role in guiding many aspects of behavior (Chang et al., 2013; Feldman, 2017). The PLAY, NURTURE, and LUST systems all involve positive, approach-related emotional motivation toward conspecifics. The RAGE and PANIC emotional ­systems engage motivated behavior in agonistic encounters and in response to separation distress. Although some specific behavioral patterns differ across mammalian species, there is considerable homology in neurochemical and neuroanatomical controls over affective responses related to these motivated behaviors. For example, there is a high degree of concordance in the controls of maternal behavior and sexual desire across mammals (Argiolas & Melis, 2013; Love, 2014; Lonstein, Levy, & Fleming, 2015). For humans and many nonhuman primates, the social world is of critical importance and also incredibly complex. Variables such as dominance, kinship, reciprocity, and alliance formation factor into every encounter (de Waal, 1996; Cheney & Seyfarth, 2007; Dunbar & Shultz, 2017). Emotionally mediated motivated behaviors play important roles in guiding many aspects of social behavior. Among humans, elaborate brain systems involved in perceptual and cognitive processing of social information are interconnected strongly with brain regions related to motivated behavior and emotion (Adolphs, 2009; Chang et al., 2013). This connectivity suggests that emotion and motivation permeate virtually all aspects of social behavior.

Development

The role of motivation in development is often overlooked, but is a vitally important adaptive feature. The stimuli and contexts that induce motivated behavior vary in a systematic fashion across development (Nelson, Lau, & Jarcho, 2014; Nelson, Jarcho, & Guyer, 2016). This is perhaps most evident in changes that take place in social motivation during adolescence. However, regulated changes in affective sensitivity may apply in other domains and during other developmental periods as well (Forbes & Dahl, 2010; Spear, 2011; Spielberg, Olino, Forbes, & Dahl, 2014; Nelson et al., 2016). For example, caretaker separation induces a potent motivated response in early development, but this is greatly attenuated with age (Zhang et al., 2012). Similarly, physical play with peers demonstrates a classic inverted-U response that peaks in late childhood and declines into adolescence and adulthood (Panksepp, Siviy, & Normansell, 1984; Vanderschuren & Trezza, 2014). Emotional responses to peer acceptance follow a similar trajectory, 18

peaking shortly after puberty (Steinberg & Morris, 2001; S. J. Blakemore & Mills, 2014). From the standpoint of biological utility, developmental shifts in patterns of emotional responding may direct motivated behavior toward features or stimulus categories that are most relevant for the specific phase of development the organism is in. Development of the nervous system includes mechanisms such as pruning, which is sensitive to environmental input. Because emotional responding directs attention and learning toward developmentally relevant features in the environment, through motivated behavior it may have potent effects on developmental outcomes.

Maladaptive Emotional Responses

Despite the fact that emotions evolved because of their capacity to generate biologically adaptive motivated behaviors, there are a number of ways in which motivated responses can be nonadaptive. Among humans, one factor that contributes to maladaptive emotional experience and expression is the radical difference between environments that modern humans have constructed and our environments of evolutionary adaptation (Pinker, 2002). This is particularly evident in motivated behaviors associated with the SEEKING emotional system. Obtaining hydration, calories, nutrients, and social contact with group members both is essential for survival and depends on behavioral engagement. Appetitive behavioral responses geared toward seeking such essential features in the environment generate powerful reward responses upon consumption, which evolved in environments where sought-after stimuli such as high-calorie foods were scarce. However, such items are readily available now, making compulsory seeking and overconsumption much more problematic than in our evolutionary history. The most obvious example of this is overconsumption of food, but recent changes in the availability of constant social contact via social media provides another illustration of potentially problematic overconsumption (Primack et al., 2017; Shensa et al., 2017). Furthermore, the ability to cultivate and manufacture neurochemical agents (opiates, cocaine, methamphetamine) that potently activate the seeking/reward system independent of environmental experience has created a huge societal problem in which the functional utility of endogenous reward processes have, for some, been usurped (Panksepp, Herman, Conner, Bishop, & Scott, 1978).

Emotions as Regul ators of Motivated Behavior

A second factor that contributes to maladaptive emotional responding in humans is the extent of bidirectional communication between “top down” regulation and executive functions and “bottom up” primary emotional systems. Humans have developed a strong capacity to willfully regulate behavioral expression and override emotional/motivational tendencies by engaging top-down inhibitory mechanisms (Buhle et al., 2014). This is often an adaptive response in certain environments/contexts and can serve as an important means of managing excessive emotional expression (Buhle et al., 2014). However, the ability to dissociate motivated behavioral expression from the experience of emotion can eventuate in dysfunctional brain response patterns in the long term. Chronic stress associated with the repeated overriding of natural motivated behavior tendencies predicts mood and anxiety disorders, and compensatory drug and alcohol use (Mah, Szabuniewicz, & Fiocco, 2016; Nusslock & Miller, 2016; Sharp, 2017). Thus, there are both benefits and potential drawbacks to using executive functions to override motivational tendencies. The maladaptive aspect of strong bilateral connections between primary emotions and executive functions is also evident in reverse—hyperactivation of basic emotional systems can generate long-term alterations in executive functions such as attention and memory, thereby reinforcing dysregulated emotional expression (MacLeod et al., 1986; Rapee & Heimberg, 1997). Another way in which emotional/motivational activation and behavioral responses can differ meaningfully is in the duration of experience. Whereas salient stimuli and events often occur transiently in the environment, emotional responses can linger from seconds to hours and generate even more long-lasting emotional states (Heller et al., 2009, 2013, 2015). The persistence of emotional responding in the absence of behavioral action can result in  long-term detrimental functioning (Teicher, Samson, Anderson, & Ohashi, 2016), although emotion may be amenable to conscious regulatory intervention in the absence of behavioral output (Denny, Inhoff, Zerubavel, Davachi, & Ochsner, 2015). Finally, an important aspect of the relationship between emotion and behavior in humans is its equifinality: there is not always a unique behavioral expression for each experienced emotion. For instance, fear may generate drug seeking, compulsive hand-washing, or freezing. Anger may elicit agonistic physical encounters, but it may also trigger

e­ xcessive alcohol consumption or behavioral shutdown that accompanies depression (Sharp, 2017). Although emotions evolved because of the ­adaptive value of motivated behavioral responses, resulting responses are not always optimal. This is particularly relevant for modern humans, in part due to the highly flexible nature of human behavior and executive functions, and in part the result of the  relatively artificial environment humans have created for themselves.

Current Methods and Findings

There are a number of ways to assess the effects of emotions on brain and behavior. In human-based studies standard approaches include functional neuroimaging, electroencephalography, and magnetoencephalography. More recent approaches include functional near-infrared spectroscopy (Hoshi, 2016), in which the blood oxygen level–dependent (BOLD) signal is assessed through light sensors placed on the skull, and transcranial electrical stimulation, in which current is delivered to the brain from scalp electrodes (Yavari, Jamil, Mosayebi Samani, Vidor, & Nitsche, 2018). The typical approach in all of these methods is to have participants engage in a task (usually on a computer) that manipulates emotionality with either standardized (e.g., expressive faces or monetary gains/losses) or customized probes (Salimpoor, Zald, Zatorre, Dagher, & McIntosh, 2015; Abrams et al., 2016). Although most neuroimaging approaches still rely on regression and parametric statistical comparisons, a number of novel approaches have emerged recently. These include graph theory, causal modeling, independent component analysis, and machine learning approaches such as multivoxel pattern analysis (Bullmore & Sporns, 2009; Marinazzo, Liao, Chen, & Stramaglia, 2011; Saarimaki et al., 2016; Xie, Douglas, Wu, Brody, & Anderson, 2017). A key problem with these approaches is that they impose strong limits on the degree to which behavior can be expressed. Brain measures typically require data acquisition in a highly controlled environment in which participants are not allowed to move. However, some recent approaches have incorporated measures of subtle differences in behavioral responses expressed inside the scanning environment. These differences may provide important insights into the relation between emotion and behavior. For example, researchers have begun to investigate brain differences in generating approach or withdrawal responses with joysticks (Radke et al., Nelson, Morningstar, and Mat tson

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2015, 2017), by directing attention toward or away from a threatening stimulus (Price et al., 2014; Ceravolo, Fruhholz, & Grandjean, 2016), and via grip strength elicited by aversive emotional stimuli (R. L. Blakemore, Rieger, & Vuilleumier, 2016). In some ways, animal studies are much more flexible for inducing emotional states and measuring brain and behavioral responses. In addition to standard pharmacological, electrophysiological, and targeted lesion methods, more recent advances include genetic knockouts (Crawley et al., 2007; Araragi & Lesch, 2013) and in vivo regulation of brain function with optogenetics (Deng, Xiao, & Wang, 2016). Human analogs of some of these approaches include assessment of behavior among individuals following naturally occurring brain lesions (Damasio & Carvalho, 2013), or in rare cases invasive measurement of brain function with intracranial recordings or deep brain stimulation, performed for clinical reasons (Pourtois, Spinelli, Seeck, & Vuilleumier, 2010). A full accounting of findings from research on the intersection between emotion and motivated behavior in the brain is beyond the scope of this chapter, but general observations can be made based on existing findings. First, engagement of emotional and motivational states in humans and animals ­typically involves networks of brain regions including both subcortical and neocortical structures (Hamann, 2012; Kragel, Knodt, Hariri, & LaBar, 2016; Nummenmaa & Saarimaki, 2017). Sub(neo) cortical regions are more closely associated with what is typically considered to be the motivational (i.e., behavioral responsiveness) component of emotion, even though associated behavior is restricted in most human-based studies. The most prominent structures associated with motivation and emotion include the insular and anterior cingulate cortices (which are evolutionarily older cortical regions that lie underneath the neocortex), the amygdala, striatum, and midbrain regions such as the ventral tegmental area and periaqueductal gray. Aberrant ­activity in these regions is often associated with emotion/motivation-based psychopathologies— such as anxiety, depression, addiction, and borderline personality (Drevets, Savitz, & Trimble, 2008; Filbey et al., 2016; Lichenstein, Verstynen, & Forbes, 2016; Rigoli, Ewbank, Dalgleish, & Calder, 2016; Gola et al., 2017; Hein & Monk, 2017; Lago, Davis, Grillon, & Ernst, 2017; Sharp, 2017). Second, there is a tremendous amount of variability in patterns of brain network activity engaged across studies. However, several recent meta-analyses 20

using pattern analysis techniques have detected emotion-specific patterns in neuroimaging studies (Hamann, 2012; Kragel et al., 2016; Saarimaki et al., 2016; Nummenmaa & Saarimaki, 2017—but see also Lindquist et al., 2012). Although emotion-specific differences in brain activation are detectable in human neuroimaging studies, these differences tend to be evident only at the network level and are not reflected in one-to-one mapping of brain regions with specific emotions. Although more specific associations between individual brain regions or neurochemical systems is more evident in animal-based emotion research than in human research, it is clear that emotions are better characterized with networks than by activity within unique and specific neural structures (Floresco, 2015; Douglass et al., 2017).

Ongoing Controversies

There continues to be a great deal of debate among investigators who study the neurobiology of affect regarding what exactly constitutes an emotion, to what extent different emotions represent “kinds” in nature, how similar emotional experience is across individuals, and how much homology exists in emotional experience across species. Panksepp’s affective neuroscience model details unique signatures for seven basic emotional systems, each strongly tied to a range of motivated behaviors (Panksepp & Biven, 2012). In this model, different emotional systems are unique “kinds” in the brain: they are fundamentally shared across a number of species, typically contain specific behavioral outputs, and do not require high-level cognitive activity to be experienced. Although the details vary somewhat across investigators, this basic concept is largely shared by many researchers who adopt a traditional behavioral neuroscience and animal-based approach to emotion (Darwin, 1872/2009; Maclean, 1990; Ekman & Davidson, 1994; Berridge & Kringelbach, 2013; Perusini & Fanselow, 2015; Panksepp et al., 2017). On the other end of the spectrum are researchers who argue against the notion that emotions are unique kinds in the brain, or that common experiences can be assumed across individuals and particularly across species (LeDoux, 2014; Barrett, 2016). Investigators who adhere to this perspective believe that emotion is largely a high-level cognitive interpretation that emerges from a variety of inputs, including but not limited to physiological response patterns. A variety of intermediary concepts lie along this continuum, including dimensional approaches in which emotion is construed as elaborations along valence and arousal dimensions (Zachar & Ellis,

Emotions as Regul ators of Motivated Behavior

2012; Russell, 1980), and more truly hybrid approaches in which basic kinds exist but also interact with cognitive schemas and interpretations (Izard, 2007; Damasio & Carvalho, 2013). Some of the controversy in this area relates to differences in semantics or fundamental inconsistencies in definitions and terminology (Izard, 2007). However, real conceptual differences do exist and have important effects on interpretation of the intersection of motivation and emotion. Although we certainly lean toward the Pankseppian model of basic kinds of emotion that are directly tied to ­motivation and behavior, this is by no means a universally accepted approach (Barrett, 2016). Indeed, many of the initial neuroimaging studies that have attempted to differentiate emotional experiences based on functional brain activation have not been supportive of many of the specific models. Although functional neuroimaging has revealed emotional activation of both cortical and subcortical structures (Pauli et al., 2015; R. L. Blakemore et al., 2016), there tends to be a great deal of overlap between different emotions. Furthermore, contrary to Panksepp’s model, imaging studies of emotions often do not demonstrate strong activation patterns within brain stem regions (Hamann, 2012; Lindquist et al., 2012). However, recent studies using more sophisticated approaches to inducing and measuring emotion have reported unique patterns of activation by emotional category, largely contained within the cortex (Hamann, 2012; Saarimaki et al., 2016). An important caveat of all magnetic resonance imaging research is that, although it is the state of the art for noninvasively measuring neuronal activity, it imposes several methodological constraints on the elicitation of emotion. Neural “events” must be generated while participants lie perfectly still inside a huge metal tube, and because the BOLD signal is relatively weak, experiences must be repeated many times over the course of a single experimental ­session. The emotional experiences induced under these circumstances are likely only a very weak resemblance to those generated by the naturalistic and highly salient situations typically associated with emotion. The experiences measured in the scanner may be closer to what Panksepp has referred to as secondary or tertiary emotional experiences derived from the more potent subcortically based primary emotions (Panksepp & Biven, 2012; Panksepp et al., 2017). Controversies such as this have plagued emotion research since its inception (Izard, 2007; Barrett, 2016) and continue to be a barrier for truly integrative neuroscience research. However, some

advances are being made, and careful use of definition and terminology may further facilitate progress (Izard, 2007; Panksepp et al., 2017). Another issue that has plagued emotion research—particularly at the intersection of animal and human studies—is the role that conscious experience plays in emotional experience and expression (LeDoux, 2014; Panksepp et al., 2017). There is no clear consensus on whether consciousness is necessary for emotion, whether conscious experiences are comparable enough across species to make generalizations, or even what the basic elements of consciousness are. These are issues at the forefront of neuroscience and philosophy—at present we have no clear empirical resolution.

Theoretical Synthesis and Future Directions

Our perspective is that emotion has strong and pervasive effects on behavioral expression, and that any behavior that results from emotional induction is motivated behavior by definition. When compared to behavior that does not result from emotion induction, motivated behavior is pervasive in that it involves a coordinated effort of cognitive, motor, neuroendocrine, and other physiological systems all  focused on a single stimulus, event, or goal. Behaviors that emerge from motivational states are usually directed toward adaptive outcomes, although this is not always the case. Motivated behavior is usually a highly effective means of obtaining desired goals, but can be particularly difficult to manage or suppress when those goals are not adaptive for the individual. Indeed, emotion induction does not always generate behavior. The ability of an individual to manage behavioral expression in spite of emotional engagement, or the ability to manage the degree of emotional engagement elicited by a stimulus (emotion regulation), is an important skill that can also result in complex neuronal and psychological states that may be linked to psychopathology. There are several important directions for future research to address. First, from a practical standpoint, it is important to gain a better understanding of how to manage motivated behavior that is ­maladaptive for the individual. Two classic examples of maladaptive motivated behavior are compulsive drug use that occurs in addiction and excessive avoidance behaviors that occur in anxiety. Probably the most effective way of altering such maladaptive motivation is through a combination of medication and/or top-down regulation to reduce the intensity of the motivational state and encourage behavior that is inconsistent with the maladaptive motivation. Nelson, Morningstar, and Mat tson

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Modern therapeutic approaches for humans, such as cognitive-behavioral therapy, use these methods to promote effective management of maladaptive motivated behaviors. For these examples, therapeutic goals might include reducing drug seeking or stopping avoidance of feared stimuli. These changes in behavior are extremely challenging to achieve, but repeated changes to the association between emotion and behavior can improve the likelihood of adaptive outcomes. Although effective methods have been developed on these fronts, continued efforts to refine and improve these approaches are needed. Second, at a more holistic level, motivational states can often be parsed into a pre-exposure period and a consummatory period. This is most commonly done for rewarding states (Berridge & Kringelbach, 2013; Luijten, Schellekens, Kuhn, Machielse, & Sescousse, 2017), but also may apply to aversive situations where exposure to a potentially aversive condition is anticipated before it is experienced (Grupe & Nitschke, 2013; Jarcho et al., 2015). In both appetitive and aversive conditions, the most powerful effects of motivation appear in the period preceding exposure. This is also where the maladaptive behavioral aspects of motivated behavior are most prevalent. The anticipatory and consummatory components of a motivated experience are fundamentally different from each other at a neurobiological level, but they are also completely interdependent. An important challenge for motivational research will be to gain a better understanding of how consummatory and anticipatory components of a motivated experience are regulated and how they vary across individuals. Finally, a fundamental question for motivation research is how novel motivational states become acquired. Although some stimuli (e.g., required nutrients, potential predators) are inherently motivational, for others the motivational states are acquired through learning (e.g., money) or development (e.g., sexual desire). Moreover, the motivational pull of stimuli that were once highly appealing can fade over time. Understanding how these motivational states change at the level of the brain and fluctuate with experience is an important feature of motivational learning that will be crucial to characterize further.

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Saez, R.  A., Saez, A., Paton, J.  J., Lau, B., & Salzman, C.  D. (2017). Distinct roles for the amygdala and orbitofrontal cortex in representing the relative amount of expected reward. Neuron, 95, 70–77. Salimpoor, V.  N., Zald, D.  H., Zatorre, R.  J., Dagher, A., & McIntosh, A.  R. (2015). Predictions and the brain: How musical sounds become rewarding. Trends in Cognitive Sciences, 19, 86–91. Schacter, S., & Singer, J.  E. (1962). Cognitive, social, and physiological determinants of emotional state. Psychological Review, 69, 379–399. Scherer, K.  R. (2009). Emotions are emergent processes: They require a dynamic computational architecture. Philosophical Transactions of the Royal Society of London Series B Biological Sciences, 364, 3459–3474. Schettino, A., Keil, A., Porcu, E., & Muller, M.  M. (2016). Shedding light on emotional perception: Interaction of brightness and semantic content in extrastriate visual cortex. Neuroimage, 133, 341–353. Sharp, B. (2017). Basolateral amygdala and stress-induced hyperexcitability affect motivated behaviors and addiction. Translational Psychiatry, 7, 1–13. Shensa, A., Escobar-Viera, C. G., Sidani, J. E., Bowman, N. D., Marshal, M. P., & Primack, B. A. (2017). Problematic social media use and depressive symptoms among U.S.  young adults: A nationally-representative study. Social Science and Medicine, 182, 150–157. Spear, L. P. (2011). Rewards, aversions and affect in adolescence: Emerging convergences across laboratory animal and human data. Developmental Cognitive Neuroscience, 1, 392–400. Spielberg, J.  M., Olino, T.  M., Forbes, E.  E., & Dahl, R.  E. (2014). Exciting fear in adolescence: Does pubertal

development alter threat processing? Developmental Cognitive Neuroscience, 8, 86–95. Steinberg, L., & Morris, A. S. (2001). Adolescent development. Annual Review of Psychology, 52, 83–110. Stiles, J. (2008). The fundamentals of brain development: integrating nature and nurture. Cambridge, MA: Harvard University Press. Teicher, M. H., Samson, J. A., Anderson, C. M., & Ohashi, K. (2016). The effects of childhood maltreatment on brain structure, function and connectivity. Nature Reviews Neuroscience, 17, 652–666. Vanderschuren, L. J., & Trezza, V. (2014). What the laboratory rat has taught us about social play behavior: Role in behavioral development and neural mechanisms. Current Topics in Behavioral Neuroscience, 16, 189–212. Xie, J., Douglas, P.  K., Wu, Y.  N., Brody, A.  L., & Anderson, A.  E. (2017). Decoding the encoding of functional brain networks: An fMRI classification comparison of non-negative matrix factorization (NMF), independent component analysis (ICA), and sparse coding algorithms. Journal of Neuroscientific Methods, 282, 81–94. Yavari, F., Jamil, A., Mosayebi Samani, M., Vidor, L.  P., & Nitsche, M.  A. (2018). Basic and functional effects of transcranial electrical stimulation (tES): An introduction. Neuroscience and Biobehavioral Reviews, 85, 81–92. Zachar, P., & Ellis, R. (2012). Categorical versus dimensional models of affect: A seminar on the theories of Panksepp and Russell. Philadelphia, PA: John Benjamins. Zhang, B., Suarez-Jimenez, B., Hathaway, A., Waters, C., .  .  .  Nelson, E.  E. (2012). Vaughan, K., Noble, P.  L.,  Developmental changes of rhesus monkeys in response to separation from the mother. Developmental Psychobiology, 54, 798–807.

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CH A PTE R

3

Emotions as Regulators of Social Behavior

Lane Beckes and Weston Layne Edwards

Abstract This chapter provides an overview and novel theoretical synthesis of the literature on how and why emotions regulate social behaviors. It outlines how theorists in this domain have long disagreed on how to conceptualize the role of evolution and innateness in terms of functions of emotions. Parsing theoretical and empirical traditions by level of domain specificity, the chapter argues for a domain-relevant approach to emotion, which is more congruent with current understanding of neurodevelopment and gene–environment interactions. It examines emotion as emergent information about the motivational landscape and offers an alternative metaphorical approach to thinking about evolution as it relates to socioemotional life based on river formation and change. Keywords: emotion, social behavior, evolution, domain specific, construction, basic emotions, attachment, emotion theory, emotion regulation, social baseline theory

Emotions, even though their hallmark is the internal state of the individual—the viscera, the gut—are above all social phenomena. They are the basis of social interaction, they are the products of social interaction, their origins, and their currency. —Zajonc (1998, pp. 619–620)

Introduction

For humans, emotion emerges in social more than nonsocial contexts (Reis, Collins, & Berscheid, 2000). Social connection is so critical that people are substantially more likely to die if they are socially isolated (Holt-Lunstad, Smith, & Layton, 2010). Therefore, the manner in which emotions shape social behavior, and vice versa, is of paramount importance to the study of emotion and its (dys)regulation. There is wide disagreement regarding the domain specificity of emotions and their functions. Couched within this greater dispute are various interpretations of the mechanisms and nature of emotions. Resolving this debate is central to the goal of understanding how emotions influence social behavior. All perspectives might benefit from separating motivation and emotion more explicitly and defin-

ing emotion as emergent information about the motivational landscape. Moreover, our motivations and emotions are tied directly with our ability to predict and adapt to the environment through learning and allostasis. Most of our basic needs are regulated through complex, highly variable systems that develop with domain-relevant functions evolved to promote survival, growth, and reproduction. Thinking of the brain as possessing many ­domain-specific mechanisms is incongruent with evidence, and arguing that all mechanisms are therefore domain general is oversimplifying. Here we introduce a new metaphor for these developmental processes, adding potentially useful language and heuristics for understanding how human sociality and emotionality are intimately linked. This metaphor uses the language of geology and fluvial systems to organize thinking about issues 27

related to nature and nurture, arguing that these processes behave more like the development of river systems than the en vogue computer processing metaphor can capture. This heuristic view of socialemotional development predicts specific types of hypotheses linking emotion and social behavior through developmental processes. Finally, we argue that humans are adapted to a primarily social ecological niche that drives organization of neural systems in a manner that is domain relevant. In this chapter, we start with a discussion of the theoretical divisions regarding the domain specificity of emotion processes. Indeed, emotional influences on social behavior can only be understood by taking a particular theoretical perspective. Because of disagreements about most basic elements of what defines an emotion, the theoretical convictions of any given theorist are critical in interpreting evidence and decoding relations between emotion and social behavior.

Theoretical Perspectives on the Nature and Mechanisms of Emotion and Its Functions

Quarrels among emotion theorists emerged long ago in philosophical debates between seminal philosophers such as Plato and Aristotle (see Scherer, 2000). The greatest dividing feature of these approaches is currently the degree of domain specificity of emotions. Domain-specific mechanisms of emotion are most strongly associated with basic emotion theories, which argue for natural kind types of emotion (c.f. Barrett, 2006). Domainspecific approaches assert that mental mechanisms, often conceptualized as mental modules (see Fodor, 1983), act to guide responses to recurring adaptive problems in human evolutionary history (Cosmides & Tooby, 1994). These mechanisms are frequently thought to act independently and automatically with the appropriate sensory or motivational input, leading to preprogrammed or prepared behavioral repertoires. For example, I may feel jealousy because I perceive a threat to my relationship from an interloper, and that emotional state produces behavioral tendencies such as mate guarding or intrasexual competition (Arnocky, Ribout, Mirza, & Knack, 2014). Thus, emotion in such models predicts clear, stereotyped elements within the emotion–social behavior relationship. Despite the heuristic benefits, it is now widely believed that theories arguing for ­domain-specific mechanisms in most areas of psychology are largely untenable. Lisa Feldman Barrett (2017) has taken early ideas about emotion as a psychologically constructed 28

phenomenon and developed a domain-general view of emotion. That is, the brain does not produce emotions via domain-specific neurobiological mechanisms, but rather via domain-general core systems (Barrett, 2014). The first is core affect, which is composed of both valence (determination of whether something is positive or negative as it relates to the organism) and some degree of peripheral nervous system arousal (Lindquist, 2013). The second ingredient, conceptualization, is a process by which bodily sensations (core affect) and cues from outside of the body are made meaningful, transforming ­ambiguous core affect into a disambiguated discrete emotion. Critically, this view of emotion argues that each instance of an emotion may be highly variable, but that through degeneracy the brain categorizes the context and physiological state of the organism as a specific emotion (Barrett, 2017). Degeneracy refers to the fact that many different neurons will feed into one, suggesting that many different patterns of activity can result in the same categorization. Thus, many possible patterns across perceptual, motor, and cognitive systems might produce any given emotion. Conceptualization also functions primarily to assist allostasis (stability through change) or the maintenance of homeostatic systems through the procurement of resources, such as food from the environment, and functions in a predictive rather than reactive manner. We contend that Barrett’s (2017) view of emotion is likely more correct on several fronts than most current emotion theories. Yet, there are some potential problems with this view of emotion, raising important questions. Is everything domain general, and are there gradients of domain generality and specificity? We all agree that certain outcomes are necessary for survival, growth, and reproduction, but where do they fit in the domain-general model of emotion? Behaviorists made a mistake ­decades ago when they assumed all learning was simply a function of our most basic needs (e.g., food, water, etc.). Harlow (1958) disproved this position, showing that infant monkeys preferred a soft stimulus to a food stimulus. Given that we need various resources—hence the need for allostasis— and that those resources are rewarding and preferred in a noncontingent manner, how does an entirely domain-general system self-organize in such an adaptive manner? Furthermore, how does sexual behavior develop given that it is not a physiological need? If the conceptual separation of the brain and body is a mistake (c.f., Barrett, 2017), then how

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does one contend with relatively domain-specific endocrine functions such as the angiotensin system and its regulation of fluid balance in a domaingeneral account? Yes, variability in even these most basic systems is both high and critically important in understanding human emotion and motivation. Yet does the domain-general argument risk ignoring that measures of dispersion are most useful in conjunction with measures of central tendency?

Evolution and Innateness

Best estimates put average associations between ­genetic variants and complex behavioral phenotypes a little under 50% (Polderman et al., 2015). Despite clear links between genes and behavior, developmental neuroscience approaches reveal clear problems with the modularity hypothesis and domainspecific theories more generally (Buller & Hardcastle, 2000; Karmiloff-Smith, 2015; Manuck & McCaffery, 2014). Genetic studies indicate that any given behavioral phenotype is associated with numerous ­individual genes that only explain a small portion of variance in phenotypes (Manuck & McCaffery, 2014). Additionally, it is likely that very rare genotypes, gene–environment interactions, epigenetics (processes that modulate and modify gene expression), and epistasis (gene–gene interaction) play important roles in how genetic information gets translated into phenotypic presentations. This complexity challenges the notion that massive modularity is the norm in brain development, but does not fully dispel the position. In combination with evidence regarding brain development, however, the case for  modularity falls apart rapidly. Unfortunately, Barrett’s (2017) argument that degeneracy can explain all such findings is also wanting. Why does degeneracy seem to favor some types of outcomes more than others? Why does brain organization have tremendous normative properties if everything is simply degeneracy and all mechanisms are domain general? This position is close to correct, but missing critical subtlety as it relates to neurodevelopment. Karmiloff-Smith (2006,  2009,  2015) takes the neuroconstructivist position that biases in development lead to brain organization that is domain relevant, but not domain specific. This position is wholly in line with decades of research on neurodevelopment and argues that complex interactions at multiple levels of the system (i.e., genes, epigenetics, molecular and cellular processes, network-level processes, and environmental inputs) all interact and contribute to specialization and generalization of various systems across the brain. Over time certain

circuits or functions become domain dominant, but not domain specific. In this sense the human brain is composed of many domain-relevant features, but few domain-specific features. The process of human brain development is largely competitive, through which various circuits and neurons compete to respond to environmental signals (Karmiloff-Smith, 1992, 1998). During this competition, synapses and neurons are pruned from the system and specialization begins to emerge in circuits that have appropriate connections, neurotransmitters, receptors, and other features that make a given circuit, region, or network effective at responding to a specific type of stimulus. A good example of this process comes from the face processing literature, which provides strong evidence for modularity within the fusiform face area (FFA; Kanwisher & Yovel, 2006). Kadosh and colleagues (Kadosh & Johnson, 2007; Kadosh, Johnson, Dick, Kadosh, & Blakemore, 2013) note that this processing specialization only develops over time, and the FFA only gradually becomes specialized during the first decade of life. Neuroconstructivism and domain-relevant thinking are wholly consistent with evidence regarding brain development, neural specialization, and innate input into human behavior. It is an elegant solution to the nature–nurture debate, and is consistent with current understanding of gene–environment interactions. We argue that any emotion theory that is to  stand the test of time will require this type of domain-relevant thinking.

Adaptive Basins as an Alternative Model and Metaphor

The massive modularity hypothesis conceptualizes the human mind as a set of diverse computational processes. This conceptualization comes from the computer processing metaphor of the mind and brain (Von Neumann, 1958/2012), and has been the dominant framework for decades in psychology. A  recent surge in radical embodiment theories pushes back against the metaphor, arguing for a more dynamic and organic perspective (Chemero, 2009; Barrett, 2011, Wilson & Golonka, 2013). Here we present an alternative metaphor that better captures these dynamic and naturalistic features as related to innateness versus construction. For this, we suggest the metaphor of a river. River form is highly variable as a function of a number of features of the environment and various inputs into the river system (Charlton, 2007). River formation occurs because a region has more water Beckes and Edwards

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than the soil can absorb. Over time, large rivers form with many tributaries acting as sources for the river. The form of the river is always changing, subject to morphological systems, such as those related to hill slopes and geological and biological features of  the channel, and cascading systems, which refer to  the flow of water through the morphological system. These two systems interact to further shape a river. For a river, many morphological systems are substantially formed before a river matures. Thus, many aspects of the morphological system create structure upon which the river will form. Once ­sufficient water flow develops, cascades begin to further carve the morphological system, cutting a deeper river basin. Conceptualizing innate processes this way, evolved features of the mind start out as morphological features defining the boundary conditions for developing domain-relevant basins. Normative development requires appropriate inputs into the system for competitive processes to unfold. Some inputs, like tributaries, have their own morphological features, some more rigid than others. The most rigid of these tributary processes include highly instinctive or reflexive features of behavior. Classic examples of such rigid morphologies include fightor-flight responses, which Ledoux (2012) refers to as survival functions; reflexes, such as the grasping, suckling, or rooting reflexes (Schott & Rossor, 2003); and homeostatic functions, like the angiotensin systems in thirst (Fitzsimons, 1998). These more rigid systems are exclusively evolved to solve adaptive problems related to homeostatic, reproductive, and survival functions. Critically, abnormal development may occur if cascade processes are missing. If too little energy is entering the system, it will fail to mature properly. If tributary sources that are typical for development don’t receive enough input themselves, then an entire source of cascade energy is missing for larger downstream systems. For example, babies often show attentional biases to faces (e.g., Frank, Vul, & Johnson, 2009), but infants classified as high risk for autism spectrum disorder (ASD) attend less to faces and other social stimuli than other infants (Chawarska, Macari, & Shic, 2013). Perturbations in tributaries to developing socialemotional systems may affect later development in highly significant ways through impoverished cascades. How does this model inform emotion and social behavior, and what is emotion from this perspective? 30

Applying the Adaptive Basins Model

The adaptive basins model is congruent with Barrett’s (2017) view of what “a brain is for” in that the primary function of the brain is to predict an organism’s best actions given physiological needs. Allostasis, in conjunction with incentive processes (c.f., Berridge, 2007), determines current motivational demands. Emotions organize motivation by providing feedback about success, failure, opportunity, risk, and problems with current predictions of outcomes. Thus, emotion acts as information about motivation and goal pursuit.

Emotion as Information

Researchers increasingly agree that emotions function to guide behavior, but not all researchers agree on the manner by which this occurs. Baumeister, Vohs, De Wall, and Zhang (2007) argue for a dualprocess model of affect in which emotions function primarily as feedback that can be used to anticipate future experiences and promote more functional behavior. In this way emotion is a learning signal. This position is originally associated with Schwarz and Clore’s (1983; Clore & Huntsinger, 2007; Clore & Storbeck, 2006; Clore, Wyer, Dienes, Gasper, Gohm, & Isbell, 2001) affect-as-information hypothesis. According to this theory, ­affective phenomena, including emotions, provide critical information regarding motivation. For example, sad music makes short hills look steeper (Riener, Stefanucci, Proffitt, & Clore, 2003). And specific emotion inductions modulate decision making in meaningful ways (Lerner, Small, & Lowenstein, 2004; Mackie, Devos, & Smith, 2000; Schnall, Haidt, Clore, & Jordan, 2008). The affect-as-information hypothesis is highly congruent with neuroscience models of emotion such as Damasio’s (1994) somatic marker hypothesis. This theory suggests that judgment and decision making are influenced by somatic information, including heart rate, muscle movements, facial expressions, endocrine activity, respiration, and feedback through the brainstem and thalamus into the somatosensory cortices, insula, and cingulate cortex. This information is integrated with information regarding motivation, long-term memory, and motor planning in the ventromedial prefrontal cortex (vmPFC) to guide decision making. The vmPFC creates somatic states through its top-down connections with various structures such as the amygdala, allowing for simulations of possible scenarios, further aiding decision making. Numerous studies

Emotions as Regul ators of Social Behavior

i­ndicate that damage to the vmPFC or any of the regions that provide affective information to the vmPFC impairs judgment in a variety of tasks (Bechara & Damasio, 2005). Van Kleef (2009) takes the affect-as-information theory one step further by arguing that emotion not only regulates individual behavior but also regulates the behavior of others in close proximity. The emotion-as-social-information model outlines how perception of another person’s emotional expressions is perceived, processed, and taken into consideration during behavioral decision making. This insight is critical for understanding human behavior as it places emotions directly into a social context, which we argue is the primary ecological niche of the human species.

Human Social Development, Attachment, and Emotion

Attachment theory (Bowlby, 1969/1983) is not primarily a theory of emotion, but shares common features, and serves as an excellent starting point when thinking about domain relevance and the adaptive basins conceptualization in emotional and motivational processes. Bowlby’s (1969/1983) seminal theory describes processes by which infants maintain physical proximity to caregivers. He hypothesized that an innate behavioral system evolved to keep vulnerable infants in close contact with attachment figures (a primary caregiver with whom the infant has a special bond). This system activates under stress, such as sickness, injury, and fear, or when the child is separated from the attachment figure. The primary result of activating the attachment system is an emotional state called separation distress, which motivates proximity-seeking behaviors such as crying, following the attachment figure, and clinging to the attachment figure. Once proximity is achieved, the child begins to experience felt security, an emotional state associated with a sense of calm and comfort, at which point the child begins exploratory activity again. Two elements of attachment theory are important for our purposes. First, the theory clearly describes how social emotions drive social behaviors. Second, Bowlby proposes an innate behavioral system, consistent with domain-relevant as opposed to domain-specific theories. He argued that while certain elements of this system are hard-wired, the behavior system is shaped by experience. For example, clinging, suckling, crying, and other attachment behaviors are instinctive, but only through

experience do these instincts become a goal-corrected behavioral system. From our perspective one can ­reimagine this system as an adaptive basin whereby environmental feedback shapes these instincts in the service of a particular set of attachment-related goals. Progress toward or away from desired end states is signaled through emotion. In this light emotion is an emergent domain-relevant phenomenon that acts as a learning signal to organize behavioral and motivational components of the developing system. Myron Hofer’s (1984,  2006) research on social relationships as hidden regulators illustrates the adaptive-basins concept in action. Social isolation in rat pups produces changes in adrenal endocrine activity, heart rate, respiration, ultrasonic vocalizations (homologous to crying), and over long periods decreases in growth hormone release (Hofer, 1984, Kuhn, Pauk, & Schanberg, 1990; Rosenfeld, Wetmore, & Levine, 1992; Shapiro & Salas, 1970; Stanton, Wallstrom, & Levine, 1987). Sensory stimulation mimicking the softness, warmth, and other features of the rat’s littermates and dam decreases these homeostatic responses. Sensory features of social contact serve as early tributary systems for ­developing social attachments. Several homeostatic functions are regulated through social contact, including thermoregulation, energy regulation, and stress regulation (see Beckes, Ijzerman, & Tops, 2015). These functions are in turn supported by highly rigid tributary behavioral systems akin to instincts, such as crying, huddling, clinging, and suckling. Over time these tributary functions provide cascade energy into a developing attachment basin, which serves to regulate attachment-related motivations and promotes behaviors that support normative development. Emotion acts to monitor and update attachment needs and motivations, providing feedback regarding whether and how attachmentrelated goals are being met. Separation distress often functions to indicate a need for change, whereas felt security often serves as information that attachment needs are being met. The degree to which these systems receive appropriate environmental input is critical to the development of the system. In rat pups, high-archedback nursing and licking and grooming behavior increases the expression of hippocampal glucocorticoid receptors (Liu et al., 1997), leading to less anxious behavior in adulthood. This example shows how cascading inputs, licking and grooming, modify developing morphological systems, hippocampal Beckes and Edwards

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glucocorticoid receptor densities, in determining emotional endophenotypes. These differences feed back to future emotional episodes, creating a dynamic recursive feedback process that further shapes social-emotional development. Severe social deprivation produces unusual emotional behavior in children, such as disorganized attachment, in which the child shows indiscriminate friendliness and poor organization of attachment behaviors (Bakermans-Kranenburg et al., 2011), which is frequently associated with extended time in institutional care. The adaptive-basins model would argue that a lack of appropriate cascade system activity—in the form of stable relationship interactions with a small number of caregivers—­ interacting with morphological features such as variations in the dopamine receptor D4 gene (Wazana et al., 2015) is likely to lead to disorganization in the system. And greater risk accumulates over developmental time as systems go through pruning (Bakermans-Kranenburg et al., 2011). Extensions of Bowlby’s ideas suggest that attachment dynamics also emerge in adult relationships, whether sexual mates (e.g., Carter, Grippo, Pournajafi-Nazarloo, Ruscio, & Porges, 2008; Hazan & Diamond, 2000; Hazan & Shaver, 1987) or a broader set of relationship partners (Beckes & Coan, 2011; Taylor, 2006). One of the key controversies surrounding such extensions is whether any of these relationships are truly attachment relationships and, if so, how to verify their status as attachment relationships (Fraley & Shaver, 2000). From the adaptive-basins perspective, this question is moot as there is no reason to imagine a categorical delineation of attachment status. Early features of the developing brain may promote what is commonly considered a true attachment, such as interactions in norepinephrine release and hippocampalamygdala development (see Sullivan, 2003), but differences are more likely emergent properties of  sensitive periods and the unique nature of the ­caregiver–child relationship. Patterns that develop early begin to form our general social behavior but are subject to change with more input into the various tributaries and basins that feed into the more general social basin. Relationships continue to serve as regulators of homeostasis, but the manner in which they do so varies by relationship, age of the individual, and other factors. The broadest sense in which social relationships regulate homeostasis is described by social baseline theory (Beckes & Coan, 2011). 32

Social Baseline Theory and Our Social-Ecological Niche

Social baseline theory (SBT; Beckes & Coan, 2011, 2012; Coan, Brown, & Beckes, 2014, Coan & Maresh, 2014; Coan & Sbarra, 2015) argues that humans are adapted primarily for life in social groups, and that placement within a network of interdependent others is core to health and ­ well-being. This theory posits two ways in which social proximity is a baseline human condition. First, humans are not adapted to any particular terrestrial environment, achieving this flexibility ­ primarily through social cooperation (Cohen & Janicki-Deverts, 2009; Holt-Lunstad et al., 2010). Second, physical contact with loved ones reduces anxiety, stress responses, and threat reactivity (e.g., Brown, Beckes, Allen, & Coan, 2017; Coan, Schaefer, & Davidson, 2006; Coan et al., 2017), but researchers have not yet identified a clear neural mechanism (e.g., vmPFC, ventral striatum) for this effect. Beckes and Coan argue that there is a mistaken assumption that aloneness is a baseline condition for humans. For example, when looking at data in which social contact is manipulated, we tend to assume that being alone is the natural state. Alternatively, if one assumes that togetherness is the natural state for humans, a hypothesis for which there is now overwhelming evidence (see Berscheid, 2003; Brewer & Caporael, 1990; Keltner, Haidt, & Shiota, 2006), then being alone is a potentially anxiety-provoking situation for many people. SBT posits that through two primary mechanisms, risk distribution and load sharing, humans are able to budget energy expenditure on various tasks in more efficient ways, including anticipatory anxiety and vigilance for threat. Risk distribution refers to various processes through which vigilance and individual risk get distributed, such as when any animal forms a group, there are more eyes and ears to detect predators (Krebs, Davies, & Parr, 1993). Load sharing refers to the fact that humans also form social networks characterized by interdependence and joint attention and goals, and can rely on each other for aid and support more broadly. The net gain from social contact and proximity is a reduction of risk and effort for the individual, altering perception and energy budgeting. Evidence that energetic considerations alter the perceived difficulty of tasks is mounting (E.  B.  Gross & Proffitt, 2013; Proffitt, 2006). For example, wearing a heavy backpack increases the perceived slope of a hill, making the task appear more challenging

Emotions as Regul ators of Social Behavior

(Proffitt, Stefanucci, Banton, & Epstein, 2003; Stefanucci, Proffitt, Banton, & Epstein, 2005). In a similar manner, close proximity to reliable and predictable relationship partners modifies our perceptions and predictions regarding resource use, effort, and risk. If one assumes that affect and emotion act as information about motivational features of the situation, then the potential for risk distribution and load sharing is included in the perception of the individual’s affective state, and outcome predictions. In a bottom-up manner, this information changes the perceived difficulty of the environment, anticipatory anxiety, and the individual’s energy budget. As a thought experiment, one can think of many times in which one had to walk in an unfamiliar place late at night. This is potentially risky, and it is normative for people to experience increased vigilance and anxiety. However, with a group, one automatically perceives the potential for load sharing and risk distribution, reducing anxiety. Thus, information about our social resources is embedded in the information that emerges as an emotional experience. The manner in which any individual perceives those social resources is influenced by the development of cascading and morphological systems (e.g., Gonzalez, Beckes, Chango, Allen, & Coan, 2015; Maresh, Beckes, & Coan, 2013). A more challenging history in cascade systems, such as unreliable relationship partners or poor neighborhood quality, and certain morphological features, such as decreased hippocampal glucocorticoid receptor expression or allele variations of the oxytocin receptor gene rs237915 (Gonzalez, Puglia, Morris, & Connelly, 2017), interact to change the likelihood that one will perceive risk and the potential benefit of social resources. These cascading and morphological features of the individual and his or her environment serve as features that form domain-relevant social systems (see Figure 3.1). From this organization, individuals develop differences in their perception of risk, energy, and social resources, modifying how affective information emerges and guides behavior. In a very real sense, domain relevance is an important feature of these systems, emotion serves as information about domain-relevant situations, and the type of emotion conceptualization one experiences is linked through learning to domains in a probabilistic, not causal, manner. For example, lust is more likely to emerge due to activity in a domainrelevant sex basin than not.

Given the premise that humans are primarily adapted to a social ecology rather than a particular physical ecology, it stands to reason that much of human emotional content will be social in nature. Moreover, to the extent that domain-relevant systems exist in the human mind, many of those systems will be involved in managing the social environment. Traditional models of evolved emotional mechanisms cannot capture the complexity of such systems, which are not modular. Rather, thinking of emotion as emergent information about motivation that is largely rooted in the dynamic development of domain-relevant, distributed systems likely captures this subtlety and complexity.

Synthesis

From these frameworks, we propose a definition of emotion as emergent information about the motivational landscape. We think this conclusion serves two purposes. First, it fits data indicating that emotions are not natural kinds, and are therefore emergent phenomena, but are often domain relevant and have functions derived from both evolution and sociocultural processes. Second, defining emotion as information about motivational concerns helps clarify that emotion is a dynamically recursive process that is composed of many components, but its  main function is to provide information about ­motivationally relevant aspects of life, such as homeostatic function. A good starting place is to follow J.  J.  Gross’s (2015) definition of emotion. He notes that affect is an overarching term for emotion-related elements. Affect is a state of valuation and includes moods, emotions, and stress. Notably, he distinguishes moods and stress from emotion, indicating that moods are kind of like the climate, long term and less variable, whereas emotions are brief perturbances or variations like weather. Moreover, one may have activation of the autonomic nervous system without an emotion, but such activation is often considered a necessary component of emotion. Emotions from this view are loosely coupled changes in emotional components (subjective experience, physiological arousal, and behavior). For such a phenomenon to be nonemergent, basic, or latent, there would need to be a central mechanism that triggered these loosely coupled responses. Yet, there is little evidence for such central mechanisms, and emotions are better characterized as emergent processes than as superordinate basic mechanisms. Moreover, given that stress without an Beckes and Edwards

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Figure 3.1  A conceptual model of the adaptive-basins approach to thinking about domain-relevant motivational systems. The model shows how certain tributary systems related to instinctive behaviors such as suckling, crying, and clinging feed into basins that regulate homeostasis in energy, thermal, and stress systems through social interaction organizing a broader domain-relevant basin of attachment behavior. That basin then feeds into more general social behaviors that develop over time. Notably, the attachment basin is not the sole feed into the general social basin. Moreover, one failing of this metaphor is that in neural systems information flow is multidirectional, unlike water systems. While imperfect, the metaphor provides heuristic language that clarifies certain features of domain-relevant systems, such as tributaries, morphological systems (represented as elevation and slope in this figure), cascading systems, and the general idea of a flexible but clearly structured basin upon which neural systems become domain relevant. Map is modified and based on map data from Google ©2017.

emotion is widely recognized by emotion researchers, it is clearly the case that arousal of the sympathetic nervous system can occur before an emotion. If this is true, it creates a conundrum for defining emotion. Arousal typically occurs in response to a change in the motivational landscape. It frequently entails the detection of something surprising or of  motivational relevance such as an opportunity or  risk, which leads to the body’s preparation for action. If this is not an emotion, then more components are needed for emotion to occur. We think a separation between the mobilization and perceptual phases of emotions clarifies this distinction. If we consider the mobilization element as more closely related to changes in the motivational landscape and emotion as part of the perception of that change, then it might be better to clarify that motivation is more associated with the mobilization phase and emotion is more associated with the perceptual phase. Further, this definition comports well with the idea that emotion serves as information. Notably, we are not arguing that this separation is always clear in practice, or that one can truly separate these two constructs. Both constructs are conceptual ideas that have correlations with reality 34

but are not clearly definable only from the external world. In a sense, emotional episodes can be thought of as having mobilizing and perceptual features that dynamically and recursively feed back to each other. Emotion as a concept is better characterized as the perceptual part of the cycle and motivation as the mobilization part of the cycle. In addition, we argue that many human emotions will be social in nature. As information, those emotions feed into our ability to form opinions and judgments or to decide on actions, and ultimately are critical in determining many of our social behaviors. Many of those emotions are domain relevant because they tap into flexible behavioral systems that act as adaptive basins for human behavior. Those basins include attachment behavior—including separation distress and felt security—and sexual behavior, for which lust and passionate love may provide information about our goals, whether we can achieve them, and, if so, how.

Future Directions

We recommend several directions for future research. First, researchers should pay close attention to developmental processes. Any understanding of

Emotions as Regul ators of Social Behavior

emotion from our perspective needs to attend to how emotional responses affect and are affected by social context in development. Further, understanding how emotion becomes dysregulated must be sensitive to developmental processes and attuned to whether the social and emotional environment is supplying stimulation. Second, researchers who study human development should attempt to determine the degree to which likely innate behaviors, such as fight or flight, crying, suckling, following, and so forth, provide a foundation for later behavior. In particular, studying the neurodevelopment of other systems as they relate to survival circuits and simple social and emotional behaviors may illuminate how psychological adaptations emerge within development and guide the formation of better models of social and affective disorders. In addition, efforts should be made to make clear connections between emotion theory and theories of motivation and social behavior. Many such theories have amassed tremendous evidence that is directly relevant to emotion theory. Third, social context must be considered when understanding emotion and its (dys)regulation. Social connection is foundational for human life, and inattention to social networks will lead to a failure to fully understand any given individual’s emotional and psychological situation. Often emotion dysregulation is not simply an intrapersonal phenomenon, but an interpersonal problem, and it should be recognized as such.

Conclusion

The emotion field has been rife with dichotomous thinking about the nature of emotion. While debates have frequently been fruitful, accurate models will need to contend with both variability between people and normative tendencies across the species. We suggest that thinking of emotion as emergent information about motivation helps to bridge this divide. It clearly defines emotion as the perceptual side of a motivated process, frequently related to domain-relevant behavioral systems that emerge through complex developmental processes, many of which are likely social in nature. Those domainrelevant processes are not innate per se, but are the result of gene–environment interactions across development. Some processes, usually very simple ones, may be relatively more rigid and modular than others, but most will be large, dynamic systems that work in a domain-relevant rather than a ­domain-specific manner.

References

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CH A PT E R

4

Cognition and Emotion in Emotion Dysregulation

Kateri McRae and Paree Zarolia

Abstract Emotion dysregulation often implies that high levels of (frequently negative) emotion are simply not regulated by cognition. However, emotion dysregulation can refer to positive feedback loops that are created and maintained both by a lack of effective cognitive processes that regulate emotion, and by strong effects of emotion on cognition. This chapter first discusses the effect of cognition on emotion, with an emphasis on the effects of attention and cognitive control (e.g., emotion regulation) processes upon emotions. Then, it discusses the effect of emotion on cognition, with an emphasis on attention, memory, decision making, and cognitive control. Finally, it examines the implications of both types of emotion–cognition interactions by discussing the positive-feedback cycles that can produce dysregulated emotion. Keywords: cognition, emotion, cognitive control, emotion regulation, decision making, memory, attention

Introduction

Emotion dysregulation is often defined by patterns of emotional experience and expression that interfere with adaptive, goal-directed behavior (Thompson, 1994). By this definition, emotion dysregulation is observed in many forms of psychopathology (see Beauchaine, 2015). Despite a common focus on the emotional outcome (the magnitude or amount of emotion present), emotion dysregulation more specifically implicates not merely that emotions are at unwanted levels, but that the high levels of emotion have not been effectively diminished or kept in check by emotion regulation. It is common to think of regulation as brakes or  checks on a system, or the ability to reduce unwanted emotions. However, regulation can refer to any change to the frequency, rate, or extent of another process. More important, regulation is often the product of complex, interdependent systems, in which the same processes both are regulated and perform regulation. In the case of emotion regulation, emotional neural systems and responses are often thought of as

being regulated, while cognitive neural systems are thought of as performing regulation (Buhle et al., 2013). However, to understand dysregulated emotion, it is more appropriate to think of emotion and cognition as parts of a complex system, having bidirectional influences on one another (Todd, Cunningham, Anderson, & Thompson, 2012). The goal of the present chapter is to review literature outlining interactions between emotion and several types of cognition: attention, memory, decision making, and cognitive control. In light of the complex, bidirectional relationships between emotion and cognition, we divide this chapter into two parts: how cognition affects emotion and how emotion affects cognition. We will focus our review on dysregulation of negative emotion because of its clinical relevance; however, many of the effects of emotion on cognition have been attributed to emotional arousal more generally, which characterizes both negative and positive emotion. We will discuss key differences between negative and positive emotion when relevant. 39

How Cognition Affects Emotion

There is a large literature focused on the effects of cognition on emotion. Specifically, one prolific research tradition defines emotion regulation as a variety of processes by which someone can influence his or her own emotional trajectory in terms of the onset, offset, magnitude, duration, or quality of an emotional response (Gross, 2015; Gross & Thompson, 2007). This research was born of the coping literature, but in its current instantiation, it largely references the process model of emotion regulation, which outlines five points during emotion generation in which regulation processes might occur (Gross, 1998b). These include situation selection (avoidance or engagement with situations that have potential to cause unwanted emotion), situation modification (utilizing agency to change properties of situations that may cause unwanted emotion), attentional modification (directing attention toward and away from aspects of situations that may cause unwanted emotion), cognitive change (changing the cognitions, evaluations, and appraisals that lead to emotion), and expressive suppression (directly influencing emotional responses, including bodily responses and facial expressions of emotion). Attentional modification and cognitive change are most relevant to this review because they refer to well-specified cognitive processes. It is possible to use attentional modulation and cognitive change to either diminish or enhance emotional responding.

How Attention Influences Emotion How attention can diminish emotion

Most theories of emotion imply that some attentional resources must be devoted to an emotional event to elicit a response (Gross, 1998b). If emotion is a downstream consequence of attention, it follows naturally that changes in attention can have strong effects on subsequent emotion. More recently, researchers have examined whether emotional stimuli require focused attention (or even conscious awareness; Jessen & Grossmann, 2015; Pessoa, 2005) to be processed preferentially in the brain compared to neutral stimuli (Anderson, Christoff, Panitz, De Rosa, & Gabrieli, 2003). These studies use laboratory manipulations that severely limit or prevent conscious processing of emotional stimuli, and examine whether a stimulus still elicits an emotional (> neutral) brain and/or bodily response. Using amygdala activation and physiological responses as indices of emotion, there is considerable evidence that directed attention is not necessary for the brain and body to respond to certain stimuli (Anderson 40

et al., 2003; Habel et al., 2007; Winston, O’Doherty, & Dolan, 2003), and some scholars argue that conscious awareness is not required, much less focused attention (Jessen & Grossmann, 2015; Morris & Dolan, 2001; Whalen et al., 2004; but see Pessoa, 2005). Another set of studies explores a closely related question: whether restricting attentional resources affects the magnitude of brain and bodily emotional responses. These studies examine restricted attention by presenting emotional and nonemotional stimuli together, with instructions to respond to nonemotional stimuli, or by presenting a dual task along with emotional stimuli. These researchers find that emotional responding diminishes as concurrent attentional demands increase (Pessoa, Padmala, & Morland, 2005; Silvert et al., 2007). In other words, emotional responses to stimuli can be diminished significantly under more impoverished attentional conditions (Habel et al., 2007). So, while complete attention does not seem to be required for the production of brain and/or bodily emotional responses, these responses do decrease when attentional resources are more limited. Examining distraction as an explicit emotion regulation strategy is one way that emotion researchers have examined influences of attention on emotion (Gross, 1998b; Salovey, Mayer, Goldman, Turvey, & Palfai, 1995). In an everyday context, distraction from a negative event, such as a breakup of a romantic relationship, might involve a purposefully overstuffed social calendar; an increased focus on other priorities, such as work; or engagement with unrelated narratives, such as those in books or films. In a laboratory context, distraction from negative stimuli can be implemented either broadly, with an instruction such as “think of something else so that you do not feel as negative,” or quite specifically, by giving the participant a secondary task to complete while processing emotional stimuli. Both types of distraction are effective, in that when implemented, they reduce self-reported negative emotion (Joorman, Siemer, & Gotlib, 2007; Sheppes & Meiran, 2008), along with other brain and bodily emotional responses (Kanske, Heissler, Schönfelder, Bongers, & Wessa, 2011; McRae et al., 2010; Shafir, Schwartz, Blechert, & Sheppes, 2015). One benefit of distraction is that it can be used even when there is limited time for emotion regulation (Sheppes & Gross, 2011; Sheppes & Meiran, 2008). In addition, it can be used to effectively reduce emotional responding even in response to relatively intense emotional stimuli. However, there is some evidence that

Cognition and Emotion in Emotion Dysregul ation

the effectiveness of distraction is not long-lasting, in that it does not generalize beyond the encounter during which distraction is used (Thiruchselvam, Blechert, Sheppes, Rydstrom, & Gross, 2011). When distraction is used as an emotion regulation strategy and the same stimulus is encountered at a later time, the emotional response unfolds as though no emotion regulation has ever taken place. Finally, it is possible that emotion regulation occurs when one changes attentional biases, albeit with some amount of practice. A relatively recent literature has examined the role of attention training paradigms on biases toward (and away from) emotional stimuli. These training paradigms emerged from a broader literature on attention and findings that some anxiety disorders are associated with vigilance for threatening stimuli and negative emotion (Yiend, 2010). In these studies, attention biases become a target of an intervention in which focus is directed away from negative emotion by directing participants to engage in hundreds of attention modifying dot-probe trials (Amir, Beard, Burns, & Bomyea, 2009; Heeren, Reese, McNally, & Philippot, 2012). Several studies have demonstrated that by the end of the training session, attention can be directed away from emotional stimuli, which produces concomitant changes in anxiety symptoms (Bar-Haim, 2010).

How attention can enhance emotion

Despite an emphasis in the literature on the use of attention to diminish affective responding, attention can also be used to enhance emotion. Directing attention toward an emotional cue increases cognitive processing of that stimulus (Pessoa et al., 2005; Silvert et al., 2007). Rumination refers to the ­process of redirecting attention to causes and consequences of a negative emotional response (Koster, De Lissnyder, Derakshan, & De Raedt, 2011), which often has the effect of prolonging or maintaining the emotion (Young & Nolen-Hoeksema, 2001). Individual differences in rumination are associated with depressive symptoms and negative affect (Nolen-Hoeksema, 2000).

How Cognitive Change Affects Emotion: Cognitive Reappraisal How reappraisal diminishes emotion

Cognitive reappraisal is perhaps the most commonly studied form of emotion regulation. Consistent with appraisal theory, the modal model of emotion suggests that a person must evaluate an event as consistent or inconsistent with his or her

goals, consciously or not, before an emotional response can occur (Gross, 1998a). Reappraisal, then, refers to any attempts to change an interpretation or evaluation of an emotional stimulus or an event in order to change its meaning and, therefore, the emotion that follows (Giuliani & Gross, 2009). For example, a public case of mistaken identity might be later reappraised as a comedic goldmine for future stories, transforming embarrassment into delight. Studies of individual differences indicate that frequent use of reappraisal to regulate emotions is largely adaptive, in that it is associated with lower depressive symptoms and negative emotion, and higher positive emotion (Aldao, NolenHoeksema, & Schweizer, 2010; Gross & John, 2003; Potthoff et al., 2016). Increases in use of reappraisal are associated with better treatment ­ response and recovery from psychopathology ­ (McRae, Rekshan, Williams, Cooper, & Gross, 2014; Smits, Julian, Rosenfield, & Powers, 2012). Frequency of reappraisal use is less heritable than either neuroticism, a personality variable characterized by negative emotion, or suppression, another emotion regulation strategy (McRae et al., 2017). By contrast, reappraisal is relatively more influenced by environmental variables not shared with siblings, which could reflect educational, social, and career contexts, as well as efforts to change emotion regulation over the course of psychotherapy. In a therapeutic context, reappraisal is often referred to as “cognitive reframing” and is a cornerstone of cognitive and cognitive-behavioral therapies (Beck & Dozois, 2011). Over the past several decades, researchers have found that cognitive reappraisal, when deployed in  the laboratory, can reduce negative emotional ­responding, including self-reported negative affect (Gross, 1998a), expression of negative emotion (Goldin, McRae, Ramel, & Gross, 2008; Jackson, Malmstadt, Larson, & Davidson, 2000; Ray, McRae, Ochsner, & Gross, 2010; Webb, Miles, & Sheeran, 2012), psychophysiological responding (McRae, Ciesielski, & Gross, 2012), and recruitment of amygdala resources (Ochsner, Bunge, Gross, & Gabrieli, 2002), which likely modulates some of these bodily changes. Furthermore, changes due to reappraisal are relatively long-lasting. Upon re-exposure to a stimulus that you’ve previously reappraised, there is some savings of that previous effort, reflected in lower levels of emotional responding (Denny, Inhoff, Zerubavel, Davachi, & Ochsner, 2015; Thiruchselvam, Blechert, Sheppes, Rydstrom, & Gross, 2011). Therefore, M c Rae and Zarolia

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r­eappraisal is viewed as a relatively effective emotion regulation strategy.

How reappraisal enhances emotion

Although reappraisal is often used to diminish negative emotional responding, reappraisal can also be used to increase positive or negative emotion (Giuliani, McRae, & Gross, 2008; Kim & Hamann, 2007). For example, amygdala activation can be both enhanced and decreased by reappraisal (Ochsner et al., 2004), with both directions of reappraisal recruiting largely overlapping regions in prefrontal and parietal cortices. In addition, reappraisal can be used to create negative emotion in response to a neutral stimulus, as evidenced by enhanced amygdala activation to neutral stimuli when paired with self-generated (Ochsner et al., 2009) or other-generated (Otto et al., 2014) negative narratives. Finally, reappraisal can be used to enhance positive emotion, even in response to a negative stimulus (McRae, Ciesielski, & Gross, 2012; Shiota & Levenson, 2012; Waugh et al., 2016).

Limitations of reappraisal

Although reappraisal is generally adaptive, there are several situations in which reappraisal is not as effective or even unhelpful. Studies have shown that reappraisal may be less preferred, less effective (Shafir et al., 2015), and more effortful (Silvers, Weber, Wager, & Ochsner, 2015) when used on intense negative emotions, and it is not as effective when the time available to reappraise is severely limited (e.g., in the context of reappraising a negative picture, < 4 seconds; Sheppes & Meiran, 2008). Reappraisal may also be counterproductive when the situation leading to the emotional response is controllable—the most adaptive response to negative job performance feedback from a trusted supervisor, for example, may be a change in behavior rather than a change in thinking (Troy, Shallcross, & Mauss, 2013). Furthermore, there is preliminary evidence that the way an emotion is generated might affect how it is regulated. Specifically, emotions generated perceptually, by encounters with negative stimuli, may be less effectively regulated by cognitive reappraisal than emotions generated cognitively, by imagined or invented current or future situations (McRae, Misra, Prasad, Pereira, & Gross, 2011; Nelson, Fitzgerald, Klumpp, Shankman, & Phan, 2015). Cognitive reappraisal recruits medial and lateral prefrontal cortices, including regions that are thought to subserve cognitive control more broadly (Ochsner, Silvers, & Buhle, 2012; Morawetz, Bode, 42

Derntl, & Heekeren, 2017). Neuroimaging evidence has indicated that reappraisal recruits largely overlapping regions with other forms of cognitive control, such as distraction, although most regions that support both reappraisal and distraction are recruited by reappraisal to a greater degree (McRae et al., 2010). Individual differences in reappraisal are also related to cognitive control and executive functioning (Lantrip, Isquith, Koven, Welsh, & Roth, 2016; McRae, Jacobs, Ray, John, & Gross, 2012; Schmeichel, Volokhov, & Demaree, 2008). In addition, reappraisal and several other forms of cognitive control improve throughout adolescence, which coincides with prefrontal cortex development (McRae, Gross, et al., 2012; Silvers et al., 2012). Studies of transcranial magnetic stimulation indicate that reappraisal use can be facilitated by stimulation of the dorsolateral prefrontal cortex (Feeser, Prehn, Kazzer, Mungee, & Bajbouj, 2014; Lantrip, Gunning, Flashman, Roth, & Holtzheimer, 2017). Therefore, it is likely that reappraisal will be less effective in individuals whose prefrontal cortex is not fully developed, degenerating with age, or compromised by injury or disease. Similarly, there are other conditions that lead to suboptimal prefrontal engagement, potentially mediated by poor prefrontal functioning, such as high stress (Troy, Wilhelm, Shallcross, & Mauss, 2010) or poor sleep quality (Mauss, Troy, & LeBourgeois, 2012). Taken together, these findings reveal that many types of cognition can enhance, diminish, and change emotional responses in a variety of contexts. Exerting cognitive control over emotional responding can be a powerful tool, leading to emotional lives that are more in line with our emotional goals. However, the influence of cognition on emotion is not unidirectional, and emotion can also affect cognitive control, including what we attend to, remember, and decide.

How Emotion Affects Cognition Effects of Emotion on Attention and Memory How emotion enhances attention and memory

Emotions have a powerful effect on attention. More specifically, the presence of emotional stimuli is known to capture attention, sustain attention, and make it harder to disengage with the stimulus (Öhman, Flykt, & Esteves, 2001), especially if it  signals threat (Koster, Crombez, Van Damme, Verschuere, & De Houwer, 2004). For example, a snake might be more quickly identified than a rock when hiking, or the sound of a baby’s cry might

Cognition and Emotion in Emotion Dysregul ation

seem to cut through a noisy house more than the sound of household electronics. The preference for emotion in attentional capture is supported by findings that emotional items (especially faces) are more quickly identified in a search task (Vuilleumier, 2005) and that emotional, especially negative, stimuli draw early eye movements, perhaps to facilitate collection of relevant information (Huang, Chang, & Chen, 2011). Emotional stimuli can even continue to capture attention when they are no longer present (Hajcak & Olvet, 2008), as evidenced by poorer performance following emotional stimuli in an attentional blink task (Ogawa & Suzuki, 2004). Finally, emotional stimuli are more difficult to disengage from than neutral stimuli, meaning they sustain our attention longer. Unrelated, or background emotional states can also influence attention. Attentional biases toward emotional information are strengthened when in a congruent mood state, such as faster reaction times to positive words among individuals reporting high levels of state positive emotion (Strauss & Allen, 2006). Another way in which emotion affects cognition is through memory. Emotion-enhanced memory refers to the preferential treatment of emotion memories in encoding and storage (Phelps, 2004). Previously neutral stimuli that are paired with highly emotional events are remembered better, and can later elicit emotional responses consistent with the emotional stimulus, a variant of classical conditioning known as fear conditioning. In addition, highly arousing stimuli (whether positive or negative) are remembered better than neutral stimuli (Buchanan, Etzel, Adolphs, & Tranel, 2006; Cahill & McGaugh, 1995). This enhanced memory usually reflects increased memory for central (rather than peripheral) aspects of emotional events or scenes (Kensinger, Garoff-Eaton, & Schacter, 2007; Mather et al., 2006), especially in the case of negative information (Touryan, Marian, & Shimamura, 2007). In that sense, emotionally enhanced memory might be considered a consequence of enhanced (and narrowed) attention for emotional stimuli rather than neutral stimuli. Fear conditioning is thought to be mediated by amygdala circuits (LaBar, Gatenby, Gore, LeDoux, & Phelps, 1998), as patients with amygdala damage are unable to encode or retrieve new associations with fearful stimuli. Emotionally enhanced memories are thought to arise from arousal-based amygdala influences on the hippocampus (Cahill et al., 1996; Hamann, 2001), making the amygdala a central brain region in the effect of emotion on memory.

Mood-congruent memory, which refers to i­ncreased availability of memories that are consistent with a current mood state, is another way in which emotion influences memory (Bower, 1981; Riskind, 1989). People feeling sad, for example, can bring to mind more sad events from their past than people feeling neutral or happy (Berntsen, 2002; Mayer, McCormick, & Strong, 1995). Positive states also make positively-valenced items more ­accessible for memory retrieval (Isen, Shalker, Clark, & Karp, 1978).

How emotion diminishes attention and memory

The effects of emotion on attention and memory may not always be desirable. For example, negative mood states result in a narrowed attentional focus, where the central object of our attention receives prioritized processing compared with peripheral ­details (Berntsen, 2002; Fenske & Eastwood, 2003; Fredrickson & Branigan, 2005). (This narrowing quality of attention may be specific to highly arousing negative emotions (Gable & Harmon-Jones, 2010; Kensinger et al., 2007; Mather et al., 2006; Talarico, Berntsen, & Rubin, 2009).) By the same token, mood-congruent memory occurs at the expense of mood-incongruent memory, which can lead to decreased accuracy in mood mismatch conditions. This may be especially true among those with a history of major depression (Joormann & Siemer, 2004). Mood-incongruent memory, although requiring more effort, may be one avenue for emotion regulation—for example, the effortful recall of positive memories can counteract a negative emotional state (Rusting & DeHart, 2000). Finally, highly arousing events tend to result in an increase in subjective confidence in memories, resulting in the perception of highly accurate “flashbulb” memories. However, it is likely that these ­effects are more likely to reflect perception than reality. Studies demonstrate that the effect of emotion on subjective confidence is seen despite marked inconsistency in memories over time (Talarico & Rubin, 2003). One important ramification of these relationships between emotion, attention and memory is that together, they can create self-sustaining feedback loops. For example, if the central object of attention contains negative information, it is likely to capture and sustain attention, this sustained attention may cause an increase in negative mood, leading to mood-congruent memory. This increased accessibility of negative memories may prolong ­ M c Rae and Zarolia

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negative mood even more, which may bias attention toward incoming negative information, further sustaining negative mood. Therefore, emotional effects on attention and memory can compound, contributing to a “downward spiral” of emotion and cognition (Garland et al., 2010).

Effects of Emotions on Decision Making How emotions hurt decision making

It is a common assumption that decisions should be made from a dispassionate, purely reason-based perspective. Research findings are often consistent with this assumption, with studies demonstrating that emotion can bias our choices away from optimization. One such theory in decision-science prospect theory revolutionized economics by demonstrating that emotional responses to choices—defined broadly as rapid positive or negative responses—can cause systematic biases in decision making. These biases may lead individuals to make decisions that may not be in their best interest (Kahneman & Tversky, 1979; Tversky & Kahneman, 1991). For example, loss aversion refers to people’s tendency to overweight a loss as compared to the same monetary gain; loss aversion produces a pattern of decision making that suggests that individuals do not simply assess the overall objective value of each option (which is equal for losses and gains) but also the emotional value, or a summary value based on how one feels toward the option. Subsequent research has extended early findings, demonstrating that emotional influences in decision making often lead to suboptimal choices as measured by financial gain in investment paradigms. For example, when participants are asked to make an investment under conditions of risk, they often underinvest even though investing regardless of the risk would ultimately leave them with more money (Shiv, Loewenstein, Bechara, Damasio, & Damasio, 2005). In these tasks, emotional biasing (i.e., an emotional influence on decision making) is thought to prevent risk taking even when that risk would lead to better outcomes. Healthy participants and patients with cognitive deficits (but not emotional deficits) did not make the most optimal choice (i.e., always investing), though patients with emotional deficits consistently chose to invest, leading to more optimal decision making (Shiv et al., 2005). This pattern indicates that the ability to “rationally” choose the riskier option is improved by a lack of emotion, suggesting that emotional responding, rather than cognitive processing, leads to loss (and risk) aversion. 44

Prospect theory describes biases as primarily detrimental and tangential to decision making. The risk-as-feeling hypothesis extends prospect theory by stating that feelings are a source of information as central to decision making as other cognition, but maintains that these feelings are often detrimental to optimal decision making. In fact, when emotional responses and other cognitions diverge, feelings often dictate behavioral outcomes (Loewenstein, Weber, Hsee, & Welch, 2001). The risk-as-feeling model posits that responses to risky situations are a composite of both direct emotional influences and cognitive evaluations. The theory states that direct—or anticipatory—emotion is generated from the stimulus itself, a direct reaction to a feature of one’s decision (e.g., a reaction to the color, price, or size of something), and is independent of cognitive evaluations (Floresco & Ghods-Sharifi, 2007; Slovic, Finucane, Peters, & MacGregor, 2004; Slovic & Peters, 2006; Song & Schwarz, 2009). Furthermore, subsequent research reveals that direct neural projections from sensory regions can bypass cognitive regions to influence behavior directly (Öngür & Price, 2000; Zald, 2003). Thus, emotional responding appears to be central to decision making, rather than a supplemental influence on cognitive inferences.

How emotions help decision making

While some research appears to support colloquial beliefs that emotions impair decision making, some research demonstrates that this might not be the case. The affect-as-information hypothesis (Schwarz & Clore, 1983) is one such line of research. It states that individuals use emotion, or affect more broadly, experienced at the moment of the decision as a reaction to what is being judged, to guide behavior. This phenomenon has been illustrated in myriad domains as disparate as consumer products (Adaval, 2013) to life satisfaction (Schwarz & Clore, 1983). In the latter example, participants reported greater life satisfaction on sunny days compared to rainy, demonstrating that they inferred that their “sunny” disposition was due to their overall satisfaction with life (Schwarz & Clore, 1983). The affect-as-information hypothesis explains such behavioral patterns as the result of individuals using their current emotional state to determine the value of choice options. The affect-as-information hypothesis further posits that in addition to incidental emotional evaluations, emotional responses can also be generated by the decision options. This occurs when we have rapid,

Cognition and Emotion in Emotion Dysregul ation

valid, informative emotional responses to choices that indicate whether we like or dislike them. Importantly, these evaluations are often adaptive and can provide critical decision-relevant information about possible outcomes. These decisionrelevant, emotional evaluations can be generated in response to any sort of option or option feature, whether they are similar (e.g., the price of each option) or dissimilar (e.g., the style of option 1 and the status of option 2). Emotion, or affect more broadly, therefore may serve as a common currency through which individuals can compare distinct options that are not readily comparable through cognitive evaluation alone (Clore & Huntsinger, 2007). This model solidifies that emotion plays a critical role in decision making and proposes that this role is a helpful one. The somatic marker hypothesis further extends the role of emotion from complementary to necessary in the decision-making process. Not only are somatic markers an essential part of decision-making processes, but also cognitive evaluation may even be superfluous (Bechara & Damasio, 2005; Bechara, Damasio, Tranel, & Damasio, 2005; Dunn, Dalgleish, & Lawrence, 2006). The central premise of the somatic marker hypothesis is that emotional responses conveyed through bio-regulatory mechanisms (e.g., changes in electrodermal activity, endocrine release, heart rate, smooth muscle contraction, posture, facial expression, etc.) are necessary for adaptive decision making (Bechara & Damasio, 2005; Dunn, Dalgleish, & Lawrence, 2006; Reimann & Bechara, 2010). Thus, there are two key elements of this hypothesis: (1) bio-regulatory mechanisms convey emotional information that is relevant to the decision at hand, and (2) use of this emotional information during decision making is in fact adaptive. These are significant additions to previous theories, which identified potential benefits of emotions on decision making but did not view them as essential to adaptive choices (Schwarz & Clore, 1983; Clore & Huntsinger, 2007; Loewenstein et al., 2001; Kahneman & Tversky, 1979).

Effects of Emotion on Cognitive Control

Many processes affect our ability to engage in cognitive control, which allows us to make and implement long-term, multistep cognitive plans; strategically direct attention; inhibit prepotent responses; and hold multiple pieces of information in mind— often referred to as executive functioning (Miyake et al., 2000). The executive functioning literature

examines how we enact top-down control to maintain, inhibit, and shift between different types of information. Studies of instructed emotion regulation, such as those that direct participants to use reappraisal and/or distraction, are helpful for identifying many separable executive functions (Ochsner & Gross, 2005). Much of the literature to date has focused on establishing a meaningful taxonomy of cognitive control in a neutral context (Miyake & Friedman, 2012). However, some researchers have examined the effects of cognitive control on emotion by examining the degree to which cognitive control can also operate on emotional, rather than neutral, stimuli (Zelazo, Qu, & Kesek, 2010). Other researchers have induced emotions in the laboratory and then asked participants to engage in neutral cognitive control tasks, therefore examining the ­effects of induced emotional contexts on cognitive control.

How emotion hurts cognitive control

Most studies report impaired performance when cognitive tasks are performed on emotional (rather than neutral) stimuli. These studies conclude that emotion (positive or negative) can impair performance in cognitive control domains, including conflict adaptation (Padmala, Bauer, & Pessoa, 2011), working memory (Schweizer & Dalgleish, 2016), and switch costs (Zhou et al., 2011). One explanation for these findings is that emotional stimuli capture attention (i.e., are distracting), which leaves fewer resources for initiating and executing cognitive control processes (Blair et al., 2007). There is some evidence that the presence of emotional stimuli can reduce engagement of prefrontal regions typically associated with cognitive control during these tasks (Dolcos & McCarthy, 2006; Hur et al., 2015). Additionally, these decreases in prefrontal engagement are paired with increases in other cortical regions and/or limbic regions, which is consistent with a distraction effect (Dolcos & McCarthy, 2006). Trait and state negative affect may also have ­detrimental effects on cognitive control. Studies of trait anxiety indicate that anxiety impedes cognitive control processes such as working memory (Hayes, Hirsch, & Mathews, 2008) and switching (Derakshan, Smyth, & Eysenck, 2009). In addition, there is a large literature indicating deficits in cognitive control more broadly among individuals with depression (Holmes & Pizzagalli, 2007; Joormann & Siemer, 2011; Snyder, 2013). M c Rae and Zarolia

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How emotions enhance cognitive control

However, in a few cases, emotion can enhance cognitive control. There is some evidence that even negative emotion can improve conflict resolution (Kanske & Kotz, 2011; Schuch, Zweerings, Hirsch, & Koch, 2017) and can enhance conflict adaptation in a Flanker task (Zeng et al., 2017) and working memory (Levens & Phelps, 2008; Xie & Zhang, 2016). Positive emotion seems to have a more ­consistent facilitation effect on cognitive control. Positive emotion has long been thought to facilitate creative thinking, and state positive affect has been shown to improve performance on tasks like remote associates (Isen, Daubman, & Nowicki, 1987), and may also make people more likely to focus on similarities and therefore group things together (Isen & Daubman, 1984). It is possible that positive emotion enhances cognitive flexibility (switching) and broader (global) thinking at the expense of more narrow attentional focus, which can lead to greater working memory maintenance and stability (Dreisbach & Goschke, 2004; Storbeck & Maswood, 2016). When participants can earn a reward for their performance on a task, cognitive control ability is enhanced (Krebs, Boehler, & Woldorff, 2010; Savine, Beck, Edwards, Chiew, & Braver, 2010). Much of the literature lumps emotion and motivation together—that is, positive emotion (pleasant subjective feeling) is often expected to have the same effect on cognitive control as reward contexts (tasks in which performance is positively reinforced). Both positive emotion and reward might improve cognitive processes such as task switching, and lower switch costs (Wang & Guo, 2008). The benefits of reward contexts extend to enhanced go–no-go performance under reinforcement conditions, but diminished control under threat conditions (Cohen et  al., 2016). Reward contexts seem to enhance engagement in the prefrontal cortex during cognitive control (Locke & Braver, 2008). Work connecting positive emotion and reward to tonic and phasic dopaminergic activity, respectively, makes strong predictions about the more specific effects of positive emotion versus reward on cognitive control (Chiew & Braver, 2014). For example, experimental work demonstrates that a reward context might bias cognitive control toward proactive control rather than reactive control (Chiew & Braver, 2011). One possible neural mechanism for this shift might be increased activation in cognitive control regions under conditions of reward (Jimura, Locke, Braver, & Smith, 2010). 46

Implications of Emotion–Cognition Interactions

We have summarized multiple ways in which emotion can affect attention, memory, cognitive control, and decision making, as well as ways in which these cognitive processes in turn can affect emotion. Because of these bidirectional relationships, the possibility exists for unchecked feedback, either in the direction of more emotion (typically thought to be undesirable in the case of negative emotion) or in the direction of less emotion (typically thought to be desirable in the case of negative emotion). Previous scholars have referred to these unchecked feedback loops as downward and upward spirals, respectively (Burns et al., 2008; Fredrickson & Joiner, 2002). One common downward spiral, for example, might involve the quick capture of a negative stimulus into attention, resulting in enhanced processing of that stimulus, leading to increases in negative mood and increased accessibility of negative memories, and then prolonging negative mood, which disturbs sleep. Prolonged negative mood and sleep disruption may further affect cognitive control, making the use of cognition to curtail emotion less effective. In this example, the feedback between cognitive and emotional systems continues to enhance negativity. Conversely, an upward spiral might occur when someone is able to successfully engage in emotion regulation and curtail a negative emotion, diminishing the possibility that more negative emotions will be cued in autobiographical memory, making sleep disturbances less likely, and preserving cognitive control resources to handle future encounters with negative stimuli or situations. Therefore, interrupting downward spirals might be effective as one type of intervention. Even more potent might be the elicitation of positive emotion, given that some cognitive effects of positive emotion might be opposite to those of negative emotion. Therefore, positive emotion not only slows or halts the downward spiral process but also might reverse it. Generating positive emotion may be one way to begin an upward spiral, as noted in the positive psychology literature (Fredrickson, 2001). One important implication of these spirals is that there are multiple points of entry to enact change. Cognitive reappraisal is a commonly used tool in cognitive-behavioral therapy because it is one way to interrupt a downward spiral (Mansell, Harvey, Watkins, & Shafran, 2008). Interventions such as cognitive-behavioral therapy and/or an intervention that might improve sleep and therefore

Cognition and Emotion in Emotion Dysregul ation

improve regulatory functioning could be powerful ways to slow the spiral. However, it is possible that any disruption of a negative emotion, such as using distraction, might result in a short-term reprieve from negative emotion, which could be a first step to reducing a downward spiral. Psychoactive medication, for example, antidepressant medication, typically has as its primary target the blunting of negative emotion. Although these neurotransmitters are likely to act upon emotion generation and emotion regulation neural circuitry alike, it is thought that this initial effect can be capitalized upon if then paired with a cognitive intervention, such as cognitive-behavioral therapy (Cuijpers, Van Straten, Hollon, & Andersson, 2010). Individuals who benefit most from antidepressant medication are those who increase their frequency of reappraisal, even when not undergoing formal psychosocial treatment (McRae et al., 2014). The interactions between emotion and cognition outlined here support a potential distinction between two types of emotion dysregulation (Baumeister, Heatherton, & Tice, 1994; CampbellSills & Barlow, 2007; Carver & Scheier, 1981). Some dysregulated affect may be the result of underutilization of effective regulatory mechanisms, a spiral in which strong negative emotion is going largely unchecked by cognitive processes. However, other dysregulation might be due to use of maladaptive emotion regulation strategies, which has been termed misregulation of emotion (CampbellSills & Barlow, 2007). Misregulation of emotion might paradoxically result in up-regulation (rather than down-regulation) of negative emotion. Rumination is one example of misregulation of affect (Nolen-Hoeksema, 2000). Individuals whose negative emotion is unchecked due to underutilization of regulation might benefit from interventions targeted at emotion regulation frequency. However, those who are misregulating emotions might benefit from interventions that instead target the success, or efficacy, of those emotion regulation strategies (McRae, 2013). Emotion dysregulation is a hallmark of many mood and anxiety disorders (Aldao et al., 2010; Gross & John, 2003; Kring & Werner, 2004), but it is the result of any number of interactions between emotion and attention, memory, decision making, emotion regulation, or cognitive control processes. The heterogeneity of mechanisms that can produce emotion dysregulation may be frustrating for anyone trying to simply understand the causes of his or her distress. However, this heterogeneity also

offers multiple targets for intervention, which is a cause for hope that many individuals will be able to find a point in the emotion–cognition interaction spiral to make meaningful change.

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What Emotion Dysregulation Looks Like Inferences from Behavioral Observations

K. Ashana Ramsook, Pamela M. Cole, and Margaret A. Fields-Olivieri

Abstract Recent conceptualizations of emotion dysregulation define it as a process that unfolds over multiple time scales and that leads to short- or long-term impairments. This chapter discusses the advantages of observational methods for measuring emotion dysregulation as a process, focusing on three patterns and associated evidence of them from observational studies. First, the chapter discusses context-inappropriate emotion, the absence of an expected emotional reaction or an atypical reaction for the situational context. Second, it discusses atypical emotion dynamics, specifically emotional expressions that change abruptly, including but not limited to emotional lability. Third, it discusses ways in which emotions endure and are difficult to modify, pointing to ineffective strategy use as a mechanism. It concludes by discussing new directions for observational research, including creative study design and analytic methods that can capture emotion dysregulation. Keywords:  emotions, emotion dysregulation, observational methods, behavioral observations, context-inappropriate emotion, atypical emotion dynamics, emotional lability, observational research, emotional behavior

Introduction

Mental health professionals—including both scientists and practitioners—often use the term “emotion dysregulation” to refer to emotional behavior that appears to compromise individuals’ adaptive function (Beauchaine, 2015; Thompson, 1990; Chapter  8, this volume). This may include emotional reactions that are unusual in or insensitive to the context in which they occur. For example, an adolescent might unemotionally describe witnessing his father’s violent attack on his mother, or a child may be frightened by a birthday party game that other children enjoy. Other examples include unpredictable emotional changes (i.e., lability), such as a parent laughing about a child’s misbehavior in one moment and then exhibiting hostility toward the child the next moment. Emotional reactions may also endure despite one’s coping efforts. These and other observations fuel intense interest in emotion regulation and dysregulation.

In recent years, a vast amount of research has emerged on emotion dysregulation as a possible mechanism in psychiatric disorders (e.g., Aldao, Nolen-Hoeksema, & Schweizer, 2010; Joormann &  Gotlib, 2010; Kring & Moran, 2008; Mennin, Heimberg, Turk, & Fresco, 2002). In fact, emotion dysregulation has been offered as an explanation for symptoms such as affective lability, mania, blunted affect, prolonged irritability, callousness, and other symptoms involving emotions (e.g., Blair, 2010; McMillan, Williams, & Bryant, 2003; Reich, Zanarini, & Fitzmaurice, 2012). Emotion dysregulation is so pervasive among mental health problems that emotion-related constructs were included in the National Institute of Mental Health Research Domain Criteria (RDoC; Fernandez, Jazaieri, & Gross, 2016; Insel et al., 2010). RDoC is a transdiagnostic framework intended, among other diverse objectives, to guide and advance mental health research by focusing on how functional psychological 53

processes, such as those involved in healthy emotional functions, deviate from normal and become dysfunctional. The RDoC matrix comprises five domains, including positive, negative, cognitive, social, and arousal/regulatory systems—which collectively capture aspects of emotional functioning involving threat, frustration, loss, reward, and affiliation. Taken together, clinical observations, clinical research, and the efforts such as RDoC underscore the need to understand the role of emotion in impaired psychological function. The study of emotion dysregulation is one approach to understanding the nature and development of these problems and ultimately treating or preventing them (e.g., Beauchaine & Zisner, 2017). In this chapter, we discuss how observations of emotional behavior can be translated into meaningful research on emotion dysregulation. We offer definitions of emotion, emotion regulation, and emotion dysregulation, acknowledging the lack of consensus, and exploring whether emotion regulation can be differentiated from emotion. We then illustrate three clinical patterns of emotion dysregulation that can be studied using behavioral observations (Cole, Hall, & Hajal, 2017). Next, we review available evidence for these patterns, discuss limitations of existing research, and suggest future directions that can contribute to meaningful observational research on emotion dysregulation.

Theoretical Perspectives and Definitions

Defining emotion dysregulation offers several challenges. For example, there is no consensus regarding whether humans are biologically prepared to experience and express a core set of universal emotions, whether emotions are constructions of our perceptions and interpretations of physiological arousal, or both (see, e.g., Tracy & Randles, 2011). Discrete emotion theories posit that emotions such as joy, anger, fear, sadness, and disgust are biologically prepared and observed across cultures and even species (Ekman, 1992; Izard, 2007; Tomkins, 1962,  1963; Panksepp, 1992,  2017; Sauter, Eisner, Ekman, & Scott, 2010; Chapter  2, this volume). In contrast, according to core affect theory, humans’ physiological experiences vary in valence and arousal, and our interpretations of these experiences yield cognitive constructions that we experience as emotion (L.  F.  Barrett, 2011; James, 1884; Russell, 2003; Widen & Russell, 2008). We see value in understanding both the fundamental function of emotion and different functions of discrete emotions. To this end, we draw from the 54

functional perspective on emotional development (K. C. Barrett & Campos, 1987; Campos, Mumme, Kermoian, & Campos, 1994), as well as dynamic systems principles (Fogel et al., 1992; M. D. Lewis & Granic, 2002). According to these perspectives, emotions are relational, dynamic, and continuous psychological processes rather than events. These perspectives inform how we approach the concept of emotion regulation and how we distinguish regulatory patterns that are normal and effective from those that are atypical and dysfunctional. The functionalist perspective views emotions as relational processes. That is, emotions are defined by how we relate to situations, both actual and perceived, as they bear on our short- and long-term goals for well-being (K. C. Barrett & Campos, 1987; Campos et al., 1994). In this view, emotions are not discrete events; they are not things. Rather, emotions are continuous, interactive processes through which we relate to changing environments in ways that promote our own well-being, while simultaneously preparing us to act to achieve those goals (see Cole, 2016 for further discussion). What we interpret as a discrete emotion—a feeling or an emotional expression—is the product of (1) continuous appraisal of the significance of ongoing circumstances for well-being and (2) continuous changes in readiness to act in particular ways (e.g., approach with force, yield, escape) to regain, preserve, attain, or maintain our goals (Arnold, 1960; Frijda, 1986). This informs how we conceptualize emotion dysregulation. Prior to the 1980s, the term “emotion dysregulation” appeared only sporadically in empirical papers in psychology. During a resurgence of scientific interest in emotion in the 1980s, the term appeared in titles of a special issue of Developmental Psychology (Dodge, 1989) and an edited volume (Dodge & Garber, 1991). These publications did not define emotion dysregulation but used the term to imply dysfunctional patterns of emotion regulation. The emphasis on regulation is important. It acknowledges that emotions are never out of control; what appears out of control to the average person is a pattern of emotion that is problematic by some criterion (Cole, Michel, & Teti, 1994). Even sustained or intense emotion is not inherently dysfunctional; over millennia, the capacity for strong, enduring emotions has been conserved because this capacity enables us to protect and achieve our goals for wellbeing, helping us communicate our needs and act on our own behalves (Cole, 2016; Cole, Martin, & Dennis, 2004).

What Emotion Dysregul ation Looks Like

As outlined earlier, the functionalist perspective defines emotions as continuous processes. Application of dynamic systems theory to emotion provides a way to conceptualize and study these processes. Both approaches view emotions as dynamic, inherently regulatory processes (Campos et al., 2004; Hollenstein & Lanteigne, in press; Witherington & Crichton, 2007). Notably, however, if emotion is conceptualized as ­self-organizing, it may not be possible to differentiate emotion regulation from emotion (Campos et al., 2004; Hollenstein & Lanteigne, in press). Dynamic systems theory draws on evidence from diverse human biological functions, such as motor development and self-organization of the nervous system (e.g., Kelso, 1994; Ochsner et al., 2009; Thelen, 2002). Behavioral observations, however, involve a different level of analysis, as intrinsic biological dynamics are not observable. Observational studies often conceptualize emotion regulation as application of intra- and interpersonal strategies to shape and constrain emotional experience and expression (e.g., Sheppes et al., 2014). This conceptualization entails regulatory influences that are not defined by emotion and yet have the capacity to regulate emotion. In fact, to infer emotion dysregulation from observations, the distinction between regulatory influences (e.g., strategies) and emotions is necessary. To integrate these viewpoints and levels of analysis, we conceptualize emotion regulation as a change in a changing process (Cole et al., 2004). We appreciate the dynamic, continuous, changing physical nature of emotions as we encounter and navigate the ever-changing circumstances of life. We assert that one form of emotion regulation, sometimes referred to as top-down regulation, involves recruitment of one set of processes—executive processes—that can modulate intrinsic dynamics of self-organizing emotion systems (e.g., Beauchaine & Zisner, 2017). We find this approach to be not only essential for use of behavioral observations but also clinically useful as interventions often rely on teaching individuals strategies to modulate emotional experience. In this chapter, we focus on observations of patterns of emotion that are atypical and often dysfunctional, and involve the absence of or ineffective use of strategies to alter the intrinsic dynamics of emotions. Specifically, observed emotion dysregulation can be conceptualized and measured in terms of atypical intrinsic emotion dynamics, which may often involve ineffective strategic efforts to modulate emotion dynamics. As outlined earlier, emotion dysregulation involves patterns of emotional experience and/or

e­ xpression that interfere with a person’s immediate (e.g., problem solving or a social interaction) or long-term developmental goals (e.g., socioemotional competence or mental health). We emphasize that certain patterns of emotion regulation can be both functional and dysfunctional, depending on context (Cole et al., 1994). Consider dissociation, the experience of psychological disconnection from ongoing circumstances, which often occurs among young children who experience incest (Cole & Putnam, 1992). In the immediate situation, dissociation protects these children from overwhelming, confusing circumstances and associated physiological stress. It is protective for young children who often have few alternatives for preventing or ending the abuse. However, for some survivors, dissociation becomes a routine regulatory process that is dysfunctional. Overreliance on dissociation interferes with coping and may lead to interpersonal problems and relationship failures in the long term. Thus, spontaneous cognitive processes that interrupt emotional experience can be adaptive in reducing psychological and physiological stress, but establish a pattern of emotion dysregulation when it later interferes with healthy functioning. It is thus critical to understand emotion regulation across multiple time scales (Cole & Hollenstein, 2018; Granic, 2005), to understand how moment-to-moment behaviors and expressions, which may serve immediate goals, become repeated experiences that develop into maladaptive, dysregulated patterns.

Inferring Emotion Dysregulation Through Observation

Why focus on behavioral observations when there are less time-consuming ways, such as self-report, to conduct emotion dysregulation research? Our view of emotion dysregulation as a dysfunctional dynamic pattern unfolding on quick time scales in situational context necessitates behavioral observations (Cole et al., 1994; Cole et al., 2004). Other methods have advantages but are limited in capturing emotion dysregulation as a set of processes. In addition, behavioral observations provide an alternative when participants are unable to report or have difficulty reporting accurately on their emotional experiences and strategy use. In this section, we discuss advantages of behavioral observations and describe three patterns of dysregulation that we observe clinically. Self-reports of emotional experience, reports from others close to an individual, and perceptions of professional observers are primary methods Ramsook, Cole, and Fields-Olivieri

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through which we evaluate and study emotion (dys) regulation (Aldao et al., 2010; Cole et al., 2004; Rothbart & Bates, 2006). Often, we administer questionnaires to one or more informants (e.g., parents, teachers). Advantages of this method include its convenience in terms of cost and time, the fact that informants often have extensive experience with the client, and, in the case of self-reports, the access yielded to subjective experiences. Commonly used questionnaires for studying emotion dysregulation in children are the Emotion Regulation Checklist (Shields & Cicchetti, 1997) and the Emotion Management Scales (Zeman & Garber, 1996; Zeman, Cassano, Suveg, & Shipman, 2010). For adults, the Difficulties with Emotion Regulation Scale (Gratz & Roemer, 2004) is most commonly used, and other instruments include the Toronto Alexithymia Scale (Bagby, Parker, & Taylor, 1994), the Affective Control Scale (Williams, Chambless, & Ahrens, 1997), and the Affect Regulation and Experiences Questionnaire (Westen, Muderrisoglu, Fowler, Shedler, & Koren, 1997). Questionnaires and rating scales focus on traitlike characteristics of the individual but are limited in detecting changes in emotion dysregulation processes in context (Diaz & Eisenberg, 2015). Conceptualizing emotion dysregulation in terms of fast time scale changes situated in the ecology of a person’s circumstances requires a less static approach. Experience sampling methods (Csikszentmihalyi & Larson, 2014), such as daily diaries and ecological momentary assessment (Stone & Shiffman, 1994), can evaluate emotion dysregulation in situational context. They too are self-report methods, but carry the advantage of situating self-report in both time and circumstance, often repeated over hours or days. They permit temporal analyses, including antecedent conditions of emotional reactions, sequences of emotions and strategies, and their consequences. However, they also share some limitations of selfreports. In particular, some participants are not able to report on their experiences, such as young children and individuals with conditions that impair their self-report ability or accuracy (Denham, Wyatt, Bassett, Echeverria, & Knox, 2009). Our interest in children’s emotion regulation, and how it deviates from normal development and contributes to emerging psychopathology, motivates our use of behavioral observations. Such observations are critical because of the limitations of accurate self-report with young children, who are developing other crucial cognitive and emotional capacities that facilitate awareness and description 56

of internal states (see Durbin, 2010; A.  R.  Lewis, Zinbarg, & Durbin, 2010; Zeman, Klimes-Dougan, Cassano, & Adrian, 2007). Although we include parent and/or teacher reports, these adults may not always observe more subtle aspects of children’s emotion regulation. Indeed, young children may engage in self-regulation more readily when caregivers are not present. For example, in our research on young children’s masking of disappointment (e.g., Cole et al., 1994), parents often express concern about how their children behave and are surprised to learn that typically developing children manage to smile when a research assistant gives them a “prize” that they clearly do not want. Moreover, in some risk conditions, there is heightened likelihood of bias in adult reports (e.g., Boyle & Pickles, 1997; Chilcoat & Breslau, 1997; Najman et al., 2001); parents with their own psychological problems may be overly negative or minimize regulatory behaviors of their children. Thus, observations are essential when studying emotion dysregulation dynamics, especially in children. In sum, if we conceptualize emotion dysregulation as a set of dynamic, moment-to-moment processes, we cannot capture it through static approaches that summarize perceptions of behavior. In contrast, we can use behavioral observations to infer regulatory processes, to discriminate regulatory attempts that occur on a moment-to-moment basis, to link these to evidence of current or subsequent impairments in psychological functioning, and, ultimately, to investigate heterogeneity of patterns that characterize normative and pathological functioning (Aldao & Nolen-Hoeksema, 2010; Cole et al., 1994). By studying emotion dysregulation as a set of processes, we can conduct observations that are clinically relevant, a crucial step for full understanding of the development of psychopathology, and for using evidence to improve the design of preventive or therapeutic interventions (Wakschlag et al., 2005). We illustrate three patterns of observable behavior indicative of emotion dysregulation (Cole, Hall, & Hajal, 2017): 1.  Emotions that are context inappropriate 2. Emotions that change too abruptly 3. Emotions that endure because strategies are ineffective In the next section, we provide illustrations of these patterns and highlight observational evidence for each. As we show, there is a dearth of rich observational studies of emotion dysregulation. Therefore, after our review, we provide an additional section

What Emotion Dysregul ation Looks Like

discussing future directions that can enrich our ability to understand the nature and development of emotion dysregulation using observational methods.

Emotions That Are Context Inappropriate

Maria, a 13-year-old, was admitted to a psychiatric unit by her adoptive parents because they could not control her defiance, truancy, and running away. Although they were concerned about her well-being, they stated they could no longer care for her and had begun proceedings to relinquish custody. In group therapy sessions, individual therapy sessions, and interactions with nursing staff, Maria laughed and dismissed staff attempts to help her deal with her situation. Her emotions, although on the one hand positive, interfered not only with her therapy but also with progress of other youth in the group. After eight weeks of intensive inpatient intervention, Maria succumbed to deep depression. She expressed hopelessness that any parent could love her. She also came to understand that her laughing and joking masked her painful sadness. Slowly, she came to terms with her circumstances and began to manage her sadness and cope with her situation. Maria’s presentation of positive emotion in the context of staff efforts to help her deal with the realities of her situation was not consistent with the seriousness of her circumstances. Laughing and joking served to avoid the overwhelming sadness of  her impending loss and its meaning. Maria’s ­context-inappropriate emotional presentation is but one way that emotional reactions may deviate from normative responses. Moreover, context-inappropriate emotions often impair a person’s interpersonal function or problem solving. Evidence that context-inappropriate positive emotion represents one form of emotion dysregulation comes from studies linking it to a variety of childhood problems. For example, some children (ages 4 to 14 years) express happiness while viewing fear-eliciting film clips, whereas most children display fear. Children who express happiness are rated by their parents as callous and unemotional (Dadds et al., 2016). Context-inappropriate positive emotion is also observed in dyadic interactions between mothers and preschoolers who exhibit externalizing behavior problems (Cole, Teti, & Zahn-Waxler, 2003; Lunkenheimer, Kemp, Lucas-Thompson, Cole, & Albrecht, 2017). In one of these studies, analysis of parent–child and child–parent contingent emotions reveals that, in dyads with clinically elevated externalizing symptoms, both partners ­express positive emotion when the other is angry, often laughing at the partner’s anger (Cole et al.,

2003). Preschool- and school-age children from families in which a parent is abusive or has depression also display positive emotion, in addition to hostility, while observing simulated angry conflicts between two adults (Maughan & Cicchetti, 2002; Maughan, Cicchetti, Toth, & Rogosch, 2007). Context-inappropriate positive emotion in response to neutral or negative stimuli is also observed in adults and differentiates those with bipolar disorder from healthy controls (Gruber, 2011). Thus, expressions of joy or happiness, although generally regarded as healthy, are associated with externalizing behaviors when present in situations that normally elicit negative or neutral emotions. There is less research on context-inappropriate negative emotion, but the available evidence links it with anxiety. In novel and uncertain situations, most toddlers display some degree of hesitation or fear, but children who are especially fearful are at greater risk for developing social anxiety disorders (Schwartz, Snidman, & Kagan, 1999). Moreover, toddlers who are fearful in novel but low-threat situations that most toddlers enjoy (e.g., a puppet show) show more symptoms of social anxiety and more wariness in social interactions by the time they  reach kindergarten (Buss et al., 2013). Thus, context-inappropriate fear is a risk factor for development of anxiety symptoms (Buss, 2011). Although fear is a desirable response to circumstances that may pose a threat to well-being, displaying fearful behavior in low-threat situations is context inappropriate and predicts development of later impairment. Another form of context-inappropriate emotion is the absence of typical or expected emotional responses. In fact, access to a full range of emotions is a hallmark of emotional competence and mental health (e.g., Saarni, 1999). Kindergartners with externalizing behavior problems display less fear and sadness in response to parental anger, but similar levels of anger, relative to nonproblem children (Stoolmiller & Snyder, 2006). Moreover, exposure to certain forms of anger or maltreatment can lead to the absence or blunting of emotional responding in situations that typically elicit strong emotion. Some four- to six-year-olds who are exposed to maltreatment, domestic violence, or maternal depression do not appear distressed during anger simulations, as typically developing children do, which is interpreted as emotional overcontrol (Cummings, 1987; Maughan & Cicchetti, 2002; Maughan et al., 2007). This pattern also extends to positive emotion expression. In parent-child interactions, one- to Ramsook, Cole, and Fields-Olivieri

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four-year-olds who experienced maltreatment displayed less intense positive affect than their peers who were not maltreated (Robinson et al., 2009). In sum, there is observational evidence that ­context-inappropriate emotion is a form of emotion dysregulation. This evidence links indicators of psychopathology with either context-inappropriate positive emotion or a lack of observable emotion. Very few studies address context-inappropriate negative emotion. Context-inappropriate emotion can also reflect an effort to control or avoid emotions, as with Maria’s avoidance of sadness.

Emotions That Change Too Abruptly

Mateo, a 15-year-old boy, is on a psychiatric inpatient unit because of an overdose of an over-the-counter medication. He has been working with the staff to earn a weekend pass. He appears happy at the outset of a family session where he will tell his parents that he has earned the pass. However, without warning, he becomes very angry, cursing at his father, surprising his parents and therapist. He is inexplicably enraged and efforts to calm him do not help. The nursing staff come and escort Mateo to an isolation room where he is asked to reflect on his behavior. He starts laughing, but staff insist he remain in the isolation room and prepare to discuss his behavior calmly. When the nurse comes to process events with him, he is at first pleasant and polite but suddenly becomes enraged again. Mateo’s anger is intense but it also occurs abruptly and without staff or his parents being able to predict his outbursts. Therefore, it is difficult for adults to find ways to help him understand his feelings and manage his reactions to make them less abrupt. Thompson (1990, 1994) suggests that temporal dynamics of emotion expressions—latency, duration, rise time to peak intensity, and recovery from peak intensity—index emotion regulation. These may also serve as observable indices of dysregulation. Indeed, latency to the onset of an emotion and rise time to peak intensity may distinguish individuals with and without symptoms of various forms of psychopathology. Kindergarteners with behavior problems are quicker to express anger compared to kindergarteners without behavior problems (Stoolmiller & Snyder, 2006, 2013). Moreover, one-year-olds who are quicker to express anger in challenging situations have more serious behavior problems by age five than one-year-olds who anger more slowly (Halligan et al., 2013). Longitudinally, typically developing children become increasingly slower to express anger in frustrating situations between ages 18 and 48 months, particularly between 58

ages 24 and 36 months (Cole et al., 2011). Thus, short latency to react emotionally may indicate emotion dysregulation. Emotional lability, defined by quick rise time to peak intensity and frequent changes in emotion types, may be a more sensitive index of emotion dysregulation than simple latency. Indeed, emotional lability is one of the two scales of the oft-used Emotion Regulation Checklist (Shields & Cicchetti, 1997). Using experience sampling methods, greater reports of emotional lability are related to elevated symptoms of depression in adolescents (Silk, Steinberg, & Morris, 2003) and higher levels of behavior problems in children with attention-deficit/ hyperactivity disorder (Rosen, Walerius, Fogleman, & Factor, 2015). Individuals with borderline personality disorder, relative to healthy controls, also report more emotion changes while passively viewing emotion-eliciting video clips (Schoenleber et al., 2016). We could not find observational studies of intrapersonal emotional lability, although emotional lability is attributed to children with disorders such as autism spectrum disorder (Ashburner, Ziviani, & Rodger, 2010; Scarpa & Reyes, 2011) and attentiondeficit/hyperactivity disorder (Biederman et al., 2012; Surman et al., 2011). However, several observational studies capture emotional lability in interpersonal contexts. For example, during a challenging construction task between preschool-aged children and their mothers, children in dyads that exhibit more frequent, unpredictable emotional shifts have higher levels of mother-rated externalizing problems by kindergarten (Lunkenheimer, Olson, Hollenstein, Sameroff, & Winter, 2011). Dyads with aggressive preschoolers also show more transitions between escalating and de-escalating aversive behaviors during a conflict (Snyder, Edwards, McGraw, Kilgore, & Holton, 1994). Greater emotional lability, defined by wider range of emotions and less predictable emotions, is also observed during planning and problem-solving interactions of parents and their ­depressed adolescent relative to nondepressed adolescents (Hollenstein, Allen, & Sheeber, 2016). In addition, mothers and self-injuring adolescents are more likely to escalate conflicts, as measured by the intensity of their moment-to-moment aversive behaviors (Crowell et al., 2013). Emotional lability is also associated with callous-unemotional characteristics. Across three observations of parents and their adolescents, adolescents rated as higher in callousunemotional traits displayed more within-person variability in anger or irritability compared to

What Emotion Dysregul ation Looks Like

a­dolescents without callous-unemotional traits (O’Connor, Humayun, Briskman, & Scott, 2016). These quasi-naturalistic observational procedures are designed to mimic typical situations in families’ lives, strengthening their ecological validity. Moreover, the paradigms and analyses used in this dyadic research could easily be applied to the study of emotions or behaviors within an individual (Hollenstein, 2007). In sum, emotions that change too abruptly make up another relevant pattern of emotion dysregulation. Several studies document links between behavioral impairment and shorter than typical onset of emotional expression—particularly anger. Less is known about temporal factors related to other discrete emotional displays (e.g., latency to exhibiting happiness, sadness, or fear). In addition, an extensive literature documents the importance of emotional lability to various forms of psychopathology. Although this work has focused largely on self-reports of emotion in adults, observations with parent–child dyads provide support for this pattern being linked to child psychopathology as well, and offer the advantage of measuring lability in an ecologically valid context. This work can be extended to examine emotional lability in other social contexts or when an individual is alone.

Emotions That Endure Because Strategies Are Ineffective

Lena, a nine-year-old girl, is invited to a friend’s birthday party. However, Lena suffers from social anxiety. Lena is a polite, cooperative child and when her parents reason with her she nods and agrees—she will enjoy the party. She also does breathing exercises they encourage. Lena decides to go to the party. However, with each step she takes, her anxiety builds. She starts perspiring and says she cannot go. Her parents continue to coach her, and she cooperates with their suggested strategies, but she is overwhelmed and begins to cry. Lena misses the party. Lena’s anxiety is not lessened or resolved by reasonable strategies her parents offer. She tries their suggestions but the anxiety increases. Their suggestions involve commonly prescribed strategies, such as countering negative thoughts and breathing more deeply. Yet, when she does these things, her attempts seem to exacerbate her anxiety. Emotions that resist change, or do not easily resolve, also indicate dysregulation, particularly when they interfere with an individual’s functioning and well-being. Lena’s example points out that strategies, even those that should work, are not always effective.

Enduring emotions have been studied in several ways. Perhaps most well documented is the observation that emotions endure longer in at-risk and clinical populations. This pattern of longer durations of negative emotion has been documented in young children who were maltreated or whose mothers are depressed (Cummings, 1987; Maughan & Cicchetti, 2002; Maughan et al., 2007), preschoolers with elevated externalizing and internalizing symptoms (Cole et al., 1994), and 4- to 12-year-olds admitted to psychiatric hospitals (Potegal, Carlson, Margulies, Gutkovitch, & Wall, 2009; Potegal & Davidson, 2003). More advanced analytic approaches reveal more nuance to this dysregulated pattern in observational work, capturing not just one temporal indicator, but overall patterns across tasks that suggest enduring emotions. For ­example, preschool-age girls with hostile mothers show increasingly longer duration of negative emotion as their negative emotions accumulate (Dagne & Snyder, 2011). Thus, not only can children’s emotions endure longer than expected, but also accumulation of these emotions can lead to even longer durations as observations progress. Moreover, emotional rigidity—the tendency to “get stuck” in emotional states—is a hallmark of psychopathology (Cole, 2016). It is observed in parent–child dyads in which children have internalizing and externalizing problems (Coburn, Crnic, & Ross, 2015; Hollenstein, Granic, Stoolmiller, & Snyder, 2004). In dyadic observations, emotional rigidity is characterized by a limited range of emotional states, infrequent transitions between states, and long durations within states (Hollenstein et al., 2004). Although it has not been studied in an intrapersonal context, methods used to study emotional rigidity could easily be applied in this way (Hollenstein, 2007). What these studies do not tell us is why emotional responses endure or resist change. There may be a number of reasons, but in many studies of ­adolescent and adult emotion regulation the focus is on strategy use, that is, engagement of strategies that should modulate emotion (e.g., Aldao et al., 2010; Gross & Thompson, 2007). In Gross’s model (1998), for example, there are particular times when different strategies to modulate emotions can be engaged and certain strategies should be more effective than others. Reappraisal and distraction are considered to be the most effective strategies—a claim supported by studies using experimental paradigms in which participants are instructed to use particular strategies while they view emotion-eliciting images (Augustine & Hemenover, 2009). This method is Ramsook, Cole, and Fields-Olivieri

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limited, however, as it does not evaluate spontaneous strategy use and images may lack personal relevance/ecological validity vis-à-vis everyday experience. When using behavioral observations to infer emotion regulation in young children, a few studies assess spontaneous strategy use and emotion expression (e.g., Calkins, Gill, Johnson, & Smith, 1999; Cole et al., 2011; Gilliom, Shaw, Beck, Schonberg, & Lukon, 2002, Stansbury & Sigman, 2000). Measuring both observed emotions and strategy use enables assessment of the degree to which strategies successfully regulate emotions (Cole et al., 2004), although few studies actually test direct effects of strategies on emotion change. However, some evidence suggests that emotions endure when strategies are ineffective. At-risk preschool boys use strategies that should enhance frustration tolerance—specifically, distracting oneself with an activity or passively waiting. However, although these strategies are expected to minimize frustration, their use is not associated with less anger (Gilliom et al., 2002). The method used did not reveal whether there were momentary decreases in anger after those boys’ strategy use; however, another study used advanced modeling of time-series data to examine temporal dynamics in the same type of waiting task ( Cole, Bendezú, Ram, & Chow, 2017). For children described by their mothers as higher in temperamental negative affectivity, strategy use amplified their desire for the restricted item and frustration about waiting. Thus, although these children used putative regulatory strategies, their strategies exacerbated their difficulty tolerating the wait. There are similar patterns observed in adults with bipolar disorder (Gruber, Harvey, & Gross, 2012). Although these individuals report engaging in appropriate spontaneous strategy use after watching emotional video clips, observations reveal that reported strategies are less effective at reducing their emotional responses. In sum, prolonged emotions are observed in atrisk and clinical populations. Conceptual models of emotion regulation suggest particular strategies that should decrease the duration of negative emotions. Studies capitalizing on time-series analytic approaches of observational data are few, but these can reveal that even when individuals spontaneously use a strategy, its use may not account for change in emotion. Understanding when strategies fail to shorten the duration of an emotion and understanding when (and for whom) they succeed are ­important areas for future research. 60

Synthesis and Future Directions

Emotional symptoms are common in many forms of psychopathology, and emotion dysregulation may be a central mechanism in their development and maintenance (e.g., Aldao et al., 2010). There is no commonly accepted definition of emotion dysregulation; however, there is growing consensus that emotion dysregulation should be conceptualized as a process. The functional perspective on emotional development informs our definition of emotion regulation and dysregulation as a set of psychological and physiological processes through which one relates to the environment, and dynamic systems principles inform how one set of processes (e.g., strategy use) influences emotion dynamics. From this perspective, emotion regulation unfolds over the course of situations (moment-to-moment changes), and changes with age (longer time scale) (Cole & Hollenstein, 2018; Granic, 2005). We regard emotion dysregulation as those patterns of emotion regulation that compromise an individual’s short- or long-term developmental goals, even if they serve some useful immediate function. We illustrated three examples of emotion ­dysregulation—context-inappropriate emotion, abruptly changing emotion, and enduring emotion that is not responsive to strategy attempts—that we observe clinically and can study using observational methods. For each pattern, there is research support, however limited. As we will discuss, there are innovative observational approaches that will enrich our understanding of these and other patterns of emotion dysregulation. These involve new features of design and analysis. First, we discuss the need to consider the length and number of observations required to observe patterns of emotion dysregulation, including the length of a single observation and the use of multiple observational periods across development. Next, we describe task considerations that can strengthen inferences drawn from observations, including careful consideration of task contexts and the measurement of stimuli to which ­individuals are exposed. Finally, we review analytic approaches that capitalize on the rich, complex nature of observational data and allow researchers to  test hypotheses about dynamics of emotion ­dysregulation.

Length and Number of Observations

Although some patterns of emotion dysregulation may be observed during a short observational period, others may occur infrequently or emerge

What Emotion Dysregul ation Looks Like

slowly, and may therefore be captured best through more extended observations. Many published observational studies of emotion regulation or dysregulation use single, relatively short (e.g., 10 minutes or less) tasks (e.g., Cole et al., 2011; Lunkenheimer et al., 2017). Others examine overall emotion patterns (often dyadic) across longer periods (e.g., hours), sometimes across multiple types of tasks (e.g., Dagne & Snyder, 2011; Hollenstein et al., 2004). The length of an observation that is sufficient to detect emotion dysregulation processes is an open question in research (Aldao, 2013). Thus, it is important to consider carefully the dynamics of a particular pattern, or set of patterns, of emotion dysregulation and to design observations sufficient in length or number to capture that dysregulated process. For example, a researcher interested in ­ studying emotions that endure or change slowly may need to consider that children’s immediate and delayed emotional responses may be meaningfully different. Researchers interested in this pattern may need to design observational paradigms that are longer than a few minutes, and continue to observe the participant during recovery periods after an evocative or challenging task. Importantly, manipulating task length or frequency may influence emotion dysregulation. In studies of adult self-regulation that focus on resource depletion, increased task length or number of observations appears to tax regulatory capacity (Baumeister & Heatherton, 1996; Baumeister, Muraven, & Tice, 2000). To our knowledge, no studies have tested whether the length or order of tasks influences our ability to observe emotion ­dysregulation. Studies with children frequently use a series of challenging tasks interleaved with nonchallenging tasks that serve as recovery periods. Psychophysiological studies document changes in baseline reactivity across multiple tasks (Beauchaine, Hong, & Marsh, 2008; Beauchaine, Katkin, Strassberg, & Snarr, 2001), indicating cumulative physiological effects of undergoing a series of challenges, even with brief opportunities for recovery. In addition, one observational study shows changes in the speed at which individuals are able to downregulate negative emotions as negative emotion experiences accumulate over the course of a one-hour observation (Dagne & Snyder, 2011). More research is needed to understand how the length or order of observational tasks influences regulatory patterns, and whether that depends on characteristics of the individual. For example, individual differences in

autonomic nervous system arousal during postchallenge recovery periods are linked to children’s behavior (Santucci et al., 2008) and adolescents’ externalizing symptoms (Heleniak, McLaughlin, Ormel, & Riese, 2016; Sijtsema, Van Roon, Groot, & Riese, 2015). Finally, longitudinal designs that incorporate multiple observations across development will also help researchers distinguish normative from dysregulated patterns of emotion. There are longitudinal studies suggesting trait-like continuities in emotion regulation across developmental periods (Blandon, Calkins, Keane, & O’Brien, 2008; Feldman, 2015; Halligan et al., 2013; Gullone, Hughes, King, & Tonge, 2010; Raffaelli, Crockett, & Shen, 2005). However, observational designs provide a unique opportunity to describe normal development of emotion regulation dynamics and deviations that are linked to later psychopathology or impairments in functioning (Granic, 2005). For example, as early as 36 months, children rated as higher on externalizing problems show a regulatory process of emotional and behavioral responses that dampened their use of effective regulatory strategies (Cole, Bendezú et al., 2017). Observational research that examines dynamics longitudinally may expand on this work by identifying normative changes in patterns of emotion and behavior, deviations from normative processes, and their implications for longer term functioning and psychopathology.

Task Considerations

Another design consideration is careful selection of the type and variety of observations needed to observe particular patterns of emotion dysregulation. One issue to consider is whether tasks are designed to tap inter- or intrapersonal dysregulation processes. Another is to consider whether multiple types of tasks, or strategic changes in task demands, are required to capture patterns of dysregulation. Importantly, much of the observational research evidence on emotion dysregulation has focused on regulation processes within interpersonal context. Evocative relationships are likely key to observing emotion dysregulation and have the advantage of being personally relevant to individuals. In the case of young children, the family context is crucial for emotion socialization processes (e.g., Morris, Silk, Steinberg, Myers, & Robinson, 2007), so it is not surprising that parent–child interactions are opportune for researchers to elicit emotional response patterns. In the available research, evocative contexts Ramsook, Cole, and Fields-Olivieri

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are often used to test hypotheses about an individual’s emotional reactions or regulation during or after interactions with significant others (Cummings, 1987; Maughan et al., 2007; Stoolmiller & Snyder, 2006). This approach was used to test hypotheses related to different patterns of emotion dysregulation, including context-inappropriate emotion and emotions changing too abruptly and changing too slowly or enduring. Yet it is also important to ­consider emotion dysregulation as an intrapersonal process, for example, examining the influence of strategies on emotion (Cole, Bendezú, et al., 2017). If emotions indicate an individual’s appraisal of his or her environment, knowing what aspects of the environment are eliciting emotions is a critical next step in research. Dynamic systems approaches involve systematically manipulating aspects of the environment—causing perturbations to a system— and observing subsequent changes in emotional and behavioral patterns (Granic, Hollenstein, & Lichtwarck-Aschoff, 2016). Thus, it can be useful to use tasks with multiple phases designed to challenge an individual’s emotion regulation. For example, during a parent–child problem-solving task, patterns of mutual hostility emerge only after the level of challenge is increased (dyads are told to “wrap up”), and only for children with comorbid externalizing and internalizing symptoms (Granic & Lamey, 2002). Measuring a person’s emotional responses subsequent to these changes in a task can help strengthen inferences that an environmental factor altered an emotional response. In intrapersonal paradigms, researchers can consider measuring aspects of stimuli, such as marking important events or characters in films. These types of clear events and changes in stimuli can help researchers tap dynamics of change in an emotional or behavioral response, consistent with dynamics systems approaches. Finally, adaptive or maladaptive patterns may be detected not only within tasks but also across tasks. For example, a study using self-reports to assess emotion found that individuals who were depressed reported feeling sad while viewing multiple films, each intended to elicit a variety of emotions; this was interpreted as depression involving contextinsensitive emotion (Rottenberg, Gross, & Gotlib, 2005). Other studies examine emotional reactions in situations designed to elicit varying intensities of an emotion. For example, fear dysregulation, defined as displaying fearfulness in low-threat situations, is a risk factor for development of anxiety 62

symptoms (see section on emotions that are context inappropriate; Buss, 2011; Buss et al., 2013).

Analytic Approach

If emotion dysregulation is appreciated as a dynamic process, then we must understand its temporal features, changes in emotion and regulatory efforts as task time unfolds. Too often researchers conduct observations that are video-recorded and later painstakingly coded, often using brief time intervals; however, they then sum or aggregate the data across the entire observation. Rather than consider emotion dysregulation as the total amount of negative or positive emotion expressions or regulatory attempts, a dynamic systems perspective suggests that we model time, the moment-to-moment changes in emotion and how they are changed by regulatory attempts (Cole et al., 2004; Hollenstein & Lanteigne, in press). To quantify emotions in this dynamic way, observational researchers have capitalized on several analytic approaches. First, examining patterns of emotion dysregulation requires researchers to have independent ­examinations of emotions and behavior, and to establish their temporal order (Cole et al., 2004). As discussed previously, emotion expressions and behaviors are often treated the same, but evidence reveals that they operate differently (Hubbard, 2001; Strayer & Roberts, 2004). The degree to which emotions influence inappropriate behavior and, conversely, behaviors such as regulatory strategies influence emotions also requires researchers to establish temporal precedence. Sequence analyses are a relatively simple method that several researchers have capitalized on to address questions about the unidirectional influence of behaviors on concurrent and subsequent emotional responses (Buss & Goldsmith, 1998; Gilliom et al., 2002; Stifter & Braungart, 1995). More advanced time-series analyses such as ordinal differential equation modeling allow researchers to test bidirectional associations between emotions and behaviors over time (Cole, Bendezú, et al., 2017). Temporality is also important for capturing patterns of emotions enduring or changing too abruptly. Capturing this by measuring the latency to emotional or behavioral displays, and average duration of these displays, is most common in the work we have reviewed (e.g., Cole et al., 2011, Potegal et al., 2009). However, other approaches may provide unique information. For example, in the experience-sampling literature, mean squared

What Emotion Dysregul ation Looks Like

successive difference (MSSD) scores (Woyshville, Lackamp, Eisengart, & Gilliland, 1999) have been used to capture emotional lability or instability. MSSD includes information about variability in emotions in terms of amplitude, frequency, and temporal order (see Ebner-Priemer, Eid, Kleindienst, Stabenow, & Trull, 2009 for review). Greater MSSD of suicidal ideation in adults uniquely predicts suicide attempts (Witte, Fitzpatrick, Joiner, & ­ Schmidt, 2005). This method can be applied to observational work, which similarly contains complex time-series data that have temporal dependencies. State-space grids have also been used to capture stability or instability of emotional patterns in dyads, and this work could be applied to intrapersonal paradigms, such as examining changes in emotional responses across meaningful events or perturbations (Hollenstein, 2007). In addition to measuring overall emotional (in)stability in observations, timeseries approaches can be applied to test how quickness and slowness of emotional responses change within an observation. Survival analysis and Bayesian approaches can be used to examine changes in emotional or behavioral responses as a function of recurring events or perturbations (Dagne, Brown, & Howe, 2003; Stoolmiller & Snyder, 2006). An especially new approach, multistate convergence cross-mapping, allows researchers to estimate bidirectional, nonlinear associations in time-series data when evaluating emotional responding in dyadic interactions (Crowell, et al., 2017).

Limitations to Observational Work

Although research benefits from observational methods, which can enhance assessment of emotion dysregulation as a process, there are limitations to observational approaches. First, single or even a few  observations of an individual’s behavior may not be representative of that person’s behavior in daily life. For example, there is evidence that children’s ­ behaviors differ across contexts, and that when multi-informant reports differ in ratings of behavior, this captures meaningful information (De Los Reyes, Henry, Tolan, & Wakschlag, 2009; Hourigan, Goodman, & Southam-Gerow, 2011). This additionally highlights the value of using multiple observations in research. Second, not all patterns of emotion dysregulation are observable. We may not see an emotional reaction (masked anger) or a regulatory strategy (cognitive reappraisal). Physiological methods are often used to strengthen inferences about the meaning of

behavior or the absence of an expected behavior. For example, when using emotional suppression strategies, adults display greater sympathetic nervous system arousal despite having reduced facial expressions of negative emotion (Egloff, Schmukle, Burns, & Schwerdtfeger, 2006; Gross & Levenson, 1993). Moreover, recent work suggests that desynchrony between facial expressions and autonomic reactivity predicts severity of boys’ externalizing symptoms (Marsh, Beauchaine, & Williams, 2008) and discordant patterns of these measures predict girls’ internalizing symptoms (Lanteigne, Flynn, Eastabrook, & Hollenstein, 2014). Increasingly, researchers employ both behavioral observations and physiological measures, a pairing that lends itself well to temporal analyses of emotion dysregulation dynamics (Beauchaine & Gatzke-Kopp, 2012; Brooker & Buss, 2010). It is noteworthy that the use of multiple levels of analysis also presents challenges that are beyond the scope of this chapter (but see Fox & Calkins, 1999; Calkins & Fox, 2002).

Conclusions

Emotion dysregulation has long been of clinical interest and is a core feature of many forms of psychopathology (Aldao et al., 2010; Dodge, 1989). In this chapter, we present three clinically relevant patterns of emotion dysregulation: context-inappropriate emotion, emotions that change too abruptly, and emotions that endure because regulatory attempts are ineffective (Cole, Hall, & Hajal, 2017). These patterns were used to illustrate the advantages of observational methods for enriching our understanding of patterns of emotion dysregulation. Finally, we reviewed several future directions for observational methods, including considerations related to study design and analytic approaches. We emphasize that methods that capture patterns of behaviors unfolding across a carefully designed task and over developmental time are critical next steps in this research.

Acknowledgments

The research reported here was supported in part by a training grant from the Institute of Education Sciences (R305B090007), awarded to the first author. Opinions expressed are those of the  authors and do not necessarily represent the granting ­agencies. This work was supported by a grant from the Eunice Kennedy Shriver National Institute of Child Health and Human Development, HD076994, awarded to the second author. This material is based on work supported by the National  Science Foundation Graduate Research Fellowship (DGE1255832), awarded to the third author. Any opinion, findings, and conclusions or recommendations expressed in this

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material are those of the authors and do not necessarily reflect the views of the National Science Foundation.

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CH A PTE R

6

Emotion Dysregulation and Aging

Patrick Whitmoyer and Ruchika Shaurya Prakash

Abstract This chapter presents an overview of literature relevant to understanding relations between aging and emotion dysregulation. Although a number of studies suggest that aging leads to shifts in emotion regulation and emotional well-being, the extent to which aging affects emotion dysregulation is less clear. To clarify the effects of aging on emotion dysregulation, this chapter begins by examining shifts in effectiveness of emotion regulation that occur with age, considering pertinent theories, and then expands on these findings by examining more specifically how context appropriateness of emotions, consequences of emotions on behavior, duration of emotions, and etiology and presentation of ­psychopathology are altered by aging processes. Finally, this chapter concludes by identifying gaps in the literature and recommendations for future empirical endeavors to advance our current understanding of effects of aging on emotion dysregulation. Keywords: aging, emotion dysregulation, strategy use, context, cognitive control, behavior

Introduction

Aging is characterized by notable declines in physical and cognitive function. Despite these declines, an  abundant literature suggests that emotional well-­being—referring to a state of good mental health and adaptive experience of both positive and negative affect—remains stable and may even improve with age. Both cross-sectional studies and longitudinal follow-up studies, which help rule out cohort effects, provide evidence for continued stability and enhancement of hedonic well-being in late adulthood (Carstensen, Pasupathi, Mayr, & Nesselroade, 2000; Charles, Reynolds, & Gatz, 2001; Hasin, Goodwin, Stinson, & Grant, 2005; E.M. Kessler & Staudinger, 2009; Kunzmann, Little, & Smith, 2000; Mroczek & Kolarz, 1998; Reynolds, Pietrzak, El-Gabalawy, Mackenzie, & Sareen, 2015). This paradoxical finding of maintained emotional health despite declining physical and cognitive function is  at center stage in the aging literature, much of which is devoted to understanding the extent to which such age-related shifts represent general age-

related shifts in the experience of emotions or changes in the emotion regulation process. One proposed explanation is that shifts in the processes that underlie the experience and expression of emotion account for age-related shifts in emotional well-being. Emotions themselves are ­inherently regulatory (Campos, Mumme, Kermoian, & Campos, 1994; Cole, Hall, & Hajal, 2017). The experience of emotions of varying valences and ­intensities often begins or is closely followed by ­appraisal or evaluation of the current situation, which elicits a regulatory action—either adaptive or maladaptive—to current circumstances. One of the prominent theories, the aging brain model, proposed by Cacioppo, Bernston, Bechara, Tranel, and Hawkley (2011), posits that the experience of emotions shifts as a function of age-related declines in the structural integrity of the amygdala, a subcortical brain region that is critical to generating various emotions (among other functions). According to Cacioppo et al., reduced integrity of the amygdala alters emotional processing (i.e., evaluation/appraisal) and 69

reactivity (i.e., emotion generation and behavioral responsivity to emotion), which leads to reduced sensitivity to negative, but not positive, stimuli, thus explaining age-related shifts in well-being. However, contrary to this model, there is significant neuroimaging evidence for structural and functional preservation of the amygdala with increasing age relative to other brain regions (Allen, Bruss, Brown, & Damasio, 2005; Nashiro, Sakaki, & Mather, 2012). Postmortem studies indicate no volumetric decline in the amygdala with age (Brabec et al., 2010), and functional studies suggest preserved amygdala reactivity in older adults (Jacques, Dolcos, & Cabeza, 2010; Wright et al., 2008). Thus, there is currently little support for the theory that age-related shifts in general emotional reactivity are responsible for age differences in emotional well-being. In contrast, emerging evidence from behavioral and neuroimaging investigations suggests that emotion regulation goals and strategies play a critical role in explaining age-related shifts in emotional well-being (for a review see Nashiro et al., 2012). As a result, emotion regulation—referring here to volitional (explicit) and avolitional (implicit) processes involved in modulation of initial emotional responses (Cole et al., 2017; Gross, 1998, 2015)—is a dominant topic of study in the aging and well-­being literature. Several recent theories propose that emotion regulation goals and the manner in which such goals are implemented shift with age, and that these shifts help to account for shifts in well-being. Socioemotional selectivity theory (SST; Carstensen, Fung, & Charles, 2003), for example, proposes that as temporal horizons shrink with increasing age, emotion regulation goals become more salient. As a result, older adults are more motivated to allocate greater resources to emotion regulation and use more effective strategies to regulate, leading to enhanced emotional well-being. The cognitive control hypothesis subsumed within SST accounts for agerelated cognitive decline, positing that older adults still require cognitive control for successful emotion regulation and thus older adults with preserved ­cognitive control should exhibit greater emotional well-being than those with lower cognitive control capacities (Mather & Carstensen, 2005). Consistent with predictions from SST, there is reliable evidence supporting age-related shifts in strategies used to regulate emotions (for a review see Mather, 2016), age-related decreases in future time perspective (Carstensen, Isaacowitz, & Charles, 1999; Gruhn, Sharifan, & Chu, 2016; Lang & Carstensen, 2002), age-related increases in motivation to regulate 70

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emotions (Carstensen et al., 1999; Lang & Carstensen, 2002), and a critical role of cognitive control in ­successful emotion regulation among older adults (Mather & Knight, 2005; Opitz, Lee, Gross, & Urry, 2014). However, there is inconsistent evidence for limited future time perspective as an underlying mechanism of positive emotional function in late adulthood (Charles & Carstensen, 2008; Lang & Carstensen, 2002). Rather, numerous studies indicate that limited future time perspective is associated with worse negative emotional outcomes (Allemand, Hill, Ghaemmaghami, & Martin, 2012; Gruhn et al., 2015; E.M.  Kessler & Staudinger, 2009; Ramsey & Gentzler, 2014). Thus, there may in fact be an increasing emphasis on emotion regulation with advancing age, but shrinking future horizons may not mediate effects of age on enhanced well-being. The selection, optimization, and compensation with emotion regulation framework (SOC-ER; Urry & Gross, 2010), an application of Baltes and Baltes’s (1990) selection, optimization, and compensation theory (SOC), offers a different explanation for how age-related shifts in emotion regulation lead to enhanced well-being. The SOC-ER framework suggests that older adults use alternative methods of emotion regulation that rely more heavily on resources that improve or are relatively preserved with age (e.g., social networking, predicting feelings of arousal) to compensate for losses of other resources (e.g., cognitive control). Support for this framework comes from findings indicating that in the wake of significant cognitive decline, older adults exhibit greater preference for and are more effective at implementing emotion regulation strategies that rely less on cognitive control processes than young adults (Allard & Kensinger, 2014b; Isaacowitz, Toner, Goren, & Wilson, 2008; Scheibe, Sheppes, & Staudinger, 2015). Combining aspects of the SST and SOC frameworks, strength and vulnerability integration theory (SAVI; Charles & Piazza, 2009) specifies several age-related strengths and weaknesses that appear to account for instances in which age confers affective benefits. Strengths identified include increased motivation to regulate emotions and shrinking perception of time left with age, whereas weaknesses include ability to regulate emotions in response to prolonged stressors that elicit high levels of arousal. SAVI extends upon tenets of SST and SOC by proposing that daily contexts in which emotions are experienced and regulated are integral to developing a complete understanding of age-related shifts in emotional well-being. Together,

SST, SOC-ER, and SAVI posit that aging should be associated with more effective emotion regulation contingent upon the availability of sufficient resources. These theories propose several age-related shifts in emotion regulation likely to play an integral part in contributing to emotional well-being in late adulthood (e.g., strategy shifts, cognitive decline). In contrast to emotion regulation, emotion dysregulation—defined broadly within this volume as any pattern of emotional experience and/or expression that interferes with appropriate goal-directed behavior and therefore disrupts and compromises adaptive life outcomes (Beauchaine, 2015)—has received little direct attention in the aging literature. Emotions can be considered dysregulated when they are functionally maladaptive in terms of either their short-term or long-term consequences, beginning with their immediate, context-dependent effects. However, even if immediately effective, patterns of emotion expression can be dysfunctional if their long-term costs outweigh their short-term benefits (Cole et al., 2017; Cole, Michel, & Teti, 1994). It is also important to consider that emotions are usually characterized as dysregulated only when repetitive patterns of emotional responding are maladaptive—not by a single instance in which a maladaptive response occurs. Considering symptoms of psychopathology can help to distinguish emotion dysregulation from competent emotion regulation. For instance, in the Diagnostic and Statistical Manual of Mental Disorders, 5th edition (DSM-5; American Psychiatric Association, 2013), emotional symptoms typically meet diagnostic criteria for various forms of psychopathology when they are disproportionate/excessive in the context in which they occur and endure for a prolonged period of time, thereby causing significant distress and impairing function across a number of life domains. Similarly, emotion dysregulation is characterized by emotional responses that endure despite regulation attempts, are context inappropriate, interfere significantly with behavioral function, and change too quickly or slowly in response to regulation e­fforts (Cole et al., 2017; Thompson, 1990). It is imperative to evaluate further the extent to which shifts in emotion regulation reflect emotion dysregulation to better understand their meaning and clinical relevance. Increasing focus on emotion dysregulation vis-à-vis clinically meaningful criteria should help produce a more objective, comprehensive view of aging effects on emotion regulation and emotional well-being. Given that emotion dysregulation refers to ­maladaptive patterns of emotional experience and

e­ xpression, in this chapter we start with a discussion of age-related shifts in emotion regulation processes, and how these shifts relate to immediate regulation goals and emotional outcomes. Understanding emotion regulation processes requires that we specify how resources used to regulate emotions shift with age, and how preferences for particular emotion regulation strategies shift with age. In the remainder of this chapter we therefore focus on clinically meaningful outcomes to more thoroughly identify and distinguish emotion dysregulation from competent regulation. We pay particular attention to (1)  contexts in which emotions are regulated, (2) effects of emotions on behavioral function, and (3) durations of emotions in response to regulation efforts. Given that development of psychopathology is often accompanied by problems with emotion dysregulation, our review concludes by examining how the etiology and presentation of psychopathology shift with age. Finally, we offer a synthesis of current findings, highlight gaps in the literature, and offer suggestions for future research.

Aging and Emotion Regulatory Processes

Understanding how emotion regulatory processes change with age is an important starting point for understanding relations between age and emotion dysregulation. The extent to which age changes are observed in immediate emotion regulation efforts provides some initial insight into how aging affects emotion dysregulation. General age-related shifts in emotion regulation are also tied strongly to appropriateness of emotional responses across contexts, effects of emotions on behavior, and the extent to which emotions resist change. To understand effects of aging on emotion regulation, we must first understand how the resources required for emotion regulation and emotion regulation strategy use shift with age.

Age Differences in Cognitive Control During Emotion Regulation

A primary resource needed for successful emotion regulation at most any age—including late adulthood—­ ­ is cognitive control (Mather & Carstensen, 2005; Mather & Knight, 2005; Urry & Gross, 2010). This notion may seem paradoxical given that age-related cognitive decline is well documented; older adults exhibit declines across a number of cognitive domains (Verhaeghen, 2011; Verhaeghen & Salthouse, 1997), as well as structural declines in brain regions critical to implementing cognitive control processes associated with successful emotion Whitmoyer and Prakash

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regulation (Fjell et al., 2009; Kryla-Lighthall & Mather, 2009; Ochsner & Gross, 2005). Nevertheless, several sources of evidence suggest that successful emotion regulation among older adults depends on the availability of cognitive resources and active use of cognitive control strategies (Kryla-Lighthall & Mather, 2009). First, older adults with better cognitive abilities are more effective at regulating their emotions. Greater executive function is associated with enhanced positivity during processing of emotional memories (Mather & Knight, 2005), increased resistance to declines in mood (Isaacowitz, Toner, & Neupert, 2009), and greater emotion regulation success (Opitz et al., 2014). Emotion dysregulation is also more common among older adults with compromised cognitive capacities—such as those with mild cognitive impairment (MCI) and Alzheimer’s disease (AD)—than among healthy older adults (Geda et al., 2008; Goodkind, Gyurak, McCarthy, Miller, & Levenson, 2010; Sturm et al., 2013). Additionally, how older adults process emotional information appears to depend on cognitive processing constraints. A bias toward positive emotional information is only observed when sufficient resources are available for goal-directed processing (Mather & Knight, 2005). Of note, older adults exhibit a bias toward negatively valenced emotional stimuli when cognitive resources are limited (Knight et al., 2007). The role of cognitive control in emotion regulation is typically assessed by examining correlations between cognitive measures and either self-reports or behavioral measures of emotion regulation, or by directly manipulating cognitive control during emotion regulation tasks. In such studies, computerized or pencil-and-paper neuropsychological tests, such as the Flanker task (Scheibe et al., 2015) and the Attentional Network test (Mather & Knight, 2005), are commonly used to index cognitive function. Direct manipulation of cognitive control occurs via placing constraints on cognitive resources such as attentional processing during emotion regulation (Knight et al., 2007). Self-report measures of  emotion regulation typically assess more stable characteristics of emotional function, whereas behavioral tasks can be used to provide information about functional relations between stimuli and elicited emotional responses under controlled conditions (Wilhelm & Grossman, 2010). Likely due to the increased level of control they permit, behavioral tasks are more commonly used to evaluate effects of cognitive control on emotion regulation success. During behavioral emotion regulation tasks, participants 72

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are usually asked to either upregulate or downregulate emotional responses to emotional stimuli such as pictures or film clips. Emotion regulation success in these tasks is typically defined by one’s ability to increase or decrease emotional responses over a short time interval, consistent with instructions (e.g., if instructed to decrease negative emotions in response to pictures, emotions during instructed regulation periods are less intense than emotions during passive observation of pictures). Emotional responses are typically assessed via self-report (e.g., “How strongly did you experience negative emotion?”) but may also be assessed via physiological measures such as skin conductance, heart rate, or neural activity (most commonly measured using electroencephalography [EEG] or functional magnetic resonance imaging [fMRI]) during emotion regulation. Recent reviews identify several brain regions, particularly in the prefrontal cortex (PFC), that play key roles in implementing cognitive control over emotion (Mather, 2016; Ochsner, Silvers, & Buhle, 2012). Four subregions of the PFC that are critical for cognitive control are most commonly implicated in both emotion regulation and its decline with age. These include the ventromedial prefrontal cortex (vmPFC), orbitofrontal cortex (OFC), anterior cingulate cortex (ACC), and dorsolateral prefrontal cortex (dlPFC; see Beauchaine & Zisner, 2017; Mather, 2016). Some studies show that older adults recruit the lateral PFC less than young adults, and that reduced recruitment is associated with less successful downregulation of negative emotions (Opitz et al., 2012; Winecoff, LaBar, Madden, Cabeza, & Huettel, 2011). In addition, less successful downregulation of amygdala activity is associated with poorer performance on cognitive measures (Winecoff et al., 2011). Such findings suggest that cognitive control plays an important role in emotion regulation among younger and older adults alike, but that older adults may be less successful at exerting cognitive control to regulate emotions than younger adults. This latter notion seems to conflict with findings of enhanced emotional well-being in late adulthood. More recent investigations offer some explanation for these seemingly discrepant findings. In a recent series of analyses, Allard and Kensinger (2014a, 2014b) examined age differences in timing and neural recruitment during downregulation of negative emotions in response to emotional film clips, focusing on average activation throughout the entirety of film clips, as well as activation during specific emotional clips. In contrast to initial findings indicating that older adults are less successful at

recruiting PFC regions to regulate emotions, these analyses revealed that older adults are as successful as young adults at recruiting the PFC to downregulate negative emotions, but that specific regions recruited vary by age. Older adults recruited more medial PFC regions, including the vmPFC and OFC, which are less susceptible to age-related decline than lateral PFC regions (Fjell et al., 2009). In contrast, young adults recruited more from lateral PFC regions. The timing of PFC recruitment also differed by age groups, such that older adults recruited from PFC regions only during emotional peaks of film clips, whereas young adults recruited from the PFC throughout the entirety of film clips. Thus, older adults may exert cognitive control more selectively than younger adults for purposes of emotion regulation and rely more on medial cognitive control regions as opposed to lateral regions that are more susceptible to age-related decline. These findings suggest that general declines in cognitive resources might not necessarily lead to difficulties in implementing emotion regulation, so long as compensatory mechanisms are intact. However, such age differences in PFC recruitment do imply that older adults engage differential strategies to regulate their emotions.

Shifting Emotion Regulation Strategies With Age

Consistent with findings of differential PFC recruitment during emotion regulation among older adults, strategies used to regulate emotions also shift with age. Since strategy choices have ramifications for emotion regulation success, understanding agerelated shifts in preferred strategies and their effectiveness is important for understanding whether shifts in emotion regulation patterns are adaptive or maladaptive (i.e., whether emotions are regulated or dysregulated). Although emotions may be regulated through either volitional or avolitional processes (Gyurak, Gross, & Etkin, 2011), very few behavioral studies examine the mechanisms of avolitional emotion regulation, most likely due to the difficulty of directly measuring such processes (Mauss, Bunge, & Gross, 2007). Thus, the aging literature has predominantly focused on the different ways in which emotions are volitionally regulated. According to Gross (2015), there are five families of strategies through which emotion generation may be volitionally regulated: by changing situations experienced (situation selection), by changing features of a situation (situation modification), by shifting attention to different features of a situation (attention

deployment), by modifying perception of a situation (cognitive change), and by modifying emotional ­reactions, such as thought suppression or expressive suppression (response modulation). Thus, various regulation strategies may be implemented either before (antecedent) or after (response focused) an emotion is generated. Among these, age-related differences have been examined in use of (1) cognitive reappraisal (i.e., a cognitive change strategy that involves reinterpreting perceptions of emotional stimuli), (2) thought/experiential suppression (i.e., a response modulation strategy in which thoughts and/or feelings are pushed down), (3) expressive suppression (i.e., a response modulation strategy in which outward expression of emotions is restrained), (4) attention deployment strategies such as distraction or selective attention (i.e., viewing only particular aspects of emotional stimuli), and (5) situation selection (sometimes referred to as avoidance; Gross & John, 2003; Mather, 2012; Prakash, Whitmoyer, Aldao, & Schirda, 2015; Scheibe et al., 2015; Schirda, Valentine, Aldao, & Prakash, 2016). One overarching theme in the aging literature is that older adults prefer passive strategies that do not involve direct confrontation with emotiongenerating stimuli, such that use of proactive strategies involving direct confrontation of negative emotions declines with age (Blanchard-Fields, Stein, & Watson, 2004; Etxeberria, Etxebarria, Urdaneta, & Yanguas, 2016; Lipovcan, Prizmic, & Franc, 2009; Scheibe et al., 2015; Yeung, Fung, & Kam, 2012). Given that the ability to effectively use proactive strategies declines in late adulthood, adopting use of passive strategies may compensate for shifts in available cognitive resources (Heckhausen, 2006; Urry & Gross, 2010). In support of this notion, disengagement from negative stimuli to selectively attend to positive emotional information appears to entail selective deployment of attentional resources. This is suggested by increased vmPFC and ACC activity among older adults who show increased positivity biases during passive viewing tasks (Brassen, Gamer, & Buechel, 2011; Jacques et al., 2010; Leclerc & Kensinger, 2011). These are the same PFC regions that older adults rely on more often than younger adults during emotion regulation tasks (Allard & Kensinger, 2014a,  2014b). Also, passive strategies are less demanding than more active strategies. Preliminary evidence suggests that (1) older adults exhibit less lateral PFC recruitment when using passive strategies than when using more active strategies (Allard & Kensinger, 2014b) and (2) preference for distraction is associated negatively with cognitive Whitmoyer and Prakash

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resources (Scheibe et al., 2015). Although passive regulation strategies are typically regarded as less ­effective than proactive strategies, they may nevertheless be more optimal for older adults who are motivated to limit negative experiences (Carstensen et al., 1999). Consistent with this notion, older adults appear to be more effective than younger adults at using passive strategies such as avoidance (Birditt, 2013) and attention deployment (Lohani & Isaacowitz, 2014). Among young adults, these strategies tend to be maladaptive, yet older adults’ tendency to implement attention deployment strategies is associated with reports of higher well-being and more positive mood (Isaacowitz et al., 2008; Scheibe et al., 2015). Additionally, some evidence suggests that age-related increases in more passive, repressive strategies to regulate emotions may be linked to reduced rates of psychopathology observed in late adulthood (Erskine, Kvavilashvili, Conway, & Myers, 2007). That older adults are able to regulate emotions using passive cognitive strategies suggests that such strategies may be a particularly efficient way of allocating available cognitive resources. Although there is fairly consistent evidence for increased use and effectiveness of disengagement strategies with age, evidence for reappraisal is more mixed, with some studies reporting increases with age (John & Gross, 2004; Peng, Tian, Jex, & Chen, 2017), others finding decreased use (Erskine et al., 2007), and others finding no age differences (Brummer, Stopa, & Bucks, 2014; Schirda et al., 2016). Part of this discrepancy appears to be attributable to different ways in which emotional stimuli can be reinterpreted via reappraisal. Two distinct reappraisal strategies have been identified and exhibit differential relations to aging: detached reappraisal (reinterpreting situations from an unemotional and distanced perspective) and positive reappraisal (reinterpreting a situation to emphasize positive outcomes). Notably, several self-report measures, such as the Emotion Regulation Questionnaire (Gross & John, 2003), fail to distinguish between these different means of reappraisal, and instead combine them into one general “cognitive reappraisal” strategy. At the same time, laboratory studies of emotion regulation often fail to distinguish among particular types of reappraisal that participants are asked to use. When focusing on studies in which positive and detached reappraisal strategies are distinguished, a clearer picture of age differences in reappraisal emerges. Detached reappraisal may rely more on 74

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cognitive control since it requires ignoring emotions, whereas positive reappraisal requires sustaining focus on emotions (Shiota & Levenson, 2009). Consistent with this view, initial evidence suggests that detached reappraisal is associated more strongly with cognitive control—specifically mental setshifting—than positive reappraisal (Liang, Huo, Kennison, & Zhou, 2017). Also consistent with this view are findings that detached reappraisal is used less frequently (Scheibe et al., 2015; Shiota & Levenson, 2009) and is less effective (Scheibe et al., 2015; Smoski, LaBar, & Steffens, 2014) among older adults, whereas most studies indicate that use and effectiveness of positive reappraisal increase with age (Garnefski & Kraaij, 2006; Lohani & Isaacowitz, 2014; Shiota & Levenson, 2009, but also see Schirda et al., 2016 and Nolen-Hoeksema & Aldao, 2011). Despite difficulties with detached reappraisal among older adults, positive reappraisal appears to be a more effective strategy to regulate negative emotions than suppression or attention deployment (Lohani & Isaacowitz, 2014) and is associated with wide-ranging benefits including better mental health and overall well-being (Kraaij, Pruymboom, & Garnefski, 2002; Nowlan, Wuthrich, & Rapee, 2015,  2016). Together, these findings indicate that aging is associated with increased reliance on positive reappraisal to regulate emotions, and that increased reliance on positive reappraisal may be an adaptive compensatory mechanism. Associations between positive reappraisal and emotional benefits among older adults suggest that its more frequent use may contribute to less emotion dysregulation among older adults. However, further investigation of positive reappraisal in daily life, and its relation to more long-term emotional goals, is required to substantiate this claim. As with reappraisal, the extent to which older adults prefer and are able to use different suppression strategies varies (Nolen-Hoeksema & Aldao, 2011; Peng et al., 2017; Schirda et al., 2016). Suppression refers to either pushing thoughts/feelings out of one’s mind (thought/experiential suppression) or hiding outward expression of emotion (expressive suppression). Although older adults are able to implement expressive suppression (Brummer et al., 2014; Magai, Consedine, Krivoshekova, KudadjieGyamfi, & McPherson, 2006; Peng et al., 2017; Phillips, Henry, Hosie, & Milne, 2008; Shiota & Levenson, 2009), thought suppression requires greater inhibitory control, and ability to implement this strategy appears to decline with age (Anderson,

Reinholz, Kuhl, & Mayr, 2011; Beadel, Green, Hosseinbor, & Teachman, 2013; Magee & Teachman, 2012). Of note, preference for each suppression strategy appears to depend on its effectiveness. Whereas frequency of expressive suppression increases with age (Brummer et al., 2014; Hofer, Burkhard, & Allemand, 2015; Peng et al., 2017), adults tend to use thought suppression less frequently as they age (Erskine et al., 2007; Prakash et al., 2015). However, despite fairly consistent behavioral evidence for preservation of expressive suppression ability with age (Hofer et al., 2015; Magai et al., 2006; Shiota & Levenson, 2009; Lohani & Isaacowitz, 2014), ­self-­report findings are more equivocal, and indicate that expressive suppression may be related to increased depressive symptoms and poorer well-being (Orgeta, 2011a; Gross & John, 2003) or, paradoxically, to increased affective well-being (Brummer et al., 2014; Peng et al., 2017). These contradictory findings may indicate that expressive suppression is effective initially for regulating emotions but has negative ramifications in the long run. However, further investigations into long-term consequences of expressive suppression are required to understand implications of increased use with age. In contrast, thought suppression is implicated consistently as a maladaptive emotion regulation strategy, and its  effectiveness appears to decline with age. Thus, reduced reliance on this strategy seems to be an adaptive approach to emotion regulation in late adulthood.

Understanding Emotion Dysregulation in Aging

The literature reviewed previously indicates clear age-related shifts in volitional processes associated with emotion regulation. As regulation strategy preferences shift to compensate for declining cognitive resources, engaged strategies nevertheless yield successful regulation of emotional responses. Although understanding emotion regulation offers an important starting point for specifying emotion dysregulation, we must also consider affect modulation in terms of (1) contexts within which emotional responses occur, (2) functional ramifications of regulated responses, and (3) the duration of emotional responses. In the next section, we provide an overview of these modulating factors.

The Role of Context in Emotion Dysregulation

Adaptive emotion regulation requires appropriate responses to varying contextual demands (see Cole

et al., 2017). Although there is solid evidence for age-related shifts in emotion regulation strategies, many studies neglect context. This is a significant oversight given that substantial shifts in context typically occur with age (e.g., retirement, reduced physical activity), along with physical declines that may be related to emotional functioning. Thus, the extent to which emotion regulation and particular emotion regulation strategies are adaptive or maladaptive across various contexts is poorly understood in the aging literature (Aldao, 2013). One context in which age differences in emotion regulation have been well studied is the context of stress and arousal. Studies that assess moderating effects of arousal on relations between emotion regulation and aging typically involve instructions to modify emotions while viewing emotional stimuli of varying arousal levels. In these studies, age-related improvements in emotion regulation appear to be greater for low-arousal stimuli than for higharousal stimuli (Dolcos, Katsumi, & Dixon, 2014; E.M. Kessler & Staudinger, 2009), as indicated by self-report (E.M. Kessler & Staudinger, 2009) and reduced amygdala reactivity as corroborated by self-report (Dolcos et al., 2014). Additionally, relative to younger adults, older adults show a greater bias toward neutral and low-arousing stimuli and away from high-arousal stimuli (Sands & Isaacowitz, 2017; Scheibe et al., 2015). This suggests that older adults may possess some awareness of their limited resources and use avoidance strategies to compensate. However, when unable to avoid such stimuli, older adults may be less effective at regulating their emotions. Still, emotion regulation is more difficult for higher arousal stimuli, regardless of age (Sheppes, 2014). Thus, it is difficult to determine from available data the extent to which emotion regulation difficulties are age related. When assessing whether emotional responses during stress and arousal are context appropriate or atypical, it is also important to consider how the experience of stressors in daily life shifts with age. Older adults experience fewer daily stressors than young adults (Brose, Scheibe, & Schmiedek, 2013; Neupert, Almeida, & Charles, 2007; Piazza, Charles, & Almeida, 2007) and exhibit less variability in the types of stressors they experience (Brose et al., 2013). Older adults may also exhibit less emotional reactivity to stressors (Brose et al., 2013; Neupert et al., 2007; Piazza et al., 2007), particularly in response to interpersonal stressors (Birditt, Fingerman, & Almeida, 2005). Age-related increases in affective well-being and reductions in daily stressors Whitmoyer and Prakash

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are linked to older adults’ reliance on avoidance strategies (see earlier), at least in contexts of interpersonal stress (Charles & Carstensen, 2008; Charles, Piazza, Luong, & Almeida, 2009). Thus, older adults’ reduced stress and stress reactivity may help to ­explain their increases in emotional well-being. However, age differences in reactivity to stress have not yet been linked directly to more global or longterm measures of emotional well-being. Additionally, similar to laboratory findings that older adults are less able to regulate emotions in response to higher levels of arousal (Dolcos et al., 2014; E.M. Kessler & Staudinger, 2009), older adults exhibit greater ­affective reactivity in response to more intense stressors than young adults (Mroczek & Almeida, 2004; Sliwinski, Almeida, Smyth, & Stawski, 2009; Wrzus, Mueller, Wagner, Lindenberger, & Riediger, 2013). Taken together, these findings suggest that relations between aging and emotion dysregulation may depend on both the frequency and intensity of stressors. Aging may be associated with adaptive emotion regulation patterns in response to less chronic and less intense/complex stress, but less adaptive emotion regulation in response to prolonged, intense stress. Although several studies have investigated age differences in emotion regulation in certain contexts, there is not a clear picture of how aging affects whether adaptive or maladaptive emotion regulation strategies are used across various contexts (i.e., the extent to which effective strategies across contexts differ with age). To our knowledge, only one study to date has examined this question. Using an idiographic contextual emotion regulation assessment (Aldao & Nolen-Hoeksema, 2012), we recently examined age differences in the use of several strategies across various emotion-eliciting contexts (emotion elicited, intensity of emotion, and situation type [social vs. achievement]; Schirda et al., 2016). Participants generated 24 personal situations that occurred over the preceding two weeks in a 3 × 2 × 4 matrix consisting of the levels of different contexts: intensity (low, moderate, high), emotions elicited (anxiety, anger, sadness, happiness), and ­situation type (social, achievement). Then, eight of these situations (selected quasi-randomly from the 24 situations generated) were presented back to participants that elicited each of the four types of  emotions at two of the intensities (moderate, high), and participants were asked to recall the emotion regulation strategies used in each of these situations. We then conducted factor analyses across the reported strategies to identify clusters 76

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of strategies in our sample. We uncovered three main factors: cognitive strategies (e.g., reappraisal, problem solving), maladaptive strategies (e.g., ­experiential suppression, expressive suppression, self-­criticism, thought avoidance, worry/rumination), and acceptance (i.e., allowing or accepting feelings) as its own unique factor. The results of our study provided support for the critical role of context in explaining age-related differences in strategy use. Compared to young adults, older adults reported greater use of acceptance strategies in situations of moderate intensity and in situations that evoked anxiety and sadness. In contrast, there were no age differences in use of  cognitive strategies. In addition, use of maladaptive strategies declined with age in high- and moderate-intensity situations and in situations evoking ­anxiety and sadness. Older adults’ reduced use of maladaptive strategies and increased use of acceptance strategies may suggest that aging is associated with more effective emotion regulation in response to situations eliciting moderate-intensity anxiety and sadness. However, maladaptive strategies were identified merely based on factor analysis and reference to previous literature, and no other measures of emotion regulation success or emotion dysregulation were collected. Given some evidence for age-related shifts in strategy effectiveness (e.g., Brummer et al., 2014; Lohani & Isaacowitz, 2014), clear links between aging and strategy effectiveness across various contexts cannot be inferred until results are replicated using more direct measures of emotion regulation.

Effects of Emotions on Behavior

To classify patterns of emotion regulation as functionally adaptive or maladaptive, aside from identifying whether they are context appropriate, it is important to specify behavioral consequences of emotional responses. As outlined previously, emotion dysregulation is often defined by any pattern of emotional experience and/or expression that interferes with appropriate goal-directed behavior (Beauchaine, 2015). Patterns of either positive or negative emotion can therefore be dysregulated if they lead to violations of social norms or compromise goals (Cole et al., 2017). Consistent with this conceptualization, relations between aging and effects of emotions on behavior can be assessed by examining emotion–behavior sequences, by studying how typical behavior under intense emotion differs across the lifespan, or by investigating how reactions to an initial emotional response lead to inappropriate be-

havior (see Cole et al., 2004). Some recent studies (e.g., Orgeta, 2009; Prakash et al., 2015) have ­examined age-related shifts in behavioral consequences of emotional responses via self-report. These studies reveal age-related declines in effects on goal-directed behavior when individuals are upset. Both studies used the Difficulties in Emotion Regulation Scale (DERS; Gratz & Roemer, 2004), which assesses characteristic reactions during the experience of intense emotions. To date however, assessment of relations between emotions and behavior among older adults has predominantly examined effects of emotion on more specific behaviors such as decision making, cognitive task performance, and responding to interpersonal conflict. Although older adults’ tendency to increase ­engagement with positive emotional material and disengage from negative material (see earlier) seems to serve adaptive purposes in terms of immediate mood regulation, there is some concern that such strategies could interfere with decision making. For example, such strategies may lead to overweighting positive information and underweighting negative information, producing suboptimal choices. Decision-making biases have most commonly been explored in contexts of health outcomes, as such decisions become especially important in light of increased chronic illnesses in older age. A bias toward positive information could limit health-related information seeking in older adults (Löckenhoff & Carstensen, 2004). Consistent with this hypothesis, when reviewing health-related information without specific instructions, older adults review and recall more positive than negative information about skin cancer, physicians, and health care plans (Isaacowitz & Choi, 2012; Löckenhoff & Carstensen, 2007). However, these age differences are eliminated when both older and younger adults are given instructions that elicit information-gathering goals (Isaacowitz & Choi, 2012; Löckenhoff & Carstensen, 2007). Additionally, when given instructions to review information with the goal of managing emotions, older adults typically look less at negative content, more rapidly regulate their moods, and when making decisions are less affected than young adults (Isaacowitz & Choi, 2012). This suggests that age-related shifts that are considered to be beneficial for emotional well-­being may limit health-related information seeking and influence attention, memory, and decision making. However, effects on information seeking and decision making seem to be attributable largely to age-related goals, and can be eliminated by simple motivational manipulations.

In contrast to limiting effects of older adults’ emotion regulation goals on decision making, increased motivation to regulate emotions appears to benefit older adults’ behavior in social settings. Biases toward more positive aspects of close relationships in late adulthood lead to a selective narrowing of social networks (English & Carstensen, 2014). Older adults report deciding to actively discontinue social relationships primarily as a function of reduced interest in these relationships (Lang, 2001), and emotion plays an increasingly central role in determining the relationships that receive continual investment in later life (Lang, Wagner, Wrzus, & Neyer, 2013). This selective pruning process appears to serve as an antecedent form of emotion regulation as longitudinal evidence indicates that social network reductions are primarily observed in the number of peripheral members, and cross-sectionally, older adults report that social network members elicit less negative and more positive emotion, which in turn predicts more positive daily emotional experience (Carstensen, Gross, & Fung, 1997; English & Carstensen, 2014). Such selectivity—along with age-related increases in motivation to regulate emotions—may also enable older adults to exhibit more adaptive behavior in social contexts even amid conflict. Preliminary evidence seems to support this notion. When attempting to resolve interpersonal problems, older adults use a more diverse repertoire of strategies that are more closely tailored to problem-solving contexts at hand, including the domain of the problem and the types of emotions elicited (Blanchard-Fields et al., 2004; Hoppmann & Blanchard-Fields, 2010). In contrast, younger adults prefer active problem-solving strategies (Blanchard-Fields, Chen, & Norris, 1997). When solving emotionally salient interpersonal problems, older adults use more passive emotion regulation strategies and experience less anger (Blanchard-Fields et al., 2004; Blanchard-Fields & Coats, 2008), consistent with findings of reduced affective and physiological reactivity to negative social interactions with increasing age (Luong & Charles, 2014). Older adults also more effectively employ strategies, particularly when responding to interpersonal problems (Blanchard-Fields, 2009; BlanchardFields, Mienaltowski, & Seay, 2007). Thus, it seems that older adults’ increased consideration of emotional context when resolving interpersonal problems may help them respond more effectively. However, it is possible that age-related reductions in the i­ntensity of emotions produced by these negative social interactions could be confounding results given that older Whitmoyer and Prakash

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adults report less anger (a high-arousal emotion). Replication using more salient mood inductions may be required to rule out this possibility. One common way to investigate effects of emotions on behavior is to evaluate emotion regulation during performance of neuropsychological tasks that assess cognitive constructs such as working memory and processing speed (see earlier). Such investigations reveal that cognitive performance is less affected by emotion regulation efforts among older versus younger adults. When instructed to downregulate feelings of disgust following mood induction, older adults exhibit increased working memory performance, whereas young adults exhibit decreased performance (Scheibe & Blanchard-Fields, 2009). Similarly, engaging in expressive suppression during a memory task led to reduced memory for emotional stimuli only in young adults (Emery & Hess, 2011). Healthy older adults’ performance on cognitive tasks also appears to be less affected by anger and regret (Brassen, Gamer, Peters, Gluth, & Büchel, 2012). In this study, age-related decreases in responsivity to regret were paralleled by increases in ACC activity and more reward-specific striatal activation, suggesting adaptive shifts in emotion regulation with age. Nevertheless, laboratory investigations require replication across a broader array of cognitive domains and emotionally salient contexts.

Duration of Emotions

Given that effective emotion regulation depends on modulating emotional responses in the service of long-term and short-term goals, another important consideration for distinguishing shifts in emotion dysregulation is the duration of emotions during and following regulation efforts. Emotions may change too slowly in response to modification efforts, indicating poor emotional recovery, or too abruptly, indicating lability. Emotions become dysregulated when they resist change to the point of impairing function (Cole et al., 2017; Thompson, 1990). Unfortunately, there is a dearth of research examining the extent to which temporal dynamics of emotion are affected by aging. Only a few studies have examined such temporal processes, all within contexts of relatively brief mood inductions in laboratory settings. Following a 10-minute anger induction and a 10-minute sadness induction, young adults reported longer durations of shame, contempt, and joy than older adults (Magai et al., 2006). Older adults were also better at suppressing emotions during an inhibition condition than younger adults. Similarly, following negative emotion induction, older adults 78

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more rapidly regulate their reactions than younger adults (Larcom & Isaacowitz, 2009). Among older adults, more rapid emotion regulation was associated with lower trait anxiety and fewer depressive symptoms, and older adults who rapidly regulated their emotions reported increases in positive affect that persisted 20 minutes later. No such effect was found for younger adults. These findings suggest that among older adults, emotion regulation may be more rapid and enduring than among young adults. In seeming contrast to these findings, a third study found that when placed in a rumination condition, older adults did not exhibit more rapid emotion recovery than younger adults, and even exhibited delayed blood pressure recovery (Robinette & Charles, 2016). Findings from this study highlight the ­important role that regulation strategies play in age differences in emotion dysregulation and suggest there may be age-specific vulnerabilities related to particular types of emotion regulation strategies. Taken together, these studies offer preliminary evidence for older adults’ ability to more rapidly regulate emotions than younger adults, and for possible age-specific benefits to such rapid regulation. However, the strategies and biological processes underlying these age differences in regulation and recovery, as well as the broader effects of such age-related shifts on functioning, are currently poorly understood.

Aging and Psychopathology

A final way of estimating effects of aging on emotion dysregulation is to examine age differences in the etiology and presentation of psychopathology. As noted previously, emotion dysregulation is a prominent characteristic of most psychiatric disorders (Beauchaine & Zisner, 2017; Kring & Sloan, 2009). In most epidemiological studies, rates of psychiatric disorders decrease with age, particularly anxiety, mood, and substance use disorders (Hasin et al., 2005; R.  C.  Kessler et al., 2005; Reynolds et al., 2015), with the lowest 12-month and lifetime prevalence rates for mood and anxiety disorders seen among those above age 65 (Hasin et al., 2005). Among older adults specifically, increased anxiety (Orgeta, 2011a) and depressive (Orgeta, 2011b) symptoms are associated with greater self-reported difficulties regulating emotional responses. Thus, ­although older adults generally exhibit lower rates of psychopathology than younger adults, aging may lead to changes in the experience and causes of certain psychiatric disorders, particularly depression and anxiety.

Late-life depression is one clinical issue that has received particular attention in the aging literature. Depression presents differently among older adults than younger adults, and may be more detrimental. Older adults often endorse fewer affective symptoms and are more likely to report cognitive changes, somatic symptoms, and loss of interest (Fiske, Wetherell, & Gatz, 2009). Late-life depression is also associated with more self-neglect, as well as higher rates of suicidal ideation, attempts, and completion relative to depression in younger adults (Blazer, 2003). Also of note, the majority of depressed older adults have their first episode after age 60 (Brodaty et al., 2001; Bruce et al., 2002; Fiske et  al., 2009), which suggests that age-specific vulnerabilities and risk factors contribute. For example, both aging and depression are associated with neuroendocrine dysregulation such as hypersecretion of corticotropin-releasing factor (CRF) and lower testosterone levels (Alexopoulos, 2005; Blazer & Hybels, 2005). Age-related neuroendocrine dysregulation may compromise the integrity of frontostriatal brain networks, increasing vulnerability to depression. In addition, reduced white matter integrity, greater declines in hippocampal volume, and Lewy bodies are more common among patients with late-life versus early-life depression (Fiske et al., 2009; Krishnan, 2002; Sachs-Ericsson et al., 2013; Tsopelas et al., 2011). Vascular damage, more commonly seen in late life, can also influence neural connectivity in frontostriatal and frontolimbic pathways that are involved in emotion regulation and may contribute to depressive symptoms (Taylor, Aizenstein, & Alexopoulos, 2013). Still, further research is necessary to link such declines to disruption in emotion regulation and establish temporal precedence of age-related declines in their relationship to symptoms. Although they have received less attention, anxiety disorders are the most common form of psychopathology experienced by older adults (R. C. Kessler et al., 2005). Anxiety commonly co-occurs with depression and predicts both incident and recurrent depressive symptoms in older adults (Potvin et al., 2013). Among older adults, anxiety is tied to increased use of maladaptive active emotion regulation strategies (Orgeta & Orrell, 2014) and reduced use of adaptive emotion regulation strategies such as positive reappraisal (Nowlan et al., 2016). Although presentation of anxiety is similar across the lifespan, there are a few notable shifts with age. Older adults with anxiety disorders worry more about health and disability and less about work and finances than

younger adults (Diefenbach, Stanley, & Beck, 2001). Additionally, much like depression, anxiety in older adults more often manifests as somatic symptoms and is associated with several medical conditions (Alwahhabi, 2003; Turnbull, 1989). Unfortunately, much of this evidence for age differences in the experience of anxiety is inferred via comparing symptom rates across studies, and there is a dearth of empirical evidence directly comparing older adults to younger adults within the same study (Wolitzky-Taylor, Castriotta, Lenze, Stanley, & Craske, 2010).

Synthesis

The aging literature paints a fairly positive picture of emotional well-being in late adulthood. For the most part, aging is associated with more adaptive patterns of emotion regulation. However, there are some moderating variables and exceptions. The extent to which aging is related to emotion dysregulation appears to depend on availability of resources and contexts in which regulation efforts occur. Aging brings about physical and neurocognitive declines that may lead to difficulty regulating emotions in response to prolonged, highly arousing stressors, and that may impair one’s ability to use cognitively demanding strategies that are adaptive among young adults. Although somewhat speculative, such declines may contribute to development of anxiety and depressive disorders in late adulthood—even though such disorders are generally less common among older adults. These declines are consistent with predictions about emotion regulation success depending on the availability of resources made by SST, the SOC-ER, and the SAVI model. However, also consistent with SAVI and SST, aging is related to increased prioritization of emotional goals; ­increased ability to regulate emotions over short intervals of time in response to acute, low-arousal stressors and interpersonal stressors; and increased ability to engage in several goal-directed behaviors under intense emotions. Age-related shifts in strategies used to regulate emotions are also observed, such that older adults rely more on less cognitively demanding strategies and selectively limit their ­exposure to intense negative stimuli. Thus, consistent with the SOC-ER framework, older adults appear to rely on more preserved processes to compensate for reduced cognitive resources and in turn optimize emotion regulation processes. However, motivations to disengage from negative stimuli may have some negative implications for decision making. Whitmoyer and Prakash

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Although the majority of the aging literature to date has focused on adaptive rather than maladaptive emotion regulation processes, age-related shifts in the effectiveness of emotion regulation have clear implications for emotion dysregulation. With regard to context, older adults appear to exhibit more adaptive emotional responses to acute, low-arousal emotional stimuli than young adults (particularly when allowed to use preferred strategies). However, in contexts of prolonged, high-arousal stressors and contexts in which constraints are placed on cognitive resources, older adults may be less effective at regulating their emotional responses. With regard to the effects of emotion on behavior, older adults seem to exhibit more adaptive behavioral responses in social settings and on cognitive performance tasks during the experience of intense emotions than younger adults. However, increased motivation to regulate emotions among older adults also appears to interfere with decision making. Finally, when considering durations of emotion, there is preliminary evidence that older adults are able to more rapidly regulate than younger adults, and that among older adults specifically, more rapid emotion regulation is related to better long-term emotional well-being.

Future Directions

Despite numerous theoretical frameworks that help to account for age differences in emotion regulation, there is still much to be understood about the effects of aging on emotion dysregulation. Although studies suggest that context moderates the effectiveness of emotion regulation efforts, emotion regulation has been explored in a limited number of contexts. As a result, there is poor understanding of the extent to which aging influences the appropriateness of emotions and regulation ability across daily life contexts outside of social settings, or how specific age-related shifts in emotion dysregulation relate to clinically relevant shifts in behavioral function. To address these gaps, future studies should assess emotion regulation shifts across a broader variety of relevant contexts (e.g., work/achievement, family life, and various health contexts), and should more thoroughly examine effects of emotion regulation on relevant measures of functional consequences (e.g., ability to complete independent activities of daily living) and clinically significant changes in psychopathology. Another gap in the literature concerns the extent to which temporal processes of emotion regulation shift with age. First, there is poor understanding of 80

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the temporal precedence of contextual factors ­related to emotion regulation. For instance, despite reported associations between age-related physical and neurocognitive declines and various metrics of emotion dysregulation such as increased psychopathology and increased use of maladaptive emotion regulation strategies, almost no longitudinal data address age-related declines as causes of emotion dysregulation. It is conceivable that emotion dysregulation precedes physical declines, especially given findings that emotional processes mediate health behavior effects on physical function late in life (Depp, Vahia, & Jeste, 2010). Second, long-term implications of short-term emotion regulation success remain unclear. Although adaptive in the short term, it is possible that passive and avoidant strategies preferred by older adults have detrimental long-term effects on behavior or emotion. To improve our understanding of such effects, future work should incorporate longitudinal designs that permit assessment of directionality in relations between emotion dysregulation and factors hypothesized to underlie age-related shifts in emotion dysregulation, such as changes in emotional goals, strategy use, and neurocognitive function. Studies of such relations should be conducted at multiple levels of analysis (self-report, behavioral, and physiological) to corroborate findings and rule out ­potential confounds. Finally, despite numerous examinations of how volitional (explicit) emotion regulation processes shift with age, the extent to which aging affects avolitional (implicit) emotion regulation is unknown and warrants direct investigation in future studies. Overall, these gaps indicate that there is still much to learn about how aging affects processes through which emotions become dysregulated. Given the central role of emotion dysregulation in psychopathology, clarifying such processes may help to identify more accurate, relevant targets for treating psychiatric disorders across the lifespan. Thus, it will be important for future studies to more thoroughly evaluate long-term functions of emotions and their modulation across the lifespan to better understand how specific aging processes may ameliorate or lead to dysfunctional patterns of emotion dysregulation.

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processes: Findings from two measurement-burst diary studies. Psychology and Aging, 24, 828–840. Smoski, M. J., LaBar, K. S., & Steffens, D. C. (2014). Relative effectiveness of reappraisal and distraction in regulating emotion in late-life depression. American Journal of Geriatric Psychiatry, 22, 898–907. Sturm, V.  E., Yokoyama, J.  S., Seeley, W.  W., Kramer, J.  H., Miller, B. L., & Rankin, K. P. (2013). Heightened emotional contagion in mild cognitive impairment and Alzheimer’s disease is associated with temporal lobe degeneration. Proceedings of the National Academy of Sciences, 110, 9944–9949. Taylor, W. D., Aizenstein, H. J., & Alexopoulos, G. S. (2013). The vascular depression hypothesis: Mechanisms linking vascular disease with depression. Molecular Psychiatry, 18, 963–974. Thompson, R.  A. (1990). Emotion and self-regulation. In R. A. Thompson (Ed.), Nebraska Symposium on Motivation: Vol. 36. Socioemotional development (pp. 383–483). Lincoln, NE: University of Nebraska Press. Tsopelas, C., Stewart, R., Savva, G.  M., Brayne, C., Ince, P., Thomas, A., . . . Medical Research Council Cognitive Function and Ageing Study. (2011). Neuropathological correlates of late-life depression in older people. British Journal of Psychiatry, 198, 109–114. Turnbull, J. M. (1989). Anxiety and physical illness in the elderly. Journal of Clinical Psychiatry, 50, S40–S45. Urry, H.  L., & Gross, J.  J. (2010). Emotion regulation in older  age. Current Directions in Psychological Science, 19, 352–357. Verhaeghen, P. (2011). Aging and executive control: Reports of a demise greatly exaggerated. Current Directions in Psychological Science, 20, 174–180. Verhaeghen, P., & Salthouse, T.  A. (1997). Meta-analyses of age-cognition relations in adulthood: Estimates of linear and nonlinear age effects and structural models. Psychological Bulletin, 122, 231–249. Wilhelm, F. H., & Grossman, P. (2010). Emotions beyond the laboratory: Theoretical fundaments, study design, and analytic strategies for advanced ambulatory assessment. Biological Psychology, 84, 552–569. Winecoff, A., LaBar, K.  S., Madden, D.  J., Cabeza, R., & Huettel, S. A. (2011). Cognitive and neural contributors to emotion regulation in aging. Social Cognitive and Affective Neuroscience, 6, 165–176. Wolitzky-Taylor, K.  B., Castriotta, N., Lenze, E.  J., Stanley, M. A., & Craske, M. G. (2010). Anxiety disorders in older adults: A comprehensive review. Depression and Anxiety, 27, 190–211. Wright, C. I., Negreira, A., Gold, A. L., Britton, J. C., Williams, D., & Barrett, L. F. (2008). Neural correlates of novelty and face-age effects in young and elderly adults. NeuroImage, 42, 956–968. Wrzus, C., Mueller, V., Wagner, G.  G., Lindenberger, U., & Riediger, M. (2013). Affective and cardiovascular responding to unpleasant events from adolescence to old age: Complexity of events matters. Developmental Psychology, 49, 384–397. Yeung, D. Y., Fung, H. H., & Kam, C. (2012). Age differences in problem solving strategies: The mediating role of future time perspective. Personality and Individual Differences, 53, 38–43.

CH A PT E R

7

Emotion Generation, Regulation, and Dysregulation as Multilevel Transdiagnostic Constructs

Sheila E. Crowell, Robert D. Vlisides-Henry, and Parisa R. Kaliush

Abstract Emotion generation, regulation, and dysregulation are complex constructs that are challenging to define and measure. This chapter reviews prevailing definitions and theories of these constructs and examines the literature across multiple levels of analysis. It adopts a developmental perspective, which guides interpretation of the literature and helps clarify discrepant points of view. The extent to which emotion generation and regulation are separable represents a significant controversy in the field. When viewed as cognitive constructs, it is virtually impossible to disentangle emotion generation and regulation. However, at the biological level, there are important differences in neural structures involved in bottom-up emotion generation processes versus those associated with top-down regulation of emotions. From a developmental perspective, emotions and emotion dysregulation emerge early in life, whereas emotion regulation strategies develop more gradually as a function of maturation and socialization. Future research should continue to reconcile different perspectives on emotion generation, regulation, and dysregulation. Keywords:  emotion dysregulation, transdiagnostic, development, emotions, multiple levels of analysis

Introduction

Philosophers, psychologists, and laypeople have long sought to understand and define emotions. Not surprisingly, this has led to many divergent perspectives on emotions—their universality, evolutionary functions, underlying neural mechanisms, physiological and behavioral signatures, and interactions with motivation and cognition. Most definitions of emotion and related processes have limitations, leading to debate in the field. This has yielded a rich and complex literature on emotion, which is among the most researched topics in psychology. Emotion regulation and dysregulation can also be challenging to define and measure. As a result, emotion regulation researchers have developed creative paradigms to capture what happens when we attempt to control or suppress emotions, reappraise or re-evaluate their meaning, amplify them, or simply let them run their natural course. Importantly, emotions are such an integral part of human experience that

when emotional processes become dysregulated, consequences can be costly. Emotional development begins in utero, with facial expressions of distress becoming increasingly complex and frequent across the third trimester (Reissland, Francis, & Mason, 2013). Thus, expressions of pain and discomfort begin before birth and therefore likely confer significant adaptive benefit for all infants. Individual differences in emotional expression also emerge early in development. Variation in intensity, duration, and soothability of negative emotion may be one index of early temperament (e.g., Johnson, Posner, & Rothbart, 1991). Several interacting and independent factors affect these temperamental differences. For example, specific genetic variants underlie aspects of early temperament, contributing to heritable differences in trait impulsivity and trait anxiety (Beauchaine, Zisner, & Sauder,  2017; Sallis, Davey Smith, & Munafò,  2018). Researchers have also begun to 85

e­xamine epigenetic effects as mechanisms of early temperament (Conradt, Adkins, Crowell, Monk, & Kobor, 2018). Epigenetics, defined by alterations to gene expression rather than gene structure, represent one type of Gene × Environment interaction that contribute to early emerging individual differences in emotional processes (see Chapter 16, this volume). By birth, postnatal environments begin to shape emotional expression through Temperament × Caregiving interactions, which lay a foundation for emotion regulation and dysregulation. Thus, emotion generation, regulation, and dysregulation are developmental processes that result from complex transactions across multiple levels of analysis beginning at conception. In this chapter, we review emotion and related constructs from a developmental perspective. This helps clarify discrepant empirical findings and theories that emerge when researchers investigate emotional processes cross-sectionally or within relatively narrow developmental windows (e.g., adolescence). Indeed, when environments are constrained, such as in early development, there are fewer influences on emotional processes and, consequently, biological predispositions take precedence. Over time, socialization, family and peer dynamics, cultural factors, exposure to interventions, and many other forces interact to affect emotion-related processes. Consistent with the developmental psychopathology perspective (Beauchaine, Constantino, & Hayden, 2018; Cicchetti, 1984, 1993), taking a lifespan approach helps elucidate continuities and discontinuities in risk/resilience trajectories and potential points for intervention.

Terms and Concepts Emotion Generation

For the past half century of psychological research, scholars have typically conceptualized emotions as a multilevel process, emerging from rapid feedback between physiological and cognitive systems. For example, Schachter and Singer (1962) described emotion generation in two steps: First, physiological arousal occurs; then, a person evaluates whether that arousal is consistent with observable stimuli. If a person perceives a match, he or she can label that experience in terms of readily available cognitions (e.g., my heart is racing and I am about to receive a shock; therefore, I am anxious). However, if there is dissonance between arousal and perception, the person may need to search for alternate explanations to describe an experience appropriately (e.g., too much caffeine). This two-step model continues 86

to inform the literature today—many scholars still view emotional processes as emerging from interactions between physiology and cognitions (see, e.g., Gross, 2015). Importantly, however, Schachter and Singer’s conceptualization does not account fully for individual differences in emotion generation and expression early in life, that is, prior to developing cognitive schemas needed to label and categorize emotional reactions. More recently, distinctions between emotion generation and regulation have become a source of ongoing debate in the field. According to one perspective, emotion generation is affected by appraisals, or the extent to which an emotional stimulus (1) captures a person’s attention and (2) is given meaning (Gross, 2015). In other words, for an emotion to emerge, a person must attend to and appraise a stimulus in some manner, even if that process occurs automatically and outside of conscious awareness. This “situation–attention–appraisal–response” perspective has been articulated in many foundational theoretical papers (Gross,  1998,  2015; Gross & Feldman Barrett, 2011; McRae, Misra, Prasad, Pereira, & Gross,  2011; Gross, Sheppes, & Urry,  2011; Ochsner et al., 2009; see Chapter 10, this volume). This perspective offers an advantage of identifying distinct and separable elements of the emotion ­generation process, each of which could be amenable to regulation. In an alternate theoretical perspective, Panksepp and colleagues define emotion generation as a biologically driven process that emerges from coordinated interactions between subcortical and neocortical regions (Panksepp,  1982,  1998; Panksepp & Watt, 2011; see Chapter 2, this volume). According to this theory, primary emotions originate within subcortical structures, which have been preserved evolutionarily across species (see also Beauchaine, 2015a). These primary emotions are not shaped by environmental inputs, prior learning, or appraisals. Rather, their principal function is to stimulate motivated behaviors, such as those that allow an organism to acquire new skills, maintain homeostasis, survive, and reproduce (Panksepp & Watt,  2011). Consequently, neural structures involved in primary emotion generation are essentially indistinguishable from circuits involved in movement, approachor  avoidance-related motivation, and reward (Beauchaine et al.,  2017). Across development, ­primary emotions become associated with specific contexts, stimuli, or patterns of stimuli. This leads to secondary emotion processes, which are characterized by learned associations between primary emotions

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and life experiences. Because environments vary widely, secondary emotional processes are necessarily more complex and variegated. Finally, tertiary emotions reflect dynamic interactions between neural systems involved in (1) primary and secondary emotions and (2) higher order processes, such as language, consciousness, and self/identity (Panksepp, 1998). Secondary and tertiary emotions rely on neocortical systems and structures—the top layer of the cerebral hemisphere that is involved in higher order functions—which are largest and most fully developed in primates. According to this perspective, emotion regulation is believed to reflect effective secondary and tertiary processes, whereas dysregulation is believed to reflect ineffective secondary and tertiary processes (see Chapter 2 for a more thorough review). More recently, Beauchaine and Zisner (2017) articulated an integrated theory of motivation, emotion regulation, and psychopathology that incorporates key elements of Gross’s (cognitive neuroscience) and Panksepp’s (basic neuroscience) perspectives as well as several independent lines of psychological and biological research. In this review and others, Beauchaine has extended neuroscientific findings to  the broader developmental psychopathology literature, placing greater emphasis on longitudinal transactions between basic motivational tendencies and potentiating environmental experiences (Beauchaine,  2001,  2012,  2015a; Beauchaine & Zisner,  2017; Beauchaine et al.,  2017). According to  this perspective, individual differences in basic motivational tendencies are driven by “bottom-up emotion generation systems,” which are largely subcortical. A primary function of emotion generation systems is to activate appropriate behavior in response to motivationally salient cues. Specifically, these neural response patterns function to motivate approach (wanting/liking) or avoidance (anxiety) behaviors and to resolve basic approach–avoidance, approach–approach, or avoidance–avoidance conflicts (see also Corr,  2013). Biologically mediated individual differences in approach and avoidance motivation form a basis for temperament, and may give rise to psychopathology at their extremes (e.g., Sutton & Davidson, 1997). Trait anxiety, an extreme manifestation of avoidance motivation or behavioral inhibition (e.g., Kagan,  2017), involves apprehensiveness about ­approaching stimuli. High behavioral inhibition is associated with altered connectivity between the amygdala and regions of the prefrontal cortex (PFC) and anterior cingulate cortex (ACC; e.g., Beauchaine

& Zisner, 2017; Felix-Ortiz, Burgos-Robles, Bhagat, Leppla, & Tye, 2016; Monk et al., 2008). Perhaps unsurprisingly, trait anxious individuals are at elevated risk for internalizing psychopathology, ­ including depressive and anxiety disorders (e.g., ­ Beauchaine & Thayer, 2015; Weems et al., 2007). In contrast, trait impulsivity, or extreme approach motivation and trait exuberance (e.g., ­ Dollar, Stifter, & Buss, 2017), is linked to risk for externalizing disorders (Beauchaine,  2015a). Impulsive individuals show less functional connectivity between mesolimbic structures and the PFC (e.g., Beauchaine & Zisner, 2017; Trost et al., 2014). Trait impulsivity is associated with concurrent and prospective risk for attention deficit hyperactivity disorder (ADHD), conduct disorder, and criminal activity (e.g., Beauchaine et al.,  2017; Blonigen, Hicks, Krueger, Patrick, & Iacono,  2005; Swann, Bjork, Moeller, & Dougherty,  2002). Similar to Panksepp, Beauchaine attributes emotion generation processes to subcortical structures. However, by incorporating motivational theories and, specifically, individual differences in behavioral approach and avoidance, Beauchaine’s theory bridges basic neuroscience research on emotion with developmental psychopathology theories. Importantly, and similar to both Panksepp and Gross, Beauchaine acknowledges that emotion regulation involves “top-down emotion regulation systems,” which are cortically mediated.

Emotion Regulation

To date, researchers have used a range of definitions of emotion regulation, and there is ongoing debate in the field. Some view emotion regulation as largely distinct from emotion generation (e.g., Beauchaine & Zisner,  2017), whereas others contend that the two cannot be disentangled (e.g., Gross,  1998). Nonetheless, across these disparate perspectives lies an overarching, mostly agreed-upon definition: Emotion regulation reflects processes through which people use top-down cortical mechanisms to identify, select, implement, and monitor how emotions are experienced and/or expressed in relation to personal goals (Beauchaine,  2015a; Beauchaine & Zisner, 2017; Gross, 1998; Thompson, 1993). Steps involved in emotion regulation have been articulated in several theoretical and empirical papers by Gross and colleagues (e.g., Gross,  1998,  2015; Gross & Feldman Barrett,  2011; McRae et al.,  2011), who propose that emotion regulation strategies can be identified at distinct points along a timeline of an unfolding emotional response. Regulation can occur

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before an emotion begins (antecedent focused) or once it has become activated (response focused). Response-focused regulation involves several steps, beginning with emotion identification. In brief, identification has two substeps: recognizing a generated emotion and deciding whether or not to regulate it. If one decides to regulate, selection follows. Selection involves choosing an emotion regulation strategy based on context and ­personal goals. That is, different situations warrant different regulation strategies. For instance, emotion regulation in anticipation of a job interview likely differs from regulation in response to encountering a dangerous animal in the woods. Implementation entails translating a chosen emotion regulation strategy into specific tactics. Finally, monitoring involves ongoing evaluation of regulation, where a person decides whether to maintain, change, or stop an emotion entirely. Gross (2015) describes monitoring as an ongoing process that is constantly acting upon emotion generation processes. For more details on these emotion regulation steps, see Jazaieri, Uusberg, Uusberg, and Gross (Chapter 10 of this volume). Emotion regulation is, by nature, difficult to measure because it is often conceptualized as the absence of emotional problems (Cole, Martin, & Dennis,  2004). Therefore, researchers rely on complex paradigms or self-report measures to determine (1) whether a person experienced an emotion and (2) whether the emotion was  regulated (Beauchaine,  2015a; Cole, Hall, & Hajal, 2017).

Emotion Dysregulation

Emotion dysregulation, in contrast, is often easier to observe and measure (see Beauchaine, 2015a). In this Handbook, we define emotion dysregulation as patterns of emotional experience and expression that are too intense, labile, rigid, or prolonged or that interfere with appropriate goal-directed or interpersonal behavior (Beauchaine,  2015a; Cole et al., 2004; Gratz & Roemer, 2004). As noted earlier, emotional expressions and sensations emerge early in development—beginning prenatally (Kurjak, Azumendi, Andonotopo, & Salihagic-Kadic, 2007)—­ and serve adaptive communicative and survival functions at birth (Abe & Izard, 1999). Therefore, emergent signs of emotion dysregulation may also have origins prior to birth. Importantly, emotion dysregulation is not merely the opposite or absence of regulation (Cole et al., 2004, 2017). As noted previously, emotion regulation involves conscious or automatic activation of a goal to influence emotions, which 88

can happen within a person (intrapersonally) or b­ etween people (interpersonally; Sheppes, Suri, & Gross,  2015). Although some emotion regulation strategies emerge early in development (e.g., thumb sucking; Eisenberg, Spinrad, & Eggum, 2010), most are shaped through coregulation and socialization— becoming increasingly sophisticated, cognitively mediated, and independent across development (Vohs & Baumeister,  2016). Thus, early signs of emotion dysregulation (e.g., expressions of emotion that are more intense than typical, age-normative distress) likely emerge earlier in development than emotion regulation. From a developmental perspective, emotion dysregulation is likely tied closely to emotion generation, especially early in life. Accordingly, individual differences in neural functions of motivational ­systems that subserve generation of approach and avoidance emotions may heighten risk for emotion dysregulation in two ways: (1) directly, due to temperamental differences in emotional intensity or ­duration, and/or (2) indirectly, as when distress remains unchanged despite attempts at self-regulation. Under typical developmental circumstances, emotion regulation skills and strategies improve as the PFC develops. However, neuromaturational development of the PFC and acquisition of emotion regulation strategies can be disrupted, especially in family environments characterized by neglect, abuse, invalidation, or coercive conflict escalation (Beauchaine, Hinshaw, & Bridge,  2019; Crowell et  al.,  2013,  2014,  2017; Crowell, Puzia, & Yaptangco,  2015). By adulthood, associations between emotion generation and emotion dysregulation may be more difficult to disentangle because effects of intervening contextual forces on neural mechanisms of emotion regulation and self-control accrue across the lifespan in high-risk environments (see, e.g., Beauchaine et al., 2017). In sum, emotion generation, regulation, and dysregulation are distinct but related constructs. Most existing definitions do not attend to developmental processes, which may contribute to discrepant views in the field. At the simplest level, emotion dysregulation could be defined as abnormal emotion regulation (i.e., “dys-” is of Greek origin and means “bad,” “abnormal,” or “difficult”). However, it may be more accurate to conceptualize dysregulation as a foundational human tendency (indeed, all infants show some degree of dysregulation) that is gradually altered across development. As a result, there is a wide phenotypic spectrum of adult emotion regulation abilities, which are shaped through

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longitudinal interactions between a child’s motivational tendencies and potentiating environmental experiences.

Developmental Theory

There is an extensive empirical and theoretical literature describing emotion generation, regulation, and dysregulation from a developmental perspective (e.g., Beauchaine, Hinshaw, et al., 2019; Crowell et al., 2013, 2017; Herts, McLaughlin, & Hatzenbuehler, 2012). Briefly, individual differences in emotion generation are highly heritable (e.g., Blonigen et al., 2005), arising from subcortical structures and networks that are established early in development (Beauchaine & Zisner, 2017). Dopamine (DA) neurons, for example, form during the first trimester (around 5 weeks postconception), and factors such as maternal nutrition, substance use, and immune functioning can affect development and function of DA neurons, producing lasting variation in infant phenotypes (Gatzke-Kopp, 2011; Luan, Hammond, Vuillermot, Meyer, & Eyles, 2018). These functional differences in neural responding provide a basis for temperament, which can be defined as “constitutionally based individual differences in reactivity and self-regulation, with the term constitutional referring to the person’s relatively enduring biological makeup” (Rothbart, Ahadi, & Hershey, 1994, p. 22). There are multiple theories of temperament, each with different labels and conceptualizations (e.g., Rothbart, 1986; Solmeyer & Feinberg, 2011). Although most existing models are based on observations of healthy infants and ordinary variation in infant disposition, they can be extended to better understand the extreme ends of continuously distributed traits. Examining these extremes is essential for understanding emotion dysregulation as a transdiagnostic vulnerability factor for later psychopathology (e.g., Beauchaine et al.,  2017). In other words, understanding the etiology of psychopathology requires consideration of more extreme trait vulnerabilities, significant environmental risks, and Biology × Environment interactions across ­development. Behavioral inhibition and trait anxiety, which are  characterized by excessive fear, worry, and/or dysphoria, predispose to later internalizing disorders, such as separation anxiety disorder and generalized anxiety disorder (e.g., Kagan, 2017; Kagan & Snidman, 1999). In contrast, trait impulsivity confers risk for externalizing disorders, including oppositional defiant disorder, conduct disorder, and substance use (Beauchaine et al., 2017). For vulner-

able children (i.e., high trait anxious and/or impulsive), risk for emotion dysregulation and psychopathology is highest within the context of adverse childrearing environments, such as those characterized by maltreatment, neglect, and/or invalidation (see Beauchaine, Hinshaw, et al., 2019). Furthermore, maltreatment rarely occurs in the absence of other significant forms of familial dysfunction, including harsh parenting, corporal punishment, inconsistent discipline, low warmth, and coercive parenting strategies that inadvertently socialize emotion dysregulation through negative reinforcement processes (e.g., Crowell, Yaptangco, & Turner,  2016; Skowron, & Reinemann, 2005; Wilson, Rack, Shi, & Norris, 2008). Thus, from a developmental perspective, emotion dysregulation emerges from heritable individual differences in emotion generation systems, which interact with potentiating environmental experiences across development to shape emotional lability and reactivity, ultimately increasing risk for many distinct forms of psychopathology.

Current Methods and Findings

Given difficulties in observing and defining emotion generation, regulation, and dysregulation, it follows that measuring these constructs is equally complex. We argue from a developmental perspective that these constructs can—and should—be measured across multiple levels of analysis (see also Cole et al., 2004). Indeed, it is misguided to assume that human emotions (and associated cognitions and behaviors) can be explained by one-dimensional measurement. Rather, multiple neurobiological systems interact with interpersonal and cultural factors to shape emotion generation, regulation, and dysregulation (e.g., Ashkanasy,  2003; Cicchetti, Ackerman, & Izard,  1995; Robinson,  2014; Rogers, Schröder, & von Scheve, 2014; Strauman, 2017). We explore some of those interacting systems next.

Intrapersonal Levels of Emotion Genetics

Identifying genetic effects (e.g., single nucleotide polymorphisms, epigenetic alterations in gene function) is one important avenue for elucidating biological underpinnings of individual differences in affective behavior (Drabant et al., 2006; Strauman, 2017; for a review of molecular genetics and ­emotion regulatory processes, see Chapter 15, this volume). This area of research aligns with Beauchaine and Zisner’s (2017) emphasis on longitudinal transactions between heritable emotion generation systems and potentiating environmental contexts in

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shaping emotion dysregulation and risk for psychopathology. For instance, the mesolimbic ­ DA  system—and related dopaminergic subsystem genes—is a primary neural substrate of affective states (e.g., wanting, liking) related to approach motivation (Beauchaine, 2015a; Beauchaine & Zisner, 2017). When individuals experience heritable deficiencies in DA responding, they may exhibit excessive approach behaviors and be at increased risk for externalizing disorders in the context of adverse childrearing environments (Beauchaine,  2015a; Beauchaine et al.,  2017). Accordingly, genes involved in DA neurotransmission have been a focus of research on externalizing behavior (e.g., Gizer, Otto, & Ellingson, 2016). The enzyme catechol-O-methyltransferase (COMT) metabolizes DA and therefore plays a key role in shaping human cognitions, behaviors, and emotion generation (Bearden et al., 2005). Drabant and colleagues (2006) explored the influence of a polymorphism (i.e., a compositional variation) in the COMT gene on corticolimbic activity during a face-matching paradigm. Individuals with the MET allele exhibit increases in hippocampal and ventrolateral prefrontal cortex activation when viewing faces with negative expressions (e.g., fear, anger) and show other neurological indices of temperamental inflexibility. The researchers concluded that those with heritable variations in DA neurotransmission, associated with the MET allele of the COMT polymorphism, may demonstrate rigid affective processing that could lead to emotion dysregulation and related psychological disorders. Decades of research have implicated genetic variants in the serotonin system in the pathophysiology of depression and other internalizing disorders (Owens & Nemeroff,  1994). More recently, researchers have extended these findings to studies of emotion regulatory processes involved in those disorders. Specifically, the serotonin transporter-linked polymorphism (5-HTTLPR) has been associated with physiological reactivity to emotional stimuli (Plieger et al., 2017), attachment and emotion regulatory capacities among young children (Viddal, Berg-Nielsen, Belsky, & Wichstrøm,  2017), poor distress tolerance among emotionally abused youth (Amstadter et al., 2012), and nonsuicidal self-injury and suicidal behaviors among adults (Mann, Brent, & Arango, 2001). In addition, our lab found that peripheral serotonergic function among self-injuring adolescents interacted with their negativity and ­parental conflict to explain 64% of the variance in self-injuring behaviors (Crowell et al., 2008). Thus, 90

polymorphisms within the serotonin system often interact with environmental exposures to potentiate risk for emotion dysregulation and related psychopathology. In considering Gene × Environment interactions, Kim and colleagues (2011) explored how genes interact with culture to influence emotion generation, regulation, and dysregulation. The oxytocin receptor polymorphism (OXTR) rs53576 is a genetic variant that has been associated with socioemotional sensitivity among European Americans (Kim et al.,  2011). Those high in socioemotional sensitivity are more responsive to social feedback regarding appropriate behavioral expression (Butler, 2012). Kim and colleagues (2011) found that emotion regulation tendencies among European and Korean Americans were associated significantly with the OXTR rs53576 GG genotype. Whereas Korean Americans with this genotype exhibited more emotional suppression, European Americans exhibited less emotional suppression. These manifestations of emotion regulation were consistent with participants’ respective cultural norms and, notably, could appear dysregulated outside of a specific cultural context. Findings highlight the importance of considering interactions among heritable emotion generation systems, cortically mediated emotion regulation processes, and environmental contexts when investigating the development of emotion dysregulation.

Neurological Level

Given the inordinate complexity of the brain, ­emotion generation, regulation, and dysregulation are challenging to delineate (see Chapter 1, this volume). One line of research stems from Gray’s early work on anxiety and impulsivity. According to  J.  A.  Gray (e.g., 1982), the septo-hippocampal system—including projections from the amygdala— subserves trait anxiety and passive avoidance of threat (see J.  A.  Gray & McNaughton,  2000). In contrast, the midbrain DA system—including projections from the ventral tegmental area to the nucleus accumbens—subserves pleasurable affective states and approach (see, e.g., Schultz,  2002). These projections and adjacent interconnected neural structures make up the ventral striatum (VS; see Beauchaine,  2012,  2015a). DA neurons in the VS are less responsive to reinforcers among ­impulsive individuals (see Plichta & Scheres, 2014). In turn, low DA responding is experienced psychologically as an aversive, irritable mood state (Laakso et al., 2003). Consequently, impulsive

Multilevel Transdiagnostic Constructs

i­ndividuals often engage in excessive reward-seeking behaviors to upregulate their aversive mood (see Beauchaine, 2012). Several researchers extended Gray’s work to further delineate neurological underpinnings of ­ emotions and approach/avoidance behaviors (e.g., Beauchaine & Zisner,  2017; Casey, Giedd, & Thomas, 2000; Davidson, 2000). Their work aligns closely with that of Panksepp (1982, 1998) by differentiating emotion generation from regulation. Whereas emotion generation derives from earlymaturing subcortical, limbic brain regions (e.g., nucleus accumbens, amygdala, hippocampus, and ventral tegmental area), emotion regulation originates from later maturing cortical structures, including the PFC, ACC, lateral orbitofrontal cortex (OFC), insular cortex, and inferior frontal gyrus (IFG). Neuroimaging studies—particularly those implementing functional magnetic resonance imaging (fMRI)—have advanced our understanding of the development and functions of these brain structures (Casey, Jones, & Hare,  2008). For instance, it is now well established that the PFC is one of the last brain regions to mature, and its ­top-down regulatory functions become more finetuned across development (Casey et al.,  2000; Casey, Tottenham, Liston, & Durston, 2005). This formulation aligns with observed normative declines in impulsive behaviors and improvements in self-regulation through adolescence and into adulthood (Casey et al., 2008). Similarly, it informs current understanding of nonlinear developmental trajectories of impulsive versus risk-taking behaviors (Casey et al., 2008). Whereas impulsive behaviors tend to decline across development due to steadily maturing cortical brain regions, risk-taking behaviors appear to increase during ­adolescence relative to childhood, likely due to an imbalance between mature emotion generation ­systems and immature regulatory control (Casey et  al.,  2008). By adulthood, both generation and regulation systems are more fully developed, which accounts for reduced impulsivity and risk taking. Cortical volumetric and functional abnormalities confer neural vulnerabilities to emotion dysregulation and related psychopathology (Beauchaine, Sauder, Derbidge, & Uyeji,  in press; Beauchaine et al., 2017). For instance, adolescents with conduct disorder and impulsive tendencies exhibit significantly less gray matter pruning in frontal brain structures as they mature (De Brito et al., 2009)—a likely neural underpinning of their difficulties with emotion regulation (Beauchaine & Zisner,  2017).

In addition, deficient connectivity between the amygdala and PFC is associated with increased ­behavioral inhibition, emotion dysregulation, and risk for internalizing psychopathology (Beauchaine & Zisner, 2017; Monk et al., 2008). Less bilateral insular cortex volume has been associated with violent and impulsive behaviors among adolescents with early presentations of borderline personality disorder (BPD; Takahashi et al.,  2009) as well as self-injuring adolescent girls who are at risk for developing BPD (Beauchaine, Sauder, et al., in press). These discoveries of extended neuromaturational time courses associated with transdiagnostic risk factors, like emotion dysregulation, self-injury, and impulsivity, offer a promising direction for prevention and early intervention programs involving emotion regulation strategies (Beauchaine, Sauder, et al.,  in press; Goldin, McRae, Ramel, & Gross, 2008).

Psychophysiology

Respiratory sinus arrhythmia (RSA) is a measure of parasympathetic influences on beat-to-beat variability in heart rate. Low resting RSA and, to a lesser extent, excessive decreases in RSA in response to emotionally evocative tasks are consistent biomarkers of emotion dysregulation (Beauchaine,  2015b; Beauchaine & Thayer, 2015). For instance, whereas adolescents with high resting RSA demonstrate resilience in the face of adversity and are buffered from internalizing and externalizing pathology, those with low resting RSA demonstrate more depressive symptoms and aggression when raised in contexts of unsupportive parenting (Beauchaine, 2015b; Gordis, Feres, Olezeski, Rabkin, & Trickett, 2010). Research on associations between RSA decreases and psychopathology are more mixed. On the one hand, some research demonstrates a protective effect of RSA withdrawal against development of internalizing psychopathology among maltreated youth (see, e.g., McLaughlin, Alves, & Sheridan, 2014). On the other hand, large decreases in RSA are associated with emotion dysregulation and ­self-harm among teens (Crowell et al.,  2005). A common interpretation is that modest decreases in RSA—as seen during attention deployment (e.g., Suess, Porges, & Plude, 1994)—reflect effective regulatory strategies, whereas excessive decreases indicate emotion dysregulation (Beauchaine, 2015a, 2015b; S.  A.  O.  Gray, Jones, Theall, Glackin, & Drury, 2017; Mezulis, Crystal, Ahles, & Crowell, 2015; Price & Crowell,  2016; Yaptangco, Crowell, Baucom, Bride, & Hansen, 2015).

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Biological Sex

Most theorists agree that emergence of sex differences in emotion generation, regulation, and dysregulation are developmental processes involving biological and social components. In infancy, boys typically demonstrate higher arousal and approach behaviors, lower language abilities, and less effortful control than girls (Brody,  1999; Martel,  2013). In contrast, girls often demonstrate high negative emotionality and effortful control and low approach behaviors (Crowell & Kaufman, 2016; Martel, 2013). These early sex differences are often attributed to gene expression and influences of sex hormones in utero (Zahn-Waxler, Shirtcliff, & Marceau, 2008). Furthermore, they contribute to differing rates of externalizing and internalizing disorders among boys and girls: Whereas boys are at heightened risk for externalizing psychopathology such as conduct disorder and oppositional defiance, girls are at heightened risk for internalizing psychopathology such as anxiety and depression (Crowell & Kaufman, 2016; Eme, 2015). These sex-typical trajectories are implicated in the disproportionate diagnostic rates of antisocial and borderline personality disorders among males and females, respectively (Beauchaine, Klein, Crowell, Derbidge, & Gatzke-Kopp,  2009; Crowell & Kaufman,  2016). Notably, a growing body of literature suggests that externalizing psychopathology is associated prospectively with borderline personality pathology among both girls and boys (Burke & Stepp, 2012; Swanson et al., 2014). As well, some boys may develop borderline personality pathology via a more traditionally internalizing trajectory (Crowell & Kaufman, 2016). Thus, despite the common occurrence of sex-specific trajectories to emotion dysregulation and psychopathology, there are also important multifinal outcomes that are likely driven by biology–environment interactions (Beauchaine et al., 2009). Sex-specific socialization practices interact with biologically based emotion generation systems to predict differences in emotion dysregulation (Crowell & Kaufman, 2016; Hughes, Crowell, Uyeji, & Coan, 2012). Through various social contexts (e.g., media, interactions with adults and peers), children internalize messages associated with their own identified sex (male or female) and proceed to practice emotion expression that aligns with their chosen sex schema (Chaplin, 2015). For example, a young boy may internalize the message that boys are tough and do not cry and consequently overregulate emotions that evoke tears, such as sadness and guilt, which are  more accepted among women. Parents often 92

r­einforce gender-based stereotypic emotion expression by using a greater variety of emotion-related words with their daughters and more anger-related words with their sons (Cervantes & Callanan, 1998; Chaplin, Cole, & Zahn-Waxler, 2005). In addition, parents are less tolerant of atypical gendered behavior among their children (Kim, Arnold, Fisher, & Zeljo,  2005). For example, parents practice more overreactive disciplinary actions when their sons and daughters exhibit internalizing and externalizing behaviors, respectively (Kim et al., 2005). Finally, peer groups can reinforce sex-specific emotional processes, as boys tend to engage in more physical activities with larger groups of children and girls typically disclose more feelings to smaller groups of friends (Rose & Rudolph, 2006). In sum, sex and gender effects offer important bridges between intrapersonal and interpersonal Biology × Environment interactions in emotion generation, regulation, and dysregulation.

Interpersonal Levels of Emotion

Emotions often occur in interpersonal contexts, and individuals may even regulate each other’s emotions, be it purposefully or automatically, for prosocial or selfish reasons (Butler,  2015). Emotional ­processes are influenced by cultural standards that dictate which emotions are warranted under various circumstances (Butler, Lee, & Gross, 2007). Thus, although literature on interpersonal levels of emotion rarely intersects with that of intrapersonal, they are of equal importance in understanding emotion regulation and dysregulation.

Dyadic Interactions

People often seek assistance from trusted friends and family when struggling with overwhelming emotions. Butler (2015) outlined a clear picture of how dynamic interpersonal emotions stem from three interdependent processes, including (1) convergence of individuals’ emotional responses to external stimuli, (2) individuals’ emotional reactions to each other, and (3) interpersonal emotion regulation. For example, we can imagine two partners, P1 and P2, rock climbing together. At the base of the climb, P1 expresses apprehension, first nonverbally, then verbally, and P2 picks up on P1’s anxiety (i.e., convergence of emotional responses to the external world). Initially, P2 may feel angry in response to P1’s expressed anxiety (i.e., emotional reaction to social partner) but is able to regulate that anger as well as P1’s emotions by making reassuring statements (i.e., interpersonal emotion regulation).

Multilevel Transdiagnostic Constructs

Diamond and Aspinwall (2003) consider these dyadic regulatory interactions as optimal developmental outcomes within relationships. When in dyadic contexts, the goal of emotion regulation is not affective homeostasis; rather, it is emotional flexibility and the capacity to pursue and prioritize different context-specific goals. These kinds of dyadic emotional interactions can be difficult to disentangle, however, because they emerge from nonlinear relations and are embedded within multilevel feedback loops (Butler, 2017). In our work (Crowell et al., 2017), we examined dynamic emotional interaction patterns among mothers and their self-injuring, female adolescents during 10-minute conflict discussions. Using a nonlinear dynamical systems approach, we found that mothers’ behaviors had a driving effect on selfinjuring adolescents’ behaviors and psychophysiological responses. These driving relations were not observed among mothers and daughters in the control group, providing evidence for theories that self-injuring adolescents are more emotionally reactive and sensitive than typical controls. In a different study, mothers of self-injuring adolescents were more likely than mothers of controls to match or escalate conflict—only de-escalating conflict in response to highly aversive adolescent behavior. In contrast, control mothers reliably de-escalated conflict, which may be one form of interpersonal emotion regulation (Crowell et al., 2013). These findings highlight the strong influence of dyadic interactions on individuals’ emotion generation, regulation, and dysregulation, particularly among vulnerable adolescents at elevated risk for psychopathology.

displayed heightened emotional reactivity—measured physiologically and behaviorally—in response to watching a sad film. Thus, they concluded that cultural norms can play an influential role in shaping emotion expression. Individuals’ capacities for emotion regulation and dysregulation are also linked to the social contexts in which they live, as if they are “culturally trained” for adaptive emotional control (Heatherton, 2011; Murata, Moser, & Kitayama, 2012; Strauman, 2017). Oftentimes, individuals’ desires for group inclusion and positive social interactions will provide incentives for regulating negative emotions (e.g., guilt, shame; for a review, see, e.g., Heatherton, 2011). In one study, Asian and European Americans were exposed to either unpleasant or neutral pictures while instructed to attend to or suppress generated emotions (Murata et al.,  2012). Asian Americans demonstrated significantly greater decreases in parietal late positive potential (LPP)—a neurological measure of emotional processing—during emotion suppression tasks. This unique pattern of downregulation was so complete that the parietal LPP returned to baseline approximately 2,000 ms poststimulus, despite initial emotional reactions being at least as pronounced as those of European Americans. These findings highlight cultural differences in emotion regulation between Asian and European Americans. Although such marked suppression of emotional experiences among Asian Americans may appear dysregulated to European Americans on a neurological level, this degree of emotion regulation is consistent with cultural values of high emotional control (Mauss & Butler, 2010).

Cultural Influences

Synthesis and Future Directions

In European American culture, resisting group norms when they interfere with personal goals is indicative of optimal social functioning (Markus & Kitayama, 1991). Consequently, individuals are encouraged to assert opinions and express emotions overtly. It follows that European Americans who are depressed respond emotionally and physiologically in opposite patterns of those that are optimal for social functioning (e.g., anhedonia and diminished physiological reactivity to emotionally evocative stimuli; Chentsova-Dutton et al.,  2007; Markus & Kitayama,  1991). This logic extends to Asian American culture as well, which values harmonious interdependence rather than individuality. Chentsova-Dutton and colleagues (2007) found that, in direct contrast with depressed European Americans, depressed Asian Americans

In summary, emotion generation, regulation, and dysregulation are multifaceted constructs that are best understood from a developmental perspective. There is still ongoing debate about how to define and conceptualize these terms, especially with regard to whether emotion generation and regulation are separable. Although intertwined, it is possible to disentangle regulation of emotions from their generation—especially when these constructs are studied at the biological level of analysis. A lifespan perspective also helps to elucidate important distinctions between basic emotions and regulatory strategies. Specifically, there are early temperamental differences in emotion generation that are observable early in development. To some degree, emotional expressions and communications in infancy could also be described as dysregulated, ­

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a­ lthough this is more difficult to distinguish from normative infant behavior. In contrast, emotion regulation is a maturational process that requires social inputs. Proximal environments, including caregivers and siblings, play a critical role in ­shaping emotion regulation through soothing and nurturing in early development, and through conflict de-escalation, praise, and responsive parenting in childhood and adolescence. Future research should continue to examine these three constructs across multiple levels of analysis. Emotional processes are central to healthy development and, when disrupted, heighten risk for a  wide range of psychiatric diagnoses. Given the importance of close relationships in socializing emotion regulation skills and strategies, scholars should continue to conduct dyadic, triadic, family, and systems-level research across development. These studies have potential to elucidate social mechanisms of risk and resilience, with potential to inform early intervention efforts and prevent psychopathology.

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CH A PTE R

8

Development of Emotion Dysregulation in Developing Relationships

Ross A. Thompson and Sara F. Waters

Abstract A developmental perspective to emotion dysregulation underscores the relational bases to developing emotion regulation capacities. In this chapter, attachment theory and functionalist emotions theory are discussed as theoretical foundations for understanding emotion dysregulation in the context of developing relationships. In the subsequent discussion of central research literatures, the chapter profiles family processes that contribute to the development of emotionally dysregulated behavior. The interaction of biological and social processes is considered next in discussions of the physiological synchrony between children and parents, the socialization of stress neurobiology, and children’s differential susceptibility to environmental influences and its consequences for emotion regulation and dysregulation. The chapter concludes with reflections on future directions, including the clinical implications of considering developing problems in emotion dysregulation as problems not just of individual children but also of relationships. Keywords: development, relationships, attachment, functionalist emotions theory, family, differential susceptibility, stress neurobiology, physiological synchrony

Introduction

Psychological studies of emotion regulation and dysregulation have naturally viewed these concepts in terms of psychological adjustment. Because emotions are so important to thinking, motivation, and sociability, well-adjusted individuals are capable of autonomously managing their emotions, and failure to do so competently may be an indicator of ­psychopathology. But a developmental approach to emotion regulation and dysregulation offers a somewhat different perspective from this conventional view. From the beginning of life when young infants depend on others to manage their arousal, emotion regulation develops not individually but in the context of social relationships. Children rely on others to foster manageable emotional experiences in which they can develop and practice their skills of emotional self-control. Moreover, as literatures on social support, empathy, and romantic relationships underscore, other people remain important to adults’

capacities to maintain satisfactory emotional balance and self-regulation (Zaki & Williams, 2013). At the end of life, older adults manage their social relationships for purposes of emotion regulation, particularly for maintaining positive affectivity (Carstensen, Fung, & Charles, 2003). Thus, emotion regulation and dysregulation develop and function in a relational context, not just within the individual. Relationships can promote the growth of constructive skills of emotion management, but they can also lead to dysfunctional patterns of emotion dysregulation. When other people impose unmanageable emotional demands (as when children live in chronically violent homes) or undermine constructive strategies of emotion self-management (as when a parent dismisses a child’s need for emotional support), for example, close relationships become associated with emotion dysregulation. The effects of relationships on emotion dysregulation can be observed throughout life (as research on family and 99

marital interaction documents) but are most readily observed in the early years when young children are so dependent on others for managing their feelings. Viewed in this light, emotion dysregulation may not be solely a problem of individual adjustment, but may also reflect relational problems. Indeed, this view is at the cornerstone of the field of infant/ early childhood mental health, which regards early problems of psychological functioning as inherently relational. It is captured in Winnicott’s famous line, “There is no such thing as a baby. . . you are describing a baby and someone” (Winnicott, 1957, p. 137). In this chapter we consider the development of emotion dysregulation in developing relationships. Our focus is primarily on the early years because this is a formative period for growth of emotion regulation and thus also a period of vulnerability to social influences that can promote emotion dysregulation. For this reason, developmental study of early emotion regulation is also the study of risk for emotion dysregulation (see Garber & Dodge, 1991). Yet some developmental processes that contribute to emotion dysregulation are very different from those that lead to skills in emotion management. We organize the chapter in this manner. In the section that follows, two central theoretical perspectives are considered: attachment theory and functionalist emotions theory. The section closes with reflection on some unresolved theoretical issues. The next section focuses on central findings and conclusions from the research literature, with particular attention to interactions among social and biological influences on developing emotion dysregulation in relationships. The chapter concludes with some ideas about future directions for this field of research.

Theoretical Perspectives on the Development of Emotion Dysregulation

Attachment theory and functionalist emotions theory are two perspectives that frame current thinking about the development of emotion dysregulation in the context of developing relationships. The first focuses on the nature of early relationships and their role in the development of self-regulation and emotion dysregulation. The second contributes a complementary focus on the nature of emotion and its management in the context of an individual’s transactions with the social world.

Attachment Theory

Attachment theory was formulated by Bowlby (1969) to explain the development of emotional ties 100

between infants and caregivers, and the psychological significance of such ties. Bowlby argued that humans have been motivated to develop these attachments throughout evolution because of the importance of infant–caregiver proximity for protection, nurturance, and social learning. As attachment researchers have learned more about early psychological development, however, many have concluded that early attachments serve broader functions, including supporting emotion regulation that derives from an infant’s trust in an adult who responds sensitively, buffers stress, provides relief from distress, and manages environmental demands (Brumariu, 2015; Cassidy, 1994). Viewed from this perspective, secure attachments promote the growth of constructive forms of emotion self-regulation in several ways, including the parent’s acceptance of the child’s feelings, willingness to communicate openly about them, and coaching emotion regulation skills (Thompson, 2015). From these influences, children develop a greater understanding of emotion and its management, and develop a broader understanding of the role of emotions in the context of close relationships. The benefits of secure attachments are especially noteworthy when contrasted with the kinds of emotion dysregulation apparent in insecure parent–child attachments, whether insecurity is manifested in resistant, avoidant, or disorganized responses. When insecure-resistant infants are observed with their mothers, they exhibit self-evident signs of emotion dysregulation. For example, when stressed by a brief separation, they have difficulty soothing even after the mother’s return and instead show continued and sometimes angry distress throughout reunion. By contrast, insecure-avoidant infants are more placid during separations from their mothers, but their behavior is belied by physiological indications of strong arousal, suggesting that they minimize expressions of distress to a caregiver who has been relatively insensitive to these signals in the past (Spangler & Grossmann, 1993). Disorganized infants show the most atypical patterns of attachment behavior including indications of disorientation, inconsistent responses to their mothers (e.g., approach combined with avoidance), fearful behavior, and/or inconsolability during reunion episodes. Attachment researchers believe that this indicates that disorganized infants lack a constructive strategy for engaging their mothers after separation because their mothers are not reliable sources of safety and emotion management. Considerable research conducted with infants, children, and adolescents confirms the advantages

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afforded by a secure attachment in the development of emotion regulation. Securely attached children tend to be more capable in managing their emotions (especially in the company of a parent), have a more acute understanding of emotions (especially negative emotions), and are more likely to identify and enlist constructive strategies of emotion management compared to insecurely attached children (Thompson, Virmani, Waters, Meyer, & Raikes, 2013; Waters & Thompson, 2016; see also Brumariu, 2015; Thompson, 2016, for reviews). Unfortunately, attachment researchers have not explored as fully the different patterns of emotion dysregulation associated with the three insecure groups, although there are indications from several studies that disorganized children are most likely to use dysfunctional strategies for coping with emotional arousal (e.g., catastrophizing) and are more vulnerable to fear and anxiety compared to children in the other groups (Brumariu, Kerns, & Seiberg, 2012; Spangler & Zimmermann, 2014). Attachment theory and research findings are consistent with broader literatures on the importance of attachment relationships as stress buffers, especially for human and animal young who are least capable of coping with stressors on their own (Gunnar & Donzella, 2002). Attachment research is also consistent with studies showing that parental sensitivity and responsiveness to distress are associated with the development of more constructive strategies for regulating negative emotion in infancy and childhood (Davidov & Grusec, 2006; Leerkes, Blankson, & O’Brien, 2009). When young children lack parental support, it is not just that they develop poorer strategies for managing emotion; they also exhibit behaviors indicative of emotion dysregulation, such as defiant noncompliance accompanied by negative affect in response to parental requests (e.g., Leerkes et al., 2009). This is because the lack of relational support not only denies young children a stress buffer but also is itself a significant stressor at an age when children depend on parental nurturance (Thompson, 2014). Consistent with attachment research, therefore, emotion dysregulation develops not only in contexts of parental harshness and negativity (e.g., Chang, Schwartz, Dodge, & McBride-Chang, 2003) but also in contexts of nonresponsiveness and emotional unavailability to the child. Such findings are important given the broad range of circumstances faced by families with young children that can cause parents to be nonresponsive and emotionally unavailable. The younger a child is,

the more likely that child is to live in a family in economic stress, with nearly half (46%) of young children in the first 3 years living in poverty or in  poor families (Jiang, Granja, & Koball, 2017). Considerable research drawn from the Family Stress Model documents how economic stress contributes to parental anxiety and depressive symptoms, increased marital conflict, and higher levels of disengaged, nonnurturant parenting (see Conger, Conger, & Martin, 2010, for a review). More than one in seven infants are exposed to major maternal depression during their first year of life (Wisner et al., 2013). More significant risks derive from the high proportions of young children who are victims of child maltreatment and enter foster care. Taken together, family conditions that contribute to the development of emotion dysregulation in children are those characterized not only by hostility but also by parental disengagement, and these conditions are far too common.

Functionalist Emotions Theory

Drawing on Darwinian theory, most theories of emotion are functionalist in orientation, emphasizing the adaptive purposes served by discrete emotions throughout human evolution. Definitions of emotion regulation are also functionalist, focused on personal, situational, and/or social goals achieved by managing emotions and their expression. Individuals regulate their emotions to feel better in difficult situations, mobilize themselves to face difficult challenges, think more clearly, strengthen relationships, and accomplish other purposes. As Thompson (1994) notes, individuals also regulate themselves to alter the temporal dynamics of emotion even if they cannot change emotion valence. For example, they may reduce the duration of fear or sadness, slow the escalation of anger or frustration, prolong feelings of pleasure or well-being, or achieve a more even and less volatile emotional demeanor. Indeed, emotion regulation may be used more often for these purposes than to change the valence of feelings. What does this mean for emotion dysregulation? One way of defining emotion dysregulation is when an individual cannot manage his or her emotions, or manages them dysfunctionally. Either way, one fails to regulate emotions or their expression according to his or her goals. This is consistent with a functionalist orientation and occurs when someone “loses control” of his or her anger, cannot recover from enduring feelings of sadness or anxiety, has difficulty experiencing happiness, undergoes disturbing Thompson and Waters

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mood swings, or responds emotionally in ways unsuited to immediate circumstances. Viewed in this light, it is easy to see how readily various kinds of affective psychopathology are interpreted as problems of emotion dysregulation. But a functionalist orientation to emotion complicates this view in several ways. First, there may be a difference between an individual’s goals in a particular context and expectations of others for those goals. Stated differently, an observer may interpret someone’s behavior as emotionally dysregulated by misconstruing the emotion goals the individual is trying to achieve. An example is when an adolescent or adult ruminates on events that cause sadness because of sympathetic responses their sadness elicits from friends. To an observer, that person is not regulating emotions very well, but viewed from that person’s perspective, emotion regulation is accomplishing its purpose of mobilizing social support. It may often be true that children are perceived by adults as emotionally dysregulated when they are actually behaving as emotional tacticians to manage their emotions, and their expression, to coerce, cajole, or entice others to produce desired outcomes. Second, many social situations in which emotion is managed involve multiple goals, both immediate and longer term, and these goals may be in­con­sist­ent. Individuals in these situations must often choose which goals should guide their emotion regulatory efforts at the cost of achieving other goals. Consider a child who is bullied by a peer (or, for that matter, an adult who is bullied by a coworker). Mobilizing feelings of anger to resist intimidation may accomplish the immediate goal of self-defense but may undermine other relationships if people are offended by the angry display. Suppressing feelings of anger or fear to endure intimidation does little to reduce it in the future but may preserve ongoing relationships of value. Expressing distress to others to mobilize social support may provide immediate assistance but may color how others perceive the self. As this example illustrates, there may be different and potentially in­con­sist­ent immediate and longer term outcomes of each strategy based on the individual’s power relative to that of the bully, beliefs and expectations of others in that setting, a person’s gender, and/or broader cultural and subcultural values. Competent emotion regulation thus involves negotiating tradeoffs between multiple goals and accepting both the costs and benefits of specific self-regulatory strategies. Emotion dysregulation in such contexts may occur when an individual’s self-­regulatory strategies accomplish neither imme102

diate nor long-term goals, or when certain goals are achieved at very high cost. Third, there are situations that undermine an ­individual’s capacity to adaptively regulate their emotions to improve well-being, and in which immediate coping occurs at the cost of long-term difficulty. These are conditions that heighten the risk for affective psychopathology and influence others’ perceptions of one being emotionally dysregulated. In these situations, dysregulation arises, at least in part, from emotionally insurmountable conditions that foster problems in emotion management. One example is the experience of young children with a chronically depressed parent (Goodman & Gotlib, 1999). Depressed mothers tend to be less positive and more punitive with their children, engage in more critical and hostile behavior, and enmesh their children in their own affect by adopting negative attributional biases toward their children, combined with helplessness in remedying their own condition (Rogosch, Cicchetti, & Toth, 2004). Thus, in addition to being unsupportive and emotionally unavailable, chronically depressed caregivers make it difficult for children to effectively manage their own emotions by involving the child in parental distress and enhancing children’s feelings of responsibility for it. Enmeshed in these circumstances, it may be difficult for children, especially at young ages, to engage in constructive emotion self-regulatory strategies that might involve, for example, reappraising the situation or disengaging from it. As a consequence, children with a chronically depressed mother not only are at heightened risk of depression but also evince dysphoric affect, diminished self-concept, and poorer social competence—all of which contribute to emotionally dysfunctional behavior outside the home, including the classroom and with peers (Goodman & Gotlib, 1999). In some cases, children’s efforts to cope with immediate circumstances create longer term emotional dysfunction. Young children at risk for anxiety disorders, for example, show hypervigilance in situations associated with fearful events, attentional orienting to anxiety-provoking stimuli, and a tendency to construe benign situations as disproportionately negative or threatening. These appraisal (and preappraisal) processes are exacerbated by influences from family members, who may themselves share a tendency toward anxious symptoms, and serve the child’s preeminent self-regulatory strategy of avoiding anxiety-provoking situations, even though this has dysfunctional long-term consequences by enhancing rather than reducing anxious psychopathology

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(Fox, Henderson, Marshall, Nichols, & Ghera, 2005; Thompson, 2001). Without the kind of concerted family support that is a goal of family therapy, however, it is difficult to know how a young child can better self-regulate in these circumstances. Children who are physically abused by their caregivers also confront a tradeoff of emotion self-regulatory goals. Children with a history of abuse, exposure to violence, and other trauma become physiologically and emotionally hypersensitive to cues of adult anger, with a lower threshold of detecting anger in adult voices and faces, and greater physiological reactivity when these cues are perceived (Pollak, 2008). These responses can serve emotion regulatory functions if they enable a child to anticipate an attack before it occurs and to be prepared to flee, although they also contribute to difficulty in managing emotion because negative emotions tend to quickly escalate to high intensity when they are evoked. In addition, outside the home their hypersensitivity to threat cues undermines competent emotion management and is socially dysfunctional (Thompson, 2011). But it is difficult to think of any other adaptive strategy children might enlist to cope with potential harm at home that does not carry these dysfunctional external consequences and threats to long-term emotional development. From a functionalist perspective, therefore, responses that appear to be emotionally dysregulated— dysphoric affect, anxious avoidance, hypervigilance, and overreactivity to threat—might also be interpreted as deriving from efforts to cope with ­circumstances that do not permit more adaptive self-regulatory strategies, even though they also have long-term costs to developmental competence. Viewed in this light, emotion regulation is a double-­edged sword because strategies that permit immediate coping render children more vulnerable to long-term problems (Thompson & Calkins, 1996). Describing these children as emotionally dysregulated in more than a broadly descriptive sense overlooks a thoughtful appraisal of the circumstances that shaped their emotional development, the multiple and sometimes conflicting emotion goals that children might be coping with, and the challenges of managing emotionally insurmountable conditions. Describing these children as emotionally dysregulated also overlooks the important and sometimes profound relational context in which efforts to manage emotions occur. An unresolved issue, therefore, is how to characterize emotion dysregulation and its treatment in

the context of its development. The traditional ­psychological orientation to emotion dysregulation is to portray it as a component of psychological ­ adjustment and as an individual characteristic that can be addressed through therapeutic intervention. But functionalist emotions theory and attachment theory together argue that developing problems manifesting in emotionally dysregulated behavior must be interpreted in a relational context because it is that context that shapes the emotional demands on the child, the goals that the child might be seeking to accomplish through self-regulatory efforts, and the outcomes of strategies the child enlists. Emotion dysregulation is, like insecure attachment, an adaptation to a particular relational context. And although these adaptations can create difficulties as the child enters other relational contexts—such as problems in peer social competence exhibited by insecurely attached children and children exposed to chronic violence—this does not mitigate the importance of understanding these adaptations within the relational frameworks in which they develop. As considered further later, addressing these developmental challenges requires not only individual therapeutic intervention but also efforts to address relational bases of their development, such as in the context of two-generation interventions.

Current Methods and Findings

In this section, we profile contemporary advances in the developmental study of emotion dysregulation. We turn first to studies of family processes that contribute to the development of emotionally dysregulated behavior. We consider next interactions of biological and social processes in sections addressing the nature of the physiological synchrony between children and their caregivers, socialization of stress neurobiology, and children’s differential susceptibility to environmental influences and their consequences for emotion regulation and dysregulation.

Family Processes

Considerable research has addressed how family ­influences affect the development of emotion regulation, although researchers have tended to be more interested in the growth of self-regulatory competency than on development of emotion dysregulation. From this research, however, it is possible to discern at least three broad ways that family processes contribute to emotionally dysregulated behavior in children (Morris, Silk, Steinberg, Myers, & Robinson, 2007; Thompson, 2013). Thompson and Waters

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First, children acquire strategies of emotion r­ egulation and patterns of emotionally dysregulated behavior from observations of other family members. A young child with a parent who has an explosive temper is likely to manifest anger similarly, especially if family members acquiesce in the face of such displays. Because of the influence of parents’ manner of emotional expression on the broader family climate, observational processes are likely to be especially influential in the development of emotion dysregulation when parents’ emotional expressions are extreme. Silk, Shaw, Skuban, Oland, and Kovacs (2006) reported, for example, that offspring of chronically depressed mothers tended to use more passive, less competent styles of managing their emotions during mood induction compared to children who lived with nondepressed mothers. Second, parenting practices directly related to the socialization of emotion also influence the development of emotionally dysregulated behavior. These socialization influences can include parents’ active coaching of emotion self-regulation; their accepting, dismissive, or punitive reactions to children’s negative emotional expressions; and conversations about emotion and its management. In a recent meta-analysis, Johnson, Hawes, Eisenberg, Kohlhoff, and Dudeney (2017) concluded that child conduct problems are predicted by parents’ nonsupportive emotion socialization practices, particularly those directed toward children’s negative emotions, and that this influence is greater with younger children. Nonsupportive practices include minimizing or punishing children’s emotional expressions, refusing to talk about the meaning or significance of children’s feelings, and frequent expressions of negative emotion, especially toward children. The authors emphasized that conduct problems and nonsupportive emotion socialization practices become mutually influential over time, and that socialization practices can have compounding effects. These processes are illustrated in a study by Mence and colleagues (2014), who found that in families of toddlers with disruptive behavior problems, parents exhibited hostile attributional biases and emotion flooding, as well as negative discipline practices. Children’s behavior problems and parents’ unsupportive emotion socialization practices became mutually maintaining elements of a negative family environment. Parents’ emotion socialization is also relevant to the development of children’s internalizing problems (Schwartz, Sheeber, Dudgeon, & Allen, 2012). Mothers’ and fathers’ negative emotional expressive104

ness at home was linked to adolescents’ internalizing and externalizing symptoms, although for internalizing symptoms, this effect was buffered by parents’ supportive emotion coaching (Stocker, Richmond, Rhoades, & Kiang, 2007). It is noteworthy that parents’ negative expressiveness predicted both internalizing and externalizing symptoms in youth, reflecting its broad emotionally dysregulatory impact. Third, consistent with the foregoing, the general emotional climate of the family influences the development of emotion dysregulation. Children’s emotion self-regulation is disrupted by the overall emotional environment created by family interactions—the relative amounts of negative and positive expressivity by family members, for example, as well as the unpredictability and emotional instability of the family climate. The influence of the family emotional climate is illustrated by research based on the Family Stress Model discussed earlier, in which economic stress promotes depressive and anxious symptoms in adults, which become manifested in marital difficulties and aversive parent–child relationships—an emotional climate that contributes to children’s behavior problems (Conger et al., 2010). The importance of the family emotional climate is also reflected in studies of the effects of marital conflict on children. In the emotional security hypothesis developed by Cummings and Davies (2010), marital conflict disrupts children’s emotional security and emotion regulation, causing children to develop heightened sensitivity to parental distress and anger, become overinvolved in their parents’ conflicts, have difficulty managing the strong emotions that conflict arouses, and show early signs of internalizing problems (Davies, Harold, Goeke-Morey, & Cummings, 2002). Taken together, family processes can contribute both to adaptive emotion regulatory skills in children and to emotion dysregulation depending on how parents act as examples of emotion regulation, their emotion socialization practices, and the broader emotional climate of the family. Development of emotion dysregulation in the family derives not only from absence of support for competent self-­regulation but also from influences that heighten negative emotional reactivity, blunt children’s efforts to manage their feelings, and dismiss, denigrate, or ignore children’s feelings altogether.

Physiological Synchrony

One way that close relationships contribute to emotion regulation—or dysregulation—is through synchrony that develops between partners’ emotions,

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behaviors, and even physiological responses. The importance of parent–child emotional and behavioral synchrony for children’s healthy social and emotional development has long been recognized (see Harrist & Waugh, 2002, for a review). More recently, developmental scientists have begun to empirically examine the influences of physiological synchrony on parent–child relationships. Their work is built on earlier studies of time-linked physiological processes of social partners. In their foundational work, for example, Levenson and Gottman (1983; Gottman & Levenson, 2000) predicted dissolution of marriage over the course of 14 years on the basis of the synchrony of couples’ autonomic nervous system responses during conflict conversations. Similarly, trajectories of mothers’ and infants’ heart rate responses during stressful episodes varied as a function of their relationship quality (Donovan & Leavitt, 1985). During the past decade, research on dyadic physiological processes has proceeded in earnest. This is due, in part, to recent improvements in physiological recording technology and, more significantly, advances in statistical modeling techniques for dynamic dyadic data analysis that have allowed researchers to unlock the complexities of these data (Butler, 2015; Crowell et al., 2017; Ferrer & Helm, 2013; Thorson, West, & Mendes, in press). Physiological synchrony (PS) can be defined as “any interdependent or associated activity identified in the physiological processes of two or more individuals” (Palumbo et al., 2017, p. 100). This definition is useful because it subsumes more specific descriptors of relational synchrony such as covariation (within time-point associations) and linkage (between time-point associations) and because it can be applied both to dyadic regulation and to dysregulation. In her biobehavioral model of bond formation, Feldman (2012) argues that physiological and behavioral processes work together to foster organization of the early parent–child relationship into a dyadic regulatory system that shapes children’s development. For instance, mothers and their 3-month-olds experienced synchronized heart rhythms during face-to-face interactions, and these episodes of PS co-occurred with episodes of increased affective synchrony (Feldman, Magori-Cohen, Galili, Singer, & Louzoun, 2011). Mothers with affective symptoms—including depression and anxiety— were less capable of establishing affective synchrony with their infants, and this was associated with infants’ poorer stress reactivity and fear regulation (Feldman et al., 2009).

As these studies illustrate, PS can be measured using assessments of heart rate. Studies with young children also commonly focus on respiratory sinus arrhythmia (RSA), which quantifies changes in intervals between heart beats across respiratory cycles (i.e., inhalation and exhalation) and is a reliable measure of parasympathetic nervous system activity. RSA at rest and RSA in response to emotionally evocative situations are indicative of individual differences in emotion regulatory capacities (see Beauchaine, 2015, for a review). Skin conductance (SC), an index of sympathetic nervous system activity, is also used in PS analyses. Salivary cortisol, which indexes limbic hypothalamic-pituitary-adrenal (L-HPA) axis activity, is another common meas­ure used to study PS, but is more often used in samples of older children and adolescents than very young children (see Saxbe et al., 2014). Studies of PS with very young children and their parents typically use one of two procedures. In the first, physiological activity is measured during a period of parent–child interaction that is briefly interrupted by a stressor to the child (e.g., the adult stops responding to the child, a brief separation from the parent), followed by a resumption of  normal interaction. Using such a procedure, Ham and Tronick (2009) found that PS (measured by SC) was observed between mothers and their 5-month-olds during stress and was positively associated with maternal sensitivity when normal interaction resumed. A second study also showed that sensitive mothers and their 6-month-old babies showed greater PS during the resumption of normal interaction, but this was not observed for other mother–child dyads (Moore et al., 2009). Greater sensitivity may enable mothers to facilitate their children’s recovery from stress as they manage their own emotions. In the second type of procedure, mothers undergo an emotion induction, and physiological reactivity of both partners is measured. Using this approach, PS (measured by RSA) was observed when mothers held their 3-month-olds as they underwent a paced breathing exercise (van Puyvelde et al., 2015). In an experimental study, mothers and their 1-year-olds were observed after mothers experienced a negative stress task. Mothers and infants exhibited PS (measured with cardiac indices) that increased over time, a pattern not observed by mothers in a control condition or mothers who experienced stressful events that ended positively (Waters, West, & Mendes, 2014). Waters and her colleagues suggested that this kind of physiological synchrony between mothers Thompson and Waters

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and babies can contribute to affective contagion in shared experiences. In this example, infants shared physiological indicators of stress that their mothers experienced. In a follow-up study, PS (measured by RSA) was observed for mother–infant dyads after mothers experienced a relaxation task but not for dyads with mothers who experienced a negative stress task (Waters, West, Karnilowicz, & Mendes, 2017). Taken together, evidence of physiological synchrony in both normal interactions and stressful conditions can be observed between mothers and their children in the first year, and this varies according to maternal sensitivity, although evidence of PS also varies according to how it is measured. Synchrony can contribute to stress contagion and also to shared recovery from it. Similar results are obtained with older children. During episodes of play and mild challenge, mothers and their preschool-age children exhibited PS (measured by RSA), but mother–child RSA was dyssynchronous (i.e., moved in opposite directions) for children with externalizing problems (Lunkenheimer et al., 2015). In the same sample, PS was weaker for dyads with mothers who were highly disengaged (Skoranski, Lunkenheimer, & LucasThompson, 2017). More research on these issues is needed, however, in light of inconsistent findings in the literature (see, e.g., Smith, Woodhouse, Clark, & Skowron, 2016). These studies indicate that the quality of parent–child relationships is an important moderator of physiological synchrony, which may help to account for the role of synchrony in the development of emotion regulation and dysregulation in early parent–infant interactions. There remains much more to be understood about the meaning of PS for social-emotional development. Physiological synchrony with a parent who experiences emotional psychopathology may pose risks for the development of emotional dysregulation, especially in young children, compared to selfregulatory support afforded by PS with emotionally healthy parents. In addition, there is more to be known about the effects of context on PS, including immediate physiological demands of situations, the quality of parent–child interactions during meas­ ure­ment, relational histories of parents and children, and characteristics of individuals.

Socialization of Stress Neurobiology

Emotion dysregulation arises, for many children and adults, from stress. Stressors, such as traumatic events that lead to posttraumatic psychopathology, can be intense, overwhelming experiences that have lasting 106

effects. Stressors can also be chronic experiences that progressively wear down psychological and physiological coping mechanisms. Developmental research on emotion regulation has focused increasing attention on the latter types of stress in recent years for several reasons: such stressors affect more children than traumatic stressors; they often occur early in life with long-lasting consequences; and these consequences can derive from reorganization of stress neurocircuitry in the brain and the effects of close relationships that can either exacerbate stress or buffer it. Stressful experiences have surprisingly early effects on development, beginning prenatally. For example, mothers’ depression during pregnancy was associated with heightened cortisol reactivity when infants were observed 3 months after birth as they underwent a moderately stressful procedure (Oberlander et al., 2008). This illustrates a kind of physiological synchrony complementary to the kinds previously discussed. These findings are consistent with many other animal and human studies describing “fetal programming” that occurs in response to signals from the mother’s body concerning nutritional sufficiency, stress, and other aspects of the world into which the fetus will be born (Davis & Thompson, 2014). They suggest that some of the foundations for emotion and stress regulatory capacities are established in mother–child interaction very early. Sometimes these effects are exerted through epigenetic changes in neural and neurohormonal systems that are implicated in  stress regulation and social affiliation (see Anacker, O’Donnell, & Meaney, 2014; Chapter 16, this volume). After birth, infants respond to their direct ­experience of stressors. Because biological stress systems—especially the L-HPA axis (discussed previously)—are maturing during the early years, they are particularly susceptible to the effects of chronic or severe stress that may progressively tax system capacities over time. Among young children living in poverty, for example, environmental characteristics such as poor housing quality, economic strain, and poor parenting were associated with dysregulated activity of the L-HPA axis from 7 months to 4 years of age (Blair et al., 2011). Moreover, toddlers living in poor families characterized by interparental violence and mothers’ “emotional unavailability” exhibited disruptions to normal L-HPA activity (Sturge-Apple, Davies, Cicchetti, & Manning, 2012). In older children, higher cortisol levels were associated with lower family socioeconomic status, and

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mothers of children with higher cortisol levels were more likely to have depressive symptoms (Lupien, King, Meaney, & McEwen, 2000). These dysregulatory effects on stress neurobiology from chronic early stressful experiences are believed to derive from adaptation of physiological systems to environmental conditions that begin with processes of fetal programming, as earlier described. Ordinary experiences of challenge and stress help “tune” biological stress systems and strengthen coping. Chronic and severe early stress, however, alters sensitivity of the L-HPA axis and other systems, in part through effects on limbic and cortical processes that regulate L-HPA activity (Ulrich-Lai & Herman, 2009). One consequence of this dysregulation is that stress responding becomes hyperreactive, with heightened responses to cues of threat and danger along with rapid escalation of response. Behaviorally, this is manifested in self-regulatory problems that can be observed in children’s heightened vigilance, emotional dysregulation, and complementary problems in cognitive and attentional focus and difficulties in social functioning (Blair & Raver, 2012). In some situations, however, chronic stress may result in neuro-adaptive “downregulation” of the L-HPA axis (Doom & Gunnar, 2013). Thus, rather than responding to threat in a hyperreactive manner, children show a lower cortisol response to stressors, and sometimes exhibit a flattened diurnal cortisol pattern throughout the day. Some researchers speculate that this alternative response pattern reflects a biological stress system that shows signs of suppression or shutting down (Bruce, Gunnar, Pears, & Fisher, 2013). There are other physiological changes associated with recurrent experiences of severe stress. Chronic stress is associated with immune suppression and “proinflammatory tendencies,” which become incorporated into biological functioning (Miller, Chen, & Parker, 2011). This helps to account for the susceptibility of children in difficult circumstances to infectious agents, both acute and chronic. There is also growing evidence of epigenetic changes in gene expression associated with chronic stress that may help to account for some of the changes in stress reactivity noted previously. The study earlier described concerning the association of prenatal maternal depression with heightened stress reactivity in 3-month-olds was related, for example, to epigenetic changes in the activation of the glucocorticoid receptor gene detected when children were newborn, a gene that is implicated in L-HPA axis function (Oberlander et al., 2008).

Taken together, potentially enduring tendencies toward emotion dysregulation can develop early in response to chronically stressful experiences. Behavior and emotion dysregulation develop because of changes in multiple physiological systems that systemically adapt to environmental experiences that signal persistent threat, challenge, and danger. Once these emotional and physiological adaptations begin to develop, they alter children’s reactions even in nonthreatening circumstances, such as school classrooms. Consequently, children in these circumstances often become identified as behaviorally disruptive and difficult, and thus evoke aversive responses from others, which can exacerbate their emotion regulatory problems. What are the circumstances leading to these developmental adaptations in behavior and biology? Researchers who examine the effects of early chronic stress most often study children in poverty, which, as earlier noted, is associated with poor housing quality, parental stress, interparental relationship difficulties, disengaged and nonnurturant parenting, and poorer child care and school quality. Other conditions studied by researchers include chronic maternal depression, foster care placement, interparental/domestic violence, and child maltreatment and chronic neglect. Significantly, in most of these circumstances, parents are either the agent of chronic stress or a victim along with the child, and are thus unable to protect the child. This underscores that the absence of parental support is an important component of severe stress for young children because of children’s dependence on adults for protection and nurturance. Without parental support as a stress buffer, children are more vulnerable to emotion dysregulation. Thus, it is important to recognize the beneficial effects that parental support can have for buffering stress or remediating its effects on children (Hostinar, Sullivan, & Gunnar, 2014). In a study of families living in rural poverty, for example, researchers found that infants’ chronic exposure to domestic violence was associated with elevated stress reactivity by age 2 years. But when mothers were observed behaving sensitively with their children in earlier home observations, repeated exposure to domestic violence was not associated with heightened stress reactivity for their children (Hibel, Granger, Blair, Cox, & the Family Life Project Key Investigators, 2011). Consistent with the findings of research on social support for adolescents and adults, reliable support from a parent is an important resource for emotion regulation in the early years. Thompson and Waters

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Differential Susceptibility

Psychological understanding of negative developmental outcomes has long been dominated by a focus on risk factors and vulnerabilities. Within the diathesis-stress model, for example, researchers examine characteristics that make some individuals more likely to succumb to the sequelae of adversity compared to those who are more resilient. There is considerable work, for example, on vulnerabilities and risk factors that contribute to the development of emotion dysregulation (e.g., Gazelle & Ladd, 2003; Kim & Cicchetti, 2010). From this perspective, some individuals have characteristics, such as difficult temperament, that heighten vulnerability to problems with emotion self-management compared with others. However, this account may be incomplete. From the perspective of differential susceptibility, individuals vary not exclusively in vulnerability factors but also in broader susceptibility to environmental influences (Belsky & Pluess, 2009). According to differential susceptibility theorists, some people are more readily influenced by their environments than others. For more susceptible individuals, the environment affects them “for better and for worse” such that they experience highly negative outcomes when environments are stressful (consistent with the diathesis-stress model), but also exhibit positive outcomes when environments are supportive. For others who are less susceptible to these environmental influences, outcomes are only slightly moderated by environmental quality. Importantly, individuals who are more susceptible to environmental influences are often viewed as being more vulnerable because research studies typically only focus on their responses to adversity, not to both adverse and supportive circumstances. Once they are studied in both contexts, positive and negative outcomes associated with putative vulnerabilities can be observed. A growing body of research has identified differential susceptibility factors in the form of phenotypic traits (e.g., temperament), neurobiological characteristics (i.e., physiological responses), and genetics (i.e., genetic polymorphisms) (Belsky & Pluess, 2009). Research studies have identified the differential influence of these factors in samples ranging from infancy through adolescence and young adulthood. In many cases, characteristics that were traditionally portrayed as risk factors that enhance vulnerability are being reconceptualized as markers of environmental sensitivity, and this is apparent from early in life. 108

Difficult temperament, which is characterized by  negative mood, reactivity, lack of rhythmicity, and slow adaptability, was among the earliest identified susceptibility factors (Belsky, Hsieh, & Crnic, 1998). In a large national sample, harsh parenting and deficient home environments predicted later behavior problems, whereas sensitive parenting was negatively associated with behavior problems, for infants with difficult temperament compared to those with average or easy temperament (Bradley & Corwyn, 2008). In another study, positive parenting in early childhood was more predictive of firstgrade academic success, social skills, peer status, and strong relationships with teachers for children who had more difficult temperaments in infancy (Dopkins Stright, Gallagher, & Kelley, 2008). Infants with difficult temperaments had better adjustment than less difficult infants when parenting quality was high but poorer adjustment when parenting was poorer. Notably, difficult temperament is not the only dispositional susceptibility factor worth considering. Associations consistent with differential susceptibility have also been found between parental effective guidance and behavior problems for highly anger-prone children, but not for non-anger-prone children (Smeekens, Riksen-Walraven, & van Bakel, 2007). Other susceptibility factors include certain patterns of physiological responding. Earlier we discussed RSA as a biomarker of individual differences in emotion regulatory capacities. Conradt and colleagues (2013) examined RSA as a potential susceptibility factor in a sample of infants growing up in poverty. They found that secure attachment predicted the least behavior problems, and that disorganized attachment predicted the greatest behavior problems for children with high resting RSA, but these associations did not hold for children with low resting RSA. In the context of family economic difficulty, in other words, higher emotion regulatory capability (indexed by high resting RSA) is associated with infants’ greater adaptation to differences in the quality of care leading to attachment. In another study, kindergarten-age children who had strong RSA responses to a series of challenging tasks subsequently exhibited the greatest behavior problems and lowest school engagement when they also experienced family adversity, but the greatest school engagement and fewest behavior problems when they did not experience adversity. Children who did not have strong RSA responses to challenge did not exhibit this for-better-and-for-worse set of associations (Obradovic et al., 2010). Whether at rest or

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in response to specific tasks, there is evidence of RSA as an indicator of a child’s susceptibility to the environment. Genetic variation can also constitute susceptibility factors. Researchers have investigated several candidate genes, most notably DRD4 gene polymorphisms. This dopamine receptor gene, particularly the allelic variant known as the 7-repeat allele, is implicated in novelty seeking and impulsive behavior. In one study, toddlers’ 7-repeat allele showed an inverse association between the quality of parenting and sensation seeking. In contrast, no such associations were found for children without the 7-repeat allele (Sheese, Voelker, Rothbart, & Posner, 2007). Others have also reported this for-betterand-for-worse effect of parenting for children with the DRD4 7-repeat polymorphism compared to those without, underscoring the significance of this Gene × Environment interaction (BakermansKranenburg & van Ijzendoorn, 2006; Windhorst et al., 2014). The expanding research literature on differential susceptibility challenges simple diathesis-stress models by suggesting that characteristics typically portrayed as vulnerability factors may instead have more complex associations with emotion dysregulation. Viewing these characteristics instead as markers of environmental sensitivity reorients researchers to elements of the environment that cause these characteristics to be associated with positive or negative developmental outcomes. It is no accident that most developmental research on differential susceptibility has emphasized the influence of parenting quality and family life, because these are the most important elements of environmental influence, especially to a young child. This has important implications for intervention (as discussed further later). Taken together, this research underscores that vulnerability to emotion dysregulation is sometimes less in the child alone and more in the Child × Context interaction.

Synthesis and Future Directions

Research described in this chapter supports the theoretical view with which we opened: emotion regulation and dysregulation develop in contexts of relationships, and developing problems in emotion management are relational problems as well as individual difficulties. This conclusion, which has roots in attachment theory, is most readily evident in studies with young children, but, as earlier noted, older children, youth, and adults also rely on others for support in emotion regulation, and relational

problems can contribute to emotion dysregulation at all ages. We propose that a relational orientation can strengthen inquiry into the nature of emotion dysregulation throughout life by contributing a deeper understanding of the influence of other people—as providers of support, sources of stress, models of emotion regulation and dysregulation, evaluators of one’s feelings, and contributors to the general emotional climate of close relationships. With the predominant orientation of current research on adult emotion regulation toward the functioning of individual strategies such as cognitive reappraisal and emotional suppression (e.g., Gross, 2015), expansion of the field to include attention to relational influences would be worthwhile (see also Beauchaine & Zalewski, 2016). Expanding inquiry into the relational bases of emotion regulation and dysregulation is important also for clinical intervention. When young children are emotionally dysregulated, infant and early childhood mental health practices are concertedly twogenerational, enlisting the child’s parents and other relational partners (such as early education care providers) into therapeutic avenues to address the relational bases for the child’s dysregulation (Zero to Three, 2016). The importance of relationships to emotion dysregulation is recognized also at older ages in marriage and family therapy. The predominant approach to psychotherapy, however, is to treat the individual, which means that associated issues of emotion dysregulation are decontextualized from the relational processes that may have contributed to their development. Greater consideration of these relational processes in therapeutic contexts is warranted. A second conclusion also points toward a future direction for the field. From research literatures focused on the physiological synchrony of relational partners (with our focus on parents and children), socialization of stress neurobiology, and differential susceptibility to environmental influences, we described connections between relational experience and biological processes associated with emotion dysregulation. These connections are complex and bidirectional: social experiences associated with stress alter how biological stress systems function, making emotion dysregulation under challenging conditions more or less likely; the social context can make environmental susceptibility factors (such as difficult temperament) assets or liabilities for outcomes related to emotion dysregulation; social influences can support or undermine emotion regulation through physiological synchrony shared by relational partners. Thompson and Waters

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These research fields contribute a biological dimension to understanding the development of emotion dysregulation and confirm the growing recognition that the traditional nature-versus-nurture dichotomy is scientifically obsolete (Thompson, 2015). They also show that biological bases of emotion dysregulation, whether in stress neurobiology, individual temperament, or genetic propensities, are far more dynamic in their influence than earlier believed because of their continuous interaction with experience. Further efforts to empirically elucidate the interplay between social (especially relational) experience and biology is certainly warranted, especially concerning the origins of differences in emotion dysregulation. Fortunately, continuing research in fields such as molecular genetics, epigenetics, and life history theory offer promise for further ­understanding. Developmental interactions between social experience and biology are also important for clinical applications. The possibility that, from the perspective of differential susceptibility, children with a susceptibility factor such as the DRD4 7-repeat allele are likely to thrive in a more supportive social context underlies therapeutic efforts focused on improving the caregiving context because these children might especially benefit from such efforts (see Bakermans-Kranenburg, van Ijzendoorn, Pihlman, Mesman, & Juffer, 2008). In other clinical contexts, recognition that prior experiences of chronic stress have dysregulated biological stress systems has oriented some therapeutic programs for young children in foster care to measure the functioning of the L-HPA axis and the security of attachment relationships as indicators of therapeutic success (see review by Thompson, 2014). Understanding emotion dysregulation as a multilevel process involving behavioral and biological factors contributes a multilevel orientation to clinical intervention and promotes attention to multiple indicators of therapeutic outcome. Finally, the functionalist approach to understanding emotion dysregulation is affirmed by the research literatures discussed in this chapter. Young children who live in poverty, live with a depressed parent, possess a genetic vulnerability to impulsivity, and/or are born with a difficult temperament are often emotionally dysregulated, but it is more important to understand the strategies they enlist to manage their feelings in the contexts in which this occurs. In some cases, differential susceptibility means that children’s characteristics may or may not predict emotion dysregulation depending on the 110

context. In other cases, emotion dysregulation derives from the child’s physiological synchrony with another who is emotionally dysregulated. For children who experience chronic stress, emotion dysregulation derives from complex emotional challenges they face. From the functionalist orientation of this chapter, understanding these children as emotionally dysregulated must lead to a more searching examination of the interaction of characteristics of the child and the social environment in the context of the multiple emotion goals the child may be seeking, implicitly or explicitly, to accomplish. Viewed in this light, children’s emotional experiences can be appreciated and understood with all the complexity and depth they warrant.

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CH A PT E R

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Operant Reinforcement and Development of Emotion Dysregulation

Christina Gamache Martin, Maureen Zalewski, Grace Binion, and Jacqueline O’Brien

Abstract Caregivers play a foundational role in the development of children’s emotion dysregulation. Yet, because there are a multitude of ways in which parent behavior can intersect with children’s emotions, the development of emotion dysregulation is complex. This chapter specifically examines the role of operant reinforcement, where the way in which caregivers respond contingently to their children’s expression of emotion influences child emotion dysregulation. It reviews (1) the central theoretical models that explicate the process by which parental responses to children’s emotions reinforce emotion dysregulation, (2) current evidence supporting these theories, and (3) interventions designed to reduce emotion dysregulation through operant reinforcement processes. It emphasizes that, in addition to unidirectional effects, operant reinforcement from a parent interacts with traits inherent to the child, and parents and children mutually influence one another in ways that highlight the transactional, dynamic processes underlying the development of emotion dysregulation. Limitations and future directions are discussed. Keywords:  emotion dysregulation, operant reinforcement, development, parent-child interactions, parental emotion socialization, coercion theory, invalidating environment

Introduction

Emotion dysregulation is more than the absence of regulation. It is “a pattern of emotional experience and/or expression that interferes with appropriate goal-directed behavior” (Beauchaine, 2015, p. 876). Moreover, there must be evidence of emotional expression that exceeds or differs from what would be warranted in a given context and for which regulatory abilities are inadequate for managing emotion, while also avoiding equating expression of a negative emotion as being “emotionally dysregulated” (Cole, Martin, & Dennis, 2004). Emotion dysregulation is a construct of interest within psychology because emotion regulation deficits serve as a transdiagnostic feature across most forms of psychopathology (Aldao, Nolen-Hoeksema, & Schweizer, 2010). From this observation, it follows that dysregulated expression and maladaptive strategies for  regulation of emotions during childhood are

precursors to several forms of psychopathology (McLaughlin, Hatzenbuehler, Mennin, & NolenHoeksema, 2011). Given the centrality of emotion dysregulation in the development and presentation of psychopathology, it is critical to identify how emotion dysregulation emerges during childhood. Operant reinforcement, a primary theory of learning, is a critical tool in understanding how ­reinforcement patterns shape a child’s (in)ability to regulate emotion. Parenting can alter children’s ability or inability to regulate emotions over time. More specifically, emotion dysregulation is shaped by ways in which caregivers respond contingently to a  child’s expression of emotion and, in turn, how the child’s subsequent responses affect caregivers. Emotional expressions or experiences that encourage or interfere with goal-directed behavior can be positively reinforced (e.g., a caregiver only responds to a child’s extreme expression of negative emotion, 115

increasing the likelihood that the child will use ­similar strategies in the future) or negatively reinforced (e.g., a child whines to avoid eating broccoli and then throws it on the floor; the parent then removes the broccoli, increasing the likelihood that the child will use similarly dysregulated strategies in the future). The development of emotion dysregulation is complex because emotions and efforts to regulate emotions are multifaceted. In addition, there are a multitude of ways in which parent behavior intersects with child emotions. The pairing of children’s emotions and regulatory efforts with positive and negative reinforcement by parents can lay the foundation for emotion dysregulation during childhood. Improved understanding of the mechanistic processes that shape emotion dysregulation has also led to novel interventions that target children’s emotional expression, promote effective regulation, and, importantly, intervene with parents to support effective responses to their child’s emotions (e.g., Havighurst, Wilson, Harley, Prior, & Kehoe, 2010). This chapter reviews theory, current evidence, and interventions that target the development of emotion dysregulation in children. Specifically, we will address the following questions: (1) What are the central theoretical models linking parental ­responses to children’s emotions with emotion dysregulation? (2) What is the current evidence supporting these theories? (3) How do interventions targeting operant reinforcement processes provide additional evidence of mechanistic processes underlying emotion dysregulation? (4) What are the limitations of the current literature and key next questions? Although beyond the focus of this chapter, it is important to recognize that operant reinforcement, in terms of positive and negative reinforcement patterns, continues to develop within peer and romantic relationships and may replicate and maintain problematic patterns of emotion dysregulation across the lifespan (see Dishion & Snyder, 2016). The current chapter focuses on how operant reinforcement in caregiver–child relationships shapes child emotion dysregulation.

Terms and Measurement Issues

Measurement tools are reviewed briefly because the definition of a construct is informed by the way in which it is measured (Larsen & Prizmic-Larsen, 2006). Emotion dysregulation is inherently multifaceted because emotions entail full-system responses. Therefore, measurement is accomplished using a range of methods, including observational 116

and behavioral measures. Specific methods often vary based on the developmental period assessed (Adrian, Zeman, & Vetis, 2011). For example, measuring behavioral responses through observational methods is more common in young children, whereas assessing subjective experience through self-report is more prevalent in older children and adolescents. Researchers often measure facial, bodily, or vocal cues associated with discrete emotions using laboratory tasks designed to elicit negative emotions. Then the corresponding emotional expressions and any behavioral attempts to manage those emotions are coded (i.e., problem solving, distraction, disruptive behavior) so that attempts are made to disentangle expression of negative emotions from regulatory efforts. In contrast, internal experiences of emotion dysregulation are measured via self-report and through physiological measures. More recently, self-report methodologies have been enhanced by the use of ecological momentary assessment (EMA), particularly with adolescents (Shiffman, Stone, & Hufford, 2008), in which sampling occurs at various instances throughout the day to more accurately assess the dynamic nature of emotions. The most common physiological index of emotion dysregulation is respiratory sinus arrhythmia (RSA). RSA, also known as vagal tone or heart rate variability, is a measure of parasympathetic nerv­ous system influence on cardiac activity. Higher resting RSA has been linked consistently with emotional stability, whereas lower resting RSA has been linked consistently with emotional lability and dysregulation (e.g., Beauchaine, Gatzke-Kopp, & Mead, 2007). Small decreases in RSA in response to a stimulus or stressor (i.e., vagal withdrawal) have been linked to effective emotion regulation (Calkins, Graziano, Berdan, Keane, & Degnan, 2008), whereas larger decreases appear to mark significant dysregulation (e.g., Crowell et al., 2005). While these measurement tools offer ways to assess emotion dysregulation, they must be embedded within specific study designs to accurately investigate operant reinforcement of emotion dysregulation. Specifically, a parent’s response must follow a child’s expression of emotion or regulatory strategy. Alternatively, reciprocal models that examine dynamic reinforcement patterns between parent and child must measure transactional influences of parents and children on each other across time. Interaction models examine how parenting affects children’s emotion dysregulation in the context of another variable, such as child sex, trait characteristics, or genetic predispositions. The dominant

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coding strategies for observational data include ­micro-coding, which examines reciprocal exchanges that occur on brief time scales, and global coding, which is based on longer coding units and may require greater inference (Julien, Markman, & ­ Lindahl, 1989). It is also common for researchers to use self-report measures to assess typical parent responses to child emotion dysregulation. However, this limits the ability to detect temporal links ­between child emotion dysregulation and parental reinforcement. More recently, researchers have combined creative study designs and multimethod approaches, which has promoted more rigorous testing of key theories of operant reinforcement and the development of emotion dysregulation.

Theoretical Perspectives

Three primary models examine how caregivers shape emotion dysregulation across childhood and adolescence by focusing on how parents respond immediately after encountering a child’s emotion or regulation strategy. The first model emerged from research on normative developmental processes and was the first to operationalize and promote rigorous measurement of children’s emotion regulation abilities. Specifically, parental emotion socialization refers to the way in which parents contribute to the development of children’s emotion competence, including emotion regulation (Morris, Silk, Steinberg, Myers, & Robinson, 2007). While various theories of parental emotion socialization exist, researchers generally agree that parents shape emotion regulation by the way they (1) respond to a child’s emotion (emotionally contingent responses), (2) regulate their own emotions in front of their child (modeling), (3) engage in parenting and form attachments with their child (family emotional climate), and (4) talk directly about emotions and emotion regulation with their child (emotion coaching; Morris et al., 2007). While emotion socialization theories have been highly influential and have prompted research on parental influences on children’s emotion regulation, they are focused predominantly on the direct or main effects of parent to child. In contrast to this unidirectional and normative developmental approach, two theoretical models originating from different traditions, coercion theory and the invalidating environment model, describe children’s emotion dysregulation as both shaped by and shaping parental behavior. Both emphasize reciprocal and dynamic exchanges that contribute to emotion dysregulation through behavioral reinforcement processes. These theories move beyond

main-effects models to better incorporate the role of operant reinforcement, and how parent and child mutually influence one another’s emotion expression and regulation. Coercion theory was born from behavioral observation and microanalytic coding of dyadic exchanges in the homes of at-risk families (e.g., Patterson, Dishion, & Bank, 1984; Snyder, 1977). This model is presented in a functional-analytic frame in which children’s aversive behaviors are negatively reinforced because they serve the function of momentarily stopping their parents’ aversive behaviors (Beauchaine & Zalewski, 2016). As noted by Patterson, DeBaryshe, and Ramsey (1989, p. 330), “the most important set of contingencies for coercive behavior consist of escape conditioning [in which] the child uses aversive behaviors to terminate aversive intrusions by other family members.” Snyder further demonstrated that aggressive boys become more likely to escalate conflict once in a dysregulated, irritable state (Snyder, Schrepferman, & St. Peter, 1997), and that intense displays of ­negative affect are more likely to cease conflict in aggressive dyads than in control dyads (Snyder, Edwards, McGraw, Kilgore, & Holton, 1994). In this way, children’s extreme emotion dysregulation, as manifested through aggression or violence, can be viewed as a subsequent outcome of reciprocal, aversive exchanges that occur repeatedly across development in at-risk families. The invalidating environment model is rooted in Linehan’s (1993) biosocial theory that depicts a transactional model in which individual (e.g., trait vulnerability) and environmental factors (e.g., lack of support) transact over time to influence emotion dysregulation. Invalidating environments can be ­defined by four primary parenting characteristics: communications of inaccuracy, misattribution, discouragement of negative emotional expression, and oversimplification of problem solving (Cummins, Zalewski, Lewis, & Stepp, under review). Across these four types of responses, the parent communicates that both internal experiences and public expressions of emotions are invalid and inappropriate. In an invalidating environment, expressions of emotion, such as fear or sadness, may only be attended to when they are extreme, while more moderate displays of negative emotion are ignored or punished. This pattern both reinforces extreme displays of emotion and fails to provide scaffolding or tools necessary to facilitate regulation at lower levels of distress. This leads the child to “oscillate between emotional inhibition on the one hand, and extreme

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emotional states on the other” (Linehan, 1993, p.  51). When extreme displays of emotion do not appear valid for the given situation, however, they tend to prompt further invalidating responses from parents, thus creating a transactional pattern. Because the invalidating environment minimizes the difficulties of solving one’s problems (e.g., a  pull-yourself-up-by-the-bootstraps approach), a child does not learn distress tolerance or the ability to set goals and expectations that are realistic and achievable. Thus, as a consequence of both trait vulnerability and a lack of support from their environment, emotionally dysregulated children struggle to  learn effective strategies for managing aversive emotional states. As a result, problematic behaviors, such as self-inflicted injury, begin to serve an emotion regulatory function, which serves as a form of avoidance or escape from negative emotions.

Current Findings

Given the focus of this chapter, we limited our review to studies that (1) specifically assessed emotion (dys)regulation or a primary component of the construct, (2) were designed in such a way that parental responses temporally preceded assessment of child emotion (dys)regulation, or (3) examined transactional models. Further, because emotion dysregulation appears to precede diagnosable psychopathology, we focus predominantly on children’s emotion dysregulation as opposed to psychopathology. We implemented this criterion because psychopathology is often used as a proxy for emotion dysregulation. Yet, we believe that it is clinically and scientifically advantageous to maintain a distinction between the two constructs to better understand the development of emotion dysregulation. While we permitted some studies to be framed as emotion regulation or a component of emotion regulation, instead of emotion dysregulation, we did so only when study results suggested that certain parental responses predicted deficits in emotion regulation. Given that there are many ways to measure emotion dysregulation, we detail how it was operationalized in each study. Finally, we organize this review in terms of the models tested: main-effects, interaction, and transactional models.

Main-effects models

Morris and colleagues (2011) sought to expand upon research delineating the benefits of supportive maternal responses (e.g., Cole, Dennis, Smith-Simon, & Cohen, 2008) by clarifying which specific ­supportive responses (i.e., comforting, attention 118

r­ efocusing, cognitive reframing) would best facilitate 4- to 9-year-olds’ expressions of anger and sadness in the context of disappointment. Children were presented with a disappointing gift in the presence of their mothers, and their mothers were instructed to respond naturally to their child’s emotional expression—a component of emotion regulation ­ (Dennis, Cole, Wiggins, Cohen, & Zalewski, 2009). The authors assessed mothers’ operant reinforcement of emotional expression by coding child affect in 10-second epochs; maternal responses were microcoded and time-synced to emotion expression epochs to examine the influence of mothers’ regulatory strategies on children’s emotional expression in the following epoch. Mothers’ attempts to comfort their children were not associated with children’s ­expressions of anger or sadness. Rather, for children younger than age 8, maternal efforts at distraction and refocusing children’s attention were associated with children immediately displaying less sadness. Moreover, when children and their mothers jointly engaged in cognitive reframing, children expressed less sadness and anger. Importantly, and in contrast to a transactional model, children’s expressed emotions did not predict which strategies were used by their mothers. Thus, in the context of a disappointing experience, mothers who can effectively distract their young children by refocusing their attention or by facilitating joint cognitive reframing enhance their children’s abilities to regulate their feelings of sadness and anger. Binion and Zalewski (in press) built upon this study of children’s expressed emotion by also observing and micro-coding preschoolers’ regulatory behaviors in a frustration-eliciting Locked Box Task (Goldsmith & Rothbart, 1996), in which emotionally regulated children typically engage in problem solving when frustrated (Dennis, Cole, Wiggins, Cohen, & Zalewski, 2009). This study, which oversampled mothers with extreme emotion dysregulation, assessed supportive maternal responses (i.e., encouraging emotion expression or provision of helpful strategies) and unsupportive responses (i.e., minimizing or punishing emotion) to children’s distress. Maternal supportive responses were associated with children’s attempts to engage in play during the frustrating task, while maternal unsupportive responses were associated with children engaging in more disruptive behaviors, such as throwing the locked box, leaving the room, and shouting at a research assistant, when frustrated. Thus, in addition to observed maternal support being associated with lower offspring expression of negative

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emotion (Morris et al., 2011), the findings from this study suggest that mothers’ self-reported unsupportive responses are associated with children engaging in more disruptive regulatory attempts in the context of negative emotions. A third study examined how parent emotion socialization shapes youth reactivity to negative events within peer and nonpeer contexts in a sample of anxious youth aged 9 to 14 (Oppenheimer et al., 2016). This study is noteworthy because most studies with older children rely solely on self-report. In this case, however, the authors observed and microcoded parents’ supportive and unsupportive behaviors second by second during a 2-minute period where the parent helped his or her child prepare for a social-evaluative speech task. Parent responses to youth during this anxiety-provoking task were used to predict youth negative reactivity during 14 EMAs of negative events across 5 days. Supportive parental responses were associated with significantly less negative affect for youth in response to negative peer events compared to nonpeer events, suggesting that supportive parenting behaviors during an anxietyprovoking task can buffer anxious children’s negative responses to stressful peer events. Taken together, the three studies reviewed here suggest that supportive and unsupportive contingent maternal responses may serve to shape children’s emotional expression, level of reactivity, and regulation in the context of distressing experiences across early childhood through early adolescence.

Interaction models

Gender may be an important moderator to consider when examining how parents respond to children’s regulation of emotion. Yap, Allen, and Ladouceur (2008) found gender effects in the context of maternal socialization of positive affect. Adolescents and mothers, in a high-risk sample, engaged in two interaction tasks designed to elicit both positive (i.e., event planning) and negative (i.e., conflict discussion) affect, respectively. Emotion dysregulation was operationalized as the frequency and duration of adolescent aversive or dysphoric behaviors, as well as fewer positive behaviors in both mother–adolescent interactions. Maladaptive emotion regulation strategies were also measured using adolescent self-­report on the Child Affect Questionnaire–Child Strategies (Garber, Braafladt, & Weiss, 1995). The study found that mothers’ validating responses to adolescents’ displays of positive affect via self-report served as a protective factor for males, who demonstrated less dysregulation of positive and negative affect during

the conflict task. The authors also deconstructed maternal invalidation into punishing and dampening (i.e., minimizing) responses to a­ dolescent positive affect, and found that when mothers responded in punishing ways during event ­pla­nning, males maintained longer durations of aversive behaviors in the conflict task, while females were more likely to reciprocate their mothers’ dysphoric behaviors. Mothers’ dampening responses were unrelated to adolescent emotion dysregulation, but were related to more frequent use of maladaptive emotion regulation strategies in females. These findings suggest that females may be at greater risk for emotion dysregulation when mothers are less validating and more invaliding of their daughters’ emotions, particularly their positive emotions. Another study with self-injuring and control teens highlighted how mother invalidating and aversive behaviors interacted with adolescent aversive behaviors during conflict to predict adolescent emotion dysregulation, as indexed by RSA (Crowell et al., 2013). Crowell and colleagues found that adolescents in dyads where both mother and adolescent exhibited high levels of aversive behavior showed the lowest resting RSA, which is indicative of greater emotion dysregulation. However, in dyads where mothers showed high rates of aversive behavior but the adolescent showed low aversive behavior, adolescents had high RSA, which may have been protective. There were no differences in adolescent RSA for dyads with low-aversive mothers. It therefore appears that maternal aversiveness may be particularly problematic for adolescent emotion dysregulation among more vulnerable adolescents. Moreover, during conflict interactions, mothers of adolescents who engaged in self-injury had a higher probability of matching or escalating the adolescent’s level of aversiveness. In contrast, mothers of control adolescents were more likely to de-escalate conflict following adolescent aversive behavior. Interestingly, the only time self-injuring adolescents and their mothers reliably deescalated conflict was in response to very high levels of aversive behavior from one another. Crowell and colleagues suggested that negative reinforcement of highly aversive behavior may function to reduce conflict in the short run but in the long run likely increases and maintains emotion dysregulation in both parent and child. Taken together, these findings suggest that treatment may be more beneficial when providers target both mother and adolescent behaviors. Genetic research provides an additional avenue to examine how child characteristics interact with

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the environment to influence emotion dysregulation. Specifically, research in this area has found that insecure attachment styles serve as a risk factor in adolescents (Zimmermann & Spangler, 2016) carrying one or two short 5-HTTLPR alleles, which are associated with greater emotional vulnerability (Canli & Lesch, 2007). Emotion regulation in adolescents was measured by their ability to engage in effective emotion regulation strategies while interacting with their mothers during an emotion-eliciting computer game task (Zimmermann & Spangler, 2016). Insecure attachment styles were associated with greater emotion dysregulation, but only for youth with genetic vulnerability. For youth with secure ­attachment styles, there was no association between genetic vulnerability and emotion dysregulation. Similar to Crowell et al. (2013), these findings highlight how an emotional environment with less optimal contingent responses from parents (i.e., aversive maternal behaviors and insecure attachments) is most problematic in terms of youths’ emotion dysregulation when the youth are more vulnerable (i.e., aversiveness or genetic risk).

Transactional models

During infancy, Kiel, Gratz, Moore, Latzman, and Tull (2011) found that mothers’ insensitive behaviors increased in response to infant distress that persisted for longer durations during the Strange Situation (Ainsworth, Blehar, Waters, & Wall, 1978), but only for mothers with high borderline personality disorder (BPD) features. In turn, infant distress was more likely to follow displays of maternal negative affect and maternal insensitive behaviors. The opposite pattern was found for mothers low in BPD features, where they were more likely to respond to infant distress with positive affect, and infant distress was less likely to be observed following maternal positive affect. This work not only supports a main-effects model indicating that maternal response to infant distress influences infants’ ability to regulate emotion but also highlights how infant distress may evoke insensitive maternal responses, especially for more dysregulated mothers. This finding underscores the crucial role of mothers’ ability to regulate their own emotions and to respond sensitively in the face of infants’ negative affect in averting dysregulation in their children. This bidirectional relationship has also been supported with longitudinal data across early childhood. Two longitudinal studies explicate associations between aversive parent–child transactions and child emotion dysregulation across early childhood. 120

Perry, Mackler, Calkins, and Keane (2014) examined the relation between maternal sensitivity and preschoolers’ emerging regulation capabilities, indexed by greater vagal withdrawal (i.e., decreased RSA in response to a stressor), in a sample of 356 mother–child dyads oversampled for children at risk for externalizing problems. At each time point, children’s vagal activity was measured while children completed age-appropriate frustration tasks (i.e., the Locked Box Task at age 2½, the Impossibly Perfect Circles Task at age 4½, and the Not Sharing Task at age 5½). Maternal sensitivity was assessed at each time point during pretend play and clean-up tasks, which was later coded and assigned a global sensitivity code for the entire interaction. Results supported a cross-lagged model, such that maternal sensitivity when children were age 2½ was associated with children’s improved regulation (i.e., greater vagal withdrawal) at age 4½, which was in turn related to increased maternal sensitivity when children were age 5½. Yates, Obradovic, and Egeland (2010) similarly examined a transactional model of parenting quality and child emotion dysregulation in an at-risk sample of children and their mothers. They observed child emotion dysregulation in the context of frustration with a series of problem-solving-tool tasks that increased in complexity at age 2 and using Block’s Barrier Box Task (Harrington, Block, & Block, 1978) at age 3½. Parenting behaviors were likewise observed and coded in terms of supportiveness, limit setting, and quality of instruction/assistance during challenging laboratory tasks at visits 1 and 2, while parenting quality at child age 6 was assessed using the Home Observation for Measurement of the Environment (Caldwell & Bradley, 1984). Their results supported a transactional model in which parenting quality at child age 2 predicted children’s emotion dysregulation at age 3½, which in turn predicted poorer parenting quality at child age 6. This model was found to be a better fit for the data than a continuity model in which parenting quality at each time point predicted parenting quality at the following time point. The results of these longitudinal studies provide support for the transactional model, demonstrating that the development of child emotion ­dysregulation emerges over time, as a transaction between children’s aversive expression of emotion and parents’ aversive responses. Finally, this same transactional pattern of ­aversive parent–child interactions has been linked to emotion dysregulation in middle childhood (Morelen & Suveg, 2012). Parents’ supportive and

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unsupportive emotional responses, as well as children’s adaptive and maladaptive emotion regulation behaviors, were observed during four 5-minute emotional discussions about a time the child felt angry, anxious, sad, and happy. Children were coded as having adaptive emotion regulation behaviors when they verbally expressed their emotion, discussed emotion, or discussed a developmentally appropriate emotion regulation strategy. In contrast, maladaptive emotion regulation behaviors were coded when the child engaged in dysregulated behavior such as whining, yelling, or making derogatory comments or when the child was rude. The results supported a transactional pattern between parent and child exchanges where children’s use of adaptive emotion regulation behaviors tended to be followed by more supportive emotion responses by parents, which were in turn followed by additional adaptive emotion regulation behaviors in children. This pattern of results was found across emotion type and parent. In contrast, when examining the transactional pattern for children prone to using maladaptive emotion regulation behaviors, unsupportive emotional responses from parents were only more common during the discussion of anger. These results appear to align with coercion theory where the transactional nature between parent and child is escalatory, as would likely be the case with anger, as opposed to a discussion related to anxiety, sadness, and happiness. In summary, results from the extant literature support theories that operant reinforcement of emotion contributes to the development of emotion ­dysregulation. Although the majority of researchers examined this process through a main-effects model, many scholars extended beyond such direct effects to examine child traits that affect parent-contingent ­responses to shape child emotion dysregulation. In addition, several research groups examined the reciprocal effects of children on parents.

Testing Operant Reinforcement Through Clinical Interventions

Clinical interventions, particularly those that use randomized controlled trial designs, offer a powerful experimental tool by which to examine mechanistic processes. Thus, in lieu of an exhaustive review of emotion dysregulation interventions, our goal here is to provide another test of key theories by examining whether interventions targeting operant reinforcement processes have an effect on emotion dysregulation. We focus on interventions that (1) target parent emotion dysregulation as a moderator

or mediator of change or (2) intervene directly on operant reinforcement models by incorporating the parent and conceptualizing parental response to child emotion as a primary agent of change. We review three principal modes of clinical intervention: parent training interventions, developed from coercion theory; dual-generation interventions, which incorporate parental emotion socialization; and interventions that target invalidating environments as a means to reduce emotion dysregulation in children and adolescents.

Parent training interventions

As evidence of parents’ role in children’s emotion (dys)regulation across development has become more prominent (e.g., Morris et al., 2007), many parent training interventions have shifted from focusing ­exclusively on parental-contingent responses to children’s problematic behaviors to also incorporating emotion coaching or emotion socialization components into their protocols. Parent training interventions that incorporate these emotional components for preschool-aged children with inattention, hyperactivity, and oppositional behaviors have shown promising results for reducing children’s emotion dysregulation. Specifically, Webster-Stratton and colleagues found that mothers and fathers in the Incredible Years (IY) program reported significant improvements in their children’s emotion regulation skills at posttreatment compared to parents of waitlisted children (Webster-Stratton, Reid, & Beauchaine, 2011), and these treatment effects were maintained at the 1-year follow-up (Webster-Stratton, Reid, & Beauchaine, 2013). These results suggest that emotion socialization components can be added to parent training interventions to help parents change the way they respond to their children’s emotions and reduce child emotion dysregulation.

Dual-generation interventions

Dual-generation interventions are those that intervene at the level of both the child and the parent to maximize benefits for the family by simultaneously targeting parental and child psychopathology or distress (Shonkoff & Fisher, 2013). Dual-generation interventions target parents’ contingent responses to child negative emotion, as well as the parent’s own emotion dysregulation difficulties (i.e., parents actively acquire emotion regulation skills). The aims of these interventions are twofold: to reduce child emotion dysregulation and children’s externalizing behaviors, and to reduce parents’ own emotion ­dysregulation.

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Havighurst and her colleagues developed a widely studied dual-generation intervention for parents and their preschool-aged children (Tuning into Kids [TIK]; Havighurst, Wilson, Harley, & Prior, 2009) or adolescents (Tuning into Teens [TINT]; Havighurst, Kehoe, & Harley, 2015). A primary aim of these interventions is to help parents become more aware of their own emotions and to “sit with” these emotions while simultaneously validating their child’s emotion and helping him or her to manage it as needed. Parents’ well-being is conceptualized as critical for their emotional availability and responsiveness to their child’s emotional needs (Havighurst et al., 2009). In comparison to waitlist control groups, results from the TIK (Havighurst et  al., 2010) and TINT (Havighurst et al., 2015) ­interventions, which coached contingent parental responses to children’s emotions, demonstrated increases in parental emotion awareness and decreases in parental emotion dysregulation while also increasing child knowledge of emotion and decreasing child problematic behaviors. Finally, when comparing TIK to a parent training intervention and waitlist control, both treatments were equally effective (Duncombe et al., 2016). Despite the overall lack of difference in treatment outcomes across the interventions, when parents were more psychologically distressed, their children benefited more from the TIK intervention, which focused on helping parents to become aware of their own emotions and to contingently respond to their children’s expression of emotion in ways that communicate understanding and acceptance. These results support the use of  a dual-intervention approach when parents are managing their own distress and psychopathology, where responding contingently to children’s emotions in a supportive manner (i.e., TIK) appears to be more beneficial than contingently responding to their behaviors (i.e., parent training).

Invalidating environment

Child abuse perpetrated by a family member or a child’s disclosure of abuse to a family member that is not fully believed or supported is an extreme example of the invalidating environment. Evidencebased treatments for trauma emphasize affect regulation and incorporate parents coaching children in regulating emotions and validating children’s negative emotions related to the abusive experience. Sharma-Patel and Brown (2016) examined the role of child emotion regulation as a mediator and moderator in trauma-specific treatment. Despite the theorized mediating role of emotion regulation, it 122

did not mediate trauma treatment outcomes. They found support for the moderating role of emotion dysregulation in the reduction of posttraumatic stress disorder (PTSD) symptoms. Specifically, they found that for children with low levels of emotion dysregulation, PTSD symptom reduction was reported at mid- and posttreatment, but for children with high levels of emotion dysregulation, PTSD symptom reduction was reported only at posttreatment. The timing of symptom reduction is important because the first phase of trauma treatment focuses on teaching coping skills to manage emotion dysregulation. These results suggest that for children high in emotion dysregulation, the phase of treatment designed to help children regulate their emotions may only be effective for children with less emotion dysregulation. However, children with low, medium, and high emotion dysregulation all demonstrated reductions in PTSD symptoms by posttreatment. Sharma-Patel and Brown (2016) speculated that these posttreatment reductions reflect the exposure component of treatment. Alternatively, these greater PTSD reductions found for children high in emotion dysregulation might also result from parents validating their emotions and experiences during the latter half of treatment. Children share their trauma narratives with their parents and parents are coached to respond in validating ways. Thus, parents are coached to contingently respond to their children’s expressions of negative emotion in supportive ways, and children’s appropriate expression of negative affect is positively reinforced, encouraging future discussion about their abuserelated emotions. A second alternative explanation relates to a methodological limitation, in that the authors only assessed parent report of child emotion dysregulation. Thus, it could be that parents with greater emotion dysregulation themselves were more likely to perceive their children as more emotionally dysregulated, especially during the earlier phases of treatment. Future research would benefit from parsing out the benefits of exposure and validating responses from caregivers to determine the role of operant reinforcement in trauma treatment for children, as well as assessing both parent and child report of children’s emotion dysregulation. To date, results from studies incorporating parental emotion socialization and coaching provide a growing base of evidence suggesting that the ways in which parents respond contingently to children’s emotions are important for children’s emotional competence and ability to regulate emotions. When comparing interventions where the focus on contin-

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gent responding is placed on child emotion versus child behavior, these interventions appear to be equally effective but may differ based on parent emotion dysregulation. In conjunction with this possibility, the finding by Kaminski, Valle, Filene, and Boyle (2008) that parent training interventions that incorporate emotional communication are associated with the greatest increase in targeted parenting behaviors or skills suggests that parents are benefiting, and it may be that, in line with dualgeneration interventions, parents who are the most dysregulated are benefiting more.

Limitations and Future Directions

First, the extant literature is biased in its focus on mothers over fathers, despite findings that fathers play an integral role in child development (Lamb, 2010) and may respond differentially to child emotion (Klimes-Dougan et al., 2007). None of the studies reviewed were exclusive to fathers, and only two included fathers (e.g., Morelen & Suveg, 2012; Oppenheimer et al., 2016), with fathers making up 5% of parents in one of the studies. In addition to missing a valuable piece of the puzzle by not including fathers or other coparents or caregivers in this research, excluding fathers makes it difficult to ­explore their influence on mothers’ contingent responding. Examining potential differences in the case of single parenting as compared to coparenting is also recommended. Rather than continuing to note the lack of fathers as a one-sentence limitation or a direction for future research, researchers must make a conceptual shift and commit to better understanding the role of fathers in children’s development of regulated and dysregulated emotion. Second, given the multifaceted nature of emotions and the multitude of ways that parental behavior intersects with children’s emotions, more theory-driven research is needed. Within the three primary theories reviewed, the majority of the extant research comes from the parental emotion socialization theory, which relies heavily on self-report measures to assess parents’ contingent responses to children’s emotions. This is problematic when the timing between the contingent response and the child’s expression of emotion or use of an emotion regulation strategy is not immediate. Moreover, this work focuses predominantly on main effects from parent to child. Although we have highlighted research examining more complex parent–child patterns of interactions, there is a relative dearth of evidence for transactional models and in particular those based on the invalidating environment theory

(e.g., Crowell et al., 2017), which emphasize the emergence of emotion dysregulation as a transaction between caregivers or other environmental influences and children. Studies seeking to test these models must assess both children’s emotion dysregulation and parenting, ideally at three or more time points across many months or years. Although such studies are costly and difficult to conduct, they more accurately assess bidirectional, reciprocal relationships embedded within parent–child interactions. Thus, the field can move forward by focusing on transactional models to better understand the nuanced dynamic parent–child relationships between the ­ interactions and their role in  the emergence of emotion dysregulation. Finally, to more fully understand all the various ways in which emotion dysregulation develops, we need to better attend to other types of relationships, such as peer and romantic relationships, particularly for adolescents. It remains unknown whether emotion dysregulation observed within the parent–child relationship extends into other relationships or whether an individual’s response varies across relationships. Moreover, additional work is needed to answer the following questions related to parentalcontingent response and the development of emotion dysregulation: (1) Does the context (i.e., positive, conflictual, emotionally distressing) in which parents are responding to emotions or the type of emotion matter? (2) In what ways does adversity experienced by parents or children relate to how parents respond to children’s emotions and across contexts? (3) What factors contribute to gender ­differences? (4) How do we most effectively enhance our clinical treatments to better intervene in conflict escalation, as well as in more subtle cases of ­invalidation? In addition to better addressing these limitations, future intervention research should continue to use dual-generation models to improve understanding of parent emotion dysregulation in child treatment programs. Additional research is likewise necessary to determine whether the benefits of more traditional parent training programs compared to emotion socialization interventions depend on parental emotion dysregulation. If intervention results depend on parent emotion dysregulation, it may be that more thorough assessments of children and their parents’ emotion dysregulation are needed in clinical settings to better match interventions with presenting problems in children and their parents. One area not yet examined is whether child emotion dysregulation can be reduced solely by intervening

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at the level of emotion dysregulation for the parent. Our group is currently investigating this possibility using dialectical behavioral therapy skills with emotionally dysregulated mothers of preschool children. In summary, emotion dysregulation is a transdiagnostic feature across multiple forms of psychopathology. Understanding its development is critical for the translation of basic science to intervention and treatment. Parents play a foundational role in the development of children’s emotion dysregulation, where the way in which parents contingently respond to their children’s expression of emotion influences child emotion dysregulation. However, parents’ role is complex. In addition to this unidirectional effect, operant reinforcement from the parent interacts with traits inherent to the child, and parents and children mutually influence one another in ways that highlight the transactional, dynamic process underlying the development of emotion dysregulation. Multimethod approaches are most advantageous for measuring emotion dysregulation rigorously. Interventions incorporating methods to facilitate supportive contingent responses from parents in response to their children’s emotions have shown promising preliminary support. At the same time, our understanding of the development of emotion dysregulation is primarily based on main-effects models, providing ample opportunity for future research to clarify the complexity through which parental operant reinforcement interacts and transacts with youth behaviors to manifest in child emotion dysregulation.

References

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CH A PT E R

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Cognitive Processes and Risk for Emotion Dysregulation

Hooria Jazaieri, Helen Uusberg, Andero Uusberg, and James J. Gross

Abstract This chapter examines cognitive processes that underlie the development of emotion dysregulation. It first introduces and defines key terms including emotion, emotion regulation, and emotion dysregulation. It then introduces the authors’ theoretical perspective, the extended process model of emotion regulation, which considers emotion generation and emotion regulation as valuation systems, and describes core regulation processes, including regulation strategies. Next, using the extended process model of emotion regulation as the guiding framework, the chapter discusses how emotion dysregulation may occur during the identification, selection, implementation, and monitoring stages. The chapter concludes by considering unresolved controversies and suggests several exciting avenues for future research across basic and applied domains. Keywords:  cognitive processes, emotion, emotion regulation, emotion dysregulation, process model

Introduction

Skillful regulation of emotions is an essential component of adaptive functioning and mental health (Gross & Muñoz, 1995). A corollary of this is that emotion dysregulation is tied closely to psychopathology (e.g., Cole, Michel, & Teti, 1994). In fact, systematic coding of psychological disorders in the  Diagnostic and Statistical Manual for Mental Disorders (DSM) suggests that affective disturbance is likely present in the diagnostic criteria for 40% of psychological disorders (Jazaieri, Urry, & Gross, 2013). Given the importance of this construct, researchers have developed behavioral, self-report, and daily assessments to monitor emotion dysregulation. Researchers have also developed efficacious treatments (e.g., dialectical behavior therapy [DBT]; Linehan, 1993, 2015) designed to teach emotion regulation skills and tools. In this chapter, we are interested in examining cognitive processes that underlie development of emotion dysregulation.

Terms and Concepts

Across time, disciplines, and subdisciplines, a variety of terms have been used to refer to emotion and emotion-related processes. While there is no consensus regarding precise definitions of these terms, it is important for researchers to be explicit regarding how they conceptualize emotion and emotionrelated constructs (Gross, 2010; Gross & Barrett, 2011). To follow, we provide our working definitions of emotion, emotion regulation, and emotion dysregulation.

Emotion

Emotions arise when a person attends to a situation and then appraises it as being potentially important to current goals. It bears noting that attention and appraisal of the situation need not occur within one’s conscious awareness. As emotions (e.g., fear, anger, sadness, joy) arise, they generally involve a set of loosely coupled experiential, behavioral, and physiological (central and peripheral) responses.

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This full-body response is typically referred to as “emotional reactivity.” The notion that emotions arise and unfold over time is at the heart of most contemporary conceptions of emotions, and there are commonly said to be four key steps in the emotion-generative process: a situation that draws one’s attention, an evaluation or appraisal of the ­situation, and a multisystem whole-body response (Gross & Thompson, 2007). Although emotions are often categorized into binary groups (e.g., “good” vs. “bad,” “positive” vs. “negative”), they are actually highly heterogeneous in nature (Gross, Sheppes, & Urry, 2011). Any given emotion can sometimes be mild and hardly detectable, while at other times it may be extraordinarily intense and demanding of one’s attention. In one context, an emotion can be useful and adaptive, and in another context that very same emotion may be unhelpful and maladaptive. Emotions can be cognitively simple and at other times require a high level of processing. They can be brief and fleeting and at other times more prolonged.

Emotion Regulation

At times emotions are useful and adaptive—for example, experiencing happiness while on vacation or experiencing sadness when separated from someone you care for. However, at other times, emotions can be unhelpful and/or maladaptive (e.g., the specific emotion type, intensity, duration, and/or frequency are not well matched to the situation; Gross & Jazaieri, 2014). During such times, people often attempt to influence the specific emotion, its timing, or how it is (or in some cases is not) experienced and/or expressed (Gross, 1998). This characterizes emotion regulation, which involves the activation of a goal to regulate an emotion followed by recruitment of strategies and tactics to achieve this goal. Sometimes the motivation for an individual to engage in emotion regulation is driven by wanting to simply feel better in a hedonic sense. For example, one may choose to downregulate anger because the physical sensations are uncomfortable for the individual. At other times, the motivation to regulate a particular emotion is driven by some other goal and altering the trajectory of an emotion simply serves a means to an end. For example, one may choose to upregulate anger to garner attention from others and influence their behavior in a way that is consistent with one’s goals. The scope of emotion regulation spans several key dimensions. First, emotion regulation refers to changing both negative and positive emotions by 128

either increasing or decreasing their magnitude, ­duration, or type. Second, regulation of emotions can occur through conscious and intentional processes or without conscious awareness and explicit intention (Gross & Thompson, 2007). Third, emotion regulation processes cannot be deemed categorically “good” or “bad,” as understanding the specific context is necessary to evaluate whether emotion regulation is adaptive or maladaptive in light of one’s goal(s).

Emotion Dysregulation

We define emotion dysregulation as “a state in which despite an individual’s best efforts, regulatory attempts are not achieving the individual’s emotion related goal(s) and the individual is unable to make necessary corrections to achieve the emotion related goal(s)” (Jazaieri et al., 2013, p. 587). Similar definitions have been used by others, defining emotion dysregulation as “the inability even when one’s best efforts are applied, to change in a desired way emotions cues, experiences, actions, verbal responses, and/or nonverbal expressions under normative conditions” (Neacsiu, Bohus, & Linehan, 2014, p. 493). Beauchaine (2015) has similarly proposed that emotion dysregulation is a “pattern of emotional experiences and/or expression that interferes with appropriate goal-directed behavior” (p. 876). It has been suggested that characteristics of emotion dysregulation may include an excess of aversive emotional experiences, an inability to regulate intense physiological arousal, problems turning attention away from stimuli, cognitive distortions and failures in information processing, insufficient control of impulsive behaviors related to strong emotions, difficulties organizing and coordinating activities to achieve non-mooddependent goals when emotionally aroused, and a tendency to “freeze” or dissociate under very high stress. (Neacsiu et al., 2014, pp. 493–494)

Others have suggested that emotion dysregulation is characterized by deficits in four specific areas: (1) (lack of ) awareness, understanding, and accepting of emotions; (2) (in)ability to engage in goaldirected behaviors and inhibit impulsive behaviors when experiencing negative emotions; (3) (in)flexible use of situationally appropriate strategies to modulate the intensity and/or duration of emotional response rather than to eliminate emotions entirely; and (4) (un)willingness to experience ­negative emotions as part of pursuing meaningful

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activities in life (Gratz & Roemer, 2004, as cited by Gratz, 2007, p. 1094). Emotion dysregulation has been linked to ­psychopathology, especially mood and anxiety disorders (e.g., Cole et al., 1994). When considering specific forms of psychopathology, emotion dysregulation has been defined in specific ways; for example, within the context of borderline personality ­disorder (BPD), Linehan (1993) defines emotion dysregulation as “high emotional vulnerability plus an inability to regulate emotions” (p. 43). Here emotional vulnerability is characterized as including (1) high sensitivity to emotional stimuli (e.g., reacting quickly and a low threshold for emotional reaction), (2) emotional intensity (e.g., extreme emotional reactions), and (3) slow return to baseline (e.g., long-lasting reactions). Others have agreed with Linehan’s emotion dysregulation definition within BPD and have suggested that individuals who exhibit greater emotional reactivity and experience emotions more intensely may be at greater risk for emotion dysregulation (Flett, Blankstein, & Obertynski, 1996). Some clinical disorders have been characterized by “pervasive emotion dysregulation,” or the inability to regulate emotions across a wide range of emotional and situational contexts (Neacsiu et al., 2014). Emotion dysregulation occurs when a regulation strategy is maladaptive in some way (e.g., it creates more of the very emotion one is trying to regulate or the strategy creates a problematic secondary emotion) and the individual is unable or unwilling to adapt his or her strategy, resulting in making the situation worse. However, it is important to keep in mind that emotional problems are not always the result of emotion dysregulation (Sheppes, Suri, & Gross, 2015). It is possible to simply experience emotion problems (e.g., generation of problematic emotions) without emotion dysregulation. For example, a person may fail to recognize that an emotion needs to be regulated in some way (emotion regulation failure), or the individual may regulate an emotion in an unhelpful, unskillful, or maladaptive way (emotion misregulation) and yet not experience emotion dysregulation. In other words, a person can experience emotion problems or emotion misregulation and then make necessary shifts, without resulting in emotion dysregulation.

Theoretical Perspectives

To understand the role of cognitive processes in the development of emotion dysregulation, it is useful to adopt the extended process model of emotion

regulation (Gross, 2015). The extended process model uses the constructs of (1) hierarchical goal representations (superordinate goals, focal goal, subordinate goals, and actions) and (2) valuation system (feedback control loops consisting of world [W], perception [P], valuation [V], and action [A] steps) to model the structure and dynamics of emotion regulation. In the following three subsections we consider (1) emotion generation and emotion regulation as valuation systems, (2) four core processes in emotion regulation, and (3) emotion regulation strategies.

Emotion Generation and Emotion Regulation as Valuation Systems

The extended process model of emotion regulation views emotion regulation in the context of two ­interacting levels of valuation systems—one that is generating emotion and one that is seeking to influence the emotion-generative process (Gross, 2015). In the first-level valuation system, people encounter an internal or external world (W), which is selectively perceived (P; i.e., attention is deployed to goal-relevant aspects of the world), valued (V; i.e., appraised to be either helpful or unhelpful for current goals), and acted upon (A; i.e., the loosely coupled changes in one’s subjective experience, physiology, and behavior that define emotion). In sum, emotion is generated when a situation (internal or external) occurs, attention is deployed, the meaning of the situation is appraised, and a response occurs. The second-level valuation system modulates or  regulates the first-level system of emotion. The second-level valuation system also has a W→P→V→A structure; however, the “W” of this cycle is the firstlevel valuation system that is giving rise to emotion. Thus, when the person is experiencing an emotion (W), he or she first “sees” or perceives (P) the emotion, judges the emotion to be either good for me or bad for me (V), and then subsequently takes action (A), which consists of generating an emotion regulation goal (i.e., a goal to upregulate or downregulate the current emotion) and finding ways of achieving this goal. The extended process model takes the perspective that emotion generation and emotion regulation are integrated valuation systems that jointly facilitate flexible pursuit of different goals. Specifically, emotion generation monitors situations from the perspective of a set of primary goals and prepares the individual for appropriate action (see Figure 10.1a; Uusberg, Uusberg, & Gross, in press; Gross, 2015). For example, we can consider how this loop generates

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the emotion of fear about a job interview. The W substep corresponds to the real or imagined situation of stumbling with words while interviewing. The P substep corresponds to attending to goalrelevant aspects of the situation, including action affordances. For example, the interviewee may focus on the implications of stumbling over her words and see few affordances for action at that point beyond starting to cry or leaving the room. In the V substep, features of the situation are appraised in light of one’s current goals. The interviewee in our example may appraise stumbling over one’s words as being incongruent with one’s goal of making a favorable impression on others. Finally, at the A substep the emotion loop activates changes in one’s experiential, physiological, and behavioral response systems and prepares the individual for action. The interviewee in our example becomes anxious, begins to sweat, and wishes to escape the situation. While emotion shapes behavior in service of some goals that the individual values, this may simultaneously cause conflict with other competing goals. At times the specific emotion type, intensity of the emotion, duration of the emotion, and/or the frequency of the emotion becomes maladaptive or in conflict with other goals. For example, the Yerkes-Dodson Law (1908) would suggest that there would be an optimal level of anxious arousal for an interviewee to experience; otherwise, having too little or too much anxiety would interfere with one’s performance. The extended process model (a)

views emotion regulation as a second-level valuation system that helps to modulate the first-level system of emotion in such circumstances (see Figure  10.1b; Uusberg et al., in press). Thus, the regulation loop is able to assess one’s current emotion in light of one’s currently activated superordinate goals and then helps to initiate a cascade of processes that are aimed at reducing any detected discrepancies. This framework allows us to distinguish among four stages of the emotion regulation process, which we turn to next.

Four Core Processes in Emotion Regulation

Emotion regulation is generally necessary when an emotion (e.g., anxiety) is interfering with a goal (e.g., getting a job). To meet a goal, a person needs to solve this discrepancy by downregulating anxiety. In the extended process model, we suggest that four regulatory stages underlie this process: identification, selection, implementation, and monitoring (see Figure 10.2; Gross, 2015; Uusberg et al., in press). We further assume that the basic structure of a feedback control loop is helpful in understanding each stage of emotion regulation. The identification stage includes perception of emotion generation and activation of a goal to regulate this emotion. In this stage, a person is deciding whether or not the emotion he or she is experiencing (or may experience in the future) needs to be regulated in some way. There are three substeps of identification worth considering—perception (P), (b)

Attentional Deployment

V

Cognitive Change

V P

Valuation

P

A

Perception

Action

Response Modulation

A

a

V W World

Situation Selection & Modification

P

A W

Figure 10.1  Emotion generation and emotion regulation as a two-level control system. Panel a. Emotion generation. A feedback process attends to and appraises goal-relevant aspects of a situation to enact changes in multiple response systems. Black arrows represent points at which emotion regulation can have an impact on emotion generation. Panel b. Emotion regulation. Another feedback process compares the current emotion to the desired emotion and launches regulation strategies to minimize discrepancies. The inset shows how panel a can be embedded in panel b for a full representation of emotion generation and emotion regulation.

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Identification

V

Selection

V P

Implementation

V

P P W

W

A W Monitoring

Figure 10.2  Stages of emotion regulation. According to the extended process model, emotion regulation is initiated when a goal is activated to change the ongoing emotion at the identification stage. Next, a broad regulation strategy is chosen at the selection stage. The strategy is then enacted as a specific tactic suitable for the given situation at the implementation stage. This cycle can go through multiple iterations, which are collectively viewed as a monitoring stage where the system maintains, switches, or stops one or more aspects of the ongoing emotion regulation episode.

valuation (V), and action (A). Perception involves detecting the emotion (e.g., anxiety), valuation includes determining whether the emotion is helpful or unhelpful for ongoing goal pursuits, and finally the action substep involves activation of the goal to regulate the emotion. Importantly, there are many points within the identification stage and each substep for emotion dysregulation to occur. Once a person identifies a regulatory goal, this activates the selection stage. This stage involves a valuation of available emotion regulation strategies from five broad families (situation selection, situation modification, attentional deployment, cognitive change, and response modulation). By evaluating candidate strategies with respect to situational demands and available resources, the selection stage results in an initial emotion regulation strategy preference. At the perception substep of the selection stage, a person perceives the available regulation strategies. Each strategy is evaluated during the valuation substep based on how effective the strategy is expected to be in minimizing the gap between the current emotion and one’s goal in light of contextual factors (e.g., cognitive and physiological resources). After this valuation, the action substep activates the goal to use a particular strategy (e.g., response modulation). Here too, there are many points at which emotion dysregulation may occur. At this point, the activated strategy is still a somewhat abstract representation of the individual’s desired end state. Thus, activation of the implementation stage allows a person to translate a general strategy (e.g., response modulation) into specific

tactics that fit the situation (e.g., pause and take a sip of cold water during the job interview). Getting from a general strategy to situation-specific tactics starts with the perceptual substep of the implementation stage. At this point, a person is able to assess available tactics and relevant situational constraints and affordances. Then at the valuation substep a person evaluates these tactics and the most promising ones are selected for implementation. The action substep is the point at which an emotion regulation strategy directly affects emotion generation. Thus, implementation of an emotion regulation strategy results in regulation of the first-level emotiongenerative valuation system. As in the prior stages, there are many points at which emotion dysregulation may occur. Each stage or loop continues to guide a person’s actions until his or her goal state is achieved or abandoned. This gives rise to the broader monitoring stage, in which a person engages in ongoing evaluation of whether to (1) keep implementing the current emotion regulation behavior (“maintaining”); (2) switch to a new emotion regulation goal, strategy, or tactic (“switching”); or (3) stop regulating altogether (“stopping”). As long as the action outputs of the three emotion regulation stages (identification, selection, and implementation) continue to minimize discrepancies between one’s emotion and current goal, the system will continue to engage in regulation. However, if the initially selected action substep does not produce expected results (e.g., anxiety is increasing or sufficient progress is not being made), a person may consciously or

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­ nconsciously choose to switch tactics, strategies, or u goals, depending on the stage at which failure occurs. Emotion regulation switching means that a goal is still activated but the specific strategy or tactic to achieve that goal (or the new goal) has been adjusted in light of the prior unfavorable results. If an emotion falls below the threshold set by the identification stage (e.g., through the new strategy’s effectiveness or changes in the situation or environment) or if repeated efforts to regulate have failed, the goal to regulate the emotion may be abandoned or stopped. The monitoring stage—like the other stages—may also lead to emotion dysregulation.

Emotion Regulation Strategies

According to the process model, we categorize emotion regulation strategies based on where they have their primary effect on emotion generation (Figure  10.1a; Gross, 1998,  2015). As noted earlier when discussing the implementation stage of emotion regulation, regulatory processes can be or­gan­ ized into five families (situation selection, situation modification, attentional deployment, cognitive change, and response modulation; Gross, 1998). Situation selection refers to efforts made to change emotions by influencing the likelihood (increasing or decreasing) of encountering situations where a particular emotion is likely to be elicited. Situation modification refers to efforts made to change emotions by altering external, physical features within the environment. Both situation selection and situation modification have their impact on the “world” (the W substep in the emotion generation process; Figure 10.1a). Attentional deployment refers to efforts made to change emotions by directing one’s attention in a particular way to change one’s perception of the situation (the P substep). Cognitive change refers to efforts made to alter one’s emotions by modifying the subjective meaning of the situation. This is achieved by changing how the situation is evaluated in light of current goals (the V substep). Finally, response modulation refers to efforts made to alter physiological, experiential, or behavioral responses of an emotion in order to alter that emotion’s trajectory (the A substep). There is evidence that skillful implementation of regulatory strategies is beneficial for emotional health (for a meta-analysis see Webb, Miles, & Sheeran, 2012). In any given situation, individuals can use one or any combination of emotion regulation strategies to influence their emotional state. Take the interviewee who is anxious about a job in132

terview. For instance, she could target the W substep in the emotion generation loop by cancelling the job interview (situation selection) or preparing note cards with answers to common questions to read from during the interview (situation modification). She could target the P substep by thinking about the relaxing weekend ahead to distract herself from attending to the threatening nature of the interview (attentional deployment). She could target the V substep by construing the job interview as an opportunity to practice communicating her thoughts and ideas to others rather than an important test of her competence as a person (cognitive change). Finally, she could take a deep breath during the job interview as a way of relaxing her body (response modulation). We now turn to examining each of the five families of emotion regulation strategies in greater detail.

Situation Selection

With situation selection, the person is deciding whether to approach or avoid a situation based on what the person hypothesizes the affective impact may be. In general, people tend to avoid situations that are likely to generate negative emotions and approach situations that are likely to generate positive emotions. Empirically, it has been suggested that situation selection may be most effective for individuals who experience intense emotions and/or experience difficulty in regulating emotions in real time (Webb, Lindquist, Jones, Avishai, & Sheeran, 2018). At times, however, the short-term emotion regulatory goal of experiencing or not experiencing an emotion comes at the expense of longer-term goals. This is exemplified by the detrimental effects of behavioral avoidance, for instance, in the case of anxiety disorders (e.g., Salters-Pedneault, Tull, & Roemer, 2004). Therefore, as with all strategies, situation selection must be evaluated within the present context and individual’s goals to understand whether it is an adaptive strategy.

Situation Modification

If the person chooses not to avoid the situation, situation modification refers to adjusting external, physical parameters in the environment to influence which emotions occur. People for a variety of reasons enter situations where they want to regulate an emotion. For example, a person with anxiety about germ-filled public restrooms may use a paper towel to open the bathroom door, or a person anxious about giving a presentation may adjust the lighting

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in the room so that the space is dim and more calming. While considerable guesswork is necessary to anticipate the specific modifications that might be necessary to change one’s emotions, research on problem-focused coping (Lazarus & Folkman, 1984) and primary control (Rothbaum, Weisz, & Snyder, 1982) suggests that efforts made to change emotions through situation modification can be effective.

Attentional Deployment

Where an individual chooses to place his or her attention can also have powerful effects on generation of emotion. With attentional deployment, the person chooses how to allocate limited cognitive resources between emotionally relevant and irrelevant aspects of the situation. Given that emotions require some capacity-limited central processing resources (Brosch, Pourtois, & Sander, 2009; Pessoa & Adolphs, 2010), changing the allocation of cognitive resources devoted to the emotional aspects of  the situation will also change the emotion. Attentional deployment can take several forms including distraction (Van Dillen & Koole, 2007), intense concentration (Csikszentmihalyi, 1975), and rumination (Nolen-Hoeksema, 1991). For example, in the case of distraction, a person who is experiencing the emotion of anger during a meeting may choose to redirect his or her attention to thoughts about a neutral topic (e.g., one’s grocery list). Attentional deployment has been found to be effective at reducing emotional intensity when diverting attention (both overtly and covertly) ­ away from emotional stimuli (e.g., Augustine & Hemenover, 2009; Ochsner & Gross, 2005; Webb et al., 2012).

Cognitive Change

This regulatory strategy involves using cognitive skills (e.g., perspective taking, challenging interpretations, reframing the situations) to modify the meaning of a stimulus or situation that gives rise to emotional reactions. Given that emotions depend on our appraisals of various aspects of the situation (e.g., how important it is, causes of the situation, anticipation of what might happen next, etc.), changing one or a series of interpretations about the situation will likely alter the course of the emotion. Specifically, reappraisal (a common form of cognitive change) entails utilizing cognitive and linguistic processes to reframe or reinterpret the meaning of a stimulus or situation in order to change emotions. Cognitive reappraisal can modify emotional reac-

tions to stressful, anxiety-provoking situations and can lead to greater psychological flexibility and emotional well-being (Gross & Thompson, 2007). Difficulty reappraising emotion-eliciting situations is considered to be a core mechanism underlying anxiety and mood disorders (Campbell-Sills & Barlow, 2007). Researchers hypothesize that some people, for a variety of reasons, may not have the cognitive resources to engage in effective cognitive change (Hofmann, Schmeichel, & Baddeley, 2012; Vohs & Heatherton, 2000). In general, cognitive reappraisal is considered to be one of the more effective strategies for regulating emotions (Webb et al., 2012); however, there is some research to suggest that when emotions are very intense, reappraisal may be less effective (e.g., Sheppes & Gross, 2011).

Response Modulation

Response modulation refers to efforts to modify experiential, behavioral, and/or physiological components of an emotion after it has been generated. Examples of response modulation can include useful tactics such as physical exercise, deep breathing, or drinking cold water, as well as less useful tactics such as eating sweets or consuming alcohol. One of the most commonly studied forms of response modulation is expressive suppression, which refers to efforts made to hide verbal and behavioral expressions of emotion. Expressive suppression has been shown to have important consequences for reducing positive (but not negative) emotions, increasing sympathetic nervous system responses, heightened amygdala activation, and worse memory, to name a few (see Gross, 2015). In short, expressive suppression has been convincingly shown to have a range of negative inter- and intrapersonal consequences. But here too, it is important to keep in mind that as with all strategies, response modulation must be evaluated within a particular context and personal goals to understand whether it is an adaptive or maladaptive strategy.

Current Findings

Here, we consider how each of the four stages in the extended process model of emotion regulation (identification, selection, implementation, and monitoring) can be used to explain adaptive and maladaptive emotion regulation (Gross, 2015; Sheppes et al., 2015). Within the extended process model, emotion regulation difficulties can be traced to the functioning of different components of the

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two-level valuation system (Gross, 2015; Sheppes et al., 2015; Uusberg et al., in press). Specifically, we review evidence related to each of the four stages— identification, selection, implementation, and monitoring—and within each stage consider three substeps of perception, valuation, and action.

Identification Stage Difficulties

When the identification stage is working well, the individual is able to detect the emotion, accurately place value on the emotion, and activate a regulation goal. One of the difficulties that can occur within the identification stage (at the perception substage) is failing to detect that an emotion may need regulating (lack of awareness or underrepresenting of emotional states). Therefore, the person fails to activate a regulation goal in a situation where it would be adaptive to do so. People vary in their emotional awareness (Taylor, 1994), and these differences in emotional awareness can impede skillful emotion regulation. Another difficulty with perception is that people may have awareness but this awareness is primarily for high-intensity emotions. For example, often when individuals report emotion dysregulation, they report emotions going “from 0 to 100” and then at times attempting to regulate (unsuccessfully) the emotion once it is around 100. Upon closer inspection, it is often the case that the emotion was present at lower intensities (e.g., 30 or 40). However, the person was simply not aware of the lower intensity emotion and therefore did not think about employing regulation efforts. Another difficulty that may occur with perception is the issue of oversensitivity, which can also lead to unnecessary regulatory efforts. For example, a hallmark feature of panic disorder is the tendency to overrepresent subtle signs of one’s current emotional state, which is often physiological in nature (Burns, 2007), such as having the thought “my heart is racing so this must mean a panic attack is eminent.” This misperception of identification of one’s emotional state triggers regulatory activity unnecessarily, which may hinder pursuit of other goals. Without adjustment, emotion dysregulation will likely occur. Regulation failures can also occur in the valuation substep. At times people overvalue certain emotional states and undervalue the goal to regulate those emotions. For example, in general, people tend to shy away from downregulating positive emotions when regulation of these positive emotions would potentially be skillful; thus, this can at 134

times cause emotion regulation failures, though these failures are not due to lack of awareness, but rather due to faulty valuation of the emotion. For example, in bipolar I (which is characterized by episodes of mania or elevated mood) or bipolar II (which is characterized by episodes of hypomania), even if a person has the cognitive capacity to regulate positive emotions when instructed (e.g., Gruber, Harvey, & Johnson, 2009), they often choose to not downregulate positive emotions (for a review see Gruber, 2011). Another potential issue in the valuation substep is undervaluing regulation of lower intensity emotions. Therefore, while the person is aware of a lower intensity emotion, they may dismiss the need or opportunity to regulate. Finally, emotion regulation problems can also arise in the action substep of the identification loop, which entails activating a goal to change emotion in some specific manner. At this substep the individual may fail to take any action and choose to continue to not regulate. For example, take the feature of learned helplessness in the context of major depressive disorder, whereby the individual has a sense of (real or perceived) absence of control (powerlessness) over the outcome of a situation (e.g., Seligman, 1975), which may then interfere with translating the detected discrepancy between current and desired emotion into a regulatory goal. At other times people may only halfheartedly activate the goal to regulate the emotion, and depending on the intensity of the emotion, this halfhearted effort to regulate may result in a regulation failure. To be effective, it is necessary to take action “all the way,” continuing to “turn the mind” toward being “willing” to take action in order to be effective (Linehan, 1993, 2015).

Selection Stage Difficulties

When the selection stage is working well, the individual is able to pick an optimal emotion regulation strategy for the current situation. However, in the selection stage several sources of difficulty may exist. First, in the perceptual substep, a person may perceive various emotion regulatory strategies. The individual is essentially generating a hypothesis (by weighing the potential costs and benefits) regarding which regulatory strategy will be most effective. In addition to considering effectiveness, the person is also considering which strategy he or she is willing and able to employ in the moment. In terms of willingness, some strategies require greater cognitive resources to employ (e.g., cognitive change) over

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others (e.g., situation selection). When considering ability, people have different repertories of emotion regulatory strategies in their regulatory toolbox (e.g., Aldao, Nolen-Hoeksema, & Schweizer, 2010) or sometimes simply believe that they have few strategies at their disposal (e.g., De Castella et al., 2013). A person’s regulatory toolbox may be relatively scarce, perhaps due to excessive reliance on only a few strategies, whereas other individuals may have a richer repertoire of regulatory strategies. In terms of the valuation substep, people may overvalue short-term relief. Empirical evidence suggests that some strategies are more effective in the short run but may be less effective in the long run (e.g., attentional deployment; e.g., Paul, Kathmann, & Riesel, 2016). Cognitive reappraisal, on the other hand, can help facilitate long-term adaptation to emotional stimuli but at some cost to immediate effectiveness (MacNamara, Ochsner, & Hajcak, 2011). It could therefore be optimal to utilize a strategy such as situation selection or attentional deployment when the immediate benefit of avoiding the situation outweighs the delayed cost of reduced adaptation (e.g., eventual habituation to strong negative emotions). On the other hand, choosing cognitive reappraisal may be more optimal if the immediate distress is manageable enough to be worth the delayed benefit of immediate relief. There is some preliminary research to support this pattern of emotion regulation choice and it is an exciting area for continued research (e.g., Sheppes, 2014; Sheppes et al., 2014). Maladaptive use of emotion regulation strategies could contribute to negative social, health, or occupational outcomes and is likely to be more pronounced among people who experience chronic emotion dysregulation. Finally, problems may also arise within the action substep. One difficulty may be the belief that one cannot effectively utilize a particular emotion regulation strategy (referred to as low emotion regulation self-efficacy), which has negative consequences for psychological health (De Castella et al., 2013). Self-efficacy beliefs may shape how intensely a person activates a particular regulation strategy and can be modified through interventions (e.g., De Castella et al., 2015; Goldin et al., 2012). An important question for researchers to consider is the relation between high emotion dysregulation and low emotion regulation self-efficacy. One might hypothesize that there would be a positive association between the two and potentially even a causal relationship. We find this to be an intriguing

question for future research on emotion dysregulation to consider.

Implementation Stage Difficulties

Once an individual selects an emotion regulation strategy, the implementation stage is initiated. When the implementation stage is working well, the individual is able to translate the general strategy from the selection stage into specific tactics that are appropriate for the given situation. As with the prior stages, emotion regulation difficulties may arise at each of the implementation stage’s substeps. One source of difficulty at this stage is that individuals may lack the skills necessary to implement the specific tactics needed in the situation (e.g., Linehan, 1993,  2015). For example, a person may decide to use cognitive change, specifically cognitive reappraisal. However, even if the person has been effective at utilizing cognitive reappraisal in the past, perhaps in highly similar situations, the person may be unable to effectively use cognitive reappraisal in the new context (e.g., due to varying emotional intensity, different goals, environmental factors, etc.). Alternatively, the person may be reappraising his or her thoughts but not actually believing the reappraisal, and thus the regulation of the emotion is ineffective. At other times the person may reappraise a thought only to have the thought come right back up (generally at a lower intensity) again. With any given thought, reappraisal may not be a one-shot effort, but instead may require repeated attention. At the valuation substep, the person is evaluating the tactics and selecting the most promising tactics to implement. Contextual variables again (e.g., emotion intensity, cognitive resources, etc.) can interfere with one’s ability to accurately value the situation (over- or undervaluing), thus resulting in the individual implementing an unsuccessful regulation tactic. Due to the enormous range of potential behaviors at this level, systematic research within this space is relatively limited (Uusberg et al., in press). Finally, the action substep may also give rise to problems if the specific tactic chosen is mismanaged in its implementation. When considering psychopathology, many studies have documented the difficulties with implementation of tactics. For example, Heller and colleagues (2009) looked at individuals with major depressive disorder and found that anhedonia in these individuals reflected an inability to sustain activation in neural circuits involved in positive affect and reward.

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Monitoring Stage Difficulties

Once the strategy has been selected and implemented, it must be monitored over time to evaluate the effectiveness and potential next action. When the monitoring stage is working well, the individual is able to effectively monitor in real time—maintaining the strategy, switching the strategy in a timely fashion, or stopping regulation at an appropriate time. In general, maintaining, switching, and stopping strategies can be considered maladaptive when their flexibility is either too low or too high. With regard to difficulties with maintaining the strategy, at times a person will continue to use the same strategy even though it is not effective in meeting his or her goals. For example, in the case of mood and anxiety disorders, the strategy of situation selection may be continually used even when it is counterproductive in achieving one’s goals (e.g., Campbell-Sills & Barlow, 2007). At other times, difficulties with maintenance occur because other competing goals interfere with the goal to regulate. This goal interference may change the initial trajectory of regulating emotions and create potential emotional problems. When considering difficulties with switching, a person must monitor in real time whether the selected strategy is sufficient for meeting his or her regulatory goals. Assuming one possesses a rich repertoire of regulatory strategies, the ability to recognize ineffective strategies opens up endless opportunities to utilize alternative strategies that may be more effective. However, if one’s repertoire of regulatory strategies is limited, the individual may choose to “stay the course” even if ineffective (a case of “failure to switch”). Alternatively, if a person has a rich repertoire and continually changes strategies and does not “settle” on a strategy or switches strategies prematurely, this can be problematic (“failure to settle”). At times, the context has shifted in some way, requiring that the person switch strategies; however, the person may fail to switch given the new context. Additionally, if a person continually switches strategies, he or she may get fatigued and eventually give up on regulation goals. The ability to engage in adaptive strategy switching has been associated with healthy functioning in terms of one’s psychological health, including lower anxiety (Kato, 2012). With regard to difficulties with stopping, premature or delayed stopping may be problematic. In the instance of premature stopping, the person would be discontinuing the regulation strategy before the emotion has had an opportunity to fully change to 136

match one’s initial regulatory goal. For example, in the case of social anxiety disorder, the individual may choose to approach anxiety-producing stimuli but may stop approaching or engaging prematurely (Liebowitz, 1987). Delayed stopping (i.e., the strategy has already “worked”), on the other hand, is an interesting case where regulation efforts continue well past the need for regulation. While the cost of premature stopping is obvious, delayed stopping can have profound consequences as well. Depending on the resources expended on extended regulation, a person could create a secondary problem such as increased physiological activation or unskillful interpersonal situations.

Unresolved Controversies and Future Directions

We have described a number of difficulties that may occur in the identification, selection, implementation, and monitoring stages and specified the substep at which these difficulties might occur. While the empirical literature within many of these domains is scant (Sheppes et al., 2015), this opens up a number of exciting avenues for future research.

Cognitive Processes and Clinical Disorders

The extended process model is a promising organizing framework for understanding how at times, when cognitive processes go wrong, this can lead to emotion dysregulation. It is important to note that there are still significant gaps in current understanding about how different cognitive processes contribute to various clinical disorders. For example, when considering the four stages (identification, selection, implementation, and monitoring), it is possible that some clinical disorders are characterized by difficulties in one, a combination of, or all four stages. Then, within each stage, there are the substeps (perceptual, valuation, and action) and it is possible that some diagnoses are characterized difficulties different combinations of these. Thus, it is important for future research to begin to identify specific difficulties among the stages and within the substeps for various clinical disorders (Sheppes et al., 2015). Relatedly, getting more precise about these difficulties for specific clinical disorders could have important implications for our growing understanding of clinical assessment and treatment. In terms of assessment, self-report questionnaires and clinician interviews could more explicitly assess these areas of difficulty. In terms of treatment, specific interventions could be developed, or modules could be

Cognitive Processes and Emotion Dysregul ation

added to existing interventions to provide individuals with skills and tools to more skillfully address these challenges. Emotion regulation efforts that are made by the individual, some maladaptive in nature, may be part of the disorder itself (e.g., BPD; Linehan, 1993). Knowing high-leverage points could help streamline clinical interventions.

Understanding Subclinical Difficulties

We have suggested that people can experience emotion problems or emotion difficulties without experiencing emotion dysregulation. People can also experience emotion dysregulation at times without experiencing chronic emotion dysregulation. Much of the research on emotion dysregulation has examined individuals with significant emotion dysregulation compared with healthy individuals (e.g., Gratz, Rosenthal, Tull, Lejuez, & Gunderson, 2006). Other researchers have compared clinical populations who differ in the extent of emotion dysregulation (e.g., Turk, Heimberg, Luterek, Mennin, & Fresco, 2005). Finally, some have compared individuals who meet criteria for a clinical diagnosis characterized by emotion dysregulation with other clinical disorders (without the hallmark feature of emotion dysregulation) and healthy/nonclinical samples (e.g., Kuo & Linehan, 2009). For a crisper empirical investigation of emotional problems versus emotion dysregulation, future research may consider examining individuals without psychopathology who also endorse experiencing some degree of unwanted emotion and emotion regulation problems (i.e., subclinical problems) with individuals who meet criteria for emotion dysregulation. Taking a dimensional approach (rather than looking at different groups of people who meet criteria for various forms of psychopathology or looking at healthy/nonclinical samples) will help the field move toward a more direct empirical examination of potential differences that may exist between those who experience various degrees of emotion problems (without emotion dysregulation) and those who experience chronic emotion dysregulation.

Implicit Versus Explicit Emotion Regulation

Much of the research conducted in the field (and cited throughout this chapter) focuses on explicit forms of emotion regulation. In explicit emotion regulation, individuals are engaging in effortful regulation. For example, in experimental settings, individuals are instructed regarding which regulatory strategy to use or which ones to choose from; thus,

the individual is aware that regulation is taking place. Recently there has been a growing interest in implicit, or more automatic and less effortful, forms of emotion regulation. For example, when probed after the fact, people report using emotion regulation on a daily basis (Gross, Richards, & John, 2006), suggesting some habitual pattern of emotion regulation. Types of implicit regulation can include inhibition of fear and regulation of emotional conflict (Braunstein, Gross, & Ochsner, 2017; Etkin, Büchel, & Gross, 2015). Researchers are still examining effective ways to measure subjective experiences of implicit emotion regulation without influencing or disrupting the process. Neuroimaging tools have provided one window into these processes; specifically, these studies have found activation in the ventral anterior cingulate cortex (vACC) and ventromedial prefrontal cortex (vmPFC; e.g., Etkin et al., 2015). Additionally, there are individual differences and contextual factors that differentiate those who readily engage in emotion regulation versus those who find regulatory efforts more effortful, which is also an interesting area for continued research.

Conclusion

In this chapter, we have examined some of the cognitive processes that may contribute to emotion regulation and dysregulation. We have argued that by understanding how emotions are generated and typically regulated, we can better understand how emotion dysregulation occurs. Utilizing the extended process model of emotion regulation as an organizing framework (Gross, 2015), we have identified some of the areas where emotion dysregulation can arise and have made suggestions for future research, assessment, and treatment. Many gaps still exist in our understanding about how different cognitive processes contribute to emotion dysregulation; thus, there are a plethora of opportunities for basic and applied researchers to contribute to current understanding of emotion, emotion regulation, and emotion dysregulation.

References

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CH A PT E R

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Interpersonal Processes and the Development of Emotion Dysregulation

Sarah A. Stoycos, Geoffrey W. Corner, Mona Khaled, and Darby Saxbe

Abstract Emotion regulation and dysregulation often unfold within interpersonal contexts. Parent–child relationships provide early scaffolding of emotion regulation processes. Parents attune to, and influence, their children’s emotions, through pathways such as physical touch, infant cry, facial expressions, and stress physiology. Interpersonal emotion regulation and dysregulation processes continue to evolve within other close relationship contexts such as romantic couple relationships in adulthood. Partners shape each other’s emotion regulation through stress contagion and physiological interconnection, and through interactions that can be conflictual or supportive. This chapter reviews the theoretical foundations and the existing literature describing how emotion regulation and dysregulation take place within interpersonal relationships. Keywords:  emotion regulation, interpersonal, dyads, synchrony, attunement, stress contagion, conflict, support

Introduction

Researchers have highlighted the reciprocal nature of emotion expression, perception, and modulation within interpersonal groups. In The Expression of the Emotions in Man and Animals (1872), Darwin postulated that emotional facial expressions play a role in evolutionary survival and group dynamics. Later researchers furthered Darwin’s account by attempting to parse out the intra- and interindividual functionality of emotional expressions (Ekman, 1992, 1993; Shariff & Tracy, 2011), theorizing that intraindividual emotion expression likely served to help regulate the individual’s own physiological state (Susskind et al., 2008), and over time, emotion expression became linked with social communication. Additionally, Bowlby’s (1969) and Harlow’s (1959) seminal research on the role of emotion in dyadic processes during infant development culminated in attachment theory and an emphasis on parent–child relationships as foundational for adult expression, perception, and regulation of emotions. James Gross and colleagues have studied individual differences

in emotion regulation and well-being (e.g., Gross & John, 2003; Ochsner & Gross, 2005), emphasizing the role of emotion regulation in adaptive functioning. Developmental researchers emphasize that infant and child emotion regulation is almost exclusively an interpersonal process, and more recent reviews theorize that adolescent and adult emotion regulation abilities remain interpersonal, rather than transitioning to an intraindividual process (Rimé, 2009). Indeed, for over a century psychologists, biologists, evolutionary scientists, sociologists, and anthropologists have studied the phenomena of interpersonal emotional expression, perception, and regulation. This chapter will focus on various types of interpersonal processes that contribute to emotion dysregulation, while acknowledging that dysregulation is only one side of the coin. Thus, we will examine interpersonal processes leading to effective emotion regulation to provide a context for emotion dysregulation as a deviation from adaptive processes. We focus primarily on close dyadic relationships, since the preponderance of research on 141

interpersonal emotional regulation and dysregulation has focused on dyads. We begin by describing interpersonal emotion transmission processes within parent–child dyads, including modalities such as touch, cry, facial expressions, and physiology. We then move to the literature on adult couples and describe research on couple conflict and couple support. Finally, we conclude with recommendations for further research.

What Is Interpersonal Emotion Regulation and Dysregulation?

Emotion regulation refers to the process of altering one’s own or another’s emotional states, typically to reach a desired outcome (Gross & John, 2003; Ochsner & Gross, 2005; Zaki & Williams, 2013). For example, two adults in a relationship might hug and console each other when one partner is upset about a troubling interaction at work. A parent may attempt to calm a crying infant by picking the baby up and rocking him or her back and forth. A pair of athletes may hype each other up for competition. All of these are arguably adaptive interpersonal processes that facilitate emotion regulation during challenging experiences. However, what happens when interpersonal dyadic processes are characterized by emotion dysregulation? Perhaps adults in a relationship direct their stress at each other through arguing instead of consoling; a parent yells at the child to stop crying instead of using touch to comfort; or athletes deflate each other’s confidence and readiness to compete. Each interpersonal process has the potential to facilitate or hinder adaptive emotion regulation. Here, we review processes of interpersonal regulation and attunement within specific types of social relationships, beginning with the parent–child relationship context.

The Role of Affiliative Bonds in Emotion Regulation: The Parent–Child Relationship

Newborn babies are reliant upon caregivers for physical, social, and emotional needs. Newborns have yet to develop language abilities and thus use emotional expression to elicit support for getting their needs met. For example, a hungry baby may cry to signal that he or she is hungry. A responsive caregiver can then meet the child’s needs by trying to decipher and respond to the newborn’s emotional signal. With the crying baby, the caregiver may speak to the baby in soothing tones or pick the baby up, providing physical contact intended to help the baby. This use of physical contact, attention, and 142

language help facilitate the child’s socioemotional development, even when the baby is too young to understand language (Rimé, 2009), and encourages bonding between infant and caregiver (Rilling, 2013). Over time, a baby learns that emitting certain emotional cues to others will elicit helping behavior and facilitate getting their needs met. The baby will also learn that certain others, especially caregivers, are safe foundations, thereby creating an enduring attachment. A healthy child learns that he or she can take risks, explore his or her environment, and return swiftly to his or her safe caregiver to return to a baseline emotional state. Vital to this interpersonal process of emotion regulation is the caregiver’s ability to interpret the child’s emotional cues, respond appropriately, and use affiliation rather than avoidance when an infant exhibits distress (Bowlby, 1969; Shaver & Klinnert, 1982; Dykas & Cassidy, 2011; Rilling & Young, 2014). The adult must be able to accurately process emotional cues and regulate his or her own emotions while also attending to the child’s needs (Rilling & Young, 2014; Rutherford, Wallace, Laurent, & Mayes, 2015). A caregiver who struggles with emotion dysregulation or who has a history of disrupted attachment relationships may struggle to  scaffold his or her infant’s emotion regulation (Dykas & Cassidy, 2011; Shah, Fonagy, & Strathearn, 2010). Attachment researchers hypothesize that individual differences in caregiver responses to distress may act as a mechanism underlying transmission of attachment patterns from caregiver to child. Caregivers may be over- or underresponsive to their child’s distress, leading to intrusive or indifferent responses instead of healthy reciprocity and synchrony (Dykas & Cassidy, 2011; Feldman, 2012a). Interpersonal emotion regulation may begin to occur during the transition to parenthood and early postpartum period via biobehavioral feedback loops between caregivers and infant (Feldman, Gordon, Schneiderman, Weisman, & Zagoory-Sharon, 2010; Rutherford et al., 2015). Research has linked mothers’ prenatal emotion dysregulation to the child’s behavioral functioning at three years old (Oberlander et al., 2010). Specifically, mothers who were struggling with depression and taking antidepressant medication during their third trimester were more likely to have children with internalizing problems in early childhood. Furthermore, mothers with depression in the third trimester who were also depressed three years postpartum had children with higher rates of externalizing symptoms (Oberlander

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et al., 2010). Children exposed to prenatal anxiety have double the risk of internalizing and externalizing symptoms and conduct problems later in childhood (O’Connor, Heron, Golding, Glover, & ALSPAC Study Team, 2003; Van den Bergh & Marcoen, 2004). The intergenerational transmission of emotion dysregulation likely has multifaceted causes, including genes, epigenetic and physiological effects of stress on the developing fetus, and interpersonal processes in early infancy. Importantly, adults with internalizing disorders respond differently to emotional cues, and perceive negative facial expressions more negatively than healthy controls (Stein et al., 2010). Those with internalizing problems also have more difficulty recognizing and responding to their own infant’s cry, showing distinct patterns of neural recruitment relative to healthy controls (Laurent & Ablow, 2012a).

How Do Parents and Infants Attune? Mechanisms of Interpersonal Emotion Transmission Physical Touch

During the transition to parenthood, adults ideally develop an affiliative response to baby cues that otherwise may have been aversive (Rilling, 2013; Rilling & Young, 2014). Physical touch has been shown to facilitate bond formation and development of healthy attachments in mammals. Physical touch between caregiver and offspring has been linked with positive development, attachment, and bonding in premature infants and their parents (Feldman, Weller, Sirota, & Eidelman, 2003). Greater maternal–child physical touch has also been linked with the child having stronger brain connectivity and reactivity in regions involved in the regulation of  emotion (Brauer, Xiao, Poulain, Friederici, & Schirmer, 2016), and mother–child touch acted as a stress buffer for teens (Lougheed, Koval, & Hollenstein, 2016). Indeed, research supports the role of physical touch in helping both child and mother regulate emotionally. Touch may contribute to caregiver–child transmission of emotion regulation and social readiness via biobehavioral feedback of the oxytocinergic system (Feldman et al., 2010; Weisman, ZagoorySharon, & Feldman, 2012). Another study investigating the role of oxytocin and parent-specific tactile contact found that both mothers and fathers have similar baseline levels of oxytocin, with relative increases seen after experiencing touch with the infant (Feldman et al., 2010). The type of tactile

contact that exhibited changes in oxytocin differed for mothers and fathers: mothers showed associations with affectionate touch (e.g., hugs, kisses), while fathers showed associations with stimulatory touch (e.g., touching infant with toys; Feldman et al., 2010). Another form of touch linked with oxytocin release and bonding is breastfeeding. One study found that mothers who were breastfeeding, compared to mothers who were formula-feeding, had greater neural responding in brain regions associated with empathy and parent–child bonding at one month postpartum, and that this was related to more sensitive parenting (P. Kim et al., 2011). The authors hypothesized that a mechanism for greater positive parenting may be the close physical contact provided during breastfeeding, and that this physiological touch helped regulate the mother’s own emotions so that she could attune to the child’s needs (P. Kim et al., 2011). Given that touch facilitates bond formation via biobehavioral feedback loops, creating opportunities for caregivers to connect with their infant through physical contact could support parental ­investment in infant rearing, which in turn could support development of healthy emotion regulation. In addition to encouraging continued parental involvement, touch also plays a fundamental role in helping a child attach to the parents. Researchers have identified the role of touch and parenting behaviors as a mechanism for the cross-generational transmission of oxytocin levels—supporting bond formation, social reciprocity, empathy, and social engagement in children (Feldman et al., 2010; Weisman et al., 2012). Weisman and colleagues (2012) found that intranasal oxytocin administration to fathers was linked with fathers’ increased use of touch, shared eye gaze, and synchrony with the infant, and that this was linked with increases in infant social engagement and oxytocin levels. The authors suggest a reciprocal association between parent and child biology and behavior.

Infant Cry

In addition to touch, infant vocalizations also serve as a strategy by which infants signal their needs to caregivers. Infant cry sounds are typically regarded as aversive and unpleasant, and yet caregivers must override their emotional responses to their infant’s cries to soothe the infant effectively. One of the most basic functions of infant cry is to ensure proximity of their caregiver; infants cry more when away from their mothers (Bell & Ainsworth, 1972), and

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mothers can recognize their own infant’s cry (Formby, 1967), suggesting that the communicative function of infant cry is reciprocal and bidirectional. Although some species can generate cry sounds that indicate specific needs (e.g., hunger vs. separation vs. cold), human cry sounds can be more challenging to differentiate, which requires that caregivers identify potential sources of their child’s distress. The challenge of interpreting infant distress can frustrate caregivers, especially for those with poor emotion regulation skills (Barr, 2012). Although in most cases caregivers are able to learn to effectively reduce their children’s distress, excessive infant crying is known to be one of the most frequent triggers of child abuse (Carbaugh, 2004). The physiological hyperreactivity hypothesis suggests that parents’ excessive psychophysiological reactivity to children’s distress might motivate aggressive and abusive parenting behavior (McCanne & Hagstrom, 1996); in other words, parents who become overaroused by cry sounds may be unable to modulate their own and their children’s distress. Similar accounts have focused on cognitive rather than physiological processes, suggesting that parents’ interpretations of infant cry as hostile or intentionally annoying may also heighten risk for abuse (Crouch, Skowronski, Milner, & Harris, 2008). Although the literature on how parents respond to infant cry sounds is relatively small, there is some evidence that autonomic (e.g., skin conductance), behavioral (e.g., handgrip force), and affective (e.g., frustration and annoyance) reactivity to crying are all associated with risk for child abuse (Reijman et al., 2016). Although not all frustrated caregivers will maltreat their infants, caregiver reactivity to infant distress may represent a form of interpersonal emotion dysregulation with a range of consequences for the caregiver–infant bond.

Facial Expressions

Infant facial expressions represent another salient infant cue by which emotion is transmitted within caregiver–child dyads. The ability of parents to track and respond to their infant’s facial expressions has been linked with stronger coordination of physiological systems (heart rate in mother in infant) and shows similar positive feedback loops as touch does, but without touch being required (Feldman, 2012b). Studies examining parent response to emotional infant faces have found that parents, compared to nonparents, are better at discerning changes in the degree of distress level on an infant face 144

(Proverbio, Brignone, Matarazzo, Del Zotto, & Zani, 2006) and have heightened reactivity to infant affect (Nishitani, Doi, Koyama, & Shinohara, 2011). This suggests that parenthood may promote heightened awareness of infant facial cues. Individual differences in parent ability to accurately identify and respond with affiliative behavior to infant distress faces and cues may be tied with the child’s emotion regulation development. For example, infants of mothers with internalizing disorders (e.g., depression) exhibit heightened reactivity to angry faces and less synchrony with their mothers (Feldman, 2012a). Similarly, researchers have found differential neural responses in new parents, based on the type of attachment behavior exhibited by the infant (Laurent & Ablow, 2012b). For example, mothers of infants exhibiting insecure attachment behaviors maintained greater activation in brain regions linked to emotional saliency, pain, and emotional memory in response to their infant’s cry (see Laurent & Ablow, 2012b for full results). This research highlights again the bidirectional relation between parent and child development of emotion regulation, behavior, and physiology.

Stress Physiology

Adrenocortical attunement, or linkage in the stress hormone cortisol, which is produced by the limbichypothalamic-pituitary-adrenal (L-HPA) axis, has been observed in parent–child dyads (Granger et al., 1998; Hibel, Granger, Blair, & Cox, 2009; Hibel, Granger, Blair, Finegood, & The Family Life Project Key Investigators, 2015; Papp, Pendry, & Adam, 2009). This may represent a modality by which parents and children transmit stress or arousal states to each other. Although some studies have suggested that L-HPA axis linkage is stronger when parent–child dyads show more sensitivity, proximity, and closeness (Atkinson et al., 2013; SethreHofstad, Stansbury, & Rice, 2002; van Bakel & Riksen-Walraven, 2008), other studies have found heightened L-HPA axis linkage within high-stress contexts such as domestic violence (Hibel et al., 2009) and maternal depression (Laurent, Ablow, & Measelle, 2011). Similarly, several studies have reported ­stronger parent–child L-HPA linkage when parents show lower levels of sensitivity and reciprocity with their children (Pratt et al., 2017; Saxbe et al., 2017) and when dyads report higher levels of negative affect (Papp et al., 2009). Several studies using experimental designs have added to this literature. In one, mothers of infants were randomized

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to either a negative or positive evaluation task (Waters, West, & Mendes, 2014). Both tasks elicited physiological reactivity in mothers, but mothers’ reactivity only transmitted to infants—that is, predicted infants’ physiological reactivity upon reunion—in the negative evaluation condition. In a follow-up study, the extent of transmission between mothers and infants was moderated by touch, such that infants who sat in their mothers’ lap showed stronger physiological linkage than infants who were in a high chair during the task (Waters, West, Karnilowicz, & Mendes, 2017). In another study, researchers randomized mothers to a positive or a conflictual discussion with their romantic partners (Hibel & Mercado, 2017). Maternal cortisol reactivity to the conflict task, but not to the positive task, predicted infants’ cortisol reactivity to an in-lab challenge. These experimental studies corroborate naturalistic findings that parent–infant physiological transmission is bolstered within stressful contexts. Shared stress responses may be adaptive from an evolutionary perspective, helping to convey information about risky environments that might require heightened vigilance. However, chronic physiological stress contagion may represent a form of interpersonal emotion dysregulation in which dyads fail to regulate, and instead exacerbate, each other’s ­ stress states.

The Role of Affiliative Bonds in Emotion Regulation: Romantic Partner Relationships

Parent–child relationships are typically the first meaningful attachment relationship and serve as a staging ground for emerging emotion regulation and dysregulation. However, individuals form other close affiliations across the lifespan that continue to contribute to interpersonal emotion regulation and dysregulation (Rutherford et al., 2015; Crowell, Puzia, & Yaptangco, 2015). In many adults, the couple relationship becomes central, serving as a “stable base” for growth and exploration while also providing a consistent interpersonal context for processing emotional experiences. Many of the same modalities reviewed earlier—touch, vocalization, facial expressions, and physiology—help to transmit emotions between partners. In addition, researchers have studied two types of couple interaction that are relevant to emotion dysregulation: conflict and support. Conflict may escalate, and support may buffer, interpersonal emotion dysregulation. Conflict and support are also important

within parent–child dyads, friendship dyads, and group dynamics. Thus, many insights from research on couples may generalize to other interpersonal contexts.

Physiological Stress Contagion within Couples

As with the parent–child literature, a growing number of researchers have found evidence for physiological linkage within couples. For example, in a study in which married couples provided multiple cortisol samples a day over three days, Saxbe and Repetti (2010) found positive correlations between husbands and wives. This finding has been replicated by other researchers, both within naturalistic daily diary studies (Liu, Rovine, Klein, & Almeida, 2013; Papp, Pendry, Simon, & Adam, 2013) and in laboratory studies (Laws, Sayer, Pietromonaco, & Powers, 2015; Saxbe et al., 2014). Within the couples’ literature, physiological linkage within systems associated with stress responding (e.g., sympathetic and L-HPA systems) has been most consistently associated with relationship dysfunction (Timmons, Margolin, & Saxbe, 2015). Positive associations in cortisol have been linked with relationship distress (Liu et al., 2013; Saxbe & Repetti, 2010), intimate partner aggression (Saxbe et al., 2015), and decreased empathy and increased risk of relationship dissolution (Schneiderman, Kanat-Maymon, Zagoory-Sharon, & Feldman, 2014). Levenson and Gottman (1983) have suggested that more strongly linked couples engage in negative affect reciprocity, in which partners become locked in escalating exchanges of negative emotion and stress. In other words, rather than modulating each other’s negative emotions or stress states, dyads that show stronger linkage may be more reactive to each other and show stress contagion rather than stress buffering. In keeping with this idea, a study of parents of an infant found that stronger L-HPA axis linkage between the members of the couple was associated with greater risk of intimate partner aggression (Saxbe et al., 2015).

Negative Emotion and Conflict within Couples

All close relationships inevitably include conflict; couples’ ability to manage and rebound from conflict is a crucial feature of a successful, satisfying relationship. Individuals who have difficulty regulating internal emotional experiences may be more likely to experience negative affect and interpersonal conflict. Indeed,

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emotion dysregulation may mediate intergenerational transmission of relationship conflict, as exemplified by one study finding that the children of parents with poor emotion regulation skills were more likely to show emotion dysregulation themselves, which in turn predicted greater interpartner conflict in their adult romantic relationships (H.  K.  Kim, Pears, Capaldi, & Owen, 2009). However, the amount of conflict is not the only factor that predicts poor relationship outcomes. Failure to effectively handle disagreements and prevent conflict escalation is also important (Seiffge-Krenke & Burk, 2015). Emotion dysregulation within couple conflict is an important marker of dissatisfaction within the relationship and  may be a precursor to more detrimental and dangerous behaviors, such as partner aggression and violence. Emotion dysregulation tends to have a cyclical ­relationship with negative emotionality. An individual who struggles to effectively integrate emotional experiences may express more negative affect, potentially due to the link between developmental formation of emotion dysregulation and later internalizing disorders or insecure attachments (Rutherford et al., 2015; Zimmer-Gembeck et al., 2017). In the midst of intense negative affect, individuals may have difficulty managing these negative emotions, and thus become dysregulated. Additionally, partners’ negative moods can be “contagious,” and couples who are dissatisfied may intensify one another’s negative affect. For example, using daily diary data, Saxbe and Repetti (2010) found that individuals’ negative mood states were associated with their partners’ negative mood states at the same time. However, withincouple correlations in negative mood were weaker among couples who reported higher relationship satisfaction, suggesting that relationship quality can buffer negative mood transmission within couples. Thus, couple characteristics may prevent negative moods from escalating into conflict. Additionally, some characteristics of each partner may impact relationship satisfaction, such as individual personality and compatibility of both partners’ personalities. While personality shapes the way an individual interacts with and responds to his or her partner, it also affects his or her ability to regulate internal emotional experiences. Vater and Schröder-Abé (2015) found that emotion regulation during a laboratory couple conflict discussion mediated the association between personality and long-term relationship satisfaction, indicating that a couple’s ability to regulate their emotional reactions during disagreements is 146

a  critical factor in understanding how partners’ personalities affect their satisfaction with one another. Difficulty regulating emotions during conflict can affect relationship satisfaction, and repeated emotion dysregulation can increase risk for intimate partner violence. Factors related to intimate partner aggression include an inability to manage extreme emotional reactions such as intense anger, losing control, and difficulty with verbal expression (see Neal & Edwards, 2015 for a full review). Adolescent couples in which at least one partner is psychologically or physically aggressive exhibit more jealousy, higher rates of conflict, and more maladaptive coping strategies (Seiffge-Krenke & Burk, 2015). Not surprisingly, adolescent partners who are ­mutually aggressive show the poorest relationship functioning, emotion dysregulation, high levels of conflict, lack of trust and acceptance for their partner, and lack of insight. Similarly, distressed married couples tend to engage in negative and aggressive interactions and are unable to manage their conflicts constructively, exemplifying difficulty with emotion dysregulation (Goldstein, 2011; O’Leary et  al., 1989). This can trigger a vicious cycle, in which emotion dysregulation leads to distress, and partners experiencing relational distress consequently struggle to manage disagreements and emotional reactions. Therefore, targeting emotion dysregulation within couples can be a valuable point of ­intervention to help diminish relationship distress, contagion of negative mood states, and subsequent risk for intimate partner violence.

Supportive Interactions within Couples

Although a troubled marriage can lead to emotional and physiological dysregulation and depression and have a negative impact on health (Robles & KiecoltGlaser, 2003; Whisman, 2001), a satisfying relationship can potentially be helpful or even protective (Cutrona, 1996). When dealing with stress, sadness, or other negative emotions, supportive interactions with a spouse or significant other may have an ameliorative effect. In fact, research suggests that married people, on the whole, tend to live longer than nonmarried individuals (Manzoli, Villari, Pirone, & Boccia, 2007), which suggests that beneficial processes may be occurring in the marital context. Researchers have operationalized supportive processes in a variety of ways and have studied support across contexts and populations. We focus on the importance of support in two contexts in which there is high risk for emotion dysregulation and

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in  which couples typically encounter challenges together: illness and the transition to parenthood. Next, we review specific processes through which partners can help each other in adverse circumstances.

suggests that support may be more valuable for women than men (Kiecolt-Glaser & Newton, 2001).

Support from a Partner during Illness

Pregnancy and the transition to parenthood is another critical time for research on partner support. Much of this research has focused on support provided by men when their partners are pregnant or soon after the birth of their child. A longitudinal study focusing specifically on effective social support, which includes indices of both quality and quantity, found that partner support was associated with less concurrent anxiety and reductions in ­anxiety across pregnancy (Rini, Dunkel Schetter, Hobel, Glynn, & Sandman, 2006). Additionally, perceptions of effective social support were predicted by both individual (e.g., attachment, individualism–­collectivism orientation) and couplelevel characteristics (e.g., intimacy, equity), suggesting that perceptions of effective support may be influenced by the personality and experiences of the person reporting it. Furthermore, a qualitative study found that partner support continues to be important in childbirth experiences, with female partners endorsing the value of their partner’s presence and support provided by the partner during birth (Somers-Smith, 1999). The postpartum period is another time of high stress. Thorp, Krause, Cukrowicz, and Lynch (2004) found that mothers who were unsatisfied with their partners’ support, specifically instrumental support, experienced more stress. This association was partially mediated by demand–withdraw communication, suggesting that this kind of interaction pattern may be particularly problematic. Many new mothers also experience symptoms of postpartum depression. Misri, Kostaras, Fox, and Kostaras (2000) tested the impact of partner involvement in treatment of postpartum depression in a randomized controlled trial. Specifically, new fathers attended several sessions with their partners, and intervention content included psychoeducation around instrumental support and positive interactions. They found that, compared with treatment that did not include a partner, women receiving this intervention showed greater improvements in postpartum depressive symptoms. In a related study, women experiencing the loss of a pregnancy endorse a desire for support from their partner (Corbet-Owen, 2003). This is consistent with research showing that

Several studies have begun to illuminate effects of partner support in times of illness and disentangle unique effects of different types of support. For the purposes of this chapter, we will focus on couples coping with a partner with cancer. A qualitative study of women with a life-threatening diagnosis of cancer found that type of support was important, with emotional support being the most commonly desired and offered. Furthermore, “mutuality” in romantic relationships, which is defined as a reciprocal intellectual and emotional openness between partners, was also highly valued (Sormanti & Kayser, 2000). In addition to emotional support, other kinds of support (i.e., informational support and instrumental support) are valuable for women coping with a breast cancer diagnosis and treatment (Kinsinger, Laurenceau, Carver, & Antoni, 2011). Specifically, perceptions of emotional and instrumental support from a partner were associated with concurrent and longitudinal relationship satisfaction. Moreover, emotional and informational support were associated with fewer sexual difficulties following treatment. Emotional support from a romantic partner is also helpful for women recently diagnosed with breast cancer (Pistrang & Barker, 1995). Importantly, however, the mere provision of support may not be sufficient to affect adjustment in illness. Rini and colleagues (2011) found that quality of partner support, rather than quantity of support, was associated with less distress in patients who received hematopoietic stem cell transplantation. The relation between perceived partner support and psychosocial adjustment may also be bidirectional; higher levels of partner-provided emotional support predict subsequent depressive symptoms, but depressive symptoms also predict subsequent perceptions of support (Talley, Molix, Schlegel, & Bettencourt, 2010). Individual characteristics may also be important in determining the effects of partner support. For example, partner support appears to be a stronger predictor of healthrelated quality of life in female compared with male cancer patients (Gustavsson-Lilius, Julkunen, & Hietanen, 2007), a finding that is consistent with literature on social support and marriage, which

Support from a Partner during the Transition to Parenthood

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avoiding talking about the shared loss of a child tends to predict higher levels of grief in one’s partner (Stroebe et al., 2013).

Behaviors Underlying Support from a Partner

In addition to elucidating the consequences of partner support, it is important to determine the characteristics of a supportive interaction. This enables us to discuss what support looks like in real life and on a moment-to-moment basis. Kirschbaum, Klauer, Filipp, and Hellhammer (1995) studied the effect of partner support before a version of the Trier Social Stress Test, a laboratory paradigm in which participants were required to speak in front of a panel about their qualifications for a hypothetical vacant job position. They instructed partners to be as helpful as possible during the ten minutes leading up to this task, provided psychoeducation about emotional and instrumental support, and told partners to use their own understanding of the participants’ coping preferences to inform how they provide support. Men, but not women, showed an attenuated physiological stress response (i.e., less of an increase in cortisol after the task) when supported by their partners. Importantly, supportive partners were instructed to avoid physical touch, and when Ditzen and colleagues (2007) used a similar Trier Social Stress paradigm but included both “verbal support” and “physical contact” conditions, they found that women showed lower heart rates and cortisol responses to stress when they received physical touch from their partners. Thus, an effective supportive interaction may look different for men and women. Another study examining partner support in a conflict discussion behaviorally coded positive emotional and instrumental supportive behavior, defined on the Social Support Interaction Coding System as reassurance, consoling, encouragement, and helpful suggestions or advice (Pasch, Harris, Sullivan, & Bradbury, 2004). The authors found that higher levels of partner support in a conflict discussion conducted soon after marriage were associated with lower levels of negative emotion in a  subsequent conflict discussion one year later (Sullivan, Pasch, Johnson, & Bradbury, 2010). This study also provided preliminary evidence that positive emotions, including empathy, may mediate the association between partner support and later marital satisfaction and stability. A related literature suggests the importance of exhibited compassion between partners. In a daily diary study, Reis, Maniaci, 148

and Rogge (2017) found an association between expressions of compassion and emotional well-being for both partners. Another recent study found that partners’ moment-to-moment displays of compassion moderated concordance in heart rates over the course of a discussion about an emotionally significant loss experience. Specifically, couples’ heart rates were more closely linked when the partner listening to a loss experience was being less compassionate (Corner et al., 2018). This same study found that partners sharing a loss exhibited decreases in heart rate over the course of the discussion, whereas partners listening to a loss showed increases. Overall, the empirical literature supports the value of positive interactions in couples. Thus, not only can negative interactions contribute to development of emotion dysregulation, but also positive interactions may be helpful or even protective. A variety of processes may occur in the context of a supportive interaction between partners. These include the provision of emotional, instrumental, and information support, as well as the expression of compassion. Importantly, it is also possible that partner support, in certain instances, can be excessive (Brock & Lawrence, 2009), and provision of support may be most effective when it is accomplished subtly and when it goes unnoticed by the recipient (i.e., “invisible support”; Bolger, Zuckerman, & Kessler, 2000). This suggests that determining what kind of partner support is “effective” is likely complicated. Additionally, associations between partner support and psychological outcomes appear to be bidirectional, and a variety of individual and relationship characteristics influence the provision of, perceptions of, and responses to partner support, including attachment styles of both members of the dyad (Cobb, Davila, & Bradbury, 2001; Simpson, Rholes, & Nelligan, 1992). Future research needs to continue studying moment-to-moment behavioral components of supportive interactions between partners, as well as moderators and mediators of associations between partner support and psychosocial outcomes.

Conclusion

In conclusion, emotion regulation and dysregulation are deeply interpersonal processes. These processes may first develop within the scaffolding ­provided by parent–child relationships, and then continue to evolve within other close relationships such as romantic couple relationships in adulthood. Both parent–child and couple relationships are characterized by social synchrony (Feldman, 2007),

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or the reciprocal exchange of nonverbal cues within interpersonal interactions. Atzil, Hendler, and Feldman (2014) suggest that social synchrony is learned initially in parent–child dyads and then generalizes, affecting a person’s ability to engage in supportive, empathic, and satisfying relationships as an adult. The ability to coordinate nonverbal cues and responses with a partner can facilitate formation of affiliative bonds and may depend on skilled detection and regulation of one’s own and others’ emotional states. The coordination or regulation of cues can extend “under the skin” and include stress physiology (Timmons, Margolin, & Saxbe, 2015) in addition to touch, vocalization, and facial expression. Within the couples’ literature, research on conflict and support helps to elucidate a range of interactions that facilitate emotional expression and regulation within dyads. Individual differences in affiliative response to distress cues are closely tied with disruptions in social synchrony. For example, in postpartum depression or other clinical disorders, there may be a disruption in coordination of behavioral responses within dyads, which perturbs biobehavioral feedback loops, potentially perpetuating emotion dysregulation. Finally, although shaped by early attachment experiences, emotion regulation skills are potentially mutable in adulthood and may be an important target for intervention. Many psychotherapies, such as dialectical behavior therapy, specifically focus on emotion recognition, expression, and regulation within interpersonal contexts (Linehan, Tutek, Heard, & Armstrong, 1994). Future research could explore short-term and long-term implications of interpersonal emotion dysregulation, including the potential intergenerational transmission of emotion dysregulation from parents to children.

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CH A PTE R

12

Respiratory Sinus Arrhythmia as a Transdiagnostic Biomarker of Emotion Dysregulation

Theodore P. Beauchaine and Ziv E. Bell

Abstract Over the past two decades, emotion dysregulation—defined as the inability to dampen strong emotional responses in the service of goal-directed behavior—has emerged as a consistent, transdiagnostic vulnerability to psychopathology. Although specific forms of dysregulated emotion vary across disorders (e.g., exuberance, anger, and related approach emotions in externalizing disorders; anxiety, panic, and related avoidance emotions in internalizing disorders), deficits in dampening emotional responses help define many psychiatric conditions. Peripherally, emotion dysregulation is often marked by low tonic (resting) parasympathetic nervous system (PNS) activity, as indexed by respiratory sinus arrhythmia (RSA). In fact, hundreds of studies conducted to date have found low RSA across diverse forms of psychopathology (e.g., anxiety disorders, autism spectrum disorder, conduct disorder, depression, panic disorder, psychotic disorders). Associations between psychopathology and RSA reactivity to laboratory tasks are less consistent. However, wide variability in tasks and psychophysiological methods may explain some of these inconsistencies. This chapter provides an updated summary of this literature, ending with discussion of methodological issues. Keywords:  emotion dysregulation, psychopathology, respiratory sinus arrhythmia, biomarker, emotion regulation, parasympathetic nervous system, anxiety disorders, depression, panic disorder, psychotic disorders

Introduction

Most psychiatric disorders are characterized by some form of emotion dysregulation (Aldao, NolenHoeksema, & Schweizer, 2010; Beauchaine, 2015a; Cole, Hall, & Hajal, 2013). Internalizing disorders (e.g., depression, panic), for example, are characterized by dysregulated anxious and fearful reactions to  real or perceived threat, whereas externalizing ­disorders (e.g., conduct problems, delinquency) are characterized by dysregulated angry and aggressive reactions to frustration and social provocation (Beauchaine, 2015b). Dysregulated emotional reactions are also implicated in many other forms of psychopathology, including borderline personality disorder (e.g., Carpenter & Trull, 2013), self-inflicted injury (e.g., Crowell et al., 2017), eating disorders (e.g., Haynos & Fruzzetti, 2011), and substance use

disorders (e.g., Berking et al., 2011), to name but a few (see also Dixon-Gordon, Haliczer, & Conkey; Garland, Bell, Atchley, & Froeliger; Hostinar & Cicchetti; Kaufman & Crowell; Kerig; Neuhaus; Racine & Horvath; Shader & Beauchaine; Wallace & Docherty, this volume). Notably, specifying associations between emotion dysregulation and psychopathology is a historically recent development. Throughout much of the 20th century, dominant theoretical models espoused by U.S.  psychologists favored behavioral and cognitive explanations for psychopathology— often eschewing emotional processes because emotion was difficult to quantify using available technologies (see Beauchaine & Zisner, 2017). Beginning in the mid-1990s, however, this state of affairs began to change. Advances in electrophysiological recording, 153

hormonal assays, and neuroimaging made objective assessment of emotion possible, producing a rich literature in which emotional states are quantified and studied systematically (e.g., Cicchetti & Rogosch, 2012; Crowell et al., 2017; Hajcak, MacNamara, Foti, Ferri, & Keil, 2013; Lapate et al., 2017). As a result, research on emotion regulation and dysregulation has flourished in the 21st century (Adrian, Zeman, & Veits, 2011). As articulated by authors throughout this volume, emotion regulation (ER) comprises biological, cognitive, social, and behavioral processes that shape and modulate one’s experience and expression of emotions in the service of adaptive, goaloriented behaviors (see Thompson, 1990,  1994). However, despite the importance of ER for adaptive human function, quantifying emotion regulatory processes becomes problematic if we attempt to do so by inferring emotion regulation from the absence of maladaptive behaviors and emotional reactions (see Cole, Martin, & Dennis, 2004; Ramsook, Cole, & Fields-Olivieri, this volume). In contrast, emotion dysregulation—defined as experiences and expressions of emotion that interfere with adaptive, goal-directed behavior (see Beauchaine & GatzkeKopp, 2012)—is often easier to quantify through direct observation (e.g., Beauchaine, 2015b; Cole et al., 2013). Strong emotional reactions can be observed and measured in laboratory settings via behavior observation and physiological reactivity, and depending on context, self-reports. Most contemporary research uses multiple measures, including behavioral, psychophysiological, and/or neural, to examine correlates and mechanisms of emotion dysregulation, particularly emotional reactions that are experienced too intensely and/or too enduringly to be adaptive (Beauchaine, 2015b; Beauchaine & Bell; Brown, Conradt, & Crowell; Jazaieri, Uusberg, Uusberg, & Gross; Leshin & Lindquist; Martin, Zalewski, Binion, & O’Brien; Speed & Hajcak; Rappaport, Hawn, Overstreet, & Amstadter; Stoycos, Corner, Khaled, & Saxbe; Thompson & Waters, this volume). In this chapter, we summarize current literature on respiratory sinus arrhythmia (RSA) as a ­peripheral, physiological biomarker of emotion regulation and dysregulation. RSA has been quantified in literally thousands of studies designed to evaluate emotional processes and their relations to typical and atypical development (see, e.g., Shader et al., 2018), vulnerability to adversity (e.g., El-Sheikh, Harger, & Whitson, 2001), and existing psychopathology (e.g., Beauchaine, Gatzke-Kopp, & Mead, 154

2007; McLaughlin, Rith-Najarian, Dirks, & Sheridan, 2015) among children, adolescents, and adults. We focus specifically on literature in which RSA—measured at rest or in response to emotional challenge—is used to evaluate emotion dysregulation among those with various forms of psychopathology. We note that this literature is extensive and cannot be reviewed comprehensively in a single chapter. In fact, in a recent meta-analysis on RSA reactivity in psychopathology, an initial literature search yielded over 4,000 articles (Beauchaine et al., 2018). Our goal here is to summarize major findings. After doing so, we outline key methodological issues critical to research assessing RSA, before discussing future directions for research on RSA as a biomarker of emotion dysregulation.

Respiratory Sinus Arrhythmia and Emotion Dysregulation

RSA refers to cyclic, respiratory-linked variation in heart beats, as quantified in the R-R interval time series (see Figure 12.1; Berntson et al., 1997; Zisner & Beauchaine, 2016). RSA can be indexed in several ways (see Shader et al., 2018), all of which capture high-frequency heart rate variability (HF-HRV). Given appropriate stimulus conditions and quantification, HF-HRV indexes parasympathetic-linked inhibitory influence on cardiac activity and reactivity (Beauchaine, 2001; Berntson et al., 1997; Grossman, Karemaker, & Wieling, 1991; Ritz, 2009). Full explanation of RSA quantification is beyond the scope of this chapter; interested readers are referred to recent, comprehensive reviews (Laborde, Mosley, & Thayer, 2017; Shader et al., 2018; Zisner & Beauchaine, 2016).

Foundational Theoretical Models

Although a few studies appeared before the 1990s, research on RSA as a peripheral biomarker of emotion regulation and dysregulation began in earnest following a foundational paper by Porges, DoussardRoosevelt, and Maiti (1994), who linked RSA specifically to emotion regulatory processes. This paper was soon followed by Porges’s (1995) elaborate theoretical model in which he presented a phylogenetic account of brainstem development that distinguished between a reptilian “vegetative” branch and a mammalian “smart” branch of the vagus nerve. According to Porges, the vegetative vagus, shared by both reptiles and mammals, is mediated by the dorsal motor nucleus (DMNX) and produces heart rate slowing (bradycardia) during orienting responses. In contrast, the smart vagus evolved in

Respiratory Sinus Arrhy thmia as Biomarker

R-R1

R-R2

R

S

P Q

R

P Q

S

P Q

S

R T

T P

Q S

R-R5

R T

T P

Q

R-R4

R

R T

P

R-R3

S

Q

S

Figure 12.1  Time series of heart beats collected from a standard electrocardiogram (ECG). QRS complexes, P-waves, and T-waves are marked. Respiratory sinus arrhythmia indexes periodic lengthening and shortening of R-R intervals across successive breathing cycles.

mammals, is mediated by the nucleus ambiguus (NA), and provides for rapid mobilization responses in contexts of environmental challenge. Porges contended that moment-to-moment vagal modulation of cardiac activity is a precondition for evolution of complex social behaviors among mammals, since fight/flight (F/F) reactions need to be inhibited to engage effectively with friendly conspecifics. In a series of papers, Porges invoked the “vagal brake” metaphor to describe inhibitory functions on cardiac output of the PNS, especially during social interactions (e.g., Porges, 1995, 2007). Although Porges’s (1995, 2007) phylogenetic account of PNS function has been debated (e.g., Grossman & Taylor, 2007), polyvagal theory ushered in a new generation of research on physiological markers of ER and emotion dysregulation (see Appelhans & Luecken, 2006; Beauchaine, 2001; Beauchaine & Zisner, 2017). Porges’s perspective provided researchers with a mechanistic theory from which to launch studies linking RSA to emotion regulatory processes across development, including associations between RSA and psychopathology.

Contemporary Theoretical Models

Since publication of Porges’s (1995,  2007) theory, considerable elaboration on likely neural substrates of RSA has emerged. Much of this research links RSA to prefrontal cortex (PFC) function, with brainstem nuclei outlined by Porges serving as the final common pathway of efferent neural traffic from the PFC to the heart (e.g., Thayer & Lane, 2000). According to this perspective, low RSA and emotion dysregulation—both of which are observed in many forms of psychopathology—emerge from insufficient top-down cortical (PFC) modulation of subcortically generated affective responding (see Beauchaine, 2015a,  2015b). Although emotional predispositions differ across subtypes of psychopathology (e.g., anxiety, fear, panic, anger, etc.),

in each case, deficient top-down inhibition of the subcortex by one or more functional subdivisions of the PFC is observed. This suggestion is supported by neuroimaging findings of altered functional connectivity between (1) specific subcortical (striatum) and cortical structures (e.g., dorsolateral PFC, anterior cingulate) implicated in externalizing disorders and (2) specific subcortical (amygdala) and cortical structures (e.g., ventrolateral PFC, ventromedial PFC) implicated in internalizing disorders (for recent reviews, see Beauchaine, 2015b; Beauchaine & Zisner, 2017; Heatherton, 2011; Tone, Garn, & Pine, 2016). Thayer and Lane (2000) introduced neurovisceral integration theory (NIT), which specifies a neural network through which PFC function regulates RSA. According to NIT, a central autonomic network—including the ventromedial PFC and anterior cingulate cortex—provides top-down regulation of cardiac function via the vagus nerve. Since 2000, Thayer and colleagues (e.g., Thayer, Hansen, Saus-Rose, & Johnsen, 2009) have elaborated and extended NIT in a series of pharmacologic blockade and neuroimaging studies. These studies demonstrate associations between resting RSA and performance on executive function tasks that recruit the PFC, including sustained attention and continuous performance tasks (see Beauchaine & Thayer, 2015). Thus, understanding associations between RSA and psychopathology may help elucidate transdiagnostic neural underpinnings of psychopathology and treatment response. RSA is of course easier to measure than central nervous system function in diverse contexts, and with clinical and developmental samples who have difficulty participating in neuroimaging studies. Although further validation of NIT is needed, support for the hypothesis that RSA activity and reactivity fall at least in part under prefrontal control has emerged. For example, in a recent review Beauchaine and Bell

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of studies conducted among healthy adults who performed mental stress tasks that recruit the PFC, Castaldo et al. (2015) found modest associations between task performance and RSA. Similarly, in a recent meta-analysis of 123 studies, Holzman and Bridgett (2017) found modest associations between RSA and performance on self-regulation tasks—including those that recruit ER and executive control. Linking RSA to ER capabilities and PFC function is important for several reasons. First, it dovetails with an extensive literature on prefrontal substrates of self-regulation, emotion, and executive control more broadly (e.g., Dixon, Thiruchselvam, Todd, & Christoff, 2017; Heatherton, 2011; Nigg, 2017). Second, tying emotion regulatory capacity to both (1) the PFC, which develops throughout childhood and adolescence (Tau & Peterson, 2010), and (2) its functional interconnections with subcortical structures that mature somewhat earlier (Brain Development Cooperative Group, 2012), is consistent with neuromaturational models that link compromised PFC development to emerging difficulties with impulse control and self-regulation in adolescence and beyond (e.g., De Brito et al., 2009; Heller, Cohen, Dreyfuss, & Casey, 2016).

Resting Respiratory Sinus Arrhythmia and Psychopathology

Low resting RSA is observed in an impressively long list of psychiatric disorders among children, adolescents, and adults (see Beauchaine, 2001,  2015a; Beauchaine & Thayer, 2015; Shader et al., 2018). Over the last 20 years, such findings have been reported for (1) internalizing conditions including depression (Kemp et al., 2010; Koenig, Kemp, Beauchaine, Thayer, & Kaess, 2016; Rottenberg, 2007),1 generalized anxiety (Chalmers, Quintana, Abbott, & Kemp, 2014), panic (Asmundson & Stein, 1994), phobias (Åhs, Sollers, Furmark, Fredrikson, & Thayer, 2009), posttraumatic stress (Meyer et al., 2016), and obsessive-compulsive disorder (Pittig, Arch, Lam, & Craske, 2013); (2) externalizing conditions including attention-deficit hyperactivity disorder (ADHD; Beauchaine et al., 2013), conduct disorder (CD; Beauchaine et al., 2007), callous-unemotional traits (de Wied, van Boxtel, Matthys, & Meeus, 2012), and substance use (Harte & Meston, 2014; Ingjaldsson, Laberg, & Thayer, 2003); and (3) various other conditions including autism spectrum disorder (ASD; Neuhaus, Bernier, & Beauchaine, 2014), borderline personality disorder (BPD; Koenig, Kemp, Feeling, Thayer, 156

& Kaess, 2016), mania (Henry, Minassian, Paulus, Geyer, & Perry, 2010), schizophrenia (e.g., Clamor, Lincoln, Thayer, & Koenig, 2016), and self-harm (Crowell et al., 2005). Thus, as outlined in the introductory paragraphs of this chapter, low resting RSA is a transdiagnostic biomarker of psychopathology (Beauchaine, 2015a,  2015b). Conversely, high resting RSA correlates positively with social function among children (Diamond, Fagundes, & Butterworth, 2012; Eisenberg et al., 2008), executive function among adults (Thayer et al., 2009), and resilience to various forms of stress throughout life (e.g., El-Sheikh et al., 2001; Souza et al., 2013). Even among those who suffer from various forms of diagnosable psychopathology, resting RSA correlates with individual differences in adaptive social function (e.g., Patriquin, Scarpa, Friedman, & Porges, 2013).

Social and Developmental Influences on Resting Respiratory Sinus Arrhythmia

Among typically developing children, RSA increases linearly from infancy to midadolescence, peaks in late adolescence and young adulthood, then decreases gradually across the lifespan (Alkon, Boyce, Davis, & Eskenazi, 2011; Shader et al., 2018).2 Differences in resting RSA between typically developing children and children with internalizing and externalizing disorders are often not evident in preschool but are observed consistently by later childhood and adolescence (e.g., Beauchaine et al., 2007; Koenig et al., 2016). This likely reflects a failure in normal maturation of emotion regulation and its physiological substrates for children with psychopathology. Development of both emotion regulation and resting RSA are affected by environmental influences in childhood and adolescence. In fact, most measures of emotion regulation are moderately heritable, suggesting considerable socialization (e.g., Goldsmith, Pollak, & Davidson, 2008). Consistent with this interpretation, a growing body of research indicates that emotion regulation, other forms of self-regulation, and related executive functions are shaped strongly across development by environmental influences, especially parent–child relationship dynamics (e.g., Beauchaine & Zalewski, 2016; Bell & Calkins, 2000; Breaux, McQuade, Harvey, & Zakarian, 2018; Bernier, Carlson, & Whipple, 2010; Smith, Calkins, & Keane, 2006; see also Beauchaine & Bell; Brown, Conradt, & Crowell; Hostinar & Cicchetti; Jazaieri, Uusberg, Uusberg, & Gross; Leshin & Lindquist; Martin, Zalewski,

Respiratory Sinus Arrhy thmia as Biomarker

Binion, & O’Brien; Speed & Hajcak; Rappaport, Hawn, Overstreet, & Amstadter; Shader & Beauchaine; Stoycos, Corner, Khaled, & Saxbe; Thompson & Waters, this volume). Such findings are unsurprising given a large literature linking environmental enrichment to structural and functional integrity of the PFC across development in both animals and humans (see Baroncelli et al., 2010; Blair, 2016). Family relationship dynamics in particular exhibit concurrent and prospective associations with children and adolescents’ resting RSA. Ineffective parenting, including inconsistent discipline and corporal punishment, are associated with low resting RSA among adolescents, whereas positive parenting and parental involvement are associated with high resting RSA (Graham, Scott, & Weems, 2017). As reviewed elsewhere, such associations emerge in part through negative reinforcement of emotional lability and associated physiological dysregulation in at-risk families (Beauchaine, 2018; Beauchaine & Zalewski, 2016; Crowell et al., 2013). Given that both emotion regulation and dysregulation are shaped strongly by environment—­ including parent–child relationship dynamics—one might expect changes in children’s RSA in response to effective family interventions, and interventions that target children’s ER directly. Although interventions targeting children’s ER are less common than such interventions for adolescents and adults (see Kehoe & Havighurst; Winiarski, Brown, Karnik, & Brennan, this volume), recent findings indicate considerable promise. For example, our research group recently completed an externalizing intervention in which we targeted children’s ER, as indexed by behavior observations, parent reports, teacher reports, and RSA. The intervention taught children strategies for regulating their emotions, including coping with anger, social problem solving, and effective communication of emotions. Parents learned effective emotion coaching aimed at helping their children understand, interpret, and cope with their own and others’ emotions (see Gottman, Katz, & Hooven, 1997). Children improved at posttreatment on all measures of externalizing behavior and ER, with large effect sizes (Beauchaine et al., 2013; Webster-Stratton, Reid, & Beauchaine, 2011). More important for purposes of this chapter, these behavioral and emotional improvements were accompanied by increases in resting RSA that were over 20 times larger than age-normative developmental shifts (Bell, Shader, Webster-Stratton, Reid, & Beauchaine, 2018). Intervention-induced changes

in  RSA are noteworthy given well-established ­associations between RSA and ER outlined previously, and given associations between low resting RSA and prospective vulnerability to worsening emotion dysregulation and both internalizing and externalizing psychopathology into adolescence (e.g., Vasilev, Crowell, Beauchaine, Mead, & Gatzke-Kopp, 2009; Yaroslavsky, Rottenberg, & Kovacs, 2013).

Respiratory Sinus Arrhythmia Reactivity and Psychopathology

According the phylogenetic account described earlier, PNS inhibition of cardiac reactivity is an evolutionary precondition for social affiliation, which requires mammals to suppress F/F responding (Porges, 1995, 2007). Thus, competent emotion regulation—at least in social contexts—should be marked by limited vagal withdrawal (Beauchaine, 2001). In contrast, under conditions of real or perceived social threat, the PNS—via the vagus nerve—withdraws its inhibitory influence, allowing the sympathetic nervous system (SNS) to mobilize unopposed in the service of F/F responding. In such situations, PNS withdrawal is near complete, and RSA is almost fully abolished (Berntson et al., 1997; Porges, 1995). The PNS therefore suppresses cardiac output when social engagement is adaptive and potentiates cardiac output when fighting or fleeing is adaptive. To the extent that socioemotional problems and associated F/F reactions characterize psychopathology, RSA reactivity should index emotion regulatory capacity (Beauchaine, 2012; Shader et al., 2018). For example, PNS withdrawal to unthreatening social stimuli could potentiate F/F responding when social affiliative behaviors are adaptive. Several studies reveal such patterns of RSA reactivity among externalizing samples (e.g., Beauchaine, Katkin, Strassberg, & Snarr, 2001; Beauchaine et al., 2007; Fortunato, Gatzke-Kopp, & Ram, 2013; Hamilton & Alloy, 2016) and among those with anxiety and panic disorders (e.g., Chalmers et al., 2014; Pittig et al., 2013). In both cases, dysregulated emotion— albeit of different forms—interferes with adaptive social function. It should be noted, however, that links between RSA reactivity and psychopathology are far less consistent than links between resting RSA and psychopathology (Balzarotti, Biassoni, Colombo, & Ciceri, 2017; Beauchaine et al., 2018; Shader et al., 2018; Zisner & Beauchaine, 2016). Although several studies indicate excessive RSA withdrawal during lab tasks among internalizing and externalizing samples (e.g., Beauchaine et al., 2001; Crowell et al., 2005; de Wied Beauchaine and Bell

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et al., 2012), and although internalizing–externalizing comorbidity is associated with greater RSA withdrawal than either internalizing or externalizing disorders alone (Calkins, Graziano, & Keane, 2007; Pang & Beauchaine, 2013), other studies indicate associations between low RSA reactivity and symptoms of psychopathology (e.g., Brugnera et al., 2017; Graziano & Derefinko, 2013; Obradović, Bush, Stamperdahl, Adler, & Boyce, 2010), and still others find no associations at all (e.g., Musser et al., 2011; Negrao, Bipath, van der Westhuizen, & Viljoen, 2011; Pittig et al., 2013). As we have reviewed elsewhere (Beauchaine et al., 2018; Shader et al., 2018; Zisner & Beauchaine, 2016), there are several methodological and sample ascertainment issues that contribute to such heterogeneity of findings. We discuss these further under the heading Methodological Considerations. First, however, we summarize existing literature on social and developmental influences on RSA reactivity.

Social and Developmental Influences on Respiratory Sinus Arrhythmia Reactivity

Specifying developmental trajectories in RSA reactivity is more challenging than doing so for resting RSA because different tasks are often used by different research groups, because similar tasks can evoke very different responses at different ages, and because emotion regulation improves across childhood and adolescence (see Beauchaine & Webb, 2017; Zisner & Beauchaine, 2016). In a recent article that combined data from five existing studies of children and adolescents (N = 559), all of whom underwent negative emotion inductions, we found steep decreases in RSA reactivity from ages 4 to 17 years (Shader et al., 2018). Such data are consistent with the notion that children and adolescents become better able to regulate their physiological reactions to negative emotion as they mature. Developmental trajectories in RSA reactivity to other types of tasks (e.g., attention allocation, positive emotion inductions) are less clear but are not as relevant for assessing emotion dysregulation, the topic of this chapter. Compared with the literature on resting RSA, fewer studies address social correlates of RSA reactivity. However, socialization mechanisms of emotional lability are almost certainly relevant given functional relations between F/F responding and PNS withdrawal. It has long been known that emotional lability is shaped and maintained by negative reinforcement mechanisms (i.e., escape conditioning) in high-risk families of both boys and girls 158

(e.g., Crowell et al., 2013; Snyder, 1977; Snyder, Edwards, McGraw, Kilgore, & Holton, 1994; Snyder, Schrepferman, & St. Peter, 1997). Recent findings from multiple research groups indicate that during dyadic interactions in high-risk families, emotionally dysregulated children and adolescents exhibit exquisite physiological sensitivity to their parents’ evocative behaviors. For example, Crowell et al. (2017) found that self-injuring adolescent girls— all of whom reported poor emotion regulation— displayed greater behavioral and RSA reactivity to their mothers’ aversive behaviors than their depressedonly and healthy control peers. In a much younger sample of three- to five-year-olds, Skowron et al. (2011) reported lower RSA during a mother–child dyadic interaction task for children with histories of physical abuse compared with controls. Thus, available data, although limited, suggest that aversive socialization mechanisms are associated with both emotional lability and excessive RSA withdrawal among children and adolescents during social exchanges with parents. Notably, studies with infants indicate that maternal socialization of children’s RSA reactivity begins as early as six months of age (Moore et al., 2009).

Methodological Considerations

As noted earlier, considerable heterogeneity exists among studies that examine RSA as a marker of emotion dysregulation and psychopathology. This is especially the case for RSA reactivity. Recent literature reviews and meta-analyses suggest that this heterogeneity is systematic, and attributable at least in part to (1) the nature of tasks used to elicit RSA reactivity (e.g., attention allocation vs. negative emotion induction), (2) differences in the nature of samples recruited (clinical vs. high risk), (3) RSA quantification methods, and (4) measurement issues (Beauchaine et al., 2018; Shader et al., 2018). Next, we briefly discuss each of these issues in turn. More extended discussions of methodological issues in psychophysiology research can be found elsewhere (Beauchaine & Webb, 2017; Zisner & Beauchaine, 2016).

Selection of Tasks

Over the past two decades or so, many task conditions have been used to elicit RSA reactivity in psychopathology research. These include negative emotion evocation tasks (e.g., Crowell et al., 2005), attention allocation tasks (e.g., Suess et al., 1994), problem-solving tasks (e.g., El-Sheikh, 2005), executive function tasks (e.g., Marcovitch et al., 2010),

Respiratory Sinus Arrhy thmia as Biomarker

and positive mood inductions (e.g., Fortunato et al., 2013), among others. Notably, RSA reactivity is often interpreted as a biomarker of emotion regulation, regardless of task conditions. This is problematic because physiological markers of specific psychological constructs are valid insofar as those psychological constructs are elicited (see National Advisory Mental Health Council Workgroup on Tasks and Measures for Research Domain Criteria, 2016; Zisner & Beauchaine, 2016). In the case of RSA reactivity, inferences about emotion regulation/dysregulation should be derived from strong negative emotion induction tasks (see Beauchaine, 2015b). This does not mean that other tasks aren’t useful in making inferences about other psychological processes. For example, modest RSA reactivity appears to be a valid peripheral index of attentional capacity during sustained attention tasks (Suess et al., 1994; see also Beauchaine, 2001). Yet we cannot infer emotion regulation from tasks that do not elicit emotional responses. Consistent with this perspective, RSA reactivity among those with diverse forms of psychopathology is most pronounced during negative emotion inductions (Beauchaine et al., 2018; Graziano & Derefinko, 2013). Furthermore, inducing different emotions yields emotion-specific patterns of RSA reactivity (Fortunato et al., 2013; Kreibig, 2010; Rainville, Bechara, Naqvi, & Damasio, 2006). Thus, although RSA reactivity is a promising biomarker of emotion regulation, any such inferences are valid only when stimulus conditions are chosen appropriately.

Sample Characteristics

When studies are grouped into those conducted with clinical samples versus those conducted with high-risk and normative samples, it becomes apparent that associations between excessive RSA reactivity and psychopathology derive primarily from clinical groups. Several studies show, for example, that children, adolescents, and adults with clinical levels of externalizing behaviors exhibit greater RSA withdrawal to emotion evocation than their peers (e.g., Beauchaine, Hong, & Marsh, 2008; Beauchaine et al., 2001,  2007; de Wied et al., 2012; Mezzacappa et al., 1996). In contrast, in normative and high-risk samples, externalizing symptoms often either correlate with less RSA withdrawal during lab tasks or show no association with RSA withdrawal (e.g., Dietrich et al., 2007; Obradović et  al., 2010). Although associations between RSA reactivity and diagnosable internalizing disorders ­

are less consistent, similar patterns have been ­reported (e.g., Crowell et al., 2005,  2017; Levine, Fleming, Piedmont, Cain, & Chen, 2016). Of note, Shader et al. (2018), in a large sample of children and adolescents (N = 559), found that low resting RSA differentiated between those with and without clinical levels of externalizing psychopathology, even though the sample-wide correlation between RSA reactivity and externalizing scores was small and nonsignificant. This suggests that relations between RSA reactivity and psychopathology may be swamped in nonclinical samples by normal variation in responding (see Zisner & Beauchaine, 2016). Thus, in the case of RSA reactivity, inferences about those with psychopathology may not be valid when extrapolated from those with ordinary variation in or only mildly elevated symptoms. Indeed, individual differences in internalizing and externalizing scores are distributed normally, and low to intermediate scores better reflect temperamental ­ tendencies such as shyness and exuberance—not psychopathology (e.g., Degnan et al., 2011).

Respiratory Sinus Arrhythmia Quantification

RSA can be quantified in a number of ways. The simplest approaches capture HRV in the time domain by evaluating beat-to-beat differences in the R-R time series (see Figure 12.1). There are several such methods, including standard deviation of R-R intervals and mean successive difference in R-R intervals, among others. The most common is root mean square of successive differences (RMSSD), which is preferred over other time-domain metrics for statistical reasons that are beyond the scope of this discussion (Berntson, Lozano, & Chen, 2005). Most research on RSA among those with psychopathology uses frequency domain assessment. Common frequency domain approaches include fast Fourier transform (FFT) analysis and autoregressive (AR) spectral analysis (Poliakova et al., 2014). Both of these spectral analytic methods quantify the amount, or “power,” of HRV in specific frequency bands. FFT and AR convert R-R time series into spectral density functions. As shown in Figure  12.2, these methods can be used to isolate and distinguish between RSA and other sources of HRV that are not of PNS origin. For adult participants, spectral density functions are typically subdivided into low-frequency (