Neuroscience Fundamentals for Communication Sciences and Disorders [2 ed.] 1635503590, 9781635503593

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NEUROSCIENCE FUNDAMENTALS for Communication Sciences and Disorders SECOND EDITION

NEUROSCIENCE FUNDAMENTALS for Communication Sciences and Disorders SECOND EDITION RICHARD D. ANDREATTA, PhD

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Copyright © 2023 by Plural Publishing, Inc. Typeset in 10.5/12 Adobe Garamond Pro by Flanagan’s Publishing Services, Inc. Printed in Canada by Friesens All rights, including that of translation, reserved. No part of this publication may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, electronic, mechanical, recording, or otherwise, including photocopying, recording, taping, Web distribution, or information storage and retrieval systems without the prior written consent of the publisher. For permission to use material from this text, contact us by Telephone: (866) 758-7251 Fax: (888) 758-7255 e-mail: [email protected] Every attempt has been made to contact the copyright holders for material originally printed in another source. If any have been inadvertently overlooked, the publisher will gladly make the necessary arrangements at the first opportunity.

Library of Congress Cataloging-in-Publication Data: Names: Andreatta, Richard D., author. Title: Neuroscience fundamentals for communication sciences and disorders / Richard D. Andreatta. Description: Second edition. | San Diego, CA : Plural Publishing, Inc., [2023] | Includes bibliographical references and index. Identifiers: LCCN 2022026602 (print) | LCCN 2022026603 (ebook) | ISBN 9781635503593 (hardcover) | ISBN 1635503590 (hardcover) | ISBN 9781635503609 (ebook) Subjects: MESH: Central Nervous System--physiology | Central Nervous System--anatomy & histology | Sensation--physiology | Perception--physiology Classification: LCC QP376 (print) | LCC QP376 (ebook) | NLM WL 300 | DDC 612.8/2--dc23/eng/20220818 LC record available at https://lccn.loc.gov/2022026602 LC ebook record available at https://lccn.loc.gov/2022026603

Contents

Preface . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xv About the Illustrator:  Maury Aaseng . . . . . . . . . . . . . . . . . . xvii Contributors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xix Reviewers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xxi Acknowledgments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xxiii

SECTION 1.  Neuroanatomical and Neurophysiological Foundations CHAPTER 1.  Introduction and Organization . . . 3 of Neuroscience Fundamentals in Communication Sciences and Disorders Richard D. Andreatta What Is Neuroscience? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 What Is This Book About? . . . . . . . . . . . . . . . . . . . . . . . . . . 4 The View From 30,000 Feet Up . . . . . . . . . . . . . . . . . . . . 6 Overview of Section 1:  Neuroanatomical and Neurophysiological Foundations . . . . . . . . . . . . . . . . . . 6 Overview of Section 2:  Sensory Systems . . . . . . . . . 7 Overview of Section 3:  Motor Systems . . . . . . . . . . . 8 Overview of Section 4:  Neural Substrates of . . . . . . 8 Speech, Language, and Hearing Study Strategies and Tips . . . . . . . . . . . . . . . . . . . . . . . . . . . 9 Closing Thoughts . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10 CHAPTER 2.  Basic Structure and Function . . . of Neurons Richard D. Andreatta Introduction and Learning Objectives . . . . . . . . . . . . . . . Discovery of Two Classes of Cells in the . . . . . . . . . . . . Nervous System The Neuron . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Neurons Are Made for Signaling and . . . . . . . . . . . . . Communication Neurons Never Function Alone . . . . . . . . . . . . . . . . . . . Neurons Perform Fundamental Activities . . . . . . . . Reflexes Provide a Window Into the Fundamental Operation of Neural Networks . . . . . . . . . . . . . . . . . . . Nerve Cells Have Different Shapes, Sizes, . . . . . . . . and Functions

13

13 14 15 15 15 17 18 20

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Structural Features of the Neuron . . . . . . . . . . . . . . . . Soma, Cell Membrane, and Cytoskeleton . . . . . Cytoplasm . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Mitochondria . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Smooth and Rough Endoplasmic Reticulum . . . . Golgi Apparatus . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . The Nucleus Mediates the Process of . . . . . . . . . . Gene Expression Axons and Dendrites . . . . . . . . . . . . . . . . . . . . . . . . . The Glial Cell . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Glial Cells Are Divided Into Two Major . . . . . . . . . . Functional Groups Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . The Top Ten List . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Chapter 2 Abbreviations . . . . . . . . . . . . . . . . . . . . . . . . . . . . Study Questions and Activities . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

21 21 23 24 24 25 25

CHAPTER 3.  Basics of Neural Signaling . . . . . . and Synaptic Function Richard D. Andreatta Introduction and Learning Objectives . . . . . . . . . . . . . . . Foundations of Neural Signaling:  The Nature of . . . . Information in the Nervous System Electronics 101 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Gradients:  Putting Substances Into Motion . . . . Developing an Electrical Gradient . . . . . . . . . . . . . Voltage, Current, and Resistance . . . . . . . . . . . . . . . The Fluid Environment of the Neuron: . . . . . . . . . . Intracellular and Extracellular Composition Ion Channels:  Tunnels Across the Neuron’s . . . . . . Cell Membrane Ion Channels Can Control the Motion of Ions . . . Ion Channels Can Gate Ionic Current in . . . . . . Three Ways Some Ion Channels Are Always Open . . . . . . . . . . Ion Pumps Are Active Transporters of Ions . . . . . Across the Neuron’s Cell Membrane Understanding Membrane Potentials . . . . . . . . . . . . .

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29 33 33 36 38 39 39 40

41 42 42 42 43 44 47 48 49 50 52 53 54

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Membrane Voltages Are Created by a . . . . . . . . . . Separation of Charges Vm Can Be Changed by Ionic Gradients . . . . . . . and Currents Development of the Neuron’s Resting . . . . . . . . . Membrane Potential The Action Potential . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Voltage-Gated Ion Channels Are Chiefly . . . . . . Responsible for AP Generation Voltage-Gated Na+ and K+ Channels Differ . . . . in Their Opening Speed The Action Potential in “Action” . . . . . . . . . . . . . . Propagation of the Action Potential Down . . . . the Axon Synapses:  The Point of Communication . . . . . . . . . Between Neurons Electrical Synapses Allow for Virtually . . . . . . . . . Instantaneous Signal Transmission Chemical Synapses:  The Workhorse of the . . . . Nervous System Structure of the Chemical Synapse . . . . . . . . . . . . . Chemical Synapse Function: . . . . . . . . . . . . . . . . . . Transmission Phase Chemical Synapse Function:  Receptive Phase . . Postsynaptic Receptors Belong to Two . . . . . . . . Different Functional Classes Ending Chemical Synaptic Transmission: . . . . . “Cleaning Up After the Party” Neurotransmitters Can Be Divided Into a . . . . . Handful of Chemical Classes A Few Final Words on Neurotransmission . . . . . . Neural Integration:  Closing (and Opening) the . . . . . Neural Signaling Loop The “Government Analogy” of Neural . . . . . . . . . . . Integration in the Postsynaptic Cell Concluding Thoughts on Neurobiology . . . . . . . . . . . . . The Top Ten List . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Chapter 3 Abbreviations . . . . . . . . . . . . . . . . . . . . . . . . . . . . Study Questions and Activities . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

56 56 58 62 64 65 65 67 71 72 72 74 76 78 78 83 84 87 88 92 93 94 94 95 96

CHAPTER 4.  Neuroanatomy of the . . . . . . . . . . . . 99 Human Nervous System:  Anatomical Nomenclature, Embryology, the Spinal Cord, and the Brainstem Richard D. Andreatta Introduction and Learning Objectives . . . . . . . . . . . . . . . 99 Getting Around the Nervous System:  Anatomical . . . . 102 Planes and Orientations

Anatomical Orientations . . . . . . . . . . . . . . . . . . . . . . . . 103 Anatomical Planes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 104 Gray Versus White Matter in the Nervous System . . . . 105 Gray Matter in the CNS and PNS . . . . . . . . . . . . . . . . 105 White Matter Consists of Bundles of Axons . . . . . . . 107 A Brief Tour of the Embryologic Development of . . . 109 the Nervous System The Human Embryo Is a Multilayered . . . . . . . . . . . 109 Collection of Cells Neural Crest and Neural Tube Cells . . . . . . . . . . . . . . 109 Differentiate Into the PNS and CNS Major Anatomical Structures and Functions of . . . . . . . 112 the Human Central Nervous System The Skull and Vertebral Column House and . . . . . 113 Protect the Tissues of the CNS The Spinal Cord . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 115 External Spinal Cord Structures . . . . . . . . . . . . . . . 116 Internal Spinal Cord Structures:  Gray Matter . . . 119 Internal Spinal Cord Structure:  White Matter . . . 121 The Brainstem:  An Overview . . . . . . . . . . . . . . . . . . . . . . . 123 The Medulla . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 126 Medulla:  External Features . . . . . . . . . . . . . . . . . . . 128 Medulla:  Internal Features . . . . . . . . . . . . . . . . . . . . 130 The Pons . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 135 Pons:  External Features . . . . . . . . . . . . . . . . . . . . . . . 136 Pons:  Internal Features . . . . . . . . . . . . . . . . . . . . . . . . 137 The Mesencephalon . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 140 Mesencephalon:  External Features . . . . . . . . . . . . . 143 Mesencephalon:  Internal Features . . . . . . . . . . . . . 144 The Top Ten List . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 145 Chapter 4 Abbreviations . . . . . . . . . . . . . . . . . . . . . . . . . . . . 146 Study Questions and Activities . . . . . . . . . . . . . . . . . . . . . . 146 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 146 CHAPTER 5.  Neuroanatomy of the Human . . . 149 Nervous System:  Cranial Nerve Systems Richard D. Andreatta Introduction and Learning Objectives . . . . . . . . . . . . . . . 149 Organization of the Cranial Nerves and Nuclei . . . . . . 149 in the Brainstem2 Functional Classifications of the Cranial Nerves . . . . . 154 Motor:  General Somatic Efferent (GSE) . . . . . . . . . 155 Motor:  Special Visceral Efferent (SVE) . . . . . . . . . . . 155 Motor:  General Visceral Efferent (GVE) . . . . . . . . . . 155 Sensory:  General Somatic Afferent (GSA) . . . . . . . . 155 Sensory:  General Visceral Afferent (GVA) . . . . . . . . . 155 Sensory:  Special Somatic Afferent (SSA) . . . . . . . . . . 155

CONTENTS

Sensory:  Special Visceral Afferent (SVA) . . . . . . . . . 155 Cranial Nerves:  Normal and Disordered Functions . . 156 CN I:  Olfactory (SVA) . . . . . . . . . . . . . . . . . . . . . . . . . . . 156 CN II:  Optic (SSA) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 158 CN III:  Oculomotor (GSE and GVE) . . . . . . . . . . . . 159 CN IV:  Trochlear (GSE) . . . . . . . . . . . . . . . . . . . . . . . . 161 CN V:  Trigeminal (GSA and SVE) . . . . . . . . . . . . . . . 162 CN VI:  Abducens (GSE) . . . . . . . . . . . . . . . . . . . . . . . . . 165 CN VII:  Facial (SVE, GVE, SVA, GSA) . . . . . . . . . . . 165 CN VIII:  Auditory-Vestibular (SSA) . . . . . . . . . . . . . . 167 CN IX:  Glossopharyngeal (SVE, GVE, GVA, . . . . 169 SVA, GSA) CN X:  Vagus (SVE, GVE, GVA, SVA, GSA) . . . . . . 171 CN XI:  Spinal Accessory (SVE) . . . . . . . . . . . . . . . . . . 173 CN XII:  Hypoglossal (GSE) . . . . . . . . . . . . . . . . . . . . . . 174 The Top Ten List . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 176 Chapter 5 Abbreviations . . . . . . . . . . . . . . . . . . . . . . . . . . . . 177 Study Questions and Activities . . . . . . . . . . . . . . . . . . . . . . 177 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 178 CHAPTER 6.  Neuroanatomy of the Human . . . . 179 Nervous System:  The Diencephalon, Cerebrum, and the Cerebral Cortex Richard D. Andreatta Introduction and Learning Objectives . . . . . . . . . . . . . . . 179 The Diencephalon . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 179 The Thalamus:  “Gatekeeper” of Ascending . . . . . . 179 Information to the Cerebral Cortex The Thalamus Is a Collection of Nuclei . . . . . . . . 182 With Unique Inputs and Outputs The Hypothalamus:  “CEO” of the Body’s . . . . . . . . 184 Homeostatic Regulatory Systems The Hypothalamic-Pituitary-Adrenal Axis . . . . . 186 (HPA) Operates as a Feedback Control System Hypothalamus Consists of Numerous Nuclei . . 186 With Unique Operations Hypothalamic Nuclei Participate in a Wide . . . . 187 Range of Homeostatic Functions The Cerebrum:  The Center of Our Lives and . . . . . . . 190 Who We Are The Lobes of the Cerebrum . . . . . . . . . . . . . . . . . . . . . . . . 193 The Frontal Lobe:  The Cognitive and Motor . . . . 195 Control Center of the Cerebrum Frontal Lobe:  Anatomical Features . . . . . . . . . . . . 197 Frontal Lobe:  Functional Features . . . . . . . . . . . . . 197 The Parietal Lobe:  Multimodal Sensory Center . . 203 of the Cerebrum Parietal Lobe:  Anatomical Features . . . . . . . . . . . . 204

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Parietal Lobe:  Functional Features . . . . . . . . . . . . . 205 The Temporal Lobe:  The “Can You Hear Me . . . . 207 Now” and “What Am I” Cerebral Region Temporal Lobe:  Anatomical Features . . . . . . . . . . 207 Temporal Lobe:  Functional Features . . . . . . . . . . . 208 The Occipital Lobe:  The Visual Center of . . . . . . . 209 the Cerebrum Occipital Lobe:  Anatomical Features . . . . . . . . . . . 209 Occipital Lobe:  Functional Features . . . . . . . . . . . 209 The Insula:  Is It a Lobe or Not? . . . . . . . . . . . . . . . . . . 210 The Cerebral Cortex . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 211 Anatomical Features of the Cerebral Cortex . . . . . . . 212 Organization of the Cerebral Cortex: . . . . . . . . . . . . . 213 Brodmann’s Areas and Cortical Columns The Cortex Is Arranged to Support Serial and . . . . . 218 Parallel Processing of Information The Cortex Is Organized to Support Cognition . . . 221 Parietal Association Areas Mediate Visual . . . . . . . . 224 Guidance, Spatial Awareness, and Attention Temporal Association Areas Recognize . . . . . . . . . . . 225 Complex Objects Phineas Gage and the Iron Spike:  An Accidental . . . 225 Study of the Frontal Association Area The Limbic System (Limbic Association Area): . . . . 228 Emotional Center of the Brain Hippocampal Formation Is Involved in . . . . . . . . 230 Spatial Learning and Long-Term Memory Hippocampal Formation Anatomy: . . . . . . . . . . . 233 Hippocampus, Dentate Gyrus, and Subiculum Amygdala Mediates Threat, Anxiety, and . . . . . . 233 Aggressive Behaviors Anterior Cingulate Gyrus:  At the Crossroads . . 235 of Emotion and Cognition Septal Area:  Key Component of CNS’s . . . . . . . . 236 Reward System Interhemispheric Connectivity and . . . . . . . . . . . . . . . . . 237 Cerebral Dominance The Top Ten List . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 239 Chapter 6 Abbreviations . . . . . . . . . . . . . . . . . . . . . . . . . . . . 241 Study Questions and Activities . . . . . . . . . . . . . . . . . . . . . . 242 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 242 CHAPTER 7.  Neuroanatomy of the . . . . . . . . . . . . . 249 Human Nervous System:  White Matter Tracts, Protective Infrastructure, and the Brain’s Blood Supply Richard D. Andreatta Introduction and Learning Objectives . . . . . . . . . . . . . . . 249

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Connectivity and White Matter Pathways of . . . . . . . . 250 the CNS Association Fibers Interconnect Areas Within . . . . 251 a Hemisphere Commissural Fibers Link Brain Regions Across . . 254 the Midline Projection Fibers Shuttle Information to and . . . . . . 255 From the Brain Protecting the CNS From Harm:  The Meninges . . . . . 259 and the Ventricular System The Meninges . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 259 The Ventricular System . . . . . . . . . . . . . . . . . . . . . . . . . . . 262 The Vascular System of the Brain . . . . . . . . . . . . . . . . . . . . 266 Neurovascular Complex Is Divided Into . . . . . . . . . . 266 Arterial and Venous Systems Anterior Arterial System . . . . . . . . . . . . . . . . . . . . . . . 266 Posterior Arterial System . . . . . . . . . . . . . . . . . . . . . . 271 Venous System Sinuses Drain Deoxygenated . . 272 Blood Back to the Heart Vascular Pathology Can Arise From Three . . . . . . . 275 General Situations Aneurysms and Hemorrhagic Stroke . . . . . . . . . . . 275 Ischemic Events . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 276 Arteriovenous Malformations . . . . . . . . . . . . . . . . . . 278 The Top Ten List . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 281 Chapter 7 Abbreviations . . . . . . . . . . . . . . . . . . . . . . . . . . . . 282 Study Questions and Activities . . . . . . . . . . . . . . . . . . . . . . 282 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 283

SECTION 2.  Sensory Systems CHAPTER 8.  Basic Principles of Sensation . . . . 287 and Perception Richard D. Andreatta Introduction and Learning Objectives . . . . . . . . . . . . . . . 287 Sensation Versus Perception . . . . . . . . . . . . . . . . . . . . . . . . 288 Nervous Systems Are Far From Ideal to Sense . . . . 289 and Perceive Perception Requires Filtering, Selection, . . . . . . . . . 289 Inference, and Prediction Sensations Are Processed by Sensory Systems . . . . . 291 Quantifying Sensation and Perception . . . . . . . . . . . . 292 All Sensory Events Possess Four Basic . . . . . . . . . . . . 294 Attributes Related to Perception Modality:  What Is the Stimulus? . . . . . . . . . . . . . . 294 Location:  Where Is the Stimulus? . . . . . . . . . . . . . . 297 Intensity:  How Strong Is the Stimulus? . . . . . . . 302

Duration:  How Long Does the Stimulus Last? . . . 304 Sensation and Perception Are Actively . . . . . . . . . . . . 305 Regulated by the CNS The Top Ten List . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 306 Chapter 8 Abbreviations . . . . . . . . . . . . . . . . . . . . . . . . . . . . 306 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 307 Study Questions and Activities . . . . . . . . . . . . . . . . . . . . . . 307 CHAPTER 9.  The Somatosensory System: . . . . . 309 Touch, Proprioception, Temperature, and Pain Richard D. Andreatta Introduction and Learning Objectives . . . . . . . . . . . . . . . 309 The Peripheral Somatosensory Apparatus: . . . . . . . . . . 310 Sensory Receptors and the Primary Afferent Cutaneous Tactile Receptors of the . . . . . . . . . . . . . . 310 Somatosensory System Proprioception Sense Is Mediated by Sensory . . . . 316 Endings in the Musculoskeletal System Temperature Reception Depends on the . . . . . . . . . . 318 Expression of Different Types of Ion Channels Nociception and the Perceptual Response . . . . . . . . 319 of Pain Axon Features of the Primary Afferent That . . . . . . . 321 Transmits Inputs Centrally Dermatomes and the Trigeminal . . . . . . . . . . . . . . . . . . 322 Innervation Zones Central Somatosensory Pathways . . . . . . . . . . . . . . . . . . . . 322 Dorsal Column–Medial Lemniscal System: . . . . . . . 324 Touch and Proprioception From the Body Anterolateral System:  Noxious and . . . . . . . . . . . . . . 328 Temperature Sensation Trigeminal System Manages All Forms of . . . . . . . . 335 Somatosensation From the Face and Head The Somatosensory Cortex . . . . . . . . . . . . . . . . . . . . . . . . . . 338 Structural and Functional Features of the . . . . . . . . . 338 Somatosensory Cortex S1 Possesses Four Complete Cortical Body . . . . . . . . 342 Representations Speech-Related Activity of S1 . . . . . . . . . . . . . . . . . . . . . 343 Outputs From the Somatosensory Cortical Areas . . . 344 Posterior Parietal Lobe Receives Inputs From . . . . . 344 Primary and Second Somatosensory Areas Neuroplasticity:  Changes to the Structure and . . . . . . 346 Function of the Brain Somatosensory Cortex Receives Diffuse . . . . . . . . . . . 347 Projections From the Thalamus S1 Plasticity as a Function of Enriched . . . . . . . . . . . . 350 Experiences

CONTENTS

The Timing of Sensory Inputs Are Critical . . . . . . . 350 Factors in Changing Cortical Representations Implication of the Neuroplasticity Literature . . . . . . 354 to Rehabilitation The Top Ten List . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 354 Chapter 9 Abbreviations . . . . . . . . . . . . . . . . . . . . . . . . . . . . 356 Study Questions and Activities . . . . . . . . . . . . . . . . . . . . . . 356 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 357 CHAPTER 10.  Auditory-Vestibular System: . . . . 361 Inner Ear Transduction Mechanisms for Sound and Balance Richard D. Andreatta Introduction and Learning Objectives . . . . . . . . . . . . . . . 361 A Quick Summary of Acoustic Transduction in . . . . . 362 the Outer and Middle Ear The Inner Ear and the Cochlea . . . . . . . . . . . . . . . . . . . . . . 362 Basilar Membrane Is a Frequency Analyzer . . . . . . . . 365 Organ of Corti Is the Chief Site for . . . . . . . . . . . . . . 367 Transduction of Auditory Inputs Hair Cell Structural and Functional Features . . . . . . 369 Stereocilia Are Key Elements for Signal . . . . . . . . . . . 371 Transduction in the Hair Cell Mechanotransduction Mechanism for Acoustic . . . . 372 Signals in the Cochlea Stereocilia Shearing and Hair Cell . . . . . . . . . . . . . 373 Receptor Activation Auditory Nerve Transmits HC Receptor . . . . . . 375 Potential Changes to the Cochlear Nuclei Auditory Nerve Firing Encodes Acoustic . . . . . . 377 Intensity and Frequency If the IHC Is the True Sensory Receptor, . . . . . . . 379 Why Do OHCs Exist? The Vestibular System . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 380 Otolith Organs Transduce Linear Motion . . . . . . . . . 381 Semicircular Canals Measure Angular . . . . . . . . . . . . 383 Acceleration Central Vestibular Pathway . . . . . . . . . . . . . . . . . . . . . . . . . . 386 Vestibulo-Ocular Response Is Critical for . . . . . . . . . 387 Keeping Your Eyes on the Target The Top Ten List . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 389 Chapter 10 Abbreviations . . . . . . . . . . . . . . . . . . . . . . . . . . 390 Study Questions and Activities . . . . . . . . . . . . . . . . . . . . . . 390 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 391 CHAPTER 11.  The Visual System . . . . . . . . . . . . . . 393 Richard D. Andreatta Introduction and Learning Objectives . . . . . . . . . . . . . . . 393

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The Nature of Light in Our Environment . . . . . . . . . . . 394 The Peripheral Visual Apparatus: Anatomical . . . . . . . 395 Overview of the Eye Gross Anatomy of the Anterior Eye . . . . . . . . . . . . . . . 395 Gross Anatomy of the Posterior Eye . . . . . . . . . . . . . . 397 Visual Fields . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 398 The Retina . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 400 Of Rods and Cones:  Light Transduction . . . . . . . . . . 402 in the Retina Rods Mediate Vision During Dim and . . . . . . . . 403 Nighttime Lighting Cones Mediate Spatial Acuity and Color . . . . . . 405 Vision in Bright Light Conditions Phototransduction Mechanism . . . . . . . . . . . . . . . . . . 407 Photoreceptors Differentially Activate . . . . . . . . . . . . 409 ON- or OFF-Bipolar Cells Signal Integration and Convergence Through . . . . . 413 the Retinal Layers Retinal Ganglion Cells Form the Beginning of . . . 414 Different Visual Processing Streams The Central Visual Pathway . . . . . . . . . . . . . . . . . . . . . . . . . 416 Retinal Ganglion Cell Axons Become the . . . . . . . . . 416 Fibers of the Optic Nerve, Chiasm, and Tract Optic Tract Neurons Project Principally to the . . . 417 Lateral Geniculate Nucleus The Primary Visual Cortex . . . . . . . . . . . . . . . . . . . . . . . 418 Dorsal and Ventral Visual Streams . . . . . . . . . . . . . . . . . . . 422 The Dorsal Visual Processing Stream . . . . . . . . . . . . . 425 The Ventral Visual Processing Stream . . . . . . . . . . . . . 425 Visual Field and Pathway Deficits . . . . . . . . . . . . . . . . . . . 426 Noncortical Visual System Projections . . . . . . . . . . . . . . 428 From the Retina The Top Ten List . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 431 Chapter 11 Abbreviations . . . . . . . . . . . . . . . . . . . . . . . . . . 432 Study Questions and Activities . . . . . . . . . . . . . . . . . . . . . . 432 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 433 CHAPTER 12.  The Chemical Senses: . . . . . . . . . . . 435 Olfactory and Gustatory Systems, and the Neural Substrate of Swallowing Richard D. Andreatta and Nicole M. Etter Introduction and Learning Objectives . . . . . . . . . . . . . . . 435 Olfactory System:  An Overview . . . . . . . . . . . . . . . . . . . . . 436 Olfactory Receptors and the Transduction . . . . . . . 438 of Odorants ORN Cilia Are Susceptible to . . . . . . . . . . . . . . . . . . 439 Environmental Pollutants

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Odorant Transduction Requires G-Coupled . . . 440 Receptors Odorants Are Detected by Different . . . . . . . . . . . . . 442 Combinations of ORN Receptors Olfactory Bulb Consists of Glomeruli . . . . . . . . . . . . 443 Olfactory Bulb Projection Neurons Target the . . . . 444 Olfactory Cortex Gustatory System:  An Overview . . . . . . . . . . . . . . . . . . . . 445 Gustatory Receptors and Transduction . . . . . . . . . . . 446 Distribution of Taste Sensitivity Across the . . . . . . . 447 Surface of the Tongue Taste Buds Consist of Collections of Taste . . . . . . . 448 Receptor Cells Tastant Transduction Process . . . . . . . . . . . . . . . . . . . . . 449 Salty and Sour Tastants Are Transduced by . . . . 450 Ion Channels Sweet, Bitter, and Umami Transduction . . . . . . . 451 Uses G-Coupled Protein Receptors Central Gustatory Pathway . . . . . . . . . . . . . . . . . . . . . . . . . . 452 Central Representation of Taste . . . . . . . . . . . . . . . . . . . . 453 Dysfunction in the Chemical Senses . . . . . . . . . . . . . . . . . 454 Chemosensory Changes Associated With . . . . . . . . . 455 Typical Aging Chemosensory Changes Associated With . . . . . . . . . 456 Surgical Intervention Chemosensory Changes Associated With . . . . . . . . . 456 Injury or Disease The Neural Substrate of Normal Feeding and . . . . . . . 457 Swallowing The Aerodigestive Tract Supports Different . . . . . . 458 Modes of Behavior Brief Overview of the Process for Feeding and . . . . 458 Swallowing Oral Preparatory and Oral Transport . . . . . . . . . . 459 Phases of Swallowing Pharyngeal and Esophageal Phases of . . . . . . . . . 459 Swallowing Neural Elements Participating in the Process . . . . . . 459 of Swallowing Olfactory Nerve Contribution . . . . . . . . . . . . . . . . . 463 Trigeminal Nerve Contribution . . . . . . . . . . . . . . . . 463 Facial Nerve Contribution . . . . . . . . . . . . . . . . . . . . . 463 Glossopharyngeal Nerve Contribution . . . . . . . . . 464 Vagus Nerve Contribution . . . . . . . . . . . . . . . . . . . . . 464 Hypoglossal Nerve Contribution . . . . . . . . . . . . . . 465 Spinal Nerve Contribution . . . . . . . . . . . . . . . . . . . . 465 Brainstem Respiratory Centers Are Voluntarily . . . 465 Modulated During Swallowing

Cortical and Subcortical Control of Swallowing . . . 465 Control and Function of the Swallowing . . . . . . . . . 467 Central Pattern Generator The Top Ten List . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 468 Chapter 12 Abbreviations . . . . . . . . . . . . . . . . . . . . . . . . . . 469 Study Questions and Activities . . . . . . . . . . . . . . . . . . . . . . 470 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 471

SECTION 3.  Motor Systems CHAPTER 13.  Muscle Tissue:  Structure, . . . . . . 475 Mechanisms of Contraction, and the Motor Unit Richard D. Andreatta and Timothy Butterfield Introduction and Learning Objectives . . . . . . . . . . . . . . . 475 Types of Muscle Tissue . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 476 Hierarchical Organization of Skeletal Muscle . . . . . . . . 477 Tissue:  From Bundle to Fiber The Muscle Fiber (Cell) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 479 Internal Structure of the Muscle Fiber . . . . . . . . . . . . 479 Organization and Structure of the Myofibril . . . . . . . . . 481 Myofibrils Are Serial Collections of Sarcomeres . . . . 481 Molecular Subcomponents of the Sarcomere . . . . . 482 Structure and Function of Myosin . . . . . . . . . . . . . 482 The Function of Actin and Accessory . . . . . . . . . . 484 Proteins in the Sarcomere Titin:  A Giant Among Proteins . . . . . . . . . . . . . . . . 485 Neuromuscular Junction Mediates the Neural . . . . . 485 Signal That Starts Muscle Contraction Contraction Physiology:  Excitation-Coupling . . . . 488 in the Muscle Fiber Contraction Physiology:  Cross-Bridge . . . . . . . . . . 489 Formation Length-Tension Relationship of Muscle Tissue . . . . 492 Investigating the Contraction Properties of . . . . . . . . . 494 Muscle Tissue Muscle Forces Increase With Firing Rate of . . . . . . . 495 the Lower Motoneuron Skeletal Muscle Fiber Types . . . . . . . . . . . . . . . . . . . . . . . 496 The Motor Unit . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 499 Size Principle of Motor Unit Recruitment . . . . . . . . 502 Regulation of Skeletal Muscle Contraction: . . . . . . . . . 504 Alpha-Gamma Coactivation The Top Ten List . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 508 Chapter 13 Abbreviations . . . . . . . . . . . . . . . . . . . . . . . . . . 509 Study Questions and Activities . . . . . . . . . . . . . . . . . . . . . . 510 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 510

CONTENTS

CHAPTER 14.  Motor Control Systems . . . . . . . . . . 513 of the CNS Richard D. Andreatta Introduction and Learning Objectives . . . . . . . . . . . . . . . 513 Neuromotor Control Elements of the CNS: . . . . . . . . . 514 Direct Versus Indirect Systems Descending Tracts of the Direct Motor . . . . . . . . . . . . . 515 Control System Descending Motor Pathways From the . . . . . . . . . . . 515 Cerebrum:  Corticospinal and Corticobulbar Tracts Anatomical Course of the Corticospinal and . . . . . 519 Corticobulbar Pathways Corticospinal Tract:  Course and Function . . . . . 519 Corticobulbar Tract: Course and Function . . . . . 520 The Curious Case of UMN Versus LMN . . . . . . . 522 Facial Palsy Descending Motor Pathways Originating . . . . . . . . 524 From the Brainstem Rubrospinal Tract . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 524 Vestibulospinal Tract . . . . . . . . . . . . . . . . . . . . . . . . . . 525 Reticulospinal Tract . . . . . . . . . . . . . . . . . . . . . . . . . . . 525 Tectospinal Tract . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 527 Cerebral Motor Area Underlying Voluntary Control . . . 527 Organization and Functional Mapping of M1 . . . . . 527 Discovery of the Inner Workings of M1 . . . . . . . . . . . 531 Different Neuron Firing Patterns in M1 . . . . . . . . . . 534 M1 Uses Population Codes to Generate . . . . . . . . . . . 535 Higher-Order Performance Features of an Action Sensory Inputs to M1 Provide Real-Time . . . . . . . . 536 Information About the Body’s Current State Developing a Broader Understanding of Action . . 537 and Behavioral Performance The Premotor Cortex . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 537 PMA Activity Is Strongly Associated With . . . . . . . 538 Upper Limb and Hand Action Supplementary Motor Area Activity Is a . . . . . . . . . . 541 Necessary Element for Speech Motor Control The Cingulate Motor Map Links Action . . . . . . . . . 542 to Emotion Neuroplasticity in Motor Maps of the Cortex . . . . . . . . 542 Deficits in Motor Control Can Result From Damage to Upper or Lower Motoneurons . . . . . . . . . . . 544 Indirect Motor Control Systems . . . . . . . . . . . . . . . . . . . . . 546 Basal Ganglia Is a Selector of Movement . . . . . . . . . . 546 The Caudate and Putamen and Their . . . . . . . . . . . . 549 Connections Globus Pallidus and Its Connections . . . . . . . . . . . . . . 550

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Subthalamic Nucleus and Its Connections . . . . . . . . 550 Substantia Nigra and Its Connections . . . . . . . . . . . . . 550 Schematic Organization and Functional . . . . . . . . . . 551 Overview of the BG Nuclei The Direct and Indirect Pathways of the . . . . . . . . . 551 Basal Ganglia Direct Pathway Operation in the BG . . . . . . . . . . 552 Indirect Pathway Operation in the BG . . . . . . . . . 552 Role of the SNpc in the BG . . . . . . . . . . . . . . . . . . . 552 Lesions to the Basal Ganglia Can Produce . . . . . . . . 553 Hypo- or Hyperkinetic Deficits Hypokinetic Disorders of the BG Are . . . . . . . . . 554 Related to Indirect Pathway Influence Hyperkinetic Disorders of the BG Are . . . . . . . . . 555 Related to Direct Pathway Overactivity Complexity of Basal Ganglia Interconnections . . . 557 Complicates the Simple Correlation Between Structure, Lesion, and Behavioral Effects Cerebellum Operates to Coordinate and . . . . . . . . . 558 Refine Movements External and Internal Anatomical Features of . . . . . 561 the Cerebellum Functional Divisions of the Cerebellum and . . . . . . . 561 Their Input/Output Pathways Functional Cerebellar Areas Form . . . . . . . . . . . . . . . . 564 Processing Circuits Vestibulocerebellar Circuit . . . . . . . . . . . . . . . . . . . . . 565 Spinocerebellar Circuit . . . . . . . . . . . . . . . . . . . . . . . 565 Cerebrocerebellar Circuit . . . . . . . . . . . . . . . . . . . . . . 567 Consequences of Cerebellar Lesion Reveal the . . . . 568 Operation of the System The Autonomic Nervous System Is the Motor . . . . . . . 570 Control System for Homeostasis Pathway Organization of the Sympathetic . . . . . . . . 571 System Pathway Organization of the Parasympathetic . . . . . 573 System The Top Ten List . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 574 Chapter 14 Abbreviations . . . . . . . . . . . . . . . . . . . . . . . . . . 575 Study Questions and Activities . . . . . . . . . . . . . . . . . . . . . . 576 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 577 CHAPTER 15.  Introduction to Motor . . . . . . . . . . . 581 Learning and Control Principles of Behavior Patrick O. McKeon and Richard D. Andreatta Introduction and Learning Objectives . . . . . . . . . . . . . . . 581 The Understanding of Motor Control Began . . . . . . . . 582 With an Idea

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What Exactly Is Motor Control? . . . . . . . . . . . . . . . . . . . . . 585 From Perception to Action . . . . . . . . . . . . . . . . . . . . . . . . . . 586 Foundations of Motor Control Theory . . . . . . . . . . . . . . 586 Two Systems of Motor Control:  Open-Loop . . . . . 587 Systems Two Systems of Motor Control:  Closed-Loop . . . . . 588 Systems The Importance of Reflexes in Motor Control: . . . 591 Insights by Sir Charles Sherrington Nikolai Bernstein:  A Russian Revolutionary . . . . . . 593 Figure in Motor Control Bernstein’s Problem and Motor Equivalence . . . . 593 From Bernstein to Current Motor Control Theories . . . 597 The General Motor Program Theory . . . . . . . . . . . . 597 The Dynamic Systems Theory of Motor Control . . . 598 Contrasting Motor Program Theory and . . . . . . . . . . 600 Dynamic Systems Theory Perception and Action Are Coupled According . . . 601 to Dynamic Systems Theory The Dynamics of Motor Skill Acquisition . . . . . . . . . . . . 604 An Example of Sensorimotor Skill Acquisition: . . . . 605 Learning to Dance Concluding Thoughts on Motor Control Theory . . . . 607 The Top Ten List . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 608 Chapter 15 Abbreviations . . . . . . . . . . . . . . . . . . . . . . . . . . 609 Study Questions and Activities . . . . . . . . . . . . . . . . . . . . . . 610 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 610

SECTION 4.  Neural Substrates of Speech, Language, and Hearing CHAPTER 16.  Neural Substrate of Speech . . . 615 and Voice Stephen M. Tasko Introduction and Learning Objectives . . . . . . . . . . . . . . . 615 Speech and Vocalization Are Complex Behaviors . . . . . 616 Neural Substrates of Speech and Vocalization: . . . . . . . . 618 How Do We Know What We Know? Peripheral Nerves Involved in Speech and . . . . . . . . . . . . 619 Vocalization Efferent Pathways . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 620 Respiratory Subsystem . . . . . . . . . . . . . . . . . . . . . . . . 620 Phonatory Subsystem . . . . . . . . . . . . . . . . . . . . . . . . . 622 Velopharyngeal Subsystem . . . . . . . . . . . . . . . . . . . . . 622 Oral Articulatory Subsystem . . . . . . . . . . . . . . . . . . . 622 Descending Pathways Onto Speech Motor . . . . 623 Neuron Pools

Afferent Pathways . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 624 Subcortical Structures Involved in Vocalization . . . . . . . 624 Reticular Formation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 625 Periaqueductal Gray Matter . . . . . . . . . . . . . . . . . . . . . . 625 Thalamus (Ventrobasal Complex) . . . . . . . . . . . . . . . . 625 Basal Ganglia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 626 Cerebellum . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 627 Cortical Bases of Speech Motor Control and . . . . . . . . 628 Vocalization Primary Motor and Somatosensory Cortices . . . . . 628 Inferior Frontal Gyrus (Broca’s Area) . . . . . . . . . . . . . . 629 Supplementary Motor Area . . . . . . . . . . . . . . . . . . . . . . . 631 Anterior Cingulate Cortex . . . . . . . . . . . . . . . . . . . . . . . . 631 Supramarginal Gyrus . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 632 Insula . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 632 Neural Basis of Auditory Processing and . . . . . . . . . . . . 632 Perception of Speech Sensorimotor Adaptation During Speech . . . . . . . . . . . . 634 Production Putting It All Together:  Computational Models . . . . 637 of Speech Production The Directions Into Velocities of Articulators . . . . . 638 Model (DIVA) DIVA — Feedfoward and Feedback Control . . . . . . 640 System Operation The Development and Refinement of Speech . . . . . . . 642 Motor Abilities Selected Neurological Disorders of Speech . . . . . . . . . . 644 and Vocalization Aphasias . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 644 Motor Speech Disorders:  Dysarthrias . . . . . . . . . . . . . 644 Other Speech Production Deficits . . . . . . . . . . . . . . . . 646 The Top Ten List . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 648 Chapter 16 Abbreviations . . . . . . . . . . . . . . . . . . . . . . . . . . 650 Study Questions and Activities . . . . . . . . . . . . . . . . . . . . . . 650 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 651 CHAPTER 17.  Neural Substrate of Language . . . 655 Jessica D. Richardson and Sarah Grace H. Dalton Introduction and Learning Objectives . . . . . . . . . . . . . . . 655 Language:  What Is It Really? . . . . . . . . . . . . . . . . . . . . . . . . 655 Neuroscience and Language Acquisition . . . . . . . . . . 656 Neuroscience and Language Evolution . . . . . . . . . . . . 658 Brain Areas Involved in Language Processing . . . . . . . . 659 Models of Language Production . . . . . . . . . . . . . . . . . . . . . 666 The “Classic” Language Model: . . . . . . . . . . . . . . . . . . 667 Wernicke-Geschwind Model

CONTENTS

Dual-Path Models of Language Processing . . . . . . . . 669 Models of Communication, Language Evolution, . . . 672 and Development Neurological Factors and Correlated Features of . . . . . 673 Language Disorders Aphasias . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 673 Dementia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 678 Traumatic Brain Injuries . . . . . . . . . . . . . . . . . . . . . . . . . 679 Right Hemisphere . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 681 Harnessing the Ability of the Brain to Change for . . . . 682 Language Rehabilitation Neuroplasticity and Constraint-Induced . . . . . . . . . 683 Therapy Approaches The Original Idea:  Constraint-Induced . . . . . . . 683 Movement Therapy Constraint-Induced Language Therapy . . . . . . . . . 684 Neural Substrate of Language Recovery . . . . . . . . . . . . . 685 Following Stroke Parting Thoughts on the Neurorehabilitation . . . . . . . 688 of Language The Top Ten List . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 688 Chapter 17 Abbreviations . . . . . . . . . . . . . . . . . . . . . . . . . . 689 Study Questions and Activities . . . . . . . . . . . . . . . . . . . . . . 690 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 691 CHAPTER 18.  Neural Substrate of . . . . . . . . . . . . 697 Hearing:  Central Auditory Pathway and the Auditory Cortices Anne D. Olson Introduction and Learning Objectives . . . . . . . . . . . . . . . 697 Central Auditory Pathway Supports Auditory . . . . . . . 698 Skills We Use Daily An Analogy:  The CAP as a Highway System . . . . . 701 The Central Auditory Pathway . . . . . . . . . . . . . . . . . . . . . . 701 Cochlear Nucleus (CN):  Anatomy and . . . . . . . . . . . . 703 Physiology CN Cell Types, Responses, and Function . . . . . . 706 Frequency Preservation in the CN . . . . . . . . . . . . . 709

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Temporal Preservation in the CN . . . . . . . . . . . . . . 709 Intensity Preservation in the CN . . . . . . . . . . . . . . . 710 Superior Olivary Complex:  Anatomy and . . . . . . . . . 710 Physiology Low-Frequency Sound Localization Is . . . . . . . . . 710 Processed in the MSOC High-Frequency Sound Localization . . . . . . . . . . . 713 Requires Action of the LSOC and MNTB SOC Allows for the Integration of Sounds . . . . . 713 From Both Ears Lateral Lemniscus:  Anatomy and Physiology . . . . . 714 Inferior Colliculus:  Anatomy and Physiology . . . . . 715 Medial Geniculate Body:  Anatomy and . . . . . . . . . . 716 Physiology Auditory Cortical Areas . . . . . . . . . . . . . . . . . . . . . . . . . . . . 717 The Primary Auditory Cortex . . . . . . . . . . . . . . . . . . . . 717 Deeper Insights Into the Properties of the . . . . . . 719 Primary Auditory Cortex Role of the Auditory Cortex in Speech and . . . . 719 Vocalization The Secondary Auditory Cortex . . . . . . . . . . . . . . . . . . 720 The Auditory Association Areas . . . . . . . . . . . . . . . . . . 720 Neuroimaging of the Human Auditory . . . . . . . . . . . 722 Cortex Reveals Distinct Features Surprise! The Auditory System Has Efferent . . . . . . . . 722 Pathways Stapedial Reflex Response Is Mediated . . . . . . . . . . . 723 Through the SOC Function of the Olivocochlear Bundle . . . . . . . . . . . . 724 The Auditory Brainstem Response . . . . . . . . . . . . . . . . . . 725 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 726 The Top Ten List . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 727 Chapter 18 Abbreviations . . . . . . . . . . . . . . . . . . . . . . . . . . 728 Study Questions and Activities . . . . . . . . . . . . . . . . . . . . . . 729 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 729 Glossary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 731 Index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 777

PREFACE Neuroscience Fundamentals for Communication Sciences and Disorders (NFCSD) was developed with three goals in mind. First and foremost, NFCSD was developed to provide senior undergraduate and graduate students in communication sciences and disorders (CSD) programs (as well as students in Doctor of Audiology [AuD] programs) with a richly illustrated, comprehensive, yet highly readable and accessible textbook covering the neuroanatomy and neurophysiology of the human nervous system. NFCSD was written as a “brain and behavior” style of textbook, while also ensuring comprehensive coverage of essential neuroanatomy in an integrative fashion. My principal goal for producing this book was (and continues to be) to help students develop a deep understanding and appreciation of critical brain-behavior relationships that can impact and help inform their careers as rehabilitation specialists for patients and clients with speech, language, and hearing disorders. Valuing the critical role of the nervous system in the behaviors, perceptions, and cognitive functioning of someone with a communication disorder is something I believe is central to the development and implementation of effective and efficient evidence-based treatments. Second, this textbook was written with the practicing clinician in mind. I wanted to provide clinical practitioners with a ready resource guide to the inner workings of the nervous system and its processes that was both accessible and comprehensive for their everyday needs. A reference book of this type is always useful in one’s professional library. Clinicians need a reference book that can be read, appreciated, and understood without having to take another formal course in the subject matter. My hope is that the accessibility of the writing and the numerous illustrations within the book can allow those who have been out of school for a while to use the material in this textbook directly to inform their practice. Aside from its direct use for informing patient care, the book can also be used for client and caregiver educational purposes; the illustrations and the explanatory analogies are ideal for helping clients better understand the brain-based nature of a disorder. Lastly, my third goal was to write a textbook for faculty who are responsible for teaching neural bases of speech and language courses, but who do not themselves have specific expertise in this area. Larger programs in CSD usually have someone on their faculty with specific neuroscience experience, but medium- to smaller-sized programs may not. I wanted this textbook to be a resource guide for any faculty colleague of mine who is in the challenging position of having to develop a class in and/or teach a neural bases course but does not feel comfortable or confident in doing so. If this happens to describe your circumstances, then this textbook can certainly be of help to you. For faculty in this position, think of the textbook as a user guide to help you develop lectures and course content. Feel free to use the analogies and examples scattered throughout the book as your own when teaching; customize them as you wish. The lecture slides that are available on the book’s PluralPlus companion website pro-

vide a framework that you should feel free to customize and change as your circumstances dictate. For faculty who adopt this book for their own classes, I welcome your thoughts and opinions on its content and organization; I really mean this! If there are sections that you feel need to be expanded or reduced, areas that should be organized differently, or areas where my interpretation of the material doesn’t conform to your own, please e-mail me. I welcome this kind of feedback and dialogue from those who are choosing to incorporate this textbook into their courses. I want this book to work for you in the best manner possible, and the only way I can accomplish this is by getting your real-use perspectives. As such, to adopting faculty as well as students and clinicians alike, if you find errors in the book, or have comments or questions, please feel free to e-mail me at [email protected] and I’ll do my best to respond promptly to your messages and take note of your thoughts. I believe that textbooks should be dynamic and living things that evolve and change as we learn more about our subject matter. As such, the contents of this book are as current as possible, with every effort made to check and cross-check its accuracy against several independent sources. Despite these efforts, there will be errors in the book, and for these I apologize in advance; the fault for these errors is mine, and mine alone.

Using the Textbook in Class: Suggestions to All Faculty Who Adopt NFCSD To faculty who adopt NFCSD 2E for their courses, the book was written to build a student’s understanding and comprehension of neuroscience gradually from the workings of the neuron to the broad functioning of systems underlying behavior and cognition. Let me offer the following suggestions for using and assigning readings from this book to help you and your students get the most out of it. First, Chapter 1 sets the stage and rationale for the textbook and provides important study ideas and strategies for student use. In other words, don’t skip over Chapter 1, as many of us are guilty of doing often. Chapter 1 will help orient students and contains important insights as to the grand scope of the book’s content. Chapters 2 through 7 (Sec­ tion 1) should be read in the order presented because these chapters lay out the essential groundwork for the remainder of the book’s content. Chapters 2 through 7 should be referenced continuously as students proceed through the textbook. It is important to think of Chapters 2 through 7 as a “reference core” within the book. I have intentionally placed throughout all the chapters parenthetical reminders to go back to this reference core to review critical concepts, figures, and descriptions. This was a pedagogical decision that xv

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I believe will help students cross-link different topical areas of information more easily. For the sensory systems section of the textbook (Sec­ tion 2), Chapter 8 is a general chapter that provides students with a basic grounding in concepts related to sensation and perception. This chapter needs to be read first because its content cuts across all the sensory systems, equally. After this is accomplished, all other sensory chapters (Chapters 9 through 12) can be read in the order that best suits your needs. I ordered the sensory chapters in this textbook solely based on my own view of their importance to CSD, with somatosensory and auditory being the most critical systems to appreciate, followed by the visual and chemical senses. The motor control section of the textbook (Section 3) ideally should be read in the presented order, but it is perfectly fine to move Chapter 13 on muscle tissue to a different content location if needed. This chapter can also be used as a self-study module if you don’t want to spend class time on this material. The motor control systems content in Chap­ ter 14 should be assigned in four separate segments: (1) direct motor systems, (2) the basal ganglia, (3) the cerebellum, and (4) the visceromotor system. Lastly, Chapter 15 on motor control theory is another chapter that can be used as a selfstudy module if so desired. Finally, Chapters 16 through 18 (Section 4) can be read in any order because each is self-contained. I can envision some faculty using Chapters 16 through 18 immediately after Section 1 of the book, or perhaps using Chapter 18 on the central auditory pathway immediately after the content on the inner ear presented in Chapter 10. Although these last three chapters are intended to be the culminating section of the book, use them as you think is best to meet your needs. In the end, what you use from the textbook will be your decision based upon your needs, the content you think is important to cover, and the realities of class time and scheduling. The textbook was designed to broadly meet the various needs of faculty in different types of CSD programs and thus can easily be adapted to fit any semester or course schedule you are working within. Depending on your department, and how integrated your curriculum is, the book can be conceivably purchased at the start of a student’s program and then used throughout the curriculum as needed. Of course, the book is intended for use in neural bases classes, but parts of

the book can potentially be adapted for use in several different courses. For example, the auditory system chapters can be held over for audiology courses; the neural bases of speech and language chapters can be used as review material for motor speech and normal language courses; the neuroanatomical content of the textbook can be incorporated into aphasia or neurocognitive classes; and so on and so forth. Regardless of how you choose to creatively use this textbook, I hope that it meets your needs and that your students find it informative and useful in their training.

New to the Second Edition! Faculty and student insights from the first edition were invaluable as preparations were made for this new edition of NFCSD. Among some of the major changes and updates in the second edition of NFCSD are: • Reorganization and division of content from Chapters 4, 5, and 6 of the first edition into six new and more digestible chapters in the second edition. • Creation of a stand-alone chapter on the cranial nerves. • Addition of more summary tables and process flowcharts to simplify the text and provide ready-made study material for students. • Addition of over 40 new full-color illustrations to increase the total number of figures in the second edition of the textbook to over 400. • Revisions to most figures throughout the book to improve their clarity and coherence with the written material. • For each chapter, a one-stop listing of all abbreviations used in the chapter has been added to improve reader usability. • Expanded and updated glossary. • Inclusion of exams and updated lecture slides to PluralPlus for faculty use. • Addition of a major section and discussion on the neural bases of swallowing. • Content updates throughout all chapters. • Corrections to figures and text.

ABOUT THE ILLUSTRATOR:  MAURY AASENG Maury Aaseng graduated from the University of Minnesota Duluth with a BFA in Graphic Design and began working as a freelance illustrator, creating graphics for young adult nonfiction. His work expanded into medical and anatomical illustration as he started collaborating with authors and experts in various medical fields to create vivid figures for publications that illuminate concepts necessary to understand the science of the body. His subject matter in this field includes illustrations of intricate imagery of human anatomy, brain surgery, endoscopic views, cellular level structures, medical devices and technological advancements, and patient education. His style range also includes vector drawn line art, cartooning, mechanical illustration, pen and ink, and watercolor. Through his emphasis on watercolor, he has created promotional materials for opera productions, illustrative signage for landscaping initiatives focusing on pollinator habitats

and botanical gardens, and custom paintings. His watercolor paintings won recognition in the juried exhibition Upstream People Gallery in 2008 and a collection of his watercolor work entitled Saturated Life was displayed at the Great Lakes Aquarium gallery in 2016. He teaches classes covering scientific illustration and nature-inspired watercolors, and over the years he has reached into his broad experience of painting and drawing to create books that demonstrate his techniques to other budding artists. Maury lives in Duluth, Minnesota, with his wife and two children near the shores of Lake Superior. Much of his artistic inspiration is drawn from the outdoors, where he spends time observing and photographing the natural world for subject matter. An online collection of his work can be viewed at mauryillustrates.com

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CONTRIBUTORS Richard D. Andreatta, PhD, ASHA Fellow Professor Department of Communication Sciences and Disorders Rehabilitation and Health Sciences Doctoral Program College of Health Sciences University of Kentucky Lexington, Kentucky Chapters 1–15

Patrick O. McKeon, PhD, ATC, CSCS Associate Professor Athletic Training Clinical Education Coordinator Department of Exercise and Sport Sciences Ithaca College Ithaca, New York Chapter 15 Anne D. Olson, PhD, CCC-A Associate Professor Department Chair Department of Communication Sciences and Disorders Rehabilitation and Health Sciences Doctoral Program College of Health Sciences University of Kentucky Lexington, Kentucky Chapter 18

Timothy Butterfield, PhD, ATC, FACSM, FNATA Professor Department of Athletic Training and Clinical Nutrition Associate Professor, Department of Physiology Center for Muscle Biology University of Kentucky Lexington, Kentucky Chapter 13 Sarah Grace H. Dalton, PhD, CCC-SLP Assistant Professor Department of Speech Pathology and Audiology Marquette University Milwaukee, Wisconsin Chapter 17

Jessica D. Richardson, PhD, CCC-SLP Associate Professor Department of Speech and Hearing Sciences Outreach Director Center for Brain Recovery and Repair University of New Mexico Albuquerque, New Mexico Chapter 17

Nicole M. Etter, PhD, CCC-SLP Associate Professor Department of Communication Sciences and Disorders Pennsylvania State University University Park, Pennsylvania Chapter 12

Stephen M. Tasko, PhD, CCC-SLP Associate Professor Emeritus Speech, Language and Hearing Sciences Western Michigan University Kalamazoo, Michigan Chapter 16

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REVIEWERS Plural Publishing, Inc. and the author would like to thank the following reviewers for taking the time to provide their valuable feedback during the development process of the original edition of the textbook: Irene M. Barrow, PhD, CCC-SLP Professor Department of Communication Sciences and Disorders James Madison University Harrisonburg, Virginia

Janis M. Jarecki-Liu, PhD, CCC/SLP Professor/Chair Department of Communication Sciences and Disorders Clarion University of Pennsylvania Clarion, Pennsylvania

Margaret Lehman Blake, PhD, CCC-SLP Associate Professor Communication Sciences and Disorders University of Houston Houston, Texas

Janie Park Magee, MA, CCC-SLP Clinical Director and Instructor Department of Speech and Hearing Sciences Delta State University Cleveland, Mississippi

William R. Culbertson, PhD Professor Communication Sciences and Disorders Northern Arizona University Flagstaff, Arizona

Kimberly D. Mory, MA, CCC-SLP, CHES, CCM Associate Clinical Professor Department of Communication Sciences and Disorders Texas Woman’s University Denton, Texas

Carol S. Deakin, PhD, CCC-SLP Associate Professor/Program Coordinator Communicative Sciences and Disorders Alabama A&M University Normal, Alabama

Diane M. Scott, PhD, CCC-A Professor Communication Disorders Program North Carolina Central University Durham, North Carolina

Jeremy J. Donai, AuD, PhD Assistant Professor Department of Communication Sciences and Disorders West Virginia University Morgantown, West Virginia

Lori L. Stiritz, MA, CCC-A Senior Lecturer Department of Communication Disorders Texas State University San Marcos, Texas

Daniel Furnas, PhD Assistant Professor Communication Sciences and Disorders Jacksonville University Jacksonville, Florida

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ACKNOWLEDGMENTS Once again, I wish to thank the editorial and production crew at Plural Publishing for giving me the opportunity and the freedom to craft a second edition of this textbook. Thanks go out to the intrepid Valerie Johns, my executive editor, for originally recruiting me for this project and for continuing to give me the resources and freedom necessary to make this book truly my own. Because of your continuous kindness, support, and confidence in my work, I believe the project became everything that I hoped it would become. Next, my deep appreciation to Elisa Andersen and Emily Pooley for being my “go to” people whenever I had one of my many questions. During the last few months of the preparation process, both of you helped keep my stress in check. I’d also like to sincerely thank my former editorial assistant at Plural, Christina Gunning, for helping me lay the critical groundwork for preparation of this new edition. I hope this new edition of the textbook lives up to everyone’s expectations and confirms the confidence that the Plural production and editorial teams have graciously placed in me. After the team at Plural, the next person who needs my deepest acknowledgment of gratitude for helping me realize the true vision for this new edition is my illustrator and collaborator Maury Aaseng. Like the first edition, this new version of the textbook would be a fraction of what it is if it were not for his illustrating talents and gifts. Maury Aaseng remains one of the finest illustrators I’ve had the pleasure of working with on any writing project. Maury was more than an illustrator . . . he was a sounding board for my ideas and thoughts. He helped me enormously as I clarified descriptions by forcing me to “think visually.” How he was able to translate my scribbles and mockups to create most of the beautiful illustrations in this book never ceased to amaze me. Thank you my friend for continuing to be my partner on this project. I can’t describe how lucky I was to have had you working with me on this book once more! There are two sets of critical contributors to this book that I need to generously thank. First to my contributing chapter authors: Steve Tasko, Jessica Richardson, Sarah Dalton, Anne Olson, Pat McKeon, Tim Butterfield, and Nikki Etter — you guys have been terrific to work with and I cannot be happier with your contributions to this textbook. Each of you had a huge task in taking enormous bodies of literature and condensing them down to chapters that would give students an excellent scope of each topical area. (I owe each of you a rather large beer, or in the case of Nikki, a Bahama mama instead!) The second group of contributors that I need to deeply thank are all my past and present students (you guys know who you are). I wish I could list all your names in the front part of the textbook, for you are all contributors and authors in this book. I sincerely mean this too! This book is the direct outgrowth of everything you have taught me throughout the years. You showed me what worked, what didn’t work, what needed better explanation and time to develop, what level of detail you could handle before revolt-

ing on me, and how to approach teaching every one of you in the most effective way possible. Being your professor has, and continues to be, my distinct honor and the highlight of my career. As I mentioned earlier, it takes a village to realize a project of this scope, and my village at the University of Kentucky’s College of Health Sciences continues to be a terrific one to be a part of. Thank you to all my colleagues at UK for your constant encouragement. I wish to thank my college leadership, Dean Scott Lephart, and Associate Deans Karen Badger and Janice Kuperstein for their consistent support and grace as I completed this work. In addition, this second edition could not have happened without the generosity of my department chair, Dr. Anne Olson. Anne — you continue to be such a cheerleader and advocate for my work. You are one of my dearest friends and I thank you so much for your willingness to grant me the time and resources needed to make this project a success. Thanks for all the little intangibles! Finally, without family, we are nothing, and I’m blessed to be a part of an incredible family of remarkable individuals. To Jane: I love you dearly and I’m so thankful each day that you somehow manage to see through my enormous number of faults and quirks and still choose to stay by my side. Your support, constant encouragement, and understanding of my various moods made this entire project possible. No kidding — you are a saint! To Jonah, Joshua, and Madeline: Each of you continues to put your stamp on the pages of this book. Although life (new jobs, college, high school, and COVID19) intervened and prevented each of you in helping as much as you did during the first edition, your love and support were always there for me . . . as well as your constant jokes about me working all the time and being glued to my favorite chair. Thanks kids — you make my life remarkable each day! Finally (although I know you still can’t read this no matter how much I’ve tried to teach you), thank you to my Stella (my Golden Retriever) for continuing to keep me company and making sure to remind me very often that there is much more to life than work — a good nap and a belly rub are just the thing to brighten one’s day. Finally, the fact that I can say that I am a professor at a major university in the United States and the author of a book is only possible because of the enormous sacrifices made by my parents, Ana and Oscar Andreatta. I am a first-generation American, and I am the proud son of Hispanic immigrants who left behind the countryside of Argentina to come to the United States to build a better life for their children. My parents came to this country with literally nothing and spent many difficult years navigating and walking the challenging path that all immigrants must do to be accepted in this country. But through arduous work, perseverance, and profound self-sacrifice, they succeeded in building a wonderful life for me and my siblings. My parents believed fervently in the power of education and the role it played in bettering one’s life. In this respect, this book is an enduring and tangible xxiii

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legacy to that belief. My dad passed away during the authoring of the first edition of this book, and my mom during the final preparations for this new edition. I lovingly dedicate this second edition to my truly remarkable and breathtakingly

courageous parents whose immigrant story continues forward within the lives of the enormous family that has grown from what they started so many years ago.

Este libro está dedicado a la memoria de mi papi, Oscar Andreatta, “El Hombre de Sucre” y mi mamá, Ana Andreatta, “La Veteranita” ◆

(This book is dedicated to the memory of my father, Oscar Andreatta, “The Gentleman from Sucre” and my mother, Ana Andreatta, “The Veteran”)

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SECTION 1

Neuroanatomical and Neurophysiological Foundations

Chapter 1. Introduction and Organization . . . . . . . . . . of Neuroscience Fundamentals in Communication Sciences and Disorders Chapter 2. Basic Structure and Function of Neurons Chapter 3. Basics of Neural Signaling and Synaptic Function

3

. . . . . . . .

13

. . . . . . . . . . . . . . .

41

Chapter 4. Neuroanatomy of the Human . . . . . . . . . . . . 99 Nervous System:  Anatomical Nomenclature, Embryology, the Spinal Cord, and the Brainstem Chapter 5. Neuroanatomy of the Human . . . . . . . . . . . . 149 Nervous System:  Cranial Nerve Systems Chapter 6. Neuroanatomy of the Human . . . . . . . . . . . . 179 Nervous System:  The Diencephalon, Cerebrum, and the Cerebral Cortex Chapter 7. Neuroanatomy of the Human . . . . . . . . . . 249 Nervous System:  White Matter Tracts, Protective Infrastructure, and the Brain’s Blood Supply 1

2

CHAPTER 1 Introduction and Organization of Neuroscience Fundamentals in Communication Sciences and Disorders Richard D. Andreatta What Is Neuroscience?

some of the nomenclature that we still use today to describe the elements of the nervous system. The pace of progress in early brain science picked up substantially in the latter half of the 18th century and into the 19th century with discoveries that (a) nerves conduct electrical signals to and from the brain, (b) different functions of the brain can be generally localized to stereotypical brain areas, and (c) focal brain damage or lesions can lead to losses of specific functions. Fast forwarding to the 20th century and up through the present day, our understanding of the nature of the nervous system and its operations has been nothing less than explosive in quantity and quality. It’s safe to say that we’ve learned more about the intricacies of the nervous system in the past 75 years than in all recorded history. The explosive growth of neuroscience as a field has been fueled by the realization that to truly study such a complexly organized and dynamic structure requires the talents of researchers from virtually all basic and clinical scientific disciplines. In recent decades, with the appreciation that nervous system function is related to wide-reaching aspects of human behavior, many diverse fields of interest have joined the fray, adding new technologies as well as different methods of investigation and analysis techniques to more traditional anatomical approaches. Today, diverse and unique subareas of neuroscience, such as cognitive neuroscience, behavioral neuroscience, neuroeconomics, neuroanthropology, neuroforensics, and neurocybernetics, are pushing the envelope in our conception of the nervous system’s impact on all aspects of human and animal life. Neuroscience today is used to inform us about our own cognitive capacity and that of other animals. Neuro­science is used to understand how we sense, perceive, and learn about the world around us. Neuroscience is even being used to inform corporations about our shopping habits, product preferences, and what ads to place on websites we visit. From questions related to how and why we create social groups, to the use of apps that supposedly help us train our brains, to technological endeavors seeking to develop artificial intelligences or brain machine interfaces for rehabilitative purposes, neuroscience seems to be everywhere these days. It sure is an exciting time to be in the neurosciences! So, after all of this discussion, are we any closer to a satisfying definition for the term neuroscience? Acknowledging its broad diversity and complexity, we can probably agree that neuroscience is the field of study with the central goal of developing and expanding our appreciation of how the nervous system functions and contributes to all aspects of behavior related

In its broadest terms, neuroscience is the scientific study of all aspects related to, directly or indirectly, the structure and operation of the nervous system in all living organisms that happen to possess one. Hmm . . . not a very satisfying definition, is it? Let me try again: Neuroscience is a composite field of study drawing its content from diverse disciplines including biology, chemistry, psychology, electrical engineering, mechanical engineering, computer science, linguistics, rehabilitation, medicine, sociology, the musical and visual arts, and economics. A little bit better and more specific, but not a tremendously satisfying definition either. And therein lies the difficulty of pinning down what exactly we mean by the term “neuroscience.” Neuroscience is an inherently difficult scientific field to define with any exactitude because studying the nature of the nervous system is an attempt to understand the very essence of human and animal behavior. In effect, the general field of neuroscience is working to answer the central question, why do humans and animals think and behave the way that they do? The only real constant in defining the term neuroscience seems to be the notion that the nervous system must act as the central focal point of any basic and/or clinical investigation. Technically, anyone from any field who studies the nervous system can call themselves a neuroscientist. Congratulations! Because you are reading this book and taking this course, you are now a neuro­scientist in training. Welcome to the club! Although neuroscience as a recognized field is relatively young compared to the old standard bearers of biology and chemistry, human interest in the workings of the brain is as old as recorded history itself. References to the brain and its operation can be found dating back to antiquity and the ancient Greeks and Egyptians. Although interest in the brain is thousands of years old, large advancements and leaps in our understanding of the brain really didn’t start occurring until the famous anatomist Galen of Pergamon came on the scene in Rome around the middle of the first century A.D. Galen, through his famous anatomical animal dissection studies, was one of the first individuals to begin piecing together the importance of the brain and nervous system, its function, and its relation to animal behavior. Progress on understanding the nature of the brain continued slowly but steadily for many centuries after Galen’s first dissections. By the early 18th century, several anatomists had completely dissected the brain and had begun developing 3

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Neuroscience Fundamentals for Communication Sciences and Disorders

to animal life. For humans, we can refine this definition by also saying that neuroscience is tasked with understanding the nervous system’s role and contribution to (a) our health and quality of life, (b) the creation of our cultural norms and preferences, and (c) the development and maintenance of our cognitive lives. At this point, you might be thinking, “I just want to be a speech-language pathologist or an audiologist. Why do I really need to learn about neuroscience and the brain?” I can’t begin to count the number of times I’ve heard some variation of this question during my years of teaching communication neuroscience to students in communication sciences and disorders (CSD). It is actually a very important question to ask — one whose answer goes directly to the heart and central purpose of this textbook. Why do you, as a CSD student, need to study the fundamentals of neuroscience? I could spend pages trying to give you lofty explanations as to the virtues of neuroscience training in CSD, but I prefer to answer this question by highlighting one inescapable truth that genuinely surprises most CSD students when they hear it for the first time. The rationale for the importance of neuroscience training in the CSD curriculum boils down to one essential idea that you can’t run away from: Whether you are treating a child with a faulty /s/ or /r/, a person who stutters, a patient who’s had a stroke and can no longer use language, or someone who has sustained a traumatic brain injury, the essence of your treatment and all clinical improvement is ALWAYS about changing the patient’s behavior, perception, or cognitive state. The moment you talk about the idea of behavioral, perceptual, and/or cognitive adaptations, you must fully realize that what you are really talking about are changes to the structure and operation of the nervous system itself. To put it plainly, everything you do as a clinical speech-language pathologist and audiologist will have a direct impact on the very nature, anatomy, and function of your client’s nervous system. Behavioral changes ARE brain changes. Let that idea sink in for a bit, and then appreciate the magnitude of responsibility that rehabilitation specialists (including those in CSD) assume when they decide to treat a person. We are actively changing the brains and nervous systems of our clients through our clinical efforts . . . period. With this understanding, how can you not want to study and understand the nervous system? As I tell my students in my university courses, rehab specialists across the spectrum are, in effect, practicing clinical neuroscientists, whether they realize it or not. And, I believe that it is better to acknowledge this reality than not. Remember: Knowledge and understanding are power. With that question put to rest, let me further say that neuroscience is one of the few topical areas in the CSD curriculum that literally cuts across and is applicable to all CSD content areas. Neuroscience training is applicable to phonology, audiology and aural rehab, voice, stuttering, child and adult language, swallowing, cognitive rehab, motor speech disorders, and the list goes on. Neuroscience cuts across these areas because we are always talking about behavioral, perceptual, and/or cognitive adaptations when it comes to

SECTION 1

treatment practice and its impact on client performance and outcomes. Neuroscience training helps you to appreciate and understand why your treatments work or do not work. It also helps you to (a) argue intelligently for the benefits of rehabilitation with other professionals or insurance companies, (b) understand scientific literature on the functioning of the brain during normal and disordered speech-language and hearing behaviors, (c) better understand brain-behavior relationships to make appropriate clinical assessments and treatment decisions, and lastly (d) be more creative as a rehab specialist by enhancing your conception of neurorehabilitation and its potential for a given client.

What Is This Book About? Neuroscience Fundamentals for Communication Sciences and Disorders was conceived and written as a brain and behavior style of textbook, with a level of complexity that is geared toward students who likely have never had coursework specifically in the neurosciences and/or neuroanatomy. What this means, from a practical standpoint, is that I go out of my way to carefully explain difficult concepts and mechanisms in a manner that can be appreciated by students. The only real academic background you need for this book is one that you probably already have. If you’ve had a basic biology or chemistry course as part of your university’s general education curricula, you should be good to go. The overriding goal of this textbook is to provide you, the student, with the depth and breadth of information needed to help you develop a solid knowledge base of fundamental operations and neuroanatomical elements of the nervous system. With this knowledge, you can begin to value the critical role of the nervous system in the behaviors, perceptions, and cognitive functioning of your future patients and clients. CSD students are not medical or nursing students and therefore do not need encyclopedic or extremely detailed neuroanatomical and neurophysiological knowledge of the nervous system. What CSD students do need, though, is a textbook and professional reference source that can accomplish four primary goals: 1. Provide a healthy level of neuroanatomical and neurophysiological detail that is necessary to meet the needs of CSD students today, as they move forward toward clinical practice and, importantly, into the future where advancements in the field of rehabilitation and brain sciences are accelerating. 2. Provide understandable, accessible, and intuitive material that explains how and why the neuroanatomical elements, processes, and mechanisms of the nervous system operate as they do during human behavior. 3. Provide a depth and scope of material that will allow students to read, better understand, and appreciate a wide

CHAPTER 1   Introduction and Organization of Neuroscience Fundamentals in Communication Sciences and Disorders

range of literature related to motor behavior, cognition, emotion, language, and sensory perception — all areas that directly impact treatment decisions for a given client or patient. 4. Ignite a deep interest and curiosity for the nervous system that may lead some to dig deeper into the discipline and take on a research career in the neurosciences and/ or CSD. As indicated earlier, neuroscience is a broad field that draws its source material from virtually all other areas of basic and clinical science. This book does not pretend to cover all areas of neuroscience; that simply isn’t possible. But what this textbook does do is give you a healthy sample of the enormity of the field and the critical importance of neuroscience for understanding human behavior and cognition in both healthy and disordered groups. The title of the book may suggest that only CSD-based examples will be used to discuss the nervous system or that the book will cover only content areas related to speech, language, and hearing. This is not the case. In fact, doing so would be a great disservice to your long-term understanding of the nervous system as a whole. It is important to recognize from the outset that while this book is geared for students in CSD, its content is intentionally broad and applicable to all forms of human behavior, from speech, to cognition, to playing an instrument, to walking across campus, or even to reaching for and enjoying your daily half-caf, skinny, organic soy, double espresso shot latte (I’m a café mocha with an extra pump of syrup person, myself ). Keep in mind that although didactic examples used in this textbook are coming from a variety of nonspeech-language-hearing sources, the concepts supported by these examples are equally pertinent to all CSD applications. To understand the impact of the nervous system in CSD applications specifically, I believe you first must understand the broad strokes of the nervous system’s anatomy and physiology. Only after such an understanding has been gained can you start to truly appreciate the specifics underlying the neural foundations of speech, language, and hearing. This book is all about providing you with that much-needed broad overview and foundation, with some introductory lessons on the neural substrates of human communication toward its conclusion. This approach has worked well for hundreds of students during my years of university teaching, and I sincerely hope this textbook accomplishes this same goal for you as well. In the text, even though there is quite a bit of neuroanatomy covered, I do spend a considerable amount of time going beyond these more structural elements to explain why and how the nervous system operates. I believe that understanding the how’s and why’s is just as important as learning the terms, labels, and locations of different nervous system elements. In all honesty, I believe that internalizing the how’s and why’s is probably a bit more critical for your long-term success. Terms

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and labels can always be looked up when needed if you happen to forget one, but essential understanding about process needs to stay with you for the duration of your curriculum and into your career. The textbook was intentionally written in an informal and casual style, as if I were having a conversation with you or telling you a story, because this is how I actively teach my courses. In fact, the book should be read as if I’m speaking to you directly or as if you’re listening to a podcast of me lecturing. In addition to the casual and explanatory style of the writing, the illustrations in this book form a central pedagogical resource. The textbook is brimming with more than 400 high-quality, full-color, and detailed illustrations that were designed to add visual explanatory power. Dozens of tables and process flowcharts are also included that help summarize chapter content. It is critical that you use and reference the illustrations and tables frequently when reading the text. The illustrations, tables, flowcharts, and text-based material were intentionally designed to work seamlessly together to convey the complex neuroanatomical and neurophysiological concepts we will tackle. You may be thinking, “There’s a lot of detail in this book. How much do I really need to know?” So that you are not surprised when you get to certain chapters and sections of the book, know that there will be topics and content discussed that may be perceived by some students as being overly detailed and divorced from what CSD students typically “need to know” for clinical practice. Specifically, I am referring to sections that will dive more deeply into topics related to genetics, protein function, voltages, electrical currents, and some of the biochemistry behind how neurons create signals and receive them from other neurons or environmental stimuli. For an author, deciding on the right level of detail to include in a book is a real challenge, especially when crafting one for such a broad range of students with varying academic backgrounds. Acknowledging the diversity of today’s CSD students, I decided early on that I would go ahead and include the details, knowing that some students and instructors will use them, and others will not. I believe the content of the book can be appreciated and understood either way. Use those sections of the book that best fit the learning goals that your professor determines. Professors are valuable resources and will help you find what level of detail is best suited for you to be successful in their classes. In the end, always keep in mind that just because the content and information is in the book, doesn’t mean you are obligated to learn it all in one semester. But if you ever want to explore the additional details, they’ll be here waiting for you. The textbook was also designed with the intent of acting as a professional reference book for your future careers. One last thought. As a professor, I’m all about pushing students to work a little outside their comfort zones. Because this book reflects my teaching philosophy, it seemed only fitting not to write a book that included only those “need to know” items, but one that gave students the opportunity to

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Neuroscience Fundamentals for Communication Sciences and Disorders

go beyond just the basics. I personally believe it is important to study and learn not just those things you need to know as a clinician, but also those things that can help you become a more deeply educated student-scholar and clinician-scholar in CSD.

The View From 30,000 Feet Up The book is divided into 18 chapters that span from the basic neurobiology of the neuron to the neural bases of speech, language, and hearing. To manage the content of this book more easily, the chapters have been grouped into four principal sections, with each section providing a piece of the grand puzzle. The sections of this textbook are: • Section 1:  Neuroanatomical and Neurophysiological Foundations (Chapters 2 through 7) • Section 2:  Sensory Systems (Chapters 8 through 12) • Section 3:  Motor Systems (Chapters 13 through 15) • Section 4:  Neural Substrates of Speech, Language, and Hearing (Chapters 16 through 18) It is always a good idea to get a feel for the proverbial “forest” before you go hiking through the trees. As such, what follows is an overview of each section’s chapters, including their general content and a brief rationale for inclusion of specific material in the book.

Overview of Section 1:  Neuroanatomical and Neurophysiological Foundations Chapters 2 through 7 in Section 1 form the backbone of the text and the essential content that will be needed to navigate the remaining sections of the book. As alluded to earlier, the book was written intentionally as a story that builds your understanding of the nervous system from one chapter to the next. Chapter 2 is designed to introduce you to the cast of characters — the cells of the nervous system. In Chapter 2, you can expect to learn a little bit about the history behind the discovery of the two major classes of cells in the nervous system: the neuron and glial cell. I also introduce you to the conceptual idea that while the neuron is the basic structural unit of the nervous system, what constitutes the basic “decision-making” unit are collections of interconnected networks of neurons, a concept known as population coding. While Chapter 2 introduces you to the structure and form of the neuron, the next chapter is designed to teach you how neurons functionally communicate with one another. In Chapter 3, we will cover the fundamental nature of neural signaling and signal transmission between neurons. Chapter 3 was prepared to carefully walk you, step-by-step, through the necessary concepts of electricity, driving forces, electrical potentials, ion channels, neurotransmitters, and

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signal integration. The reason behind the inclusion of these more abstract concepts in Chapter 3 is to help you develop a deeper and more intuitive appreciation for the physical and chemical mechanisms behind why neurons work the way they do. Neural signals, both electrical and chemical, represent the real-world “information” that is processed and managed by the nervous system. Understanding the essentials of neural signaling will form a foundation that will allow you to appreciate how the nervous system develops its capacity to learn, feel emotions, think, and perform any behavior you could possibly imagine. (Note: Chapter 3 is one of those more detailed and abstract segments of the textbook mentioned earlier. The chapter discusses topics that you are likely not familiar with or never imagined you would have to learn as a CSD student. But don’t let that be off-putting. If the details begin to overwhelm you, simply concentrate on the “big” conceptual ideas that are discussed. Having a general appreciation of neural signaling is what is ultimately important to walk away with.) Once we’ve completed our tour of the neurobiology of the neuron, the next step is to move quite a few levels of analyses upward to start learning about the gross anatomical and functional features of the mammalian nervous system. I use the term “mammalian” on purpose because much of what we know about the human nervous system comes from decades of careful and painstaking research in animal models. Animal studies have been and continue to be a critical means through which we discover and explain the operation of the nervous system in both healthy and disordered human populations. In Chapters 4 through 7, you will learn about the structural organization of both the peripheral and central nervous systems and gain an appreciation for their general functions. It is important to spend as much time as needed to internalize the material in these chapters because they form the basic gross neuroanatomy that is consistently referred to in all subsequent sections of the textbook. In fact, these are four chapters you will want to bookmark for easy and quick referencing as you proceed through the remaining parts of the book. Briefly, Chapter 4 begins by introducing you to (a) some essential neuroanatomical nomenclature, (b) terms of direction and orientation, and (c) a short discussion on the embryology of the nervous system. Following this material, gross neuroanatomy and function of the spinal cord and brainstem is presented. Chapter 5 provides you with a comprehensive overview of the structure, function, and assessment of the cranial nerves. Learning the cranial nerves well should be a key goal of yours. Readily accessible knowledge of the structure, function, and assessment of the cranial nerves is a critical skill to have in your CSD toolbox. Chapter 6 continues our neuroanatomical and functional tour of the nervous system. This chapter can be separated into two major topical areas: gross neuroanatomy and a description of the functional features of the cerebrum and cerebral cortex. Topics discussed include the diencephalon, cerebral lobes, primary and integrative processing zones of

CHAPTER 1   Introduction and Organization of Neuroscience Fundamentals in Communication Sciences and Disorders

the brain, the emotional and autonomic systems of the nervous system, and fundamental ideas related to cortical information processing. Lastly, Chapter 7 provides an overview of the brain’s critical support infrastructure. In this final chapter of Section 1, the white matter connections that functionally interlink different areas of the central nervous system are described along with the protective connective tissues of the nervous system and the brain’s blood supply. The chapter concludes with a brief overview of some major characteristics related to select forms of brain injury. In summary, Section 1 can be thought of as forming a core reference for the rest of the textbook. I will refer you back to the chapters of Section 1 from time to time so that you can review and remind yourself of different concepts, functions, and pieces of neuroanatomy when needed.

Overview of Section 2:  Sensory Systems Section 2 builds upon your neuroanatomical study and delves into the structure and function of the major sensory systems of the body: somatosensation, hearing, vision, smell, and taste. Obviously, hearing is a critical sensory stream for speech and language perception and production, but it’s not the only sensory input that has importance in CSD applications. Somatosensation is an almost equal partner to hearing for our ability to learn and produce speech — a fact that we can directly attest to after going to the dentist and trying to speak after our lips and tongues have been fully anesthetized! Tactile and proprioceptive signals arise from our articulatory behaviors and provide key sources of sensory feedback related to articulator motion and position. When we speak, we use the synchronous production of tactile (touch-related) and hearing inputs created by our own speech to monitor and regulate our production. Vision may not come readily to mind as an important sensory input for speech and language, until you remember that part of language expression and reception is based on one’s ability to read and write. Reading and writing are major sources of language input and output, requiring activity of visual brain regions and their connections to the semantic and phonological cortical networks underlying language-​ related behaviors. Vision also comes into play when observing facial gestures and body posture as part of the communication event. Visual appreciation of facial gesturing is a complementary signal to speech and language that adds greater meaning to our words by modifying the original intent of the speaker and providing crucial extra-linguistic information. The other sensations that probably don’t quite make it onto your radar related to CSD are smell and taste. But remember that two important aspects of our scope of practice in CSD are swallowing and dysphagia. Taste and smell, along with tactile sensation, are three key sensory inputs that profoundly influence our appreciation of food and our ability to manage nutritional intake effectively. Taste and smell are necessary for perceptual enjoyment and appreciation of the

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foods we eat. Tactile sensation is related to several aspects of swallowing, including our ability to (a) detect food textures, (b) manage chewing and food manipulation in the mouth, and (c) elicit reflexive components of swallowing. Chapter 8 begins our exploration of sensory systems with a general introduction to global aspects of sensation and perception that are applicable to all forms of sensory input. Following this introductory material, Chapter 9 is devoted to the structure and function of the somatosensory system. The somatosensory system, unlike other forms of sensation, is not defined by a single type of input, but rather comprises a diverse set of sensations that provides critical information regarding the state of the body within an environment. Somatosensory sensibilities include those related to touch, proprioception (knowing where your body is in space as you’re moving), temperature, and pain responses. Following our somatosensation discussion, Chapter 10 explores the peripheral processes involved in hearing. Presentation of the auditory system in this textbook is divided into two separate chapters: Chapter 10 covers the transduction mechanism of hearing, and Chapter 18 describes the central neural elements of hearing. In Chapter 10, the principal focus is on the neural mechanisms of sound transduction in the cochlea — the critical electrochemical events that begin the transmission of auditory inputs to the brain. Also included in Chapter 10 is a brief overview of the neural mechanisms underlying our vestibular or balance sense. The visual system takes front and center stage in Chap­ ter 11. This chapter provides you with an overview of the peripheral and central neural elements related to vision, beginning with the anatomy and structure of the eye, with specific emphasis on the retina — the chief transduction site for light. We discuss the operation of rods and cones — the phototransducing cells of the visual system. Also described are some of the early information processing events that fall out of retinal activity. The outcome of these retinal events become the signals that are transmitted to the occipital cortex and the primary visual areas. Along the way you will learn about (a) key central visual elements, (b) visual field organization, and (c) two grand visual processing pathways that allow us to perceive object motion, recognize and categorize objects, and aid in our appreciation of how our own bodies interact with objects that we see around us. Lastly, in Chapter 12, my colleague Dr. Nicole Etter (Penn State University) and I discuss the olfactory (smell) and gustatory (taste) systems. Our chapter explains the mechanisms underlying our capabilities to detect the concentration of chemicals in the air we breathe and within the foods and substances we eat. The transduction of chemical signals is a marvelously interesting and nuanced system that leads to our perceptual appreciation of chemically based environmental inputs. These inputs have direct access to fundamental regulatory and emotional regions of the nervous system. If you have ever wondered why the smell or taste of something can transport you to a different time and place in your past, this

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chapter will help satisfy that curiosity. We close out this final chapter of Section 2 with an overview of the essential neural elements underlying feeding and swallowing, an appropriate end to a chapter devoted to smell and taste.

Overview of Section 3:  Motor Systems Having covered the basic properties of sensory systems, our next major goal is to understand the nature of movement itself, or what we technically refer to as motor control. In Sec­ tion 3, our central goal is to develop a basic understanding of the anatomical elements, neural mechanisms, and theoretical underpinnings of our ability to perform actions. Movement, by many theoretical accounts, is at the core of our ability to seek out, discover, and learn about the world in which we inhabit. Movement functions hand-in-hand with sensation, operating as the means through which we manipulate our body’s sensory endings and explore our local environment. As you will see in the chapters comprising Section 3, movement and sensation are intrinsically coupled and linked, with one aspect not able to fully function well without the other. In the first part of Section 3, Chapter 13 provides an overview of the form and nature of muscle tissue. This chapter was written with my research colleague, Dr. Tim Butterfield, a highly respected exercise scientist with deep expertise in muscle physiology in both human and animal subjects. The beginning of Chapter 13 introduces you to the basic macro and molecular structure of muscle tissue. We then discuss, in a broad manner, the role that the molecular players have in generating muscle contraction and developing tension. With this knowledge in hand, we lastly discuss general metabolic principles operating in the muscle cell and the way the nervous system controls our muscles during performance of an action. Like Chapter 3, this chapter has been prepared to walk you step-by-step through the more abstract sections of the material. Again, if the details get to be too much, then the important things to take away from this chapter are the grand overviews and concepts. You may be asking, “What is the point of an entire chapter on muscle tissue in this kind of book?” The answer is quite simple: If you stop and consider what tissues comprise articulatory systems of the vocal tract, you quickly realize that muscular tissues predominate all these systems. Understanding muscle tissue form and function is critically important given that many treatment approaches across a variety of communication disorders use motor control tasks to accomplish their basic therapeutic goals. Not being aware of muscle structure and its functional mechanisms is akin to a medical doctor who can treat you for a cold or flu symptoms but knows nothing about the underlying bacterial and viral causes of these conditions. (I’d likely be looking for another physician very quickly.) Next, Chapter 14 will cover the central motor control areas of the nervous system, which include the primary motor

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cortex, the premotor cortex, the supplementary motor area, and the cingulate motor regions. Together, these structures form the core destinations for sensory, cognitive, memory, and emotional signals related to movement and performance. Following this material, I discuss the operation of systems that indirectly influence movement through their connections with frontal lobe structures. These systems include the basal ganglia and the cerebellum. Lastly, I will introduce and broadly cover the segment of the nervous system that is responsible for unconscious homeostatic regulation of the body: the visceromotor system. Finally in Chapter 15, you are presented with a conversational account of the theoretical principles underlying movement and motor control. This is a unique chapter in that its goal is to set the idea of movement and action into a grand context of behavior. Because one of the goals of this entire book is to emphasize the nervous system’s role in behavior, the inclusion of this chapter seemed like a natural fit. The chapter is coauthored with Dr. Patrick McKeon, a highly respected athletic trainer and exercise physiologist from Ithaca College. The chapter takes you on a tour of the history and logical theory underlying motor control, beginning with Plato and Socrates and taking you through modern-​day revolutionaries in motor control such as Charles Sherrington, Nikolai Bernstein, and Esther Thelen. This chapter places the more concrete aspects of movement and performance into the grand scheme of skill acquisition and sensorimotor learning.

Overview of Section 4:  Neural Substrates of Speech, Language, and Hearing Section 4 is the cumulative segment of the textbook, where we synthesize all the previous content and place it firmly into the context of speech, language, and hearing. Each of the three chapters in this section is authored by a colleague who is a leading authority in their area of research and teaching. Chapter 16, “Neural Substrate of Speech and Voice,” is written by Dr. Stephen Tasko. Dr. Tasko is a leading figure in the area of speech kinematics, measures of speech intelligibility, and stuttering. In his chapter, Dr. Tasko provides an overview of the neuroanatomic elements specific to speech production and relates these to functional brain systems underlying the sensorimotor control of speech production and perception. In addition, Dr. Tasko reviews critical research models of speech, including a foundational computer-based theoretical model called the Directions Into Velocities for Articulators model of speech, amusingly abbreviated as the “DIVA” model. Chapter 17, “Neural Substrate of Language,” is written by Dr. Jessica Richardson and Dr. Sarah Grace Dalton. Drs. Richardson and Dalton are part of a new group of scholars using advanced brain stimulation and imaging technology to investigate the treatment of patients who have suffered strokes and are left with severe language impairments called acquired aphasias. In their chapter, Drs. Richardson and Dal-

CHAPTER 1   Introduction and Organization of Neuroscience Fundamentals in Communication Sciences and Disorders

ton discuss a range of topics from the evolution of language to recent evidence in language development in infants, to current models of language production. In addition, the authors provide an overview of the cortical language-related areas and explain the interconnections and operations of these zones for semantic, syntax, and morphological purposes during language production. Lastly, Chapter 18, “Neural Substrate of Hearing: Central Auditory Pathway and the Auditory Cortices,” is written by Dr. Anne Olson, a research audiologist and a leading authority on principles of auditory rehabilitation. In her chapter, Dr. Olson discusses and teaches you about the central auditory pathway, its structure, connectivity, and function. The central auditory pathway elements include those that are beyond the cochlea and extend into the brainstem. At the pinnacle of this pathway are the primary auditory cortex and associated cortical areas related to hearing, the cerebral areas that initiate the sound processing underlying speech perception, and receptive language abilities. Beyond central auditory pathway operations, Dr. Olson also discusses the mechanisms for sound localization, binaural integration of sound, and the abstraction of auditory nerve signals from the cochlea that serve as the foundational inputs for later sound perception. Topics related to assessment methods, such as the stapedial reflex, otoacoustic emissions, and the auditory brainstem response, are briefly discussed at the conclusion of her chapter.

Study Strategies and Tips Let me offer several study ideas and strategies that I’ve used with my students during years of teaching communication neuroscience courses at my university. These are simple, but effective, strategies that will help you better manage and internalize the course content and the material in this book. • Make a habit of reading the pages and chapters assigned to you by your professor before class time. It is much easier paying attention to your professor if you have some basic familiarity with what he or she is discussing that day. • Use active reading strategies when working through each chapter. By active reading, I mean the following: Handwrite notes while reading either on a separate sheet of paper or in the margins of your textbook. Highlighting is fine, but I often find that students tend to highlight excessively to the point where the highlights stop being selective. Active notetaking is a far better strategy that forces you to encapsulate segments of the material you are reading into self-​ contained bulleted points. • At the end of every reading assignment, summarize your written notes into paragraph form, making sure

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to briefly cover all key points. Keep the summaries succinct and efficient. These represent an important tool that can be used later to study for major exams. • Merge and integrate your active reading notes with your class lecture notes. In this manner, you will be forcing yourself to review class notes with frequency and in some detail to find the best location to integrate and interleaf your reading notes. To help facilitate this strategy, use loose-leaf paper and a binder to store all your notes. Binders make it easy to slip in additional notes or add graphics, handouts, and other materials at just the right point in your lecture notes. Binders also allow you to reorganize your notes and materials in different ways to emphasize certain relationships over others. For example, you could organize your notes by systems on one occasion and by function on another, depending on your needs. The greater number of ways you can re-categorize the information you are learning, the greater the likelihood of you developing a lasting memory of the content’s detail. • Seek out ancillary information from other sources and locations if something you are learning and reading about is not making sense. Each chapter in the text is heavily referenced with primary journal articles, lots of review papers, and book chapters. Use these references as an important resource for gathering additional information. • Develop study groups to help quiz one another and fill in pieces of information from lectures or readings you may have missed. Plus, study groups make the process of learning much more fun and social as well. • Use the flashcards on the PluralPlus student website to quiz yourself and practice terminology. • Draw, draw, draw! I cannot emphasize enough the importance of making up your own sketches, drawings, and flowcharts to help make the material more salient to you. The textbook is heavily illustrated for a reason, and that is to help translate the text into visual representations of the book’s content. For your part, resketch or redraw simpler versions of the book’s illustrations directly into your notes. You don’t have to be a Leonardo da Vinci or Salvador Dali to make use of this strategy; any sketch you can appreciate will do perfectly well. • Use the unlabeled figures that come bundled with this textbook to practice anatomical labeling. These unlabeled figures are found on the PluralPlus student website. • As you read through the book, you will quickly discover that I love making up silly analogies to help drive home concepts and ideas. Make up your own analogies and real-world examples to help you remember the material as you study. Connecting new

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Neuroscience Fundamentals for Communication Sciences and Disorders

information to something relevant and accessible to you is a terrific means of internalizing complex ideas. An analogy is effective if you can use it on someone naive to the course material and he or she can understand the intended concept. • Pace yourself by trying to study the material in this book every day to keep all the concepts and terms fresh in your mind. Trust me, it will be difficult to cram in all this neuroanatomy and neurophysiology a few days before a major exam. Schedule a block of time each night to review your notes and the readings associated with the day’s lecture material. Rereading sections and chapters will be necessary to fully integrate your classroom work with the content of this book. Textbooks are meant to be read and reread many times. The effort you put into this strategy will pay off and translate into better course material retention and understanding. • Lastly, go and grab yourself a package of miniature sticky notes and use them to bookmark figures in each chapter. The figures in this textbook are an important and valuable resource that were carefully designed to help bring the text-based material of the book to life. Using these illustrations is a critical teaching tool that will greatly expand your appreciation of the book’s content. When bookmarking a figure, label the sticky note with a short tag or note so you can quickly identify it later. Organize your sticky note bookmarks by alternating their placement along different book edges for different chapters. For example, if bookmarking figures in Chapter 2, place your sticky notes along the top edge of the page, while for figures you mark in Chapter 3, place the sticky notes along the side edge of the page. Another strategy to help organize your bookmarks is to use different colored sticky notes for specific chapters. In short, anything you can do to make finding a bookmarked figure easy and quick will be of benefit to you when studying. I personally use this bookmarking method when I’m studying and using materials with illustrations in the course of my own academic work. It works beautifully! Go ahead and give it a try for yourself.

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Closing Thoughts With a rationale for why neuroscience training is important in CSD, a broad overview of the upcoming chapters, and some useful learning strategies, you are now ready to begin your course of study. Here are a few last reminders and suggestions before you begin tackling the material. • First, a fair amount of memorization of terms, labels, and figures is a necessary evil for content of this type but remember that memorization is just the first step in your training and learning. You must go beyond memorization and work to integrate the different elements of the system you are currently studying. Integration will allow you to see how the elements work together and interact as a dynamic system to generate a functional outcome. • Second, because the book is written in a cumulative style with one chapter building upon what has come before, review past material before and while you are learning about something new. The book is best used and your study best served if you make it a habit of going back and forth between current and related past sections and figures. The more cross-links you can develop among the chapters, the more deeply you will internalize the material. • Next, use the study tips that I outlined earlier. They are strategies that I have used successfully with my own students. They really do work! When all is said and done, let yourself enjoy and truly become fascinated by what you’re learning. Remember, you are learning about the single most complicated and remarkable biological system in the known universe — the human brain and nervous system. You will be learning about a structure that has composed symphonies and created jazz, produced amazing works of visual art, written books that have captured the human imagination and changed the course of history, built machines that have taken us to the stars, and dreamed about the marvelous possibilities of human existence (Figure 1–1)!

CHAPTER 1   Introduction and Organization of Neuroscience Fundamentals in Communication Sciences and Disorders

 FIGURE 1–1.   The power of imagination: The creative and analytical human brain.

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CHAPTER 2 Basic Structure and Function of Neurons Richard D. Andreatta Introduction and Learning Objectives

evaluate new therapy approaches based on neuroplasticity. Why? Because understanding the adaptability and plasticity of the brain (how it changes structurally and functionally) is all about understanding how neurons change their own structure and function with experience and practice. The advancements in cellular neurobiology of the nervous system since the early 20th century have led to an explosion in knowledge about the role that nervous system cells have in the complex creation and expression of animal behavior. We now understand that actions, thoughts, perceptions, remembered experiences, emotions, and virtually everything about who you are as an individual or have ever experienced in your lifetime are rooted in the cooperative activity of vast interconnected networks of cells throughout the nervous system. Additionally, our understanding of the cellular bases of complex disease states and debilitating neurological disorders has expanded to a point where neuroscience is on the threshold of finding effective therapies for conditions such as Alzheimer’s and amyotrophic lateral sclerosis (Lou Gehrig’s disease). The cellular structure and function of the nervous system is thus a crucial body of knowledge to appreciate the operation of the nervous system and the fundamental bases of behavior more fully. I hope I’ve convinced you, or at least begun to persuade you, to take the time to learn about these basic cellular principles. The time and effort you spend learning about these ideas will be well worth it as we go forward and discuss other more complex features of the nervous system. In this chapter, we focus on the cytology of the neuron: the historical foundations leading to the discovery of this cell type, its general role in behavior, and its basic structure. After completing this chapter, you should be able to meet the following learning objectives:

Chapter 2 and the one that follows focus on the structural and general functional factors characterizing the cells of the nervous system. While this topic may seem far removed from speech pathology and audiology, the reality is that an intuitive understanding of basic neurobiological principles and processes will allow you to more fully appreciate how major functional activities of the nervous system, such as motor control and perception, operate. Putting on my “Mr. Obvious” hat, speech, language, and hearing (S-L-H) all require the operation of the brain. Performing these behaviors adaptively to support human communication requires the coordinated activity of numerous brain regions under­ lying cognition, emotion, movement, and sensation. While it might seem satisfactory to simply know the major anatomical regions of the brain operating during S-L-H behaviors, it shouldn’t be satisfactory to you at all. We are living in an era where advancements in our appreciation of the brain’s functionality, its interconnectivity, and its adaptability are growing at an astoundingly rapid pace, with the majority of these leaps occurring in our understanding of the microstructure of the brain. The operation of the nervous system as a whole, or what we generally describe in this textbook as “behavior,” is based on the collective and cooperating function of tens of millions of individual cells. Without an introduction and basic foundation in cellular neurobiology (a complex-sounding term that simply means the study of how nervous system cells work), you will be left wondering why and how brain regions communicate with one another to produce their associated behavior or how these same areas change their actions in light of rehabilitation after injury or disease. Here is just one example and justification for why it’s worth your time to learn about the neurobiology of the nervous system. In recent years, the term “neuroplasticity” has become a popular buzzword in the media to describe a growing number of commercial products and apps that supposedly allow you to change your brain. Coincidentally, a number of therapeutic techniques, complete with manufactured items you can purchase for a hefty sum of money, are also being developed and sold claiming to be based on the science of neuroplasticity. As a future rehab specialist in S-L-H, one of your key responsibilities will be to select appropriate and scientifically valid treatments for your clients/patients. Without a good appreciation of the neurobiology of the brain, you simply won’t have the knowledge and tools needed to independently

• Explain the history behind the discovery of the neuron as the essential anatomical building block of the nervous system. • Identify and describe the functional roles of different structural features of the neuron. • Understand and explain the concept of population coding and how this mechanism helps form the decision-making unit of the nervous system. • Understand and explain the significance of the dendrite/soma–axon–dendrite/soma organization of information flow between connected neurons. • Apply knowledge of a simple reflex circuit to your understanding of how neurons work cooperatively to perform a behavior. 13

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• Identify and define the physical structural features of a neuron and glial cells. • Describe the function and structural features of major neuronal organelles. • Explain the basic steps in gene expression (transcription and translation).

Discovery of Two Classes of Cells in the Nervous System The idea that tissues of the body are made up of individual units called cells seems remarkably obvious and a rather mundane fact by today’s standards. But it has been only in the last 200 years (give or take a couple of decades) that our understanding of the cellular organization of life has even formally existed. The cell doctrine, the notion that animals are comprised of small components called cells, was developed only in the early part of the 19th century. A little-appreciated fact about this doctrine, though, is that it was thought to apply to every part of the body except the nervous system. The exclusion of the nervous system from the cell doctrine had much to do with the lack of experimental methods to visually identify the complex structure of nerve cells in their entirety in living tissues. In fact, it took until the turn of the 20th century for neurobiologists to finally develop the methods needed to confirm that the nervous system, like all other parts of the body, is made up of individual cellular units. This accomplishment was by no means trivial. Realizing that the brain and the nervous system are comprised of cells just like all other regions of the body began the era of neurobiological study in which we find ourselves today. We can thank three influential neurobiologists — Camillo Golgi, Santiago Ramón y Cajal, and Charles Sherrington ​— ​ who together were largely responsible for the needed technological advancements in nerve cell histology (microscopic study of tissue structure) that eventually spring-boarded the field into a new era of understanding. Golgi and Ramón y Cajal were chiefly responsible for the development of novel methods to stain or dye nerve cells to reveal their complex shapes and extensive branching. Before these stains existed, the internal structure of the nervous system was a complete mystery because of the visual uniformity of brain tissue (a generally cream-colored and beige-looking tissue with the consistency of loose Jell-O) and the inability of rudimentary microscopes of that era to focus clearly on cells with little image contrast. Imagine the excitement of early investigators upon seeing for the first time, through the use of newly developed staining techniques, the enormous complexity and diversity of nervous system cells! Neurobiologists at last had the ability to identify not only the form of nerve cells, but by using different types of staining methods, to also identify intracellular structures. Thus, the histological methods created by these

SECTION 1

and other early neurobiologists helped to establish critical distinctions both structurally and functionally between cells of the nervous system and any other cell type in the body. This early histological work led to the discovery that the nervous system is comprised of two distinct families of cells: neurons and glial cells (Kandel, Barres, & Hudspeth, 2013). If the different parts of the nervous system were a cast of performers in a Broadway musical, neurons would definitely be the stars of the show, the divas that get all the attention and get to sing the best songs. Glial cells, on the other hand, would be the members of the stage crew, working behind the scenes backstage trying to keep everything running smoothly. Neurons (also called nerve cells) are highly excitable cells capable of generating and transmitting electrical signals over a wide range of physical distances. When I say “electrical signals,” I literally mean the same general form of electricity that runs your cell phone, your laptop, and the lights in a room, albeit on a much smaller scale. Neurons are able to change their electrical state rapidly in response to environmental changes. The quick shifting of electrical activity in a neuron is made possible by the presence of specific protein structures on the neuron’s cell membrane that regulate the motion of charged particles, called ions, into and out of the cell (more on this in Chapter 3). In turn, neurons use these rapid electrical changes to trigger the release of chemical agents from within the cell that operate to interconnect neurons with one another to form functional networks (Hall, 1992). The moment-to-moment state and complexity of these networks of interconnected neurons underlie all behaviors that an animal can produce during its lifetime. We can thank the electrophysiological studies of Charles Sherrington for these fundamental insights because his work was central to the discovery of a nerve cell’s communicative abilities at locations called synapses (Kandel et al., 2013). (A little historical fact: Sherrington was the person who first introduced the term “synapse” to identify the physical communication point between neurons.) In short, neurons participate directly in all activities that we would describe and characterize as a “behavior” (Kandel et al., 2013). In contrast to neurons, glial cells don’t directly participate in signaling (the transmission of information from one place to another), but instead form a critical structural, insulating, and metabolic resource for neurons (Allen & Barres, 2009; Guyton & Hall, 2006). A silly way to remember the general role of glial cells is to think of them as packing peanuts or bubble-wrap used to protect and support fragile items when shipping a package. The importance of the structural and supportive roles of glia cells is reinforced by the fact that they outnumber signaling neurons by about 10 to 1. Absolutely astonishing! Even though the recognized roles of glial cells are backstage and not terribly glamorous, without them the show could literally not go on. We’ll elaborate on the functional and structural details of neurons versus glial cells in much more depth in the next few sections of this chapter.

CHAPTER 2   Basic Structure and Function of Neurons

For now, it’s best to appreciate the major distinctions between these two cell classes in the nervous system: Neurons signal information, and glial cells provide structural and metabolic support to neurons.

The Neuron In this next section, we will describe and characterize the major structural and functional features of the neuron. The components we will discuss are key to the way neurons obtain inputs, process information, and share that information with other neurons within highly interconnected collections or networks of cells.

Neurons Are Made for Signaling and Communication A neuron possesses four functional and associated structural zones necessary to fulfill its role in signal propagation (a term that neuroscientists frequently use to describe the sending of information over some distance) and neuron-to-neuron communication. The structural (morphological) features of a typical neuron are (a) the soma or cell body, (b) axons, (c) dendrites, and (d) the presynaptic terminal. As shown in Figure 2–1A, each of the structural features of a neuron is associated with a functional role that allows for the generation of different types of regional signals: an input site (dendrites and soma), a region for integrating (mixing things) the input signals together (axon hillock), a conducting segment (axon), and lastly an output site (presynaptic terminal). Regardless of whether we are talking about neurons that convey sensory or motor signals (Figure 2–1B), these structures and functional roles form the basis by which we can understand how individual neurons operate within the context of larger groups of neurons to generate and change behavior (Carpenter, 1991). Before we start delving into the fine-grain details of neuronal structure and function, it is beneficial to step back and first develop a more intuitive appreciation of how a single neuron’s activity fits into the grand scope of how the nervous system produces the wide range of behaviors animals perform. With this context in place, you’ll be better equipped to connect and appreciate how the finer details of neuronal structure contribute to the production of a behavior.

Neurons Never Function Alone Neurons never work in isolation, but rather are found arranged in functional collections or interconnected populations that share common inputs and outputs. What this means is that a single neuron by itself does not directly produce the types of behavior performed by an animal. Rather, it is a group, or more correctly stated, a population of neurons working

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cooperatively that in reality forms the foundation for all types of sensory, perceptual, motor, cognitive, and emotional behaviors in an animal (Kohn, Coen-Cagli, Kanitscheider, & Pouget, 2016). This notion may seem a little confusing and surprising at first, so here’s a good way of thinking about this idea so it makes more intuitive sense. Imagine a population of neurons as a group of citizens in a country, where each person in the group has the ability to cast a vote on a particular issue. During an election, each citizen can cast a “yea” or “nay” vote for the outcome they would like to see on an issue. All the votes are counted, and the majority vote outcome wins the day. The final action taken on the issue voted upon will be dependent on the sum of all of the votes cast by the citizens. In other words, whether the decision has been approved or rejected is not based solely on a single person’s voting choice, but rather on the collective decision made by ALL the citizens who voted. The “population” of citizens is therefore the basic “decision-making unit” for a democracy. Hopefully, you can see where I’m going with this analogy. Individual neurons (our citizens) are participants in the process of generating a behavior (they can cast a vote either yea or nay), but it takes large numbers of neurons working together in real time to move the needle sufficiently to produce or observe a change in a behavior (output of the entire population of citizens decides the final outcome). In short, when it comes to understanding the neural basis of behavior, it is the activity of populations of neurons that matters the most. Let’s further solidify this idea by walking through a more visual and concrete analogy of what we’ll refer to as the “population response” of a collection of neurons to produce motion in an intended direction. In Figure 2–2, a population of 48 neurons is arranged in a grid of 8 columns by 6 rows. Each box in the grid represents a single neuron. The different heights of the colored cylinders extending out of each box represent the levels of activity for each given neuron. On the front border of the grid’s columns are drawn arrows that point in different directions. The arrows represent the preferred direction of a reaching movement that will be created by the neurons in that column. For example, all the neurons in the first column (far left) will participate in or “vote for” the production of an upward arm motion, whereas the neurons in the third column will participate preferentially in a rightward reaching motion. Neurons in a given column are essentially “tuned” or biased to respond preferentially whenever a person is wanting or intending to reach in the direction indicated by the arrows. If we now take a holistic view of the activity that this specific population of neurons is creating, can we determine and predict the direction of reaching movement that is being coded for by the entire population? Let’s inspect this population’s activity column by column to find the answer to this question. In the first three columns, cell activity for the directions indicated (upward, upper right, and direct right) is variable and relatively low in strength (colored cylinders are short).

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Neuroscience Fundamentals for Communication Sciences and Disorders

A.

Input site

Integration

Conducting region

Axon

Soma

SECTION 1

Output site

Direction of transmission

Axon hillock

Presynaptic terminal (bouton)

Dendrite

Model neuron

Sensory neuron

Motor neuron

B. Input site Integration

Conducting region

Output site

 FIGURE 2–1.   Basic structure and regional function of the neuron. A. A single multipolar neuron is shown synapsing to a target neuron. B. Both sensory and motor neurons possess regional functionalization.

In the fourth column, neuron activity for a right-downward reaching action becomes more consistent and is far stronger, as shown by the increasing heights of the colored cylinders for the neurons in that column. In the fifth column, neuron activity for a downward reach is uniformly strong across all the cells in the column. In the sixth column, neuron activity for a left-downward reaching direction begins decreasing and becomes slightly more variable again. Finally, in the seventh and eighth columns, neuron activity for a direct-left or upward-left reach is very low. The take-home point of this example is that by looking at the whole pattern of activity across all the columns, we can predict that this entire popu-

lation of neurons is coding for a reaching movement that is somewhere in the right-downward to left-downward direction (see red asterisks) (Georgopoulos & Carpenter, 2015). We can make this prediction because the columns that encode right-downward to left-downward directions are the most strongly activated of all the columns (neurons) present. Let’s say that the person performing this behavior suddenly changed his or her mind and decided instead to reach in an upward and right direction. What would happen to the population’s activity then? What you would see is a shift in the population’s response in the following manner: Columns 1 and 2 would suddenly become strongly activated (high cyl-

CHAPTER 2   Basic Structure and Function of Neurons

*

*

*

 FIGURE 2–2.   Schematic illustration of population coding. A collection of 48 neurons, arranged in a grid-like pattern, represents a population of neurons encoding the direction of movement in 360 degrees, as symbolized by the arrows on the front of the grid. Colored cylinder heights represent the relative amount of activation for each neuron in the population. Notice that for motion in the right-downward, downward, and left-downward directions, all cells in those columns are highly active to different degrees. The population of neurons is encoding a specific range of movement direction, as indicated by the columns with the red asterisks.

inder levels), while the neurons in the remaining columns would become far less activated. As such, how a given neuron “votes” and how strongly it produces that vote depends on whether the desired action matches the neuron’s voting preference. Thus, the direction for any given reaching motion depends on which part of the population is the most strongly activated at any instance in time. No single neuron determined this population’s coding for a given direction of reaching motion . . . the neurons worked cooperatively to decide how the animal reached. This example highlights what typically happens when the nervous system is performing and regulating a given behavior, albeit on a much larger scale.

Neurons Perform Fundamental Activities Interconnected groupings of neurons go by several interchangeable terms including neural ensembles, neuronal groups, neural networks, and/or neural circuits. Although neural networks vary in size, complexity, and the function being served, they share a common operating plan or strategy. This operating plan ensures that information is distributed among members of the network in such a way as to give each cell an opportunity to “weigh in” or vote on the final form

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of the output being cooperatively created by the population of cells. Regardless of the form and functionality of a given neural network, each participating neuron within the network must perform three fundamental activities to ensure the effective distribution or sharing of information throughout the network: Neurons must receive an input, integrate that input, and form an output to a target (Kandel et al., 2013; Vanderah & Gould, 2010). To satisfy the first activity, neurons must receive an input from other cells at locations such as the dendrites and the soma. Neurons can also receive inputs from real-world signals associated with stimulation from the environment. The nature of these inputs can vary greatly but are generally categorized into those that increase and those that decrease the operation of the neuron. Generally, inputs that increase cellular activity in a neuron are characterized as excitatory in nature, while inputs that decrease cell activity are described as inhibitory. Excitatory inputs typically drive neurons to boost their signaling output and increase their influence on the operation of the neural network. Inhibitory inputs have the opposite effect, making the neuron less likely to participate in the population’s work during behavior. The second fundamental activity of a neuron is that it must take the sum total of the inputs it receives (excitatory and/or inhibitory) and integrate or “mix” them together to generate an overall change in the baseline or resting electrical state of the neuron. All neurons have a “resting” electrical state that they maintain when quiet and not activated. Changes in the neuron’s baseline or resting state are key to creating many different types of neural signals, each contributing in a unique way to the overall function of the cell (Hall, 1992). One of the most important neural signals generated by the neuron is called the action potential. The action potential is initiated at a highly specialized region of the neuron called the axon hillock, located at the point where the axon emerges out of the soma (see Figure 2–1). The axon hillock is responsible for monitoring changes in the electrical state of the neuron’s cell body. If these changes are great enough and of a certain quality, the axon hillock triggers the generation of the action potential. Action potentials are the signals that allow the brain to convey information throughout a network of neurons. Without action potentials, there is little effective communication possible between neurons. To satisfy the third factor, the newly generated action potential must propagate or transmit down an axon to activate the neuron’s communication system located in a region of the axon called the presynaptic terminal. Activation of the presynaptic terminal kick-starts a series of chemical activities that will lead to an output event that is passed along to the input site of the next neuron in the neural network. When you link these three fundamental activities, what arises is a basic organizational scheme for information flow: dendrite (or soma)–axon–dendrite. This organization is a key factor in understanding how neurons arrange themselves into functional populations and fits well with the functional

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Neuroscience Fundamentals for Communication Sciences and Disorders

specialization of each region of a neuron (see Figure 2–1A for examples of what this basic scheme looks like). Understanding this basic connection scheme between neurons will go a long way toward helping you appreciate how neural signaling arises and how information is shared throughout a population of neurons. This specific topic will be covered in detail in the next chapter.

Reflexes Provide a Window Into the Fundamental Operation of Neural Networks While neural networks can consist of thousands to millions of neurons, regardless of their size, they all operate in a fundamentally similar manner. Because of this fact, we can use a very simple neural network consisting of just two neurons to help us understand the essence of neural network function. For this example, we’ll use part of the circuitry of a reflex response we are all familiar with if we’ve ever had a physical exam by a physician: the knee-jerk response (Purves et al., 2018). Illustrated in the top panel of Figure 2–3 is a schematic view of the two-neuron pathway that mediates the essential component of your knee-jerk response. To keep things simple and straightforward, in this illustration, only the main segments of the neural circuit that activates the extensor muscle of the thigh are visible. As illustrated in Figure 2–3, the neural network (or in this case a neural circuit) for the knee-jerk response begins with a stretch-sensitive sensor called a muscle spindle embedded in the quadriceps tissue of the thigh. The muscle spindle has an axon (see the red neuron labeled A) that leaves the quadriceps and makes its way into the spinal cord (represented as the round slice of tissue on the right side of the top panel). In the spinal cord, the sensory axon coming from the muscle spindle connects to or synapses onto a class of cell called a motor neuron (see the blue neuron labeled B). The motor neuron, in turn, projects an axon out of the spinal cord that extends all the way back to the quad muscle of the thigh. The activation or excitation of the motor neuron is responsible for triggering a brief and small contraction of the quadriceps, ultimately causing the lower leg to rapidly extend outward in the direction of the arrow. Given this anatomical description of the knee-jerk response’s neural circuity, let’s walk through the functional operation of this simple circuit using the bottom panel of Figure 2–3 as a guide. In the bottom panel of Figure 2–3, the knee-jerk reflex circuit has been laid out linearly. Above the illustrated sensory and motor neurons of the neural circuit are depicted the different forms and types of signals generated by each of the four functional regions (input, integration, conduction, output) of the neurons shown (see Figure 2–1). The muscle tissue of the thigh is also shown at the far right with its corresponding signals above it (muscle tissues are also excitable and behave similarly to neurons). The reflex response is initiated by strik-

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ing the patellar tendon of the quadriceps with a mallet. This action causes a small and quick stretching of the tendon that then stretches the thigh muscle to which it is attached. The ensuing stretch of the quad muscle is encoded or “detected” by the stretch-sensitive muscle spindle, causing a change in the electrical resting state of the embedded sensory neural ending (labeled as receptor potential in the bottom of Figure 2–3). If the tap is strong enough, it triggers an action potential at the axon hillock of the muscle spindle that then travels along the length of the sensory axon into the spinal cord. The action potential reaches the end of the sensory axon where the release of a chemical neurotransmitter from the presynaptic terminal is triggered. At this point, the synapse or connection between the sensory and motor neuron is activated. The neurotransmitter released by the presynaptic terminal of the red sensory neuron initiates electrical changes in the dendrites of the blue motor neuron (the postsynaptic cell), resulting in a change in the electrical resting state of the motor neuron itself (labeled as postsynaptic potential in Figure 2–3). Similar to the sensory neuron, if the motor neuron experiences a change of sufficient strength in its electrical state, it will create its own action potential that then travels down the axon of the motor neuron toward the quad muscle of the thigh. The axon of the motor neuron synapses onto the muscle tissue and forms the connection that is responsible for altering the electrical resting state of the muscle. (Can you detect a theme emerging from these descriptions?) Muscle cells, like neurons, are excitable and require a driving input via a synaptic structure called the neuromuscular junction (NMJ) to generate a contraction. The motor neuron releases a neurotransmitter that causes excitation of the muscle tissue and triggers the muscle cells to contract, causing a quick extension of the lower leg (the observable response). Phew! Did you expect that the process of creating a knee-jerk response would be comprised of so many steps? What have we learned through our discussion on neural networks and the knee-jerk response about the fundamental operating principles of the brain? First, and most critically, generating a behavior (or making a change in one) depends on a population of interconnected neurons working cooperatively to shift the balance of neural activity in any appreciable way (Kandel et al., 2013; Purves et al., 2018). Second, individual neurons comprising a neural network all share a similar functional and structural organization. Finally, there are three basic factors at play in the neural control of behavior: an input from another neuron or the outside world, integration and communication of electrical and chemical signals, and motor output (Kandel et al., 2013; Purves et al., 2018). Through the use of a straightforward analogy on how neural populations are organized (review the voting and population analogy provided earlier) and how the knee-jerk response is anatomically structured and functionally generated, you’ve actually learned a great deal about the fundamental operations of the nervous system thus far. Now that we have a more intuitive appreciation of how neurons generally fit into

Muscle stretch sensory receptor Quadriceps (extensor) muscle

A

Sensory (afferent) axon

C

B Motor (efferent) axon

A. Sensory Input

Stimulus

Receptor potential

Integration Action potential triggered

Conduction AP passes down axon

B. Motor Output

Input

Integration Conduction

Transmitter is released from presynaptic terminal

Postsynaptic potential is created

Action potential triggered

AP passes down axon

C. Output Action Output

Input Integration Conduction Output

Transmitter is released Synaptic potential in muscle

Synaptic potential triggers excitation of muscle cell

Muscle contracts

Muscle Stretch

Sensory neuron

Motor neuron

Contraction

 FIGURE 2–3.   Knee-jerk reflex circuit. Top panel: A simplified version of the knee-jerk reflex circuitry. The red neuron depicts the sensory arm, while the blue neuron represents the motor arm of the circuit. The reflex circuit is activated through a mechanical tap to the patellar tendon that in turn creates a rapid stretch of the thigh muscle. This muscle stretch is encoded by a stretch-sensitive sensory ending, triggering activation of the reflex circuit. Bottom panel: The knee-jerk circuity is laid out horizontally with corresponding representations of electrochemical activity that occurs at different locations along the pathway (see red, blue, and yellow shaded boxes). 19

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Neuroscience Fundamentals for Communication Sciences and Disorders

the grand scheme of the nervous system’s ability to produce a behavior, let’s turn our focus back to the details of neuronal structure and function.

SECTION 1

the bipolar cell is called the pseudounipolar type. This variant is a cross between the unipolar and the bipolar cell shape. Pseudounipolar cells have a single, very short projection from the soma that quickly divides into two segments that pro­ ject in opposite directions. The sensory nerves that transmit touch from the skin into the nervous system are comprised by this class of cell. The last group is the multipolar cell type. This type of cell has one major extension that operates as the axon and output site, and many smaller extensions emerging from the soma that operate as the input locations or dendrites of the cell. The multipolar cell type is the shape of a neuron that most students envision when thinking about what a typical neuron might look like. Aside from these structural or morphological categories, neurons can be functionally characterized into afferent neurons, efferent neurons, and interneurons (Carpenter, 1991). Afferent or sensory neurons are those that carry neural signals toward the central nervous system. The signals carried by afferent neurons are used for developing a sensory perception or for providing feedback to motor control regions of the nervous system. Efferent or motor neurons transmit neural signals from the brain, spinal cord, and brainstem to muscle tissues and glands of the body. Efferent signals are responsible, to a large degree, for generating muscle contractions and the release of substances from glandular tissues. The functional grouping known as interneurons can be thought of as cells that help interconnect different regions of the brain,

Nerve Cells Have Different Shapes, Sizes, and Functions Aside from developing histological methods to visualize neurons, Ramón y Cajal was also the first to appreciate that neurons could be sorted into three distinct morphological (structurally defined) groups: unipolar, bipolar, and multi­ polar cells (Bear, Connors, & Paradiso, 2016; Schwartz, Barres, & Goldman, 2013). As illustrated in Figure 2–4, the main factor that determines the classification type of a neuron is the number of cytoplasmic extensions or “branches” that come out of the soma or cell body. Unipolar cells have just one main projection from the soma, with smaller branches extending off this main trunk. Typically, the smaller branches operate as the dendrites or input sites and the larger projection operates as the axon. We find unipolar cell types mostly in simpler nervous systems, such as those of invertebrates like squids and worms. Bipolar cells have two projections typically arising from opposite sides of the soma. Each of the two projections operates as either a dendrite or an axon. A prominent location for bipolar cells in the nervous system is in the retina of the eyes, as we will explore when we discuss the visual system. A variant of

Dendrites

Dendrites

Dendrites Soma

Peripheral Axon

Axon

Cell body (soma)

Dendrites

Axon presynaptic terminals

Unipolar Invertebrate neuron

Central Axon

Bipolar Retinal ganglion cells

Cell body (soma)

Cell body (soma)

Axon

Axon presynaptic terminals

Pseudounipolar Tactile primary afferent of spinal & trigeminal nerves

Multipolar Motoneuron

 FIGURE 2–4.   Neurons are classified based on the number and complexity of processes that extend from the cell’s soma. The four different cell forms shown include the unipolar, bipolar, pseudounipolar, and multipolar cell types.

CHAPTER 2   Basic Structure and Function of Neurons

spinal cord, and brainstem. In other words, interneurons (as the name implies) are go-betweens that connect one neuron to another. Interneurons are by far the most numerous functional cell type and can link neighboring areas via short axon connections or connect regions of the nervous system that are widely spread apart using longer axons. In summary, afferent neurons bring information into the nervous system; efferent neurons transmit information out of the nervous system to trigger some type of response in muscles and glands; and interneurons help to link groups of neurons, providing a means for the sharing of information. Before we leave this section, it is important to be aware of and appreciate that methods in molecular biology (analysis of genes, proteins, and chemical cell products) are now routinely used to classify and categorize neurons on a molecular and genetic level (Crick, 1999). Histology and functional categories still matter and continue to be used, but what we have discovered is that cells that may be identical morphologically may differ in great ways with regard to their molecular features. In fact, most known functional and structural differences between neurons or between neurons and any other cell type in the body can now be reduced to differences in gene expression. Molecular and genetically based differences in neurons can operate to change how these cells respond to an input and how they communicate with other neurons or targets (Crick, 1999). This new understanding was made possible through the extraordinary efforts of scientists who sequenced the entire human genome during the late 1990s and the early 2000s. Why is this important and why should you care? Well, think about this: Once the genetic profile of a neuron or class of neurons is known, neuroscientists can use bioengineering methods to create what are referred to as transgenic, knockout, or knock-in animals. These animals are genetically altered research subjects that possess phenotypic features (their physical characteristics) and physiological processes that mimic those of humans. Knockout and knock-in animals are those bioengineered to have either a gene deleted or added, while transgenic animals have new genes introduced within their nucleus. Because of the evolutionary conservation of genes and mechanisms of protein synthesis between humans and animals, bioengineered animal models can operate as a valid and critical method of discovering the molecular bases of human behavior. Specifically, once molecular and genetic markers are found for a particular human neurological disease, neurobiologists can use that information to develop genetically altered animals that have the exact same deficit or condition. These genetically altered animals can then be used to discover the etiology or cause of a disorder and to understand the effects of new treatments before they are used in humans. The use of molecular and genetic analysis and methods in neuroscience is rapidly changing the landscape of our understanding of the nervous system and offering much hope for the development of efficacious and safe treatments for debilitating neurological conditions (Crick, 1999). Take

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a look at Box 2–1 for a more in-depth discussion on the process of creating genetically modified research animals to study human behavior and disease.

Structural Features of the Neuron Soma, Cell Membrane, and Cytoskeleton The soma or cell body is the structural, metabolic, and genetic center of the neuron. From the soma, two major extensions of the cell membrane arise: the dendrites and axon. Both structures can be thought of as highly specialized extensions of the soma that operate as the chief input and output sites of the neuron, respectively. Dendrites form complex branch-like structures that receive information from the axons of other neurons and pass them to the soma. The axon, on the other hand, is often a single element extending from the soma and is dedicated to passing electrical signals to the dendrites and somas of other neurons downstream (see Figure 2–1A for an example). It should be noted that axons do divide into smaller branches called axon collaterals as the main axon trunk approaches a target (see the output site in Figure 2–1B for an example). Axon collaterals from the main axon trunk help to distribute information from a single neuron to multiple output target locations simultaneously. All these structural components are bound by the cell membrane or the neuron’s plasmalemma. The terms cell membrane and plasmalemma can be used interchangeably for all intents and purposes. The plasmalemma forms a barrier between the extracellular environment and the intracellular cytoplasm of the neuron. As seen in Figure 2–5, the cell membrane is composed of molecules know as phospholipids arranged in two opposing layers, giving the plasmalemma its characteristic moniker of a phospholipid bilayer. The

Extracellular space Hydrophilic head Hydrophobic tail

Intracellular space

 FIGURE 2–5.   Phospholipid bilayer that forms the cell membrane of the neuron. The bilayer is comprised of molecules known as phospholipids, which consist of a hydrophilic head (phosphate) and hydrophobic tail (lipid). Bilayer configuration produces a semipermeable barrier because the hydrophobic tails of the phospholipid molecules are arranged pointing inward while the hydrophilic heads face the watery cytoplasm and extracellular fluid.

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Neuroscience Fundamentals for Communication Sciences and Disorders

SECTION 1

Box 2–1. Further Interest:  I’m Going to Knock You Out! When investigating the function and effects of human genes, scientists have historically turned to model biological systems that possess analogous sets of genes to that of humans. By testing these model systems, we can determine the effect and consequence of a given gene on behavior or on a disease process. Believe it or not, humans happen to share a good deal of their genome with the simple mouse. Approximately 99% of genes in humans have a complement in mice. With this great level of genetic similarity, mice suddenly become ideal candidates for genetic experiments that cannot be performed in humans, but that are nonetheless critically needed to understand human gene functioning. Because mice are rather inexpensive to raise and maintain in colonies, geneticists first attempted to find mice in the wild with genetic alterations and mutations that mimicked human characteristics and diseases. Through lengthy cross-breeding methods, they were able to develop entire strains of mice with a certain gene that was absent or silenced. As you can imagine, such an approach was effective, but painstakingly slow to realize. But what if you suddenly had a way to speed up this process by using molecular biology to directly manipulate the mouse genome to delete or silence any gene you wanted to examine? In the last couple of decades, scientists have employed the power of molecular biology to generate what are called knockout mice. By definition, a knockout mouse is one in which geneticists have intentionally turned off (“knocked out”) an existing gene and in its place substituted an inactive or inert segment of DNA. By removing the influence of a given gene, valuable clues about how that gene normally operates can be identified. For example, changes in a mouse’s phenotype (set of observable characteristics or traits) created by a gene’s absence allows us to understand

phospholipid molecule consists of a hydrophilic (water-loving) “head” and hydrophobic (water-hating) “tail.” With these molecules arranged with their hydrophobic tails pointing inward and their hydrophilic heads facing the cytoplasm and extracellular fluid (which happens to be mostly water), you get an effective semipermeable barrier to most substances. The bilayer arrangement of the plasmalemma is actually very useful and serves an important purpose in maintaining the contents of the neuron separate from the outside world. The bilayer is selectively permeable to substances wanting access through the membrane based on the composition of those substances. As you can predict, molecules that are hydrophobic will be allowed to readily pass through the water-repelling core of the bilayer. On the other hand, hydro-

the effects of the gene on an animal’s behavior, or physical or biochemical nature. With this information in hand, measures for a given phenotype in a knockout mouse can be compared to identical metrics in a mouse that has not undergone genetic modification for a given trait. Through this comparison, geneticists can now identify the specific functions that are changed by the knockout. By extension, if the knockout gene has a high degree of similarity to a gene present in humans, geneticists can confidently say that the two genes likely function in similar ways. Effectively, we now have a way to understand a gene’s role and contribution to human forms of the condition under study. Some examples of research that use the knockout mouse include studying different forms of cancer, obesity, heart disease, diabetes, arthritis, drug abuse, anxiety, aging, and various neurological disorders. These same mice can also be very useful in testing the effects of novel pharmaceuticals and therapies for various conditions. With the introduction of the knockout mouse, the acceleration rate of genetic research for diagnosing, treating, and preventing human disease has been truly explosive . . . a fact that always just knocks me out! Resources Miko, I., & Lejune, L. (2004). Scientists can analyze gene function by deleting gene sequences [ebook]. Retrieved from https:// www.nature.com/scitable/ebooks/essentials-of-genetics-8/ 119492586#bookContentViewAreaDivID National Human Genome Research Institute. (2015). Knockout mice fact sheet. Retrieved from https://www.genome.gov/1251​ 4551 Pilcher, H. R. (2003). It’s a knockout. Nature. https://doi.org/10​ .1038/news030512-17

philic substances will be shunted away from the core and prevented from passing through. While the plasmalemma of the neuron might seem like a necessary but albeit boring part of the cell, the truth couldn’t be more different. As we’ll see in Chapter 3, the cell membrane is a key factor underlying the excitable nature of neurons and plays a critical role in the process of neural signaling. Adding internal support to the cell membrane, the soma, and its associated extensions is the cytoskeleton of the cell. Much like we have a rigid skeletal framework supporting the soft tissues of our bodies, cells possess a cytoskeleton that functions in a similar manner. The cytoskeleton consists of three major classes of filament-like components: microtubules, microfilaments, and neurofilaments (Haines, 2013). These

CHAPTER 2   Basic Structure and Function of Neurons

23

cytoskeletal structures comprise close to 25% of a neuron’s total protein content and are chiefly responsible for (a) defining the overall shape of a neuron; (b) adding internal structure to the cell body, axons (see the axon cross-section inset in Figure 2–6), and dendrites; (c) anchoring complex proteins to the cell membrane; and (d) maintaining the distribution and placement of cellular organelles throughout the neuron.

enzymes, and proteins needed for neural signaling and cell metabolism. The organelles are membrane-enclosed components that together are the internal metabolic machinery or “organs” of the cell, very much like the heart, stomach, intestines, and lungs make up our own body’s organs. Like every other type of cell in the body, neurons contain all of the typical internal structures and organelles you are familiar with from high school or college biology. Although the neuron does possess a few specialized internal components, the majority of the internal features are shared across all cell types. Using the multipolar neuron shown in Figure 2–6 as our guide, let’s briefly review the major organelles and their functions. In the figure, a portion of the neuron’s plasmalemma on the soma has been cut and removed so we can take a peek inside and see these major organelles more easily.

Cytoplasm Within the confines of the plasmalemma, we have cytoplasm, or the “goo” making up the internal space of the cell. Cyto­ plasm consists of two major components: the cytosol (the watery portion) and the organelles. The watery cytosol contains the major ions (atoms that have a net electrical charge),

Node of Ranvier Mitochondria

Axon from other cell

Smooth ER

Dendrite

Myelin

Dendritic spines

Nucleolus Cell membrane

Neurolemma Axon from other cell

Nucleus Microtubules

Smooth endoplasmic reticulum

Axon terminals Rough endoplasmic reticulum Microtubules

Golgi apparatus

Axon hillock

Lysosome

Myelin sheath Cytoplasm Mitochondria Node of Ranvier

 FIGURE 2–6.   Cutaway perspective of a multipolar neuron showing the internal structure and major organelles.

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Neuroscience Fundamentals for Communication Sciences and Disorders

Mitochondria Acting as the cell’s powerhouses are the mitochondria, responsible for cellular respiration. The mitochondria are kidney-bean shaped organelles that produce (via Krebs cycle) copious amounts of adenosine triphosphate (ATP), the key energy unit or “coin of the realm” of the neuron (and, for that matter, all cells in the body) (Guyton & Hall, 2006). As shown in Figure 2–7, ATP produced by the mitochondria is essentially a complex sugar with three attached phosphate groups. Metabolic energy, used by a cell to run all types of biochemical reactions and processes, is released from ATP through a process known as hydrolysis, a chemical reaction whereby a phosphate group is literally “cut” or removed from an ATP molecule. At that point, ATP is converted into ade­ nosine diphosphate (ADP) with a little packet of energy released to drive all the biochemical and metabolic reactions of the neuron. ADP can be converted back into the high-­ energy form of ATP through a reverse process known as phosphorylation, whereby energy is absorbed to reconnect (bind) a phosphate group to the complex molecule. Mitochondria possess their own genome and, as such, can divide independently of the remainder of the cell (Guyton & Hall, 2006). This unique property of the mitochondria is exploited by cells of the body to adjust the number of mitochondria available based on the energy consumption needs of the cell. A good example of this dynamic adjustment can be seen in muscle tissue undergoing physical training and exercise. Pretty neat, right? You can adjust your own “power supply” through self-activity! The neuron is one of the most energetic and power-hungry cells of the body and therefore

SECTION 1

possesses copious quantities of this energy-producing organelle, especially within the presynaptic terminal, a particularly critical biochemical location of the cell. Lastly, mitochondria play an important role in the management of calcium ion (Ca2+) concentration in the cell’s cytosol. As we will see in Chapter 3, the concentration of Ca2+ ions must be tightly regulated within a neuron because of the potential for this ion to initiate and influence biochemical reactions that affect the cell’s ability to create neural signals. Ca2+ is a key player in the process of synaptic transmission and communication between neurons.

Smooth and Rough Endoplasmic Reticulum Throughout the cytoplasm of the neuron are membranous channel-like structures known generally as the endoplasmic reticulum (ER). The ER comes in two forms: a smooth and a rough variety. The general functions of the ER are to (a) transport materials throughout the soma, much like a subway system will transport passengers about a city, and (b) participate in protein and lipid synthesis, ion storage, and the metabolism of carbohydrates and other substances. The smooth ER participates in both general functions except for protein synthesis. The rough ER participates in both activities as well but has the added function of being a key player in protein synthesis. What makes rough ER appear “rough” is the presence of another type of organelle attached to the ER, known as the ribosome. Ribosomes are key players in protein synthesis and operate as the “translators” of genetic instructions coming from the nucleus. An interesting fact is that rough ER was one of the first internal structures of the

Energy Absorbed

Phosphorylation

ATP

ADP P

P

P

+

P

P

P

Adenosine diphosphate (ADP) + Phosphate

Adenosine triphosphate (ATP)

Hydrolysis

Energy Released

 FIGURE 2–7.   ATP to ADP conversion. ATP is hydrolyzed to ADP to release a packet of energy that will be used to drive all biochemical and metabolic reactions of the neuron. ADP can be reenergized to ATP through the process of phosphorylation.

CHAPTER 2   Basic Structure and Function of Neurons

neuron to be identified through an early histological method developed in the late 19th century known as the Nissl stain. Just FYI . . . if you see the term Nissl substance discussed in other textbooks, they are referring to the rough ER.

Golgi Apparatus Another important part of the protein-generating machinery in the cell is the Golgi apparatus. The Golgi apparatus (or body) is a pancake-like stack of membranous discs whose function is to sort and deliver newly made proteins to all areas of the cell. The Golgi apparatus always reminds me of a FedEx or UPS distribution center: It packs, molecularly labels, and ships proteins to their respective destinations all throughout the soma. The Golgi apparatus is also involved in the activation of proteins through a complex process of folding and modifying the shape of newly created proteins coming from the ribosomes. Proteins aren’t flat ribbon-like structures; they are actually three-dimensional in shape! The folding and modification in shape of a protein molecule is central to its eventual functionality.

The Nucleus Mediates the Process of Gene Expression Last but definitely not the least of the cellular organelles is the nucleus. The nucleus is the largest of the cellular organelles and is the location of the cell’s DNA (deoxyribonu­ cleic acid). Encapsulating the nucleus from the rest of the cytoplasm is the nuclear envelope. The nuclear envelope is a porous structure that is contiguous with the rough ER. Pores within the nuclear envelop allow for the passage of chemical messengers and other molecular elements into and out of the nucleus. The single most important function of the nucleus is to preserve the integrity and form of the chromosomes and to control the mechanism of gene expression, the process of decoding our DNA to generate the molecular instructions for creating all of the proteins used by a cell for structural and metabolic purposes (Gelehrter, Collins, & Ginsburg, 1998). To give you a bit more of a grounding in the function of the nucleus, let’s briefly review how gene expression unfolds, starting with the structure of DNA. A Brief Primer on the Structure of DNA.  Within the nucleus, DNA is found in compact and tightly wound structures called chromosomes. When the chromosome is unwound, DNA takes the familiar form of a double-stranded helix of organic molecules. If you could untwist and disassemble the DNA double helix into its two individual strands, what you would notice is that each is comprised of a long chain of elements consisting of deoxyribose (a sugar) and phosphate molecules. As illustrated in Figure 2–8, the deoxyribose-phosphate molecules form the backbone or spine of each DNA strand. Each sugar-phosphate molecule of the

25

DNA backbone is subsequently linked to one of four complex organic molecules or bases: adenine (A), guanine (G), thymine (T), and cytosine (C). A base plus its corresponding sugar-phosphate backbone molecule is called a nucleotide. Each strand of DNA is then an unimaginably long chain of billions of nucleotides in a row (see Figure 2–8). Reassembling the two individual DNA strands back to their familiar helical state demonstrates that the two strands are paired in the following complementary manner: A pairs with T, and G pairs with C. The complementary pairing of nucleotides in the DNA double helix forms the basis for genetic replication during cell division as well as for transcribing (copying) nucleotide sequences (genes) into the specific codes (instructions) necessary for creating proteins (Gelehrter et al., 1998). Within each double-stranded helix of human DNA are billions of pairs of nucleotides. The reality, though, is that only select and limited groupings of these nucleotide pairings actually contain instructions necessary to create a functional protein. These protein-generating sequences of nucleotides in DNA are what we commonly refer to as our genes. Current estimates indicate that the human DNA has approximately 35,000 to 40,000 genes, although this number is still under debate by geneticists. Genes consist of stretches of nucleotides that code or provide instructions for a given amino acid (structural component of proteins), separated by stretches that do not. The stretches of DNA that code for sequences of amino acids are called exons, while those that do not code for amino acids are called introns. Molecular markers surrounding exons and introns of a DNA strand provide our gene expression machinery with cues as to where a given gene starts and stops. Before leaving the topic of DNA’s structure, it is important to clarify a common misconception about DNA’s role in animal behavior. It is a common mistake to think that DNA can store all the necessary information needed to develop complex animal behaviors. In our field, many mistakenly believe that the development of speech and language is innate and encoded by our genes. This view conceives of DNA as if it were a high-capacity flash drive crammed with all the instructions, details, and consequences underlying the complex emergence of language and speech development. The reality is that DNA does not and cannot encode for any type of animal behavior in the way that most think it does. Behavior is multidimensional and too enormously complex to be represented by a collection of molecules at the center of a cell. DNA does one thing and one thing exceptionally well . . . it provides the instructions to generate proteins, and that’s it. Now, its a fairly important “it” because proteins are the building blocks of all cells in an animal. How cells differentiate, how they form tissues, and how they communicate with each other forms the anatomical foundation of our behavior. So, when you hear that a scientist has discovered a gene to explain the development of speech or language, for example, what this really means is that researchers have discovered a gene that is related to the generation of a specific protein that

26

Neuroscience Fundamentals for Communication Sciences and Disorders

Phosphate

SECTION 1

Nucleotide

Sugar (deoxyribose)

Base

+

= DNA Strand

G

A

C

G

G A T

G

C

N

A

G

C

N

HN

C C

C N

Adenine

NH

NH2

C

N

N

CH3

HN

CH HC

T

O

O

C

C

A

G

C

G

NH2

T

C

T

T

C CH

CH H2N N

Guanine

CH

C

C NH

O

N H

Thymine

CH

C O

NH

Cytosine

 FIGURE 2–8.   Structure of DNA. DNA is a double helix comprised of long chains of deoxyribose (sugar) and phosphate molecules linked to one of four bases: adenine (A), guanine (G), thymine (T), and cytosine (C). A base plus its corresponding sugar-phosphate backbone molecule is called a nucleotide. DNA is the essential mechanism for gene expression and the coding of proteins.

itself may be involved in producing changes in how a class of cells may operate. Changes in the operation or function of that cell type are correlated to how different brain regions, believed to be active during speech and language, communicate with each other, thus influencing their development (Box 2–2). Gene Expression:  A Process of Transcription and Translation.  How do we go from genes situated on DNA

to the production of a fully realized protein at the ribosome? What critical component of the protein-generating mechanism is

responsible for shuttling genetic information between the nucleus and the ribosomes? The answer is a unique form of nucleic acid that is found mostly in the cytoplasm known as messenger ribonucleic acid or simply, mRNA. mRNA is effectively a middleman responsible for transporting genetic instructions for a protein from the nucleus to the ribosomes (Gelehrter et al., 1998). As illustrated in Figure 2–9, mRNA is created by first unwinding the DNA double helix and allowing for an enzyme known as RNA polymerase to begin synthesizing a single mRNA strand from the side of the unwound DNA that possesses the actual codes for protein material. The copy-

CHAPTER 2   Basic Structure and Function of Neurons

Transcription Non-template strand of DNA

A

C

A

A

Amino Acid

C

G

C G

T

Newly made RNA

RNA nucleotides

RNA polymerase T

27

C

A

T

G

G

T

A

C

T

T

G C

Template strand of DNA

tRNA

Growing amino acid chain tRNA leaving

Codon

tRNA docking

Codon

Anticodon

Ribosome

Translation

 FIGURE 2–9.   Transcription and translation. During transcription, the DNA double helix is unwound, allowing for RNA polymerase to begin synthesizing a single strand of mRNA. mRNA is produced as a complementary strand of nucleotides to that of DNA. The transcribed mRNA strand consists of a chain of codons that will each code for a specific amino acid. Once mRNA exits the nucleus, it binds to ribosomes to begin the translation phase of gene expression. During translation, individual amino acids are brought to the ribosome by means of transporter molecules called transfer RNA (tRNA). As mRNA is “read” by the ribosome, a growing polypeptide chain is generated by matching the anticodons of tRNA with the complementary codons on mRNA.

ing of sequences of nucleotides from DNA to a single strand of mRNA is a process referred to as transcription. As you can see in the transcription segment of Figure 2–9 (left side), mRNA is produced as a complementary strand of nucleotides to that of the DNA coding template. You can think of transcription as creating a copy of the DNA’s coding region, but the copy is not a direct one, like a photocopy of something would be. Rather, the mRNA strand being generated is in fact a “negative” version of the DNA coding region. In other words, mRNA possess sequences of nucleotides that are the opposite to what is needed to correctly build the primary structure of a protein. Here is the analogy I’d like to provide you to make this a bit more clear . . . making ice in a tray. An ice cube tray is a perfect example of what is called a negative mold; it is the opposite of what we want to make. To make the positive version of the tray (the ice cubes themselves), you fill the negative mold with water and freeze it. You have just created

a positive object (the ice cube) from a negative mold (the tray). The nature of mRNA and the way in which it is used to create a protein is characterized similarly by our analogy. During transcription, only the gene’s exons (the coding regions on DNA) are copied for export from the nucleus. The organization of the sequences of nucleotides on mRNA is divided into functional groupings, each consisting of three bases. Each grouping of three bases on the mRNA strand is called a codon. The reason for the organization of mRNA strands into codons will become apparent as we discuss the next step in the process of protein generation: translation. (Hint: it’s directly related to our ice cube tray analogy.) Once a strand of mRNA has been fully generated via transcription, the completed mRNA migrates from the nucleus through the pores on the nuclear envelope, where it heads toward and binds onto ribosomes. Ribosomes, as stated earlier, are the protein assembly plants of the cell and

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Neuroscience Fundamentals for Communication Sciences and Disorders

SECTION 1

Box 2–2. Further Interest:  The Big Brown FOXP2 Jumped Over the Lazy Dog! The discovery of the FOXP2 mutation nearly 25 years ago is considered the first realistic foray into uncovering the genetic foundations of speech and language production. The FOXP2 gene codes for a protein called forkhead box P2, which has been found to be related to the normal acquisition of speech and language. How can one simple protein impact the normal development of a complex behavior such as speech and language? The devil is in the details. The protein forkhead box P2 operates as a transcription factor, which is an element of the gene expression process that regulates the activation of other genes in a person’s DNA. The genes that are controlled by the forkhead box P2 transcription factor happen to be those related to a variety of fundamental mechanisms in the nervous system, including neuron differentiation, growth and guidance of axons, and changes to the operation of the synapse. The fact that FOXP2 is related to these nervous system events strongly suggests that this gene is likely involved in synaptic plasticity as well. Synaptic plasticity is the foundation for all mammalian learning and memory. As such, mutation of the FOXP2 gene begins a cascade of events where the efficacy of the forkhead box P2 transcription factor is

are located mostly on the surface of the rough endoplasmic reticulum. Once bound to a ribosome, mRNA undergoes a “reading” process known as translation. Translation is the process of assembling protein molecules by linking the building blocks of a protein, known as amino acids, into long complex chains (Gelehrter et al., 1998). During translation, the sequence of codons making up a stand of mRNA is used as a coding template for determining (a) which amino acids are going to be needed to produce a protein and (b) how those amino acids should be ordered in the chain. You can think of the set and ordering of codons on mRNA as a “recipe” for creating a given protein. Each amino acid is specified uniquely and unambiguously by a given codon. Much like a recipe provides you with a list of raw ingredients and the order in which those ingredients are to be used, the set of codons on mRNA provides the same general service. Because there are only 20 different types of amino acids (ingredients) floating in the cytosol of a cell, proteins are distinguished from one another by the types of amino acids used and their ordering. As illustrated in the translation section of Figure 2–9 (right side), amino acids are brought to the ribosome for protein generation by way of transporter molecules called trans­ fer RNA (tRNA). tRNA possess sequences of bases called anticodons that correspond in an exact and complementary way to the codons on mRNA. Matching tRNA anticodons to mRNA codons (like fitting together two pieces of a puzzle)

altered, which in turn leads to abnormal speech and language development. The FOXP2 mutation is related to the presence of childhood apraxia of speech (CAS). CAS is a condition whereby the speaker cannot adequately activate speech motor cortical areas, such as the inferior frontal gyrus, to program the movements underlying phonemes, syllables, and words. Such a condition renders the speech of these children highly unintelligible. Aside from speech production, the FOXP2 mutation has also been linked to receptive language deficits as well as to deficits in reading and writing behaviors. Recent studies have also correlated FOXP2 mutations to the presence of autism spectrum deficits. Resources Deriziotis, P., & Fisher, S. E. (2017). Speech and language: Translating the genome. Trends in Genetics, 33(9), 642–656. Schreiweis, C., Bornschein, U., Burguière, E., Kerimoglu, C., Schreiter, S., Dannemann, M., . . . Puliyadi, R. (2014). Humanized Foxp2 accelerates learning by enhancing transitions from declarative to procedural performance. Proceedings of the National Academy of Sciences, 111(39), 14253–14258.

ensures that the mRNA is correctly read with the right amino acid placed in the correct position of the growing polypeptide chain as dictated by the sequence of codons on the mRNA strand (Gelehrter et al., 1998). Going back to our ice tray analogy, this event is synonymous to the tray being filled with water and frozen to make the cubes. As a tRNA molecule brings an amino acid to a ribosome for linking with the growing peptide chain, an empty tRNA molecule is ejected from the other end of the ribosome into the cytosol for reuse. So, if you think of a translated protein (string of amino acids) as the sentence that you’re reading right now, then mRNA represents the template of words (codons) and their ordering pattern (sequences of codons), while tRNA would be the mechanism responsible for giving the ribosome (the reader) the correct word at just the right time and in just the right order so that the entire sentence makes sense (produce a working protein). This entire multistep process of generating a protein from transcription to translation is what we commonly refer to as gene expression (Gelehrter et al., 1998). The final step in protein synthesis involves transferring the finished amino acid chain into the ER and Golgi apparatus for modification and folding of the amino acid chain into a functional and active protein that can then serve a role in the neuron’s metabolic and signaling mechanisms. To help you study this process, Figure 2–10 provides a compact summary and flowchart for the mechanism of gene expression.

CHAPTER 2   Basic Structure and Function of Neurons

Transcription

RNA polymerase unwinds DNA to reveal coding template region

mRNA nucleotides bind in a sequential and complementary manner to DNA coding region to create mRNA strand

mRNA strand migrates out of the nucleus through nuclear pores

Translation

mRNA strand binds to ribosome to begin translation process

mRNA codon sequence determines which amino acids are needed and how they should be ordered

tRNA sequentially brings amino acids (AA) to ribosome to grow AA chain by matching tRNA anticodons to mRNA codons

Completed amino acid chain detaches from ribosome and enters Golgi body to complete protein formation

 FIGURE 2–10.   The process of gene expression, transcription (yellow) and translation (blue), is summarized in a flowchart.

Axons and Dendrites Returning to our discussion of major structures of the neuron, one could argue that none of the cell features that we’ve discussed thus far are exclusive to the neuron. Organelles, cell membranes, nuclei, DNA, and so forth are common structures across all cell types. The two remaining structural features of a neuron that we will review — the axons and

29

dendrites ​— are exclusive to neurons though and are the principal means by which information is transmitted in the nervous system. As we already know, the axon constitutes the output pathway of a neuron. Axons originate from a location on the soma called the axon hillock (Kiernan, 2005). As mentioned earlier, the axon hillock is specialized to generate the action potential, and so it makes functional sense to have the axon extending from this region. Axons can range in length from less than 0.1 mm to as long as 25 m — the length of a blue whale! The longest axons in the human body are roughly 1 m in length (or closer to 1.5 m if you’re the center for an NBA team). Axons also vary in diameter, which has important consequences for the speed at which signals propagate along this structure. One of the largest diameter axons in an animal can be found in the deep-sea giant squid. Some of the axons controlling the siphon of this animal can measure 1 mm in diameter. That’s about the thickness of a strand of cooked spaghetti and thus is clearly visible to the naked eye. While an axon is a single extension from the soma, it branches into finer components referred to as axon collaterals. Axon collaterals can appear at any place along the main axonal trunk but are most often seen toward the terminal end as the axon is approaching its target location (see Figure 2–1B for an example). At the very end of an axon or axon collateral is where you will find the presynaptic terminal (or bouton, if you prefer the fancier French term). Axons and their presynaptic terminals lack major metabolic structures such as ribosomes and Golgi bodies, requiring the need for transportation mechanisms to ensure the distribution of proteins and other metabolic products to the presynaptic terminal (Kandel et al., 2013). Experiments during the 1940s first demonstrated that axonal transport of substances, called axoplasmic flow or transport, is responsible for the shuttling of material from the soma to the presynaptic terminals (Weiss & Hiscoe, 1948). Axoplasmic transport mechanisms rely on microtubule “rails” and molecular “feet” to walk material at either fast or slow speeds down the axon to terminal locations. (I always imagine this mechanism looking like loaded passenger cars running on a modern inverted and twisting rollercoaster, the kinds you find at amusement parks like Disney World or Kings Island.) The movement of material in the direction from the soma to the presynaptic terminal is called anterograde transport. When material from the presynaptic terminal must be sent back to the soma, a similar but alternative method called retrograde transport is used. The presynaptic terminal forms the first half of the communication mechanism between two neurons known as the synapse. In a synapse, the cell conveying information is referred to as the presynaptic cell, while the cell receiving information is the postsynaptic cell. The presynaptic terminal contains virtually all the required chemical or electrical signaling machinery necessary to transmit an output to the postsynaptic cell (Hall, 1992; Kiernan, 2005).

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Neuroscience Fundamentals for Communication Sciences and Disorders

SECTION 1

Box 2–3. Clinical:  Genetic Variation and the Role of Genes in Neurological Disease A genetic variation is a permanent change in the DNA sequence that makes up a gene. Most variations are harmless or have no effect at all. However, other variations can have harmful effects leading to disease. Still others can be beneficial in the long run, helping a species adapt to change.

abnormally shaped protein that is toxic to neurons. As cells start to die, the symptoms of Huntington’s disease appear — uncontrollable writhing movements of the legs and arms, a loss of muscle coordination, and changes in personality and thinking.

• Single Nucleotide Polymorphism (SNP): SNPs are variations that involve a change in just one nucleotide. It is estimated that the human genome contains more than 10 million different SNPs. Because SNPs are such small changes within DNA, most of them have no effect upon gene expression. Some SNPs, however, are responsible for giving us unique traits, such as our hair and eye color. Other SNPs may have subtle effects on our risk of developing common diseases, such as heart disease, diabetes, or stroke. • Copy Number Variation (CNV):  At least 10% of the human genome is made up of CNVs, which are large chunks of DNA that are deleted, copied, flipped, or otherwise rearranged in combinations that can be unique for each individual. These chunks of DNA often involve protein-coding genes. This means that CNVs are likely to change how a gene makes its protein. Since genes usually occur in two copies, one inherited from each parent, a CNV that involves a single missing gene could lower the production of a protein below the amount needed. Having too many copies of a gene can be harmful, too. Although most cases of Parkinson’s disease are sporadic (without a known cause), some cases have been linked to having two or more copies of the SNCA gene, which encodes a protein called alpha-synuclein. The excess alpha-synuclein accumulates in clumps inside brain cells and appears to jam the cells’ machinery. • Single Gene Mutation:  Some genetic variations are small and affect only a single gene. These single gene mutations can have large consequences, however, because they affect a gene’s instructions for making a protein. Single gene mutations are responsible for many rare inherited neurological diseases. For example, Huntington’s disease is the result of what is called an expanded “triplet repeat” in the huntingtin gene. Normal genes often have triplet repeats, in which the same triplet amino acid code occurs multiple times in a sequence. These repeats are usually harmless. In the Huntington gene, triplet repeats of 20 to 30 times are normal. But in people with Huntington’s disease, the number of repeats reaches 40 or more. The mutation creates an

Most of the single gene mutations that cause rare neurological disorders such as Huntington’s disease have been identified. In contrast, there is still much to learn about the role of genetic variations in common neurological disorders and conditions, like Alzheimer’s disease and stroke. A few things are clear. First, for most people, a complex interplay between genes and the environment influences the risk of developing these diseases. Second, where specific genetic variations such as SNPs are known to affect disease risk, the impact of any single variation is usually very small. In other words, most people affected by stroke or Alzheimer’s disease have experienced an unfortunate combination of many “hits” in the genome and in the environment. Finally, beyond changes in the DNA sequence, changes in gene regulation — for example, by sRNAs and epigenetic factors — can play a key role in disease. Scientists search for connections between genes and disease risk by performing two kinds of studies. In a genome-wide association (GWA) study, scientists search for SNPs or other changes in the DNA sequence, comparing the genomes of subjects (people, laboratory animals, or cells) that have a disease and subjects that do not have the disease. In another type of study called gene expression profiling, scientists look for changes in gene expression and regulation that are associated with a disease. Both kinds of studies often use a device called a DNA microarray, which is a small chip, sometimes called a gene chip, coated with row upon row of DNA fragments. The fragments act as probes for DNA (in a GWA study) or RNA (in gene expression profiling) isolated from a sample of blood or tissue. Increasingly, scientists are conducting these studies by direct sequencing, which involves reading DNA or RNA sequences nucleotide by nucleotide. Sequencing was once a time-consuming and expensive procedure, but a new set of next-generation sequencing methods has emerged as an efficient, cost-effective way to get a detailed readout of the genome. Resource Edited from public domain material by the U.S. Department of Health and Human Services. (2010, July). Brain Basics: Genes at work in the brain. National Institute of Neurological Disorders and Stroke. Retrieved January 20, 2022, from https:// www.ninds.nih.gov/Disorders/Patient-Caregiver-Education/ Genes-Work-Brain#7

CHAPTER 2   Basic Structure and Function of Neurons

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Box 2–4. Clinical:  Rett Syndrome Rett syndrome is an unusual neurodevelopmental disorder mostly affecting females and genetically linked to mutations of the MECP2 gene. In this condition, infants appear to develop normally for the first 6 to 18 months before sudden deterioration of all forms of behaviors ensues, resulting in severe cognitive, motor, and communicative deficits. For the parents and caregivers, such an occurrence is devastating, to say the least. The neuropathology of Rett is subtle and is characterized by the reduction in size of cortical, basal ganglia, thalamic, amygdala, and hypothalamic neurons. All these neural structures are directly related to cognitive processing, emotional regulation, and autonomic control. Reduced processing capacity in these regions may underlie the severe cognitive and communicative deficits noted in Rett syndrome. In addition to reductions in neuron size, reduced degrees of dendritic branching, especially in frontal and temporal lobes, is also noted.

Presynaptic terminals can form synapses at three general locations on the postsynaptic cell: on dendrites, somas, and even on an axon (Haines, 2013). Illustrated in Figure 2–11 are three different arrangements of synapses that can be found in the nervous system. Axodendritic synapses are the most numerous and common form of synapse. In this type, the presynaptic terminal connects to the dendrites of the postsynaptic neuron. Axosomatic synapses are the second most numerous class and are formed between the presynaptic terminal of one neuron and the soma of the postsynaptic cell. Several examples of axodendritic and axosomatic synapses can be seen in Figures 2–1 and 2–6. The axoaxonic variety (as you can probably guess by its name) is formed between two axons. This last form of synapse plays a critical role in the regulation and modification of information transfer between two neurons in a process referred to as presynaptic inhibition. We will encounter presynaptic inhibitory mechanisms later in the text when we discuss sensorimotor control of skilled behavior and the modulation of pain responses. Within a network, neurons can arrange themselves synaptically in many different patterns and configurations. As illustrated in Figure 2–12, four general patterns can be identified that capture the vast majority of synaptic arrangements between cells in a network. The first pattern is referred to as serial and represents an arrangement where cells are organized in a linear manner, like cars on a train (Figure 2–12A). This is the most fundamental of patterns and enables transmission of information from one neuron to the next. Serial synaptic connections can be found embedded as part of more complex synaptic connection patterns if you look closely. In the second pattern, several neurons (Neurons labeled 1) are connected to and transmit their output to a single central neuron

Because of the severity of the cognitive and communicative deficits that can emerge in this condition, speech and language production is severely affected. Most communicative actions are vegetative in quality and severely restricted (vocal grunts, pitch and tonal outputs, and strings of nonsense syllables). Again, reduced neuronal size and connectivity, especially in speech motor areas of the inferior frontal lobe, are likely at the root of these speech-related deficits. Unfortunately, no treatments are available to reverse or lessen the impact of Rett syndrome on the individual. Alternative and augmentative communication is often a method that is used to give the affected individual some capacity to interact with others. Resources Woodyatt, G. (2009). Rett syndrome. In M. R. McNeil (Ed.), Clinical management of sensorimotor speech disorders (2nd ed., pp. 388–389). New York, NY: Thieme.

Axodendritic synapse

Cell body

Axosomatic synapse

Axon hilock

Axon Dendrites

Axoaxonic synapse

Terminal arborizations

 FIGURE 2–11.   Synapses can form at dendrites, at the soma, or on axons. Three different classes of synapse arrangements are recognized, including axodendritic, axosomatic, and axoaxonic.

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 FIGURE 2–12.   Networks of neurons can interconnect among themselves in a variety of different patterns to support the processing of neural signals. Four major patterns of interconnection are shown in the figure: A. Serial transmission. B. Convergent transmission. C. Divergent transmission. D. Information flow modulated by interneurons.

(Neuron 2) in a convergent manner (Figure 2–12B). This form of connectivity is ideal for helping groups of cells in a network filter, consolidate, and average information. The

central neuron uses the convergent input to “decide” whether to produce an action potential and propagate (pass along) the signal further along the network. In effect, the activity of the

CHAPTER 2   Basic Structure and Function of Neurons

three input cells must work cooperatively to drive Neuron 2 to fire a signal. In our third pattern (Figure 2–12C), Neuron 1 uses axon collaterals to distribute its output to multiple neurons (Neuron 2) simultaneously in a divergent manner. Think of divergence as a way to “pump up the volume” on a signal by helping distribute a given signal from one to several neurons rapidly and in parallel (Figure 2–12C). With this pattern type, the output of a single cell is effectively amplified by increasing the signal’s spread and growing its dominance in a network. Lastly, neurons can be synaptically arranged to form self-regulating circuits (Figure 2–12D). In this arrangement, neurons can be interlinked with interneurons in complex ways to bypass certain neurons or to form negative feedback loops that prevent a network from being overdriven and too excited. As we can see, different and overlapping synaptic connection patterns add processing richness and complexity to a neural network’s operation. The dendrite is the chief input site of the neuron and, as such, is covered with synapses (Haines, 2013). Many dendrites have small pier-like protrusions called dendritic spines (see Figure 2–6 for examples). Dendritic spines house numerous cellular mechanisms and organelles essential for the modification of the synapse with behavioral experience. One interesting and unique fact about dendritic spines is that they appear to have protein-producing ribosomal structures. The presence of ribosomal structures in the vicinity of the spine fits well with the necessary changes that spines must undergo during periods of active modification due to experience and practice. Dendritic spines are thought to be one key location where neuroplasticity can occur to modify the structure and function of a neuron. Numerous brain disorders such as Fragile X syndrome, schizophrenia, and fetal alcohol syndrome are believed to be associated with abnormal structural changes and reductions in dendritic spine numbers. While a typical neuron possesses a single principal axon, the number of dendrites a neuron has can vary tremendously (Hall, 1992; Haines, 2013). You can have neurons with so few dendrites, you could count them on two hands, to neurons with literally thousands of dendrites and densely branching arbors. (A little aside: You may come to notice that when describing dendrites, neuroanatomists tend to use tree-related terms. Dendrites do have a strong resemblance to the branching pattern of a tree, with many side arbors extending from the main trunk of the dendrite. So, if you see terms such as “branching,” “arbors,” or “arborizations,” just remember that all we are talking about is the subdividing of dendrites extending from the soma.) The density of a dendritic arbor provides us with a clue to the functionality of a neuron; the denser arbors are, the more input a cell receives, and the more signal integration is likely happening within the soma. Motor neurons and neurons of the cerebellum are two examples of cells with very dense dendritic arbors. The dense arbors of these two types of neurons correspond well with the known integrative role of these regions during movement and skill production (Guyton & Hall, 2006).

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The Glial Cell Neuroanatomists have a habit of naming cells either after themselves or based on Greek and Latin. (I’m still looking for a cool cell to name myself after! ) The word glia is a classic example of the latter convention and comes from the Greek term for “glue.” The idea of glia operating as the glue of the nervous system should not be taken literally, of course, but rather figuratively to highlight that neurons are completely embedded and surrounded by glial cells. Generally speaking, glial cells operate as key support cells helping to generate the internal structural framework of brain tissue and to metabolically maintain the health of signaling neurons. Glial cells are structurally distinct from neurons in that they do not have axons or dendrites and, as mentioned earlier, far outnumber signaling neurons in the nervous systems (Allen & Barres, 2009).

Glial Cells Are Divided Into Two Major Functional Groups Glial cells can be divided into two major functional groupings: microglia and macroglia (Haines, 2013). Microglia are part of the immune system and operate as the “sanitation workers” of the brain. Microglia are recruited to sites of injury or infection and operate through phagocytic (engulfing and destroying) mechanisms (Figure 2–13). Although the vast majority of the time microglia are useful to the nervous system, there are conditions where the overproliferation of these cells sets the stage for damaging consequences. A prime example of this situation is after a person has had a stroke. Strokes cause damage to tissues of the brain as a function of blood and oxygen loss leading to necrosis (cell death) of brain tissue. As one would expect, microglia are recruited to the site of injury, but sometimes they start doing their work a little too well and vigorously. Under normal conditions, the brain tightly regulates the action of microglia, but after a stroke, those control mechanisms are severely compromised. Microglia are known to exhibit both anti- and proinflammatory activity, meaning that they contribute to both reducing and increasing inflammation at an injury site (Stephenson, Nutma, van der Valk, & Amor, 2018). Controlling brain inflammation after stroke is known to be a key factor in preserving damaged brain tissue and aiding recovery. Proinflammatory microglial activity leads to a stronger immune response, which operates to further worsen the loss of tissue and perpetuate inflammation. Controlling microglia activity after stroke may thus be an important therapeutic strategy to help manage the negative effects of stroke (Stephenson et al., 2018). Macroglia constitute the second major class of glial cells and consist of three cell types: astrocytes, oligodendrocytes, and Schwann cells (Haines, 2013; Paxinos & Mai, 2004). Of these cell types, the oligodendrocytes and Schwann cells are the producers of myelin in the nervous system. Myelin

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SECTION 1

Box 2–5. Clinical: Apoptosis

Necrotic cells– waste products Neuron

Microglia

 FIGURE 2–13.   Microglia is a major class of glial cell that is recruited to injury sites to remove necrotic cells through phagocytosis. Microglia exhibit both anti- and proinflammatory activity.

is a fatty-like substance (it feels like Crisco) that operates to electrically isolate axons from one another. As illustrated in Figure 2–14, both the oligodendrocyte and the Schwann cell produce myelin around an axon by first extending a process from their own cell body toward an exposed axon region. At this point, the glial cell’s process begins winding itself repeatedly around the circumference of the axon, giving the axon the appearance of the cross-section of a jelly roll. The major differences between the two myelin-producing cells are their location in the nervous system and the number of axons they can myelinate at once. Oligodendrocytes produce myelin in the central nervous system. Because space is rather limited in the brain, a single oligodendrocyte can myelinate between 30 and 50 different axon segments — a very efficient cell indeed! The Schwann cell, on the other hand, is found in the peripheral nervous system. Because neural real estate is not at a premium in this region, one Schwann cell will envelop only a small segment of one axon. Before leaving the discussion of myelin-producing cells, keep in mind that these cells do not coat the axon uniformly and completely. In fact, myelin is set down in segments with short stretches (1 µm) of exposed unmyelinated axon found at regular intervals along the length of the axon (Carpenter, 1991). These exposed stretches are called the nodes of Ranvier (a really great term to say with a heavy French accent) and are key players in the process of conducting electrical signals down an axon. The significance of these nodes and the insulating features of myelin will become more apparent

Neuronal cell injury or death is a normal consequence of any form of injury or progressive disease state. When necrotic cells are found in the central nervous system (CNS), microglia are tasked with removing the messy remains. If the necrotic neural tissue is in the peripheral nervous system (PNS), the role of sanitation worker lands upon the macrophages. There is another form of neural cell death, though, that is far more neat and tidy, and is not associated with an injury or specific disease state. This form of cell death is known as apoptosis, defined as a genetically triggered and purposeful mechanism of cell death that occurs naturally during embryological and postnatal development. Note that apoptosis is not specific to the nervous system, but rather is a common functional mechanism across all parts of the body (Bredesen, 1995, 2000). Apoptosis in the nervous system is primarily triggered during neural tissue differentiation and formation when an overabundance of neurons is generated during early neurogenesis. Other reasons for apoptosis may include (a) the removal of abnormal cells, such as those with genetic mutations, which could potentially harm the organism, and (b) the removal of support cells that have completed their developmental tasks and are thus no longer needed for further neural tissue development (Alberts et al., 2002). If you envision neural tissue formation like the act of sculpting a statue, apoptosis is the process by which excess marble and granite is cut away when you’re chiseling out your intended artwork. Sometimes you have to intentionally sacrifice some neurons to achieve the structure the nervous system needs. Unlike the messy nature of cell death caused by injury or disease conditions (envision exploding cells and cellular contents leaking out all over the place), apoptosis occurs in a neat and orderly manner. During apoptosis, neurons first tend to shrink in size and then form small pimple-like cell membrane growths called blebs. The internal elements of the cell are “sliced and diced ” into smaller fragments and subsequently encapsulated by sections of membrane into discrete packages. The packaged units of cellular debris are eventually phagocytized by microglia or macrophages and eliminated from the body completely. Resources Alberts, B., Johnson, A., Lewis, J., Raff, M., Roberts, K., & Walter, P. (2002). Programmed cell death (apoptosis). In B. Alberts, A. Johnson, J. Lewis, M. Raff, K. Roberts, & P. Walter (Eds.), Molecular biology of the cell (4th ed.). New York, NY: Garland Science. Bredesen, D. E. (1995). Neural apoptosis. Annals of Neurology, 38, 839–851. Bredesen, D. E. (2000). Apoptosis: Overview and signal transduction pathway. Journal of Neurotrauma, 17(10), 801–810.

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 FIGURE 2–14.   Oligodendrocytes and Schwann cells are macroglial cells that generate myelin in the CNS and PNS, respectively. Single oligodendrocytes (left-hand side) can myelinate between 30 and 50 different axon segments within the CNS, whereas Schwann cells (right-hand side) will myelinate one segment of a single axon.

when we discuss how electrical impulses rapidly propagate down an axon. The final type of macroglia is the astrocyte and, as the name implies, these are star-shaped glial cells (neuroanatomists are not terribly imaginative folks sometimes). The astrocyte is by far the most numerous of the glial cells and the most functionally complex as well (Vanderah & Gould, 2010). The astrocyte is the chief packing material of the brain, taking up most of the spaces between signaling neurons. As shown in Figure 2–15, these cells also envelope the synaptic regions between neurons (see the black circle), suggesting a structural and metabolic role in neural signaling. The packing nature of the astrocyte, while obviously a good thing for the health of the neuron, can unfortunately turn negative in the case of infiltrating brain cancers. Glioblastomas, one of the most common astrocyte-related cancers of the brain, are devastating because death of an astrocyte invariably means death to the neurons it structurally and metabolically supports. To make matters worse, chemotherapies, radiation, and surgical management approaches are currently incapable of isolating the malignant astrocyte while preserving the health of the neuron. Functionally, astrocytes are principally involved in regulating the concentration of potassium (K+) in the extracellular space during neural signaling. Potassium regulation is important to prevent a breakdown in the signaling capabilities of neurons. Astrocytes are also active in clearing the extracellular spaces near a synapse of the excitatory neurotransmitter glutamate. Astrocytes tightly regulate extracellular levels of glutamate via molecular machinery that shuttles glutamate back into the astrocytes where it is enzymatically broken down into its constituent parts (Herndon, Tome, & Davis, 2017).

Neurons

Synapse

Astrocyte

Capillary

Astrocyte endfeet

Astrocyte endfeet eveloping capillaries form the blood brain-barrier

 FIGURE 2–15.   Astrocytes are macroglial cells that operate to protect and metabolically support signaling neurons in the CNS.

Although glutamate is the chief excitatory chemical neurotransmitter of the nervous system, at high concentrations, glutamate can be toxic to the neuron itself. This situation is

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a fascinating phenomenon known as excitotoxicity, a condition that leads to neuronal cell death and inflammation of brain tissue (Markiewicz & Lukomska, 2006; Swanson, Ying, & Kauppinen, 2004). It has always amazed me that a chemical so toxic to a neuron is the most common chemical used for communication between neurons — one of those ironies of evolution! Excitotoxicity is observed after trauma to the nervous system for three complementary reasons: (a) compromise of the chemical buffering (absorption) role of the astrocyte; (b) release of stores of glutamate from damaged neurons into the extracellular spaces; and (c) excess levels of Ca2+ intracellularly, leading to runaway metabolic processes (Ca2+ is a highly reactive ion that triggers many types of chemical reactions in the cell). These conditions feed on one another, further spiraling and worsening the consequences of the initial trauma. Cells that are most impacted by excessive levels of extracellular glutamate are those surrounding the site of an injury, a region known as the penumbra. Penumbral cells, although still functional, are metabolically fragile and thus susceptible to the cytotoxic effects of extracellular glutamate. Interestingly, these penumbral cells are also negatively impacted by overzealous microglia cells. Controlling both excitotoxicity and microglia-related inflammation may be two approaches to lessening the associated consequences of brain injuries (Swanson et al., 2004). Perhaps most importantly, astrocytes are directly involved in the creation of the blood-brain barrier (BBB) (Herndon et al., 2017). As illustrated in the lower part of Figure 2–15, populations of astrocytes send out processes terminating in hand-like structures called endfeet that rest on small blood vessels and capillaries of the brain. These endfeet attachments form tight junctions with the surface of the blood vessels. Tight junction is a term used to denote a condition where the cell membranes of adjacent cells are virtually linked to one another, forming an impermeable barrier. The BBB is a key protective mechanism of the brain and spinal cord, functioning much like a filtering system to prevent infectious agents, damaging molecules, and certain classes of immune cells from having unrestricted access to the brain. With a few exceptions (e.g., glucose), large molecules (antibodies of the immune system and most synthesized drugs) are excluded by the BBB. In short, the BBB filters the blood supply into a clear watery fluid consisting mostly of glucose and critical ions needed for metabolism and neural signaling. This glucose and ion-rich liquid is taken up by the astrocyte endfeet and transported into the brain, where it becomes the extracellular fluid in which cells of the brain and spinal cord are immersed and bathed. You can see after this brief description that the BBB is, on one hand, a useful mechanism to ensure the protection of the brain from any substance that could compromise neuronal function. On the other hand, the BBB is a major problem and headache in the development of pharmaceutical therapies for neurological diseases, disorders, and injuries.

SECTION 1

Many potentially effective drugs discovered in the lab have been thrown on the trash heap of drug research because they cannot effectively cross the BBB. Recent data have shown that autoimmune and neurodegenerative disorders such as multiple sclerosis and Alzheimer’s, respectively, are correlated to disruption of the BBB. The exact reasons for why this relationship may exist are still being investigated. I’d like to end this section on glial cells by addressing a question students often ask when they are studying the differences between neurons and glial cells: Do glial cells have any role in information processing and neural signaling? Twenty years ago, the answer to this question was a simple “No.” Glial cells were recognized only to provide structural and metabolic support to neurons. Today, the issue is not that clear. There is growing evidence that glial cells may potentially be direct players in information processing — a radically different perspective from the traditional view of glial cells operating as mere support cells (Nedergaard, Ransom, & Goldman, 2003). The discovery of neurotransmitter-sensitive proteins on the cell membranes of astrocytes suggests that glia may be capable, to some extent, of generating electrochemical signals. One can also argue that the buffering and absorption functions of the astrocyte, as described earlier, are required for effective neural signaling and thus should be considered as a part of the complex process that is electrochemical signaling. The jury is clearly still out on these ideas. But I’ve witnessed several dogmas of neuroscience come crashing down in flames over the course of my career. Discovering that glial cells may have a real role in neural signaling would not surprise me a bit.

Conclusion As this chapter has begun to show you, when it comes to understanding the function of the nervous system, we are going to have to take a rather broad view that ranges from the molecular to the macro level. As we alluded to earlier, such an approach is going to be necessary to fully appreciate the operation of the nervous system during behavior. If you take anything away from this chapter, remember first that neural cells can be divided into two broad classes, signaling neurons and glial cells, with each type possessing a variety of shapes, sizes, and functions (Figure 2–16). Our key interest, when it comes to behavior, will always be with the signaling variety. Second, also keep in mind that signaling neurons are important, but the operation of populations of interconnected neurons is where the real magic happens when trying to understand the neural bases of behavior. As you continue with the next chapter, come back to this one often to remind yourself of the idea that cooperative activity in populations of neurons is what matters the most to understanding behavior. Placing what you will be learning in the context of neural population activity will go a long way to help you more fully

CHAPTER 2   Basic Structure and Function of Neurons

Signaling neurons

37

A erent E erent Interneurons

Neuron type

Microglia Glia

Astrocyte Macroglia

Oligodendrocyte Schwann cell

 FIGURE 2–16.   Concept map of neuron types in the nervous system.

understand large-scale neural processes such as motor control, emotion, sensation, perception, and cognition. In the next chapter, we explore the neurobiological basis of what

constitutes “neural information” and come to an understanding of how information is transmitted and shared among signaling neurons comprising any given neural network.

Box 2-6. Activity:  Building 3D Pipe Cleaner Neurons and a Simple Neural Network For this activity, you will use colored pipe cleaners to construct three 3-dimensional (3D) neurons for your use to understand the basic structural and functional elements of a neuron and to appreciate neuron-to-neuron communication. A 3D neuron is far more realistic than a flat two-​ dimensional (2D) image or drawing. Viewing a neuron in 3D and arranging several of them together into a network will allow you to appreciate the complexity of neuronal structure and connectivity. The goals of this activity are: • To have you learn about the main parts of a neuron through a hands-on activity. • To visualize and appreciate neurons as 3D objects and not just 2D pictures. • To appreciate the complexity of several neurons connected to each other in a simple network. Supplies

• A package of pipe cleaners with at least six different colors available in the package • Scissors • A note card and colored markers or pencils Instructions

1. You will use Figure 2–1A and B to guide you as you construct your three 3D neurons. You can also use the

sample picture provided in Figure 2–17 to give you a visual idea of how to build a 3D pipe cleaner neuron and a simple network. 2. To begin, choose any six colors of pipe cleaners you like and assign each color to one of the six main elements that neurons possess (1) dendrites, (2) soma, (3) axon hillock, (4) axon and collaterals, (5) myelin, and (6) presynaptic terminals. 3. Use the same color scheme for each of your pipe cleaner neurons for consistency and use your scissors to trim the length of your pipe cleaners as needed (see left side of Figure 2–17). 4. Make sure that the axon on each 3D neuron has several axon collaterals (see Figure 2–1B and left side of Figure 2–17). 5. Use a note card to make a color-coded “key” to indicate what color pipe cleaner corresponds to each element on your models. 6. Once you build your three 3D neurons, arrange them into a network pattern of your choosing based on the cell arrangements found in Figure 2–12, and appreciate the complexity that only three neurons can create (see right side of Figure 2–17 for an example of a simple network arrangement).

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Box 2–6.  continued

 FIGURE 2–17.   Pipe cleaner neurons and a simple neural network.

7. As you perform this activity, think about all the available locations where other neurons could synapse on to your three neurons and the volume of inputs and outputs that just three neurons can manage. You’ll

soon realize the sheer complexity of neuronal networks (populations) under more realistic conditions, where thousands of cells are all interconnected

The Top Ten List 1. Advancements in our appreciation of the cellular neurobiology of the nervous system have led to an explosion in knowledge about the role that nervous system cells have in the complex expression of animal behavior. 2. Neurons are highly excitable cells capable of generating and transmitting electrical signals over a wide

range of physical distances in response to environmental changes. Rapid shifting of electrical activity in a neuron is made possible by the presence of specific protein structures on the neuron’s cell membrane that regulate the motion of charged particles, called ions, into and out of the cell.

CHAPTER 2   Basic Structure and Function of Neurons

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The Top Ten List  continued

3. A neuron possesses four functional and structural zones necessary to fulfill its role in signal transmission and neuron-to-neuron communication. The structural features of a typical neuron include the soma or cell body, axons, dendrites, and the presynaptic terminal. 4. Neurons never work in isolation, but rather are arranged into functional collections or interconnected populations that share common inputs and outputs. It is a population of neurons working cooperatively that forms the decision-making unit for behavior. 5. Neurons come in different shapes, sizes, forms, and functional characteristics. 6. The soma is the structural, metabolic, and genetic center of the neuron. From the soma arise two major extensions of the cell membrane — the dendrites and axon. Both structures are highly specialized cell components that operate as the chief input and output sites of the neuron, respectively. 7. Gene expression is a key role of the nucleus. Gene expression entails two critical processes — transcription and translation. Transcription is the process of copying sequences of nucleotides from DNA to form a single

strand of mRNA. Translation is the decoding or reading of the copied nucleotide sequences on mRNA into chains of amino acids. Amino acid chains are further processed into functionally active proteins by different organelles in the cell. 8. The axon constitutes the chief output pathway of a neuron. Axons originate from a location on the soma called the axon hillock. The axon hillock is specialized to generate the chief signal of the neuron, the action potential. 9. The dendrite is the chief input site of the neuron and is covered with synapses. Many dendrites have small protrusions called dendritic spines that house numerous cellular structures essential for modification of the synapse with behavioral experience. 10. Glial cells operate as key support cells, helping to generate the internal structural framework of brain tissue and metabolically working to maintain the health of signaling neurons. Glia cells are structurally distinct from signaling neurons in that they do not have axons or dendrites.

Chapter 2 Abbreviations ADP — Adenosine diphosphate

DNA — Deoxyribonucleic acid

NMJ — Neuromuscular junction

ATP — Adenosine triphosphate

ER — Endoplasmic reticulum

tRNA — Transfer ribonucleic acid

BBB — Blood-brain barrier

K+ — Potassium ion

Ca2+ — Calcium ion

mRNA — Messenger ribonucleic acid

Study Questions and Activities • What was the significance of the cell doctrine, and how did it impact our early appreciation and understanding of the form and function of the neuron? • Compare/contrast the neuron with the glial cell with at least three different characteristics. • Explain why losing one or two neurons in an area of the brain would not be of any concern to the area’s ability to process signals.

• Develop your own real-world analogy for the idea of population coding. For example, one analogy is of a group of friends with different food preferences trying to decide where to go out and eat dinner together. • Draw or sketch a simple multipolar neuron. Label its major elements. Next to each label, add a 5- to 10-word description of the element. (Include just enough detail to cue your memory.)

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Study Questions and Activities  continued

• List and briefly describe the fundamental activities of a neuron. • What lessons about the operation of the nervous system were learned from our discussion on the knee-jerk reflex? • Create a simple chart that summarizes the structural features of a typical neuron. • What is the importance of knowing something about DNA and protein synthesis?

References Alberts, B., Johnson, A., Lewis, J., Raff, M., Roberts, K., & Walter, P. (2002). The cell cycle and programmed cell death. In B. Alberts, A. Johnson, J. Lewis, M. Raff, K. Roberts, & P. Walter (Eds.), Molecular biology of the cell (4th ed., pp. 983–1026). New York, NY: Garland Science. Allen, N. J., & Barres, B. A. (2009). Neuroscience: Glia — more than just brain glue. Nature, 457(7230), 675. Bear, M. F., Connors, B. W., & Paradiso, M. A. (2016). Neuroscience: Exploring the brain (4th ed.). Philadelphia, PA: Wolters Kluwer. Bredesen, D. E. (1995). Neural apoptosis. Annals of Neurology, 38, 839–851. Bredesen, D. E. (2000). Apoptosis: Overview and signal transduction pathway. Journal of Neurotrauma, 17(10), 801–810. Carpenter, M. B. (1991). Core text of neuroanatomy (4th ed.). Baltimore, MD: Williams & Wilkins. Crick, F. (1999). The impact of molecular biology on neuroscience. Philosophical Transactions: Biological Sciences, 354(1392), 2021–2025. Gelehrter, T. D., Collins, F. S., & Ginsburg, D. (1998). Principles of medical genetics (2nd ed.). Baltimore, MD: Williams & Wilkins. Georgopoulos, A. P., & Carpenter, A. F. (2015). Coding of movements in the motor cortex. Current Opinion in Neurobiology, 33, 34–39. Guyton, A. C., & Hall, J. E. (2006). Textbook of medical physiology (11th ed.). Philadelphia, PA: Elsevier Saunders. Haines, D. E. (2013). Fundamental neuroscience: For basic and clinical applications (4th ed.). Philadelphia, PA: Elsevier Saunders. Hall, Z. W. (1992). An introduction to molecular neurobiology. Sunderland, MA: Sinauer Associates. Herndon, J. M., Tome, M. E., & Davis, T. P. (2017). Development and maintenance of the blood-brain barrier. In L. R. Caplan (Ed.), Primer on cerebrovascular diseases (2nd ed., pp. 51–56). London, UK: Academic Press. Kandel, E. R., Barres, B. A., & Hudspeth, A. J. (2013). Nerve cells, neural circuitry, and behavior. In E. R. Kandel, J. H. Schwartz,

• Explain the process of transcription and translation by creating a flowchart that characterizes the steps and events in each process. Be sure to include all the major players in your flowchart (e.g., mRNA, tRNA, codons). • Create a simple chart that lists the different features and operations for microglia and macroglial cells.

T. M. Jessell, S. A. Siegelbaum, & A. J. Hudspeth (Eds.), Principles of neural science (5th ed., pp. 126–147). New York, NY: McGraw-Hill. Kiernan, J. A. (2005). BARR’s the human nervous system: An anatomical viewpoint (8th ed.). Pennsylvania, PA Lippincott Williams & Wilkins. Kohn, A., Coen-Cagli, R., Kanitscheider, I., & Pouget, A. (2016). Correlations and neuronal population information. Annual Review of Neuroscience, 39, 237–256. Markiewicz, I., & Lukomska, B. (2006). The role of astrocytes in the physiology and pathology of the central nervous system. Acta Neurobiologiae Experimentalis, 66, 343–358. Nedergaard, M., Ransom, B., & Goldman, S. A. (2003). New roles for astrocytes: Redefining the functional architecture of the brain. Trends in Neurosciences, 26(10), 523–530. Paxinos, G., & Mai, J. K. (2004). The human nervous system (2nd ed.). London, UK: Elsevier Academic Press. Purves, D., Augustine, G. J., Fitzpatrick, D., Hall, W. C., LaMantia, A., Mooney, R. D., . . . White, L. E. (2018). Studying the nervous system. In D. Purves, G. J. Augustine, D. Fitzpatrick, W. C. Hall, A. LaMantia, R. D. Mooney, . . . L. E. White (Eds.), Neuroscience (6th ed., pp. 1–29). Sunderland, MA: Sinauer Associates. Schwartz, J. H., Barres, B. A., & Goldman, J. E. (2013). The cells of the nervous system. In E. R. Kandel, J. H. Schwartz, T. M. Jessell, S. A. Siegelbaum, & A. J. Hudspeth (Eds.), Principles of neural science (5th ed., pp. 126–147). New York, NY: McGraw-Hill. Stephenson, J., Nutma, E., van der Valk, P., & Amor, S. (2018). Inflammation in CNS neurodegenerative diseases. Immunology, 154(2), 204–219. Swanson, R. A., Ying, W., & Kauppinen, T. M. (2004). Astrocytes influences on ischemic neuronal death. Current Molecular Medicine, 4(2), 193–205. Vanderah, T. W., & Gould, D. J. (2010). Nolte’s essentials of the human brain (7th ed.). Philadelphia, PA: Mosby Elsevier. Weiss, P., & Hiscoe, H. B. (1948). Experiments on the mechanism of nerve growth. Journal of Experimental Zoology, 107(3), 315–395.

CHAPTER 3 Basics of Neural Signaling and Synaptic Function Richard D. Andreatta Introduction and Learning Objectives

quite distant from speech, language, and hearing behavior, take the time to really understand and visualize what we are going to discuss. We begin with a brief tutorial on the nature of electricity and the idea of gradients. These two topics are a necessary evil because they give us the language and understanding needed to appreciate the very nature of electrochemical signaling and make understanding the process of neural signaling that much easier. Second, we discuss the fluid environment that the neuron exists in, followed by a description of mechanisms that maintain the neuron in a “primed” or resting state, ready to generate various forms of electrical signals. Third, we discuss the generation of the action potential and why this brief and fleeting electrical signal is central to information management in the nervous system. At this point, we’re ready to discuss the operation of the synapse and the process of information transfer from one neuron to the next. During this discussion, we delve into the details of the second form of neural signaling: chemically related signaling at the synapse and intracellular communication. Finally, once we’ve developed all of these concepts, you’ll be set to fully appreciate the manner in which neurons integrate information and “cast their vote” within a population of neurons. To this end, after completing this chapter, you should be able to meet the following learning objectives:

You survived Chapter 2! Excellent! Now that you have a good foundation on the structural and general functional properties of the neuron, the time has come to take all these parts and pieces and place them in the context of neurophysiology. The neurophysiology I’m referring to is neural signaling. In neuroscience, we use the term “information” as shorthand for the electrochemical signals generated by single neurons as well as by populations of them. Neural signals (electrical and chemical) are our “coin of the realm” and represent the actual information that is processed by the nervous system. Electrochemical processes underlie your ability to combine novel real-world inputs with your remembered experiences, or to influence the learning and expression of any behavior you could possibly perform. If you stop for a moment and think about the implication of this idea, what you will realize is that all behaviors, whether they are internalized thoughts or externally observable actions, are the result of electrochemical changes in the state of complexly interconnected populations of neurons. This may sound rather reductionist — as if I’m saying that we are nothing more than electrochemical changes occurring in a lump of tissue — but that couldn’t be farther from the truth. As I like to say to my students, understanding the compositional details (e.g., notes, harmonies, rhythms) of one of your favorite songs doesn’t take anything away from its beauty and how it makes you feel. Similarly, the brain is the most complex object in the known universe. The fact that our consciousness, mind, and ability to affect the world around us are the ultimate expression of electrochemical signaling is a marvelous and truly fantastic idea to contemplate and study! Once again, let me remind you that while this information may seem rather abstract and remote from speech-language pathology and audiology, what we are learning here are essential neurobiological features of ALL behaviors. With this knowledge in your professional toolbox, you’ll be prepared to understand so much more scientific and medical literature discussing speech-hearing-language production. Understanding how a neuron creates a signal and shares that signal with other neurons is at the core of understanding higher-level brain function during all behaviors, including speech. In the end, it will be your future patients and clients who will benefit the most from your studies in neurobiology. In this chapter, we develop, step-by-step, the bases of neural signaling. While many parts of this chapter may seem

• Understand and explain the electrochemical nature and foundations of neural signaling. • Describe, in a general manner, basic principles related to electricity. • Identify and describe the function of passive and gated ion channels. • Describe the process and importance for developing the resting membrane and action potentials in the neuron. • Identify the structural features of the synapse and explain their operation relative to successful neural signaling. • Identify and define major classes of neurotransmitters and relate each to changes in the quality of neural signaling. • Describe the process of synaptic transmission and explain how it fits into neuronal communication. • Explain the basic mechanisms for how different forms of neural signals are combined. • Summarize and explain the mechanisms underlying neural integration that are needed to share signals across a network of neurons. 41

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Neuroscience Fundamentals for Communication Sciences and Disorders

Foundations of Neural Signaling:  The Nature of Information in the Nervous System A good way to approach the topic of neural signaling is to first appreciate that neural signaling can be divided into two major forms: (a) neural signals created through the interaction of chemicals and/or specialized proteins and enzymes located on the neuron’s cell membrane or within the cytosol and (b) electrical signals generated by the motion or flow of charged particles across the neuron’s cell membrane (Hall, 1992). Chemical signals are related to (1) information transfer across the synapse and (2) intracellular signaling via biochemical reactions. Electrical signaling is commonly found in all areas of the neuron to different degrees. The fact is that the cellular machinery behind chemical signaling depends on the ability of the neuron to generate and propagate (transmit) electrical signals. As such, electrical signals are of particular significance to us and important toward understanding information transmission and processing in the nervous system. Electrical signals are the means for carrying information quickly over long distances and for initiating the chemical systems that will transfer information from one neuron to the next. This implies that chemical and electrical signaling are necessarily bound together to create and move information throughout the nervous system. Because of the critical importance of electrical signaling, though, we need to develop an intuitive understanding of the nature of how neurons generate electrical signals. Who knew that you would be learning a little basic electrical engineering in a neuroscience textbook for communication sciences and disorders (CSD) students?

Electronics 101 In the following section, we will describe and discuss the basic elements and principles of electricity. While this might seem very abstract at this point in time, keep in mind that these concepts and terminology will be used later in the chapter to help you understand how neurons develop and use electrical energy as a means of signaling and information processing. As I like to always say to my students, “Everything we do has a purpose!”

Gradients:  Putting Substances Into Motion To understand the electrical nature of neural signaling, what we first must do is become familiar with a few conceptual ideas related to electricity. Electricity is created through the motion of charged particles along a pathway or through the accumulation of different types of charged particles across some form of barrier or wall. Directly implied in this statement is the idea of charged particles being placed into motion or moved in some manner from one location to another.

SECTION 1

This “movement” is accomplished through the development of driving forces that can place particles such as ions (electrically charged atoms) and other chemicals into motion. Let’s begin the discussion of driving forces with the concept of concentration gradients (also known as chemical gradients) because this is an idea we all have some real-world experience with (Andreatta, 2010; Decker & Carrell, 2004; Silverman, 1999). Imagine you have a packet of green Kool-Aid and a large glass container of water divided into two halves by a solid wall. (When I was a kid in New Jersey, we used to call green Kool-Aid bug juice! Doesn’t that sound refreshing?) Let’s say you drop the contents of the green Kool-Aid packet into the left side of the container of water. What naturally happens? The green powder at first is highly concentrated at the very top of the left side of the container, but slowly, the green powder begins to spread all throughout the water on the left-hand side (remember that the barrier is keeping the water on the left side of the chamber separate from that on the right side). If you leave the left-hand chamber of water alone for a couple of hours, what you’ll see is that the green drink mix eventually distributes itself evenly and uniformly on the left-hand side. The right side of the container, though, remains perfectly clear because the solid wall prevents any of the KoolAid solution on the left from crossing over to the right. This exact scenario is illustrated in Figure 3–1A, except that rather than green Kool-Aid, what is distributed on the left are Na+ ions (green dots). In our simple Kool-Aid example, we have demonstrated two key ideas that you will need to remember as you more forward: (a) On the left side of the container, a concentration gradient is developed and expressed through simple and passive diffusion of the green powder throughout the water, and (b) a second, yet fixed, concentration gradient is also being created between the water on the left- and righthand sides of the container. Let’s now define the concept of a concentration gradient a little more explicitly. A concentration gradient is simply a condition where the quantity of a substance (e.g., chemicals, ions, puppies, kittens, kittens dressed as puppies, people, Kool-Aid mix) is unequally distributed or changes over a given area or distance. If two areas with different concentrations (amounts of something) for a given substance are connected to each other in some manner, the gradient will be allowed to express itself or “run” from the region with the higher concentration of that substance to the region with the lower concentration. In our Kool-Aid example, the moment you dropped the green powder into the left side of the container, you created a concentration gradient for the powdered mix between the top of the container (bright, green-colored water) and the bottom of the container (clear water) on the left side. Diffusion, the movement of a substance from an area of high concentration to low concentration, was the force that placed the green-​ colored granules of the drink mix into motion. Leaving the left side of the container alone for a few hours demonstrated that a concentration gradient will continue to run until a

CHAPTER 3   Basics of Neural Signaling and Synaptic Function

a.

b.

43

c.

Na+

Na+

Na+

 FIGURE 3–1.   Concentration gradients are driving forces. A. Concentration gradients are created by conditions where the quantity of a substance is unequally distributed across two areas. B. Concentration gradients are allowed to run if two areas are physically connected to each other. Concentration gradients will always run from a region of higher concentration to that of lower concentration. C. Given enough time, concentration gradients will result in an equal distribution of the substance across both areas, a state we define as equilibrium.

state of uniformity or equilibrium is achieved. What was also shown in our Kool-Aid example was that if you separate two areas (left vs. right sides of the container) with an impermeable barrier, you prevent a concentration gradient from running. Another way to think about these two examples (diffusion in the left side of the container vs. keeping a fixed gradient between the left and right sides of the container) is in terms of the development of kinetic versus potential energy, respectively. A concentration gradient that is allowed to run is in effect creating or relying upon kinetic energy to drive the motion of a substance from its high to low concentration region. On the other hand, a concentration gradient that is held constant because of a barrier between two areas (as in the case between the left and right sides of our container) has a great deal of potential energy stored. The concentration gradient across the barrier has the “potential” or “capacity” or “ability” to place that substance into motion IF a pathway is available between the two regions (Andreatta, 2010). By adding a portal or tunnel through the barrier as is shown in Figure 3–1B, we can now physically link the left- and righthand sides of the container. Substituting our Kool-Aid mix with Na+ ions, as expected the potential energy of the concentration gradient across the barrier is now converted into kinetic energy, and Na+ ions begin moving toward and into the right side of the container. As in the Kool-Aid example, if we let some time elapse, the concentration gradient will run until the ions are evenly distributed across both sides of the barrier (Figure 3–1C). The take-home message to all this discussion is simply this: Concentration gradients have the potential of placing substances into motion if two conditions exist: (a) The distribution of a substance is unequal across adjacent areas, creating a region of high concentration versus low concentration of that substance, and (b) a pathway is available that allows for the concentration gradient to “run” toward its equilibrium state.

Developing an Electrical Gradient As we saw in the previous Kool-Aid example, concentration gradients can provide a driving force to place substances into motion due to the unequal distribution of that substance across two or more areas. Aside from concentration gradients, though, there is another means of putting substances into motion across a barrier, and that is through the development of an electrical gradient (Andreatta, 2010; Decker & Carrell, 2004; Silverman, 1999). Let’s begin our understanding of electrical gradients by getting a handle on the nature of the driving force underlying this specific form of gradient. Electrical gradients create driving forces based on attraction and repulsion behaviors of charged particles generated by force fields. Yes, force fields! Now, I’m not talking about force fields like you would see in Star Trek, but rather force fields that operate to attract or repel particles to and from one another, respectively. To understand this idea more concretely, let’s use two magnets to provide an intuitive appreciation and visible simulation of what force fields are and what they can do (Figure 3–2). We’ve all experienced what happens when you take two magnets and try to force the same poles of the magnets together (north to north, or south to south). It’s very hard to do, and in fact what you typically experience are the magnets wanting to repel away strongly from each other (Fig­ ure  3–2A). If you place one of the magnets on a smooth table, you can demonstrate to yourself how repulsion forces can move the magnet about the table’s surface. Using the second magnet that you are still holding, orient it so that identical poles are facing each other. By approaching the magnet on the table with the one in your hand, you can now move and push around the one on the table using repulsive forces. Of course, you could also do the opposite and attract the magnet on the table toward the one in your hand simply by flipping one of the magnets so that opposite poles are facing

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Neuroscience Fundamentals for Communication Sciences and Disorders

SECTION 1

Na+ Cl–

 FIGURE 3–2.   Magnets can be used to intuitively feel a force field at work. Magnets can create repulsion and attraction force fields depending on how the poles of the magnets are arranged. Trying to put together two like poles will result in repulsion forces, while attempting to touch opposite poles will result in attraction forces.

each other (Figure 3–2B). (This is a fun game to play with little kids. They’ll think you’re magical!) The tactile “feeling” of repulsion or attraction experienced through your fingers as you do this demo are force fields — albeit magnetic ones, but force fields, nonetheless. Now, let’s make the connection between our intuitive idea of force fields and the attractive/ repulsive forces developed by electrical gradients. Thinking back to a chemistry class long, long ago, you may recall that an atom typically has an equal number of positively charged protons and negatively charged electrons, giving the entire atom a net electrical charge of zero; the number of proton charges balances out the number of electron charges. You may also recall that atoms that have either lost or gained an electron are referred to as ions. Positive ions are those that have lost an election (protons outnumber electrons), whereas negative ions are those that have gained electrons (electrons outnumber protons). Ions are quite interesting because they are simultaneously a chemical (an atom) and a charged particle (like a proton or an electron). This fact is going to play a significant role in your future understanding of neural signaling, so you may want to bookmark this idea. If we take a positive and negative ion and pay attention only to its electrical charge properties for now, we can say that its electrical charges are like the poles of our magnets in the force field example, such that opposite charges (or poles) will attract each other while like charges will repel one another. These attraction/repulsion forces happen to be of fundamental importance to understanding how electrical gradients develop driving forces that move charged particles along a pathway. Consider the example in Figure 3–3, where the positive and negative ends of a battery are placed into a water bath of dissolved table salt (NaCl). Much like a concentration

 FIGURE 3–3.   Batteries can generate electrical force fields. In this illustration, the positive and negative ends of a battery are placed into a water bath of dissolved table salt. Na+ will be attracted to the negative terminal, while Cl− will be drawn toward the positive terminal. Water forms the pathway through which the electrical force field is generated. Repulsive and attraction forces become the energy to drive the motion of electrically charged particles in a given direction.

gradient needs a pathway to run, so too does an electrical gradient. Because the battery’s terminals are suspended in the bath, the water is creating a connection between the battery’s ends, allowing for the development of an “electrical” force field between the two terminals that is capable of attracting and repelling ions. Because Na+ is a positive ion, it will be attracted to and flow toward the negatively charged end of the battery, while the negatively charged Cl− ion will be attracted to and flow toward the positive end of the battery. The attraction and repulsion forces that are created become the energy for “driving” or “pushing” the electrically charged particles in a given direction along a pathway (Andreatta, 2010; Decker & Carrell, 2004; Silverman, 1999). In the nervous system, electrically charged particles are ions, and our pathways are fluid tunnels embedded in the cell membrane of a neuron that allow for the selective passage and motion of ions across the neuron’s cell membrane. Regardless of whether we are talking about batteries or neurons, these flows or currents of charged particles go by the same name: electricity.

Voltage, Current, and Resistance Electricity is a process and the outcome of many factors and basic physical forces interacting. Electricity emerges through the motion of charged particles along a pathway, or by the

CHAPTER 3   Basics of Neural Signaling and Synaptic Function

accumulation and separation of charges across a barrier. The electrical gradient (our attraction and repulsion forces) become the driving forces for generating charged particle flows. As we have seen already in Figure 3–3, a tangible and very portable form of electricity is a typical household battery. Let’s take a closer look at how batteries work to understand why they are a portable form of electrical energy. By design, batteries basically consist of two chambers, each filled with a chemical cocktail that either has a measurable positive or negative electrical charge. These chambers are kept separate from each other by a thin barrier that prevents the oppositely charged contents of each chamber from interacting with the other. As such, batteries are an excellent means of storing potential electrical energy for later conversion into a force field that can place charged particles into motion when the two ends of the battery are physically linked together. An analogy to intuitively appreciate this idea is of a parent holding a child by the hand as they enter a toy store. Toy stores, as we all know, are sources of everything wonderful for young children. Upon entering the store, every child wants to break from their parent and play with all the toys. The “potential” for interaction between the toys and the child is ever present (like a new unused battery), but that “energy” is prevented from being expressed by the parent firmly holding onto the child’s hand (much like the barrier inside the battery and the unconnected terminals). The moment the parent lets go of the child (connecting the battery’s terminals together to generate a driving force), all that pent-up potential energy is now transformed into kinetic energy, and the child is running off to his favorite toy aisle to play or find something for you to buy him (flow of charged particles is created). The potential energy that is stored in the unused battery due to the separation of charges and used to create the driving force for charged particle motion once the positive and negative terminals of the battery are connected is called voltage (V) (Andreatta, 2010; Decker & Carrell, 2004; Silverman, 1999). The term voltage describes the magnitude of potential energy a force field possesses. Thinking of voltage another way: It is a measure of the magnitude or degree of positive and negative charge separation between the two chambers of the battery. The greater the difference, the greater the voltage or potential energy that is stored in the battery. Thus, when a conductor or physical pathway connects both ends of a battery, the positive and negatively charged chambers are now allowed to interact, and the stored potential energy is then converted into the kinetic energy, which is needed to put our charged particles into motion (Figure 3–4). In a very real way, the voltage of a battery is a two-way electrical gradient: The first gradient creates the driving force to move positive charges (like Na+) toward the negative pole, while the second gradient is trying to do the opposite, by moving Cl− toward the positive pole. Voltage is not only potential energy capable of being stored, but it is also a driving force, created by the gradient of charges stored in the battery, causing charged particles to flow and move.

45

Na+

Cl Cl–

 FIGURE 3–4.   Voltage results from the separation of charged particles across a barrier. In this illustration, the battery terminals are placed in a water bath of salt that is divided in half by a phospholipid bilayer. Each side of the bath will create a force field that will attract either Na+ or Cl− to it, creating a situation whereby Na+ accumulates on one side and Cl− accumulates on the other. This situation arises because there are “tunnels” (ion channels) spanning the membrane that allow for only one type of ion to pass.

A good way to concretely conceptualize the idea of voltage as both potential energy and a driving force is to relate it to our everyday experiences with a force we are all familiar with — gravity. So, let’s take a water tower that you would see in any town and connect it to an empty drainage pool on the ground via a large diameter pipe (Figure 3–5) (Andreatta, 2010). Intuitively, we know that the water held within the tower will naturally flow into and down the pipe, draining into the pool because of gravity’s pull on the water suspended off the ground. In this case, gravity, like voltage, is a driving force because it will set the suspended quantity of water in the tank into motion. Another way you can think about this is by realizing that when you suspend the water above the earth, you are creating a “water gradient” between the tower (where all the water is located) and the earth’s surface (location of the empty drainage pool). Because gradients want to run toward a state of equilibrium, gravity forces the water in the tank into motion down the pipe and into the pool. (Do you see yet how this is all starting to fit together?) Now, if the pipe connecting the water tower and the pool is valved shut, then gravity acting on the water can be characterized as potential energy waiting to be transformed back into a driving force when the pipe’s valve is opened. As such, voltage is to electricity as gravity is to the mass of the water — forces that can both be

46

Neuroscience Fundamentals for Communication Sciences and Disorders

SECTION 1

Gravity

Water tank

Pool of Water

 FIGURE 3–5.   Water tower analogy for understanding voltage, current, and resistance.

stored and transformed to drive and set charged particles (or water molecules) into motion. One last thing before we move forward: For the reasons described earlier, voltage is also referred to as an electrical potential, or simply a potential. This alternative term for voltage captures the idea of voltage having potential energy that can place charged particles into motion. You are going to encounter many terms throughout the text that end with the descriptor potential, such as “membrane potential,” “action potential,” “postsynaptic potential,” and “receptor potential,” to name just a few. Realize that what is being described is just a voltage, simply the magnitude of the separation of charges that exists across a barrier. In the neuron’s case, we will see that the barrier is the cell membrane . . . but more on this later on! The next basic electricity principle needed to understand electrical gradients and their driving forces is current (Andreatta, 2010; Decker & Carrell, 2004; Silverman, 1999). Returning to the water tower example, we can measure the flow of water through the pipe by selecting any point along its length and determine the quantity of water that passes by that point in 1 second of time. This measure is what we would refer to as water current. Similarly, electrical current through a conductor or pathway is simply the quantity of charged particles traveling through a point along a conductor in 1 second of time. Now, it is virtually impossible to count all of the individual water molecules, let alone all the charged particles passing by some point in space in a second. To make our calculation of current much easier, we use a quantity that reflects a fixed but huge number of water molecules or par-

ticles. For example, a liter and a gallon are common quantity units for water. The equivalent quantity unit for charged particles is called the coulomb (C). Like calculating water flow in terms of liters or gallons per second, electrical current is expressed in coulombs per second and designated as the ampere (A). Thus, whether we’re talking about water molecules or charged particles, the concepts of flow and current are the same — a fixed quantity of a substance moving past a point in space within a defined span of time. Perhaps the easiest of the basic electricity principles to appreciate is resistance. Resistance is an inherent property of electrical components that influences, to some degree, the ease with which electrical current can flow (Andreatta, 2010; Decker & Carrell, 2004; Silverman, 1999). The unit of measure for electrical resistance is the ohm (Ω), with higher values indicating greater levels of resistance, and vice versa. An easy way to conceptualize resistance is to imagine putting obstacles in the path of an electrical current, much like rocks, fallen trees, or dams can restrict and impede the natural flow of water in a river. All components in an electrical device have some measurable amount of resistance. To control the motion of electricity more precisely in a device, electrical components called resistors are placed at strategic locations within an electrical circuit to change current flows through different parts of a device. Volume control knobs on car radios or cellphones, dimmer light switches, and temperature control dials on your toaster or oven are all common examples of resistive elements that we use each day and don’t even know it. The property of resistance can be directly observed through a component’s response to the application

CHAPTER 3   Basics of Neural Signaling and Synaptic Function

of electrical energy. In other words, resistance allows for the conversion of electricity into other useful energy states, such as mechanical work, light, sound, and heat. In turn, it is these energy states that provide so much of the useful work and functionality of a device that we enjoy. For example, the reason why lightbulbs shine is because of the resistive filaments within the bulb. As current flows through the bulb’s filaments, their resistance creates friction and heat, which in turn causes the filaments to glow and produce visible light. Having reviewed the concepts of voltage, current, and resistance in the previous sections, the last step is to appreciate that these three factors are all related to one another. Georg Simon Ohm (the namesake of our measure of resistance) described what has become the most fundamental theorem in electronics: Ohm’s Law (conveniently named after Professor Ohm). The theorem states that voltage is the product of current and resistance, written symbolically as V = I × R, where V is the voltage, I represents current in amps, and R represents resistance in ohms. Ohm’s Law tells us that voltage, current, and resistance are fundamentally intertwined, with a change in one variable leading to a compensatory change in the two remaining variables. Ohm’s Law, while a deceptively simple equation, is a powerful means of not only understanding and predicting the operation of all types of electrical devices, but also a means of describing the fundamental and functional electrical properties of the neuron. (Portions of this section on electronics theory were derived from Andreatta, R. D. (2010). Basic electronics theory for the practicing clinician. Perspectives on Speech Science & Orofacial Disorders, 20(2), 25–54. Used with permission from the American Speech-Language-Hearing Association, Rockville, MD.)

The Fluid Environment of the Neuron:  Intracellular and Extracellular Composition We’ve all heard some variation of the idea that the environment we live in strongly influences the way we behave. This notion is also true for the neuron. In fact, I would go as far as

47

to say that without the form and nature of the environment in which neurons exist, neural signaling would not be possible. Environments matter greatly! The environment of the neuron, both internally and externally, is comprised mostly of water. Within the fluid of the intraand extracellular spaces are four ions distributed in an uneven manner across the neuron’s cell membrane (Hall, 1992). The four principal ionic players are sodium (Na+), chloride (Cl−), potassium (K+), and calcium (Ca2+). In addition to these ions, there is one large molecular-weight, inorganic, and negatively changed protein (called an anion) trapped intracellularly that gives the intracellular space of the neuron an inherent negative bias. As seen in Table 3–1, the principal ionic and inorganic proteins each have different concentrations inside versus outside of the cell. K+ is high in concentration internally but low externally, whereas Na+, Cl−, and Ca2+ each have the opposite concentration distributions. In the case of the large negatively changed anions, they are, for the most part, present only within the neuron (Purves et al., 2012a). Why should we care about how charged particles are distributed across a barrier like the plasmalemma (cell membrane) of the neuron? (Hint: Go back and reread the section on gradients.) We need to care about gradients created by the unequal distribution of charged particles across the cell’s membrane because they create driving forces that can make these ionic players move in predictable directions. It’s not enough for me to open the back door of my house to allow my Golden Retriever, Stella, to come back inside; Stella would much rather stay outside and chase rabbits. She must have some “force” applied to get her moving through the door and into the house. (In her case, the “force” is her overpowering love of Cheetos!) Remember, as we have indicated earlier, gradients are forces that place ions into motion and create currents of electrically charged ions. These currents are the bases of neural signaling in the nervous system. As illustrated in Figure 3–6, due to the unequal distribution of ions across the cell membrane, when a pathway is present for an ion, the concentration gradients that emerge will move each ion in the following manner: K+ is driven out of the cell, while Na+, Ca2+, and Cl− are all driven into the cell.

 TABLE 3–1.   Distribution and Concentration of Ions in the Intra- and Extracellular Fluids of the Neuron Charged Particle

Intracellular Concentration

Extracellular Concentration

Ratio Intra (in) : Extra (out)

Na+

Low

High

1:10

K+

High

Low

20:1

Cl-

Low

High

1:12

Ca2+

Extremely low

High

1:10,000

Inorganic anions — A-

High

Absent

none

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Neuroscience Fundamentals for Communication Sciences and Disorders

Ca2+

Na+

SECTION 1

K+ Channel

Ca2+ Channel

Na+ Channel

Cl- Channel

Ca2+

Na+

K+

Cl-

Cl-

K+

Anions-

Direction of Concentration Gradients for Extra- & Intracellular Ions

 FIGURE 3–6.   A generic neuron is depicted within a typical ionic environment. Ionic concentration gradient current directions through passive ion channels are shown by the arrows. The size of an ion’s label indicates the relative amount (concentration) of that ion intra- or extracellularly. Large labels indicate higher concentrations of an ion, and vice versa.

Ion Channels:  Tunnels Across the Neuron’s Cell Membrane As already discussed, any time you have electrically charged particles in motion along a pathway, you have electricity. The question is now, what exactly is the nature of the pathway through which ions in the extra- and intracellular fluid move across the cell membrane? We have the force to move ions in the form of gradients, but what we don’t have yet is the physical pathway to allow for the expression of those gradients. Ions, unfortunately, cannot simply diffuse passively through the phospholipid bilayer of the cell membrane. Ions are highly hydrophilic, which means that they attract water molecules around themselves, making them unable to slide through the hydrophobic inner core of the cell membrane’s bilayer. So, what is the solution to our problem? If ions can’t slip through the bilayer and they can’t go around and bypass the cell membrane in some way, the only solution left is to build a passageway through the membrane. And that’s exactly what nature as engineered for us: the ion channel. For all intents and purposes, an ion channel (or “channel” for short) is a tunnel or fluid bridge through the phospholipid bilayer of a neuron, allowing for direct communication of the extracellular fluid with the intracellular space (Siegelbaum & Koester, 2013). Channels are not simply holes punched through the cell membrane, though. They are independent

physical structures comprised of several membrane-spanning (integral) proteins called subunits, arranged into a tunnel-​ like configuration to form a central pore (Figure 3–7). The central pore of the channel is the pathway an ion traverses to get into or out of the cell. Ion channels can be built with as few as 4 protein subunits or as many as 12 in some specialized channel types. Thanks to molecular biology and genetics-based methods, we now know that the protein subunits that comprise the many different types of ion channels in the nervous system are translated from a surprisingly large set of genes (Siegelbaum & Koester, 2013). What this means is that ion channel diversity throughout the nervous system, both functionally and structurally, is the result of mixing and matching a wide variety of subunits into lots of different patterns and arrangements. Think of it like this . . . you can build lots of different types of castles, ranches, and houses when you have many different types of Lego bricks to work with. Channel subunits are the “Lego” pieces, whereas the building you construct is the entire ion channel. Creating ion channels using different combinations and types of subunits produces channels with very diverse functional capabilities that ultimately regulate the flow of ions in different ways. Being able to regulate the flow of ions in different ways provides the nervous system with a rich ability to create a wide range of signals for different types of neural

CHAPTER 3   Basics of Neural Signaling and Synaptic Function

49

Ion Channels Can Control the Motion of Ions

Extracellular side

Intracellular side

 FIGURE 3–7.   Ion channels are complex arrangements of proteins that form a fluid bridge through a phospholipid bilayer, allowing for direct communication of the extracellular fluid with the intracellular space. Ion channels make the cell membrane of a neuron selectively permeable to different ion species.

signaling tasks (Purves et al., 2012c). Thus, the principal reason for the great versatility of neural signaling in the nervous system is based on the operation of different types of ion channels created from different combinations of subunits. Together, these factors lead to functional differences such as ion selectivity and varying rates of ion motion through a given channel, all of which contributes to the moment-tomoment electrical state of a given neuron. The rapid changes in voltage (electrical potential) that are needed for different types of neural signaling depend critically on the unique structural and functional characteristics of a given ion channel spanning a neuron’s cell membrane. Remember, without the presence of ion channels, ion currents cannot develop. As such, ion channels share one or more of three key features when it comes to regulating ionic currents across the cell membrane during signaling: (1) They are selective and will allow only specific ions to pass through depending on the physical properties of the channel; (2) they can open and close in response to signals that are electrical, chemical, or even mechanical in nature; and (3) they are the conduction pathways for ions through the phospholipid bilayer of the neuron. Because ion channels are central to the development of neural signaling, disruptions in the structure or the function of these channels can lead to the development of characteristic symptoms underlying a wide range of neurological disorders, such as myasthenia gravis, epilepsy, cystic fibrosis, and select forms of ataxia, to name a few. Ion channels are also key sites of action for both legal and illicit pharmaceuticals, with the former being a good thing for human health and the latter not so much.

As long as a given ion channel’s pore is open, motion of its corresponding ion(s) through the pore requires no expenditure of metabolic energy. The passage and direction of ion motion is actually dependent on the chemical or electrical gradient driving forces that exist across the cell membrane. What we have, in effect, is the neuron taking advantage of the “physics” of the environment to create the energy needed to propel ions through an open channel — what amounts to a free lunch for the neuron! While ion motion through an open channel pore is passive and gradient dependent, how ion flows are regulated through a pore are (a) generally an active and controlled process or (b) a process governed by inherent structural features of the channel itself (Hall, 1992). Think of it this way: If you have water running through a hose, water molecule motion depends on the pressure generated at the water’s source. But you can actively control and change the overall flow of water moving though the hose by how strongly you squeeze the trigger of the sprayer, by changing the water pattern setting you dial in on the nozzle, or by bending and kinking the hose at some point along its length. Analogously, ion channels have these same types of influences on ion flows. Ion channels have structural features that restrict the type of ion allowed to pass and the rate of ion passage. For example, the physical size and diameter of the channel pore can help limit the type of ion that passes. Ions are not uniform in size, and they attract “clouds” of water molecules about themselves called waters of hydration (Hall, 1992; Siegelbaum & Koester, 2013). The number of water molecules attracted depends on the size of the ion and the strength of its electrical field (Figure 3–8). As illustrated in Figure 3–8, Na+ is a physically smaller ion compared to K+, but because smaller ions have stronger electrical fields surrounding themselves, Na+ attracts many more water molecules to itself compared to the physically larger K+ ion. This results in the Na+ ion taking

 FIGURE 3–8.   Ions attract clouds of water molecules that alter their effective size. These “waters of hydration” form a de facto selectivity mechanism because a given ion channel must have a pore size large enough to not only pass the ion, but also to pass the associated water cloud.

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on a much larger overall size compared to K+, limiting its passage through certain varieties of ion channels. Ions that cannot physically fit within a given channel’s pore are effectively selected out and prevented from crossing the membrane and entering the cell. Another way that ion channels can select which ion is allowed to enter is through the existence of rings of charged particles near the channel’s outer opening. These rings of charged particles repel ions of a similar charge but attract those with the opposite charge (similar to the magnets discussed earlier, shown in Figure 3–2). In addition to these passive selection features, an ion channel can also regulate ion flows through its pore in a much more active and regulated manner. This form of ion motion control is called channel gating (Purves et al., 2012c; Siegelbaum & Koester, 2013). There are many different mechanisms available to gate or actively regulate ion flows through a channel. Technically speaking, the term gating refers to how a channel transitions from an open configuration to a closed one — very much like a gate on a fence can open and close to let your dog in and out of the yard. The mechanisms underlying ion channel gating are directly related to producing conformational or physical shape changes to the subunits making up a channel in response to a variety of stimuli. Believe it or not, proteins can actually change their shape and move! Subunit proteins constituting an ion channel have been observed to twist, bend, and revolve to open and close the pore of the ion channel. It may be difficult to envision a protein producing shape changes or moving, but let’s try using the following example and see if this helps. As illustrated in Figure 3–9, imagine that one of the subunit proteins that make up an ion channel is shaped like a corkscrew. Twisting the corkscrew in one direction would shift the protein deeper inward, result-

SECTION 1

ing in closure of the pore (“closure” is defined as blocking the pore and preventing ion passage). On the other hand, twisting the protein in the opposite direction would shift the protein outward, creating pore opening. In a similar manner, various stimuli (chemical, electrical, mechanical) can generate protein motion and shape changes that shift the position and alter the physical relationship of subunits relative to one another. Ultimately, the effect of these shape changes results in the opening and/or closing of the channel’s pore. This is the essence of ion channel gating.

Ion Channels Can Gate Ionic Current in Three Ways Ion channel patency or degree of openness, can be influenced by three principal gating mechanisms: ligand, voltage, or mechanical gating (Figure 3–10) (Bear, Connors, & Paradiso, 2016a; Guyton & Hall, 2006). The first form is known as ligand or chemical gating. Ligands are chemicals that can bind to more complex organic molecules to aid in the performance of a biological operation. Ligands typically trigger a shape change in the target molecule, which in fact is ideal for the situation we are describing right now pertaining to ion channel opening and closing. In this form of gating, the outer surface of the ion channel binds with a specific class of ligand known as a neurotransmitter, resulting in a change in the subunit’s configuration, thus opening the channel’s pore to allow ion passage (Figure 3–10A & Figure 3–11A–C). Other classes of ligand-gated channels are responsive to signals that develop intracellularly. Two examples of intracellularly gated channels are the Ca2+ activated channels and classes of channels that require a more complex cascade of

Open channel

Closed channel

(ion passage allowed through pore)

(ion passage prevented through pore)

Protein

Phospholipid bilayer

 FIGURE 3–9.   Ion channels can be gated through changes in the position of different protein components comprising a given channel. In this illustration, the channel can be gated open or closed depending on the depth of twisting of the corkscrew-shaped protein elements. When the corkscrew protein is positioned deeply, the channel pore is blocked, preventing ion passage. When the corkscrew is moved outward, the channel’s pore is open to allow for ion passage.

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51

a. Ligand gating Ligand binding

b. Voltage gating Change in membrane potential

c. Mechanical - Stretch or pressure gating Stretch

Cytoskeleton

 FIGURE 3–10.   Ion channels can be gated in several different ways, including through the binding of chemical ligands, through voltage changes, and mechanically. Gating allows the neuron to control current flow through the channel. A. Ligand gating. B. Voltage gating. C. Mechanical gating.

biochemical reactions to activate and open (Figure 3–11B & C). Regardless of the location of ligand binding, a good analogy for this form of gating is that of a lock and key, where the ion channel is the lock and the ligand operates as the key to open the channel and allow for ions to pass. Ligand gated channels are found in high quantities on the postsynaptic side of a chemical synapse and are key players in the process of synaptic transmission. The opening of postsynaptic ligand gated channels allows for the development of electrical currents into and out of a postsynaptic cell. Voltage gating is the second mechanism available to open and close ion channels (Figure 3–10B & Figure 3–11D–G). Voltage-gated channels respond to minute changes in the electrical potential (voltage) of the cell membrane by shifting the position of their subunits relative to each other. This form of gating relies on the response of a region of a subunit that possesses several charged amino acids — a region known as the voltage sensor. The voltage sensor can shift its position

(through attraction or repulsion forces) in response to local changes in the electrical potential of the surrounding environment. (Remember our earlier example of using magnetic force fields to move magnets about a table.) Shifting of the voltage sensor results in a shape change or sliding about of the channel’s subunits, resulting in opening/closing of the channel’s pore (Purves et al., 2012c). If ligand-gated channels resemble the operation of a lock and key, you can think of voltage-gated channels as resembling a remote keyless entry system on your car (beep, beep). As you will see later in the chapter, voltage-gated channels are going to be very important players in the process of action potential generation and operation of the presynaptic terminal’s communication system. Mechanically gated channels open and close through a change in the shape of the cell membrane in which the channel is embedded. Mechanically gated channels are anchored to the cell’s internal cytoskeleton, allowing for any type of stretching, strain, or pressure applied to the cell membrane to

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Neuroscience Fundamentals for Communication Sciences and Disorders

SECTION 1

Ligand-gated channels a. Neurotransmitter gated channel

b.Ca2+-activated K+ channel

c. Cyclic nucleotide gated channel

Na+

Na+ Glutamate

Outside

cAMP

Ca

K+

2+

K+

Inside K

+

cGMP cAMP

Voltage-gated channels d. Na+ channel

e. Ca2+ channel

f. K+ channel

Ca2+

Na+

g. Cl– channel Cl–

Voltage sensor

+

+

+

+

+

+

+

+

K+

 FIGURE 3–11.   Ligand- and voltage-gated ion channels are diverse. Ligand-gated channels can be activated through neurotransmitters (A), via Ca2+ (B), or via organic molecules that are created through intracellular chemical reactions (C). Voltage-gated channels (D through G) all operate similarly and rely on the response of a channel region known as the voltage sensor. Voltage sensors can shift position in response to electrical events happening within the surrounding membrane. Voltage sensors are represented as two circled + signs in the crown of each channel.

be transferred directly to the subunits of the ion channel (see Figure 3–10C and Figure 3–12). Under these conditions, the subunits tethered to the cell membrane are forced to shift position and create an open pore (Siegelbaum & Koester, 2013). One way to envision this action is by imagining yourself opening a bag of potato chips. Your hands apply a mechanical stress to the top of the bag, which will eventually cause the seal of the bag to give way and break open (although when I do this, chips usually go flying everywhere!). Mechanically gated channels are principally found on neurons that transduce real-world inputs from the environment for the sensations of touch, hearing, and balance, to name a few. The mechanical gating of these ion channels is ideally suited to

reliably convert environmental stimuli and forces into neural impulses that can be transmitted into the brain.

Some Ion Channels Are Always Open Aside from gated channels, there is a class of ion channel found throughout the neuron that is open all the time, sort of like gas station convenience stores. These open channels are considered passive or resting because they allow for existing electrochemical gradients to dictate the rate of ionic current through the channel’s pore. Open or resting channels can be selective for a single ion, or they may allow passage of several different types of ions. Open channels cause neurons to “leak”

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53

Mechanically-gated channel closed Ion blocked

Phospholipid bilayer

Cytoskeleton tethers are loose

Mechanically-gated channel stretched open Probe's applied force displaces cell membrane

Phospholipid bilayer

Ion passing Cytoskeleton tethers are taut and apply a pulling force on channel subunit that opens the pore

 FIGURE 3–12.   Mechanically gated channels open and close through stress applied to the cell membrane in which the channel is embedded. Internal cytoskeletal tethers connect the channel’s subunits to the cell membrane, allowing for applied stresses on the membrane to stretch open the channel.

inward or outward ionic currents depending on the direction of existing electrical or chemical gradients for a given ion type. The fact that passive resting channels make neurons leaky suggests that there must be an active mechanism to counteract the leakage and ensure the electrical stability of the cell. Luckily, there is such a mechanism, and it is known as an ion pump (Hall, 1992; Purves et al., 2012c).

Ion Pumps Are Active Transporters of Ions Across the Neuron’s Cell Membrane Ion pumps are the physiological workhorses of a neuron, operating consistently to maintain the normal ionic concentration gradients that are critical for sustaining effective neural signaling conditions. Ion pumps, as the name suggests, are channel-like transporter structures within the membrane

that actively “pump” or move ions against their natural concentration gradients. Because of this fact, pumps operate through the expenditure of metabolic energy in the form of adenosine triphosphate (ATP) (see Figure 2–7). Ion pumps differ from ion channels in their need for metabolic energy to operate and their dramatically slower rate of transporting ions across the cell membrane. Two types of ion pumps are central to our understanding of neural signaling and synaptic transmission: the sodium-potassium (Na+-K+) pump and the calcium (Ca2+) pump (Purves et al., 2012c; Siegelbaum & Koester, 2013). The Na+-K+ pump is found on unmyelinated segments of the cell membrane on both the soma and axon. It is one of the key mechanisms operating to establish the resting state of the neuron. As illustrated in Figure 3–13, the Na+-K+ pump can be analogously envisioned as a “revolving door,” or a Ferris

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1

SECTION 1

2 Outside ADP

ATP

Pi

Inside Na+

3 molecules of intracellular Na+ bind to pump

ATP keeps the pump working

4

3 K+

Na+

Pi Pi

K+

K+ is actively transported inward and released

Na+ is actively removed and extracellular K+ binds to pump

 FIGURE 3–13.  Na+-K+ pump is an active ion transporter. Activated through the hydrolysis of ATP, the Na+-K+ pump operates to move Na+ and K+ against their natural concentration gradients. The Na+-K+ pump is continuously working and is a key feature for establishing and maintaining the resting membrane potential of the neuron.

wheel type of mechanism whereby three Na+ ions are removed from the inside of the cell for every two K+ ions brought back into the cell. Because the movement of Na+ and K+ is against each ion’s natural concentration gradient, ATP is required to continuously drive the pump’s operation. (The Ferris wheel depiction of the pump in Figure 3–13 is only figurative and is simply intended to help you visualize the pump’s operation.) The Ca2+ pump can be conceived in a similar manner as the Na+-K+ pump; its principal function is to remove intracellular Ca2+ against its own natural concentration gradient and expel it from the intracellular space of a neuron (Figure 3–14). Ca2+ ion pumps are found throughout the cell membrane and within cellular organelles that store Ca2+ ions, such as the endoplasmic reticulum and mitochondria. For the purposes of understanding the process of neural signaling, though, we are concerned with the Ca2+ ion pumps located on the presynaptic terminal membrane of the chem-

ical synapse. These ion pumps are critically important for normalizing the Ca2+ gradient across the presynaptic terminal membrane to stop synaptic transmission.

Understanding Membrane Potentials Up until now, we’ve been getting up to speed on the basic terminology and concepts that form the backstory for our understanding of neural signaling. This is what you should know at this point in time: • Neurons exist within a fluid environment that possesses an unbalanced distribution of different types of ions, specifically Na+, K+, Cl−, and Ca2+. • Ions are simultaneously chemicals and electrical charges and, as such, can be placed into motion in a given direction by driving forces developed from

CHAPTER 3   Basics of Neural Signaling and Synaptic Function

55

Ca2+ ions ATP binding site ATP

Intracellular Extracellula

Extracellular Ca active transporter pump 2+

ATP

P

+

ADP

 FIGURE 3–14.  Ca2+ transporter is activated through the hydrolysis of ATP. The Ca2+ pump operates to move Ca2+ against its natural concentration gradient. Ca2+ pumps are active during synaptic transmission and during muscle contraction.

(a) concentration gradients or (b) electrical potential differences (electrical gradients) across the cell membrane. • The impermeable nature of the neuron’s phospholipid bilayer (cell membrane) allows for the development and maintenance of charge separation across the membrane, giving the membrane a voltage (an electrical potential). • Neurons possess different types of ion channels that allow for the movement of ions across the phospholipid bilayer (what we call membrane permeability).

• Because ions are charged particles, the motion of ions through a channel constitutes an electrical current. • Ion channels are diverse both structurally and functionally. They are selective for specific ion types and are able to regulate the flow of ions in different ways across the cell membrane. • Some ion channels are always open (resting channels), allowing for passive diffusion of ions down their gradients, making the cell membrane “leaky.” • Other ion channel types can actively regulate the flow of ions across the membrane through ligand, electrical,

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or mechanical gating mechanisms that control the open versus closed state of the channel’s pore. • Ion pumps are active (use metabolic energy in the form of ATP) transporter mechanisms that can move ions against their respective gradients.

SECTION 1

Vm Intracellular

Extracellular

With these key points in mind, in the next section, we will begin exploring the way neurons develop and maintain an electrical potential and change that potential to traffic information around the nervous system. Bookmark the previous sections on electricity and ion channels and refer to these often to remind yourself of key terminology and concepts as we delve further into the intricacies of neural signaling.

Membrane Voltages Are Created by a Separation of Charges Like a battery maintains a separation of positive and negative charges using a physical barrier, neurons are capable of the same feat. Neurons maintain a separation of charges by the impermeable nature of the cell’s phospholipid bilayer. Recall that the intra- and extracellular fluids of the neuron contain an uneven distribution of positive and negative charges, with the intracellular fluid having slightly more negative particles trapped within. (Remember those large negatively charged organic molecules?) Although the volumes of extracellular and intracellular fluids are electrically neutral for the most part (positive charges balance out the negative charges), the inner and outer surfaces of the cell membrane (the border between the two fluids) possess a definite electrical bias (Figure 3–15). The phospholipid bilayer of the cell is so thin that negative and positive charges are attracted to each other from across the membrane, producing a thin ribbon or film of opposite charges lined up on either side of the membrane (see the membrane in Figure 3–15). Positive charges line up on the outer membrane surface, while negative charges line up on the inner surface. This separation of charges is a voltage and is referred to specifically as the membrane potential of the neuron, abbreviated Vm. A depiction of the condition just described is seen in Figure 3–15 (Hall, 1992; Koester & Siegelbaum, 2013a; Purves et al., 2012b).

Vm Can Be Changed by Ionic Gradients and Currents By convention (which really means that a bunch of scientists agreed on something to make life easier for themselves), the extracellular fluid is set to a value of zero volts, which allows us to measure the electrical potential difference across the membrane from the point of view of the membrane’s inner surface. As described earlier and shown in Figure 3–15, when we measure the electrical potential (the degree of charge separation) across a neuron’s cell membrane, we find that the inner region of the membrane registers a slight negative reading compared to the outer surface. The Vm is what we measure

 FIGURE 3–15.   Membrane potential (Vm) is characterized by the separation of charges across the phospholipid bilayer. Positive charges line up on the extracellular side of the membrane, while negative charges line up on the intracellular side.

and observe changing during all forms of neural signaling (Hall, 1992; Koester & Siegelbaum, 2013a; Purves et al., 2012b). (This is a very important idea to remember, so go back and highlight the previous sentence.) Because electrical currents are carried by the motion of ions through ion channels positioned across the cell membrane, as illustrated in Figure 3–4, the Vm can be affected in predictable ways, depending on the charge of the ion and its natural gradient. For example, Na+ is a positive ion whose concentration gradient will drive the ion into the cell. The influx of positive Na+ ions results in a disturbance to the normal Vm such that the separation of charges across the membrane becomes smaller. If a positive ion is rushing into a cell that has a negative electrical potential, by adding all those new positive charges, the degree of charge separation across the membrane will have to decrease (i.e., the inside of the cell becomes less negative). This means that the electrical potential difference or voltage across the membrane is driven closer to 0 volts. Such a condition is called depolarization. A silly analogy to internalize this idea more intuitively is to consider a situation where you are trying to cool down a very hot cup of coffee to room temperature using cold milk. The “hot coffee” represents the negative potential of the neuron, the “cold milk” represents the positive Na+ ions that will enter the cell, and lastly, the “room temperature” represents 0 volts. When you pour the cold milk into your hot coffee (Na+ ions moving into the cell down their concentration gradient), the temperature of the coffee cools and moves closer to the temperature of

CHAPTER 3   Basics of Neural Signaling and Synaptic Function

the room (Vm is shifting toward 0 volts). The magnitude of the temperature difference between the coffee and the room is now far less after adding the cold milk. The coffee’s change in temperature toward that of the room is analogous to depolarization, or a decrease in the magnitude of charge separation. In the opposite manner, if a negative ion such as Cl− is driven into the cell (direction of Cl− concentration gradient is inward), the Vm will become more negative. If a negative ion is rushing into a cell that already has an overall negative electrical potential, the degree of charge separation across the membrane will simply increase and grow. This means that the electrical potential difference (the Vm) is now being driven farther away from 0 volts. If we modify our coffee analogy, increasing charge separation would resemble a condition where rather than trying to cool the coffee, you’re trying to heat it even more by putting it in the microwave oven on high (representing the influx of Cl−). You can also achieve a more negative Vm by allowing positive ions to exit the cell. This is exactly the case when K+ ions move down their concentration gradient and leave the intracellular region of the

57

neuron. (Recall that K + is higher in concentration internally and lower externally.) Regardless of the means, when the Vm becomes more negative or moves farther away from 0 volts (reflecting an increased separation of charge), what we have now is a state known as hyperpolarization (Hall, 1992; Koester & Siegelbaum, 2013a; Purves et al., 2012b). In summary, depolarization and hyperpolarization are two principal ways to produce changes in the Vm of a neuron (see Figure 3–16). Generally, depolarizing events will lead to further spread of an electrical impulse throughout a neuronal network and will operate to increase the activity of a neuron. For this reason, depolarization is often referred to as an excitation or excitatory event. Hyperpolarizing events lead to a decrease in the responsiveness and activity of a neuron, reducing information transfer across a network. As such, hyperpolarizing events are typically characterized as inhibitory or suppressive in nature. As we move forward in our discussion, always keep in mind that (1) all forms of neural signaling are produced by making short and rapid changes to the Vm of a neuron in either a depolarizing or hyperpolarizing direction and

Neuron’s Membrane Potential (mV)

Neuron’s Membrane Potential (mV)

Membrane voltage can be shifted in 2 ways 0

Depolarization - Vm driven in a more positive direction Depolarization

-65

-90 0

-65

-90

Firing Threshold

RMP

Time

Hyperpolarization - Vm driven in a more negative direction

Firing Threshold

RMP

Hyperpolarization Time

 FIGURE 3–16.   Membrane voltage (Vm) can be shifted in either a depolarizing or hyperpolarizing direction. The blue panel depicts a depolarization condition whereby the Vm of a neuron is pushed to a less negative potential. The pink panel depicts a hyperpolarization condition whereby the Vm of a neuron is pushed toward a more negative potential. RMP = resting membrane potential. The horizontal dashed line in each panel represents the firing threshold for action potential firing.

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that (2) regardless of the direction of change, Vm variations occur through the regulation of ionic currents through ion channels.

Development of the Neuron’s Resting Membrane Potential The negative Vm of a neuron resulting from the normally uneven distribution of charges is known as the resting membrane potential, or RMP for short (Bear et al., 2016a; Koester & Siegelbaum, 2013a). The RMP is the baseline electrical state of a neuron when it is not actively involved in generating a neural impulse or participating in integrative behaviors. Depending on the type of neuron in the nervous system, the value of the RMP ranges from −60 to −70 millivolts (mV) or −0.06 to −0.07 of a volt — a very small voltage difference across the membrane. Understanding the nature and development of the resting membrane potential is important because almost all signals that a neuron produces begin and end with the RMP. In fact, a neuron’s inability to maintain the RMP leads to disturbances in the neuron’s function and widespread disruption of information processing and signal transfer in the nervous system. The RMP emerges and is maintained by two key interacting factors: (1) passive flows of Na+ and K+ down their respective concentration gradients through passive resting ion channels selective for each ion (Figure 3–17) and (2) the active operation of the Na+-K+ pump (see Figure 3–13). As you can surmise using what you already know about the nature of these two factors, development of the RMP is essentially a balancing act between passive ion motion through resting channels and active ion motion through operation of the Na+-K+ pump. A good analogy for thinking about the RMP is that of a hovering helicopter in the sky. Gravity is a passive force wanting to pull the helicopter to the ground (ions diffuse passively through open pores of passive ion channels), but the engine and the rotors of the helicopter are a force

that actively counteract gravity’s pull (operation of the Na +-K + pump). Let’s see how this balancing act works by constructing, step-by-step, a fully operational neuron that is maintaining an RMP of −65 mV. Imagine a neuron that has no ion channels whatsoever, sitting in a fluid environment with higher concentrations of Na+ extracellularly versus intracellularly, and K+ possessing the opposite concentrations (see Table 3–1 for details). Fig­ ure 3–18A depicts a small piece of the cell membrane of our imaginary neuron in its normal ionic environment. The size of the ion labels in Figure 3–18 indicates the concentration magnitude for each ion present. Because our imaginary neuron currently lacks any ion channels, the concentration gradients for Na+ and K+ are static and thus unable to run or be expressed. For argument’s sake, let’s also assume that all the charges on either side of the membrane cancel each other out, resulting in a Vm of 0 mV. Now let’s add a passive K+ channel to our imaginary neuron (Figure 3–18B). The moment passive or resting K+ channels are inserted into the cell membrane, K+ starts moving down its concentration gradient and out of the cell (see also Figure 3–19A). As K+ exits the cell, the outer surface of the cell membrane starts to accumulate positive charges, while the inner surface starts to accumulate negative charges. Remember, ions are simultaneously chemicals (atoms) and electrical charges, so as K+ ions flow down their concentration (chemical) gradient, positive charges are effectively escaping the intracellular space too and creating an increasingly powerful electrical gradient across the membrane (greater charge separation) (see Figure 3–19A). This charge separation develops because the channels we added to our imaginary cell were selective only for K+ and no other ion or molecule. The efflux (motion of ions out of the cell) of K+ lowers the number of positive charges inside of the cell relative to the extracellular fluid. What this means functionally for our imaginary neuron is that the balance of charges that existed at the start of

Na+

K+

SECTION 1

Na+

Extracellular side

Phospholipid bilayer Intracellular side

K+

K+ channel

K+

Na+

Na+ channel

 FIGURE 3–17.  Na+ and K+ passive ion channels allow for the free diffusion of these ions across the cell membrane. Passive ion channels effectively make the neuron “leaky” to a given ion. Gradients, either concentration or electrical, operate as driving forces to create ion diffusion though passive channels. Na+ and K+ passive ion channels are key factors in the development of the resting membrane potential.

CHAPTER 3   Basics of Neural Signaling and Synaptic Function

Intracellular

Extracellular

K+

a.

A

59

K+

Na+

Na+

Cl-

A-

–

Cl

-

b.

A

K+

K+

Na+

Na+ A-

Cl-

Cl

–

K+

-

A

Na+

Na+

Cl-

A-

–

c.

K+

Cl-

 FIGURE 3–18.   A model neuron that possesses only passive K+ channels on the cell membrane. A. The model neuron is shown with the known distribution of key ions across the cell membrane. The size of the label indicates the size of the concentration for that ion. B. Passive K+ channel is placed in the cell membrane, making the model neuron selective for K+ only. Given the concentration gradient for K+, efflux of the ion begins. C. Continued motion of K+ out of the cell increases the electrical potential across the membrane. Increasing Vm results in the attraction of K+ back into the neuron. As illustrated by the double arrowhead, K+ now flows in both directions through the channel.

a. Na+

b. K+

Cl–

Extracellular side

++++++

++++

K+ concentration

Membrane

Intracellular side

K+

Na+

Cl–

gradient drives K+ out of cell

– – – – – – – –

– – – – – –

K+

K Na+

A–

+

K+ concentration gradient drives K+ out of cell

Electrical potential difference drives K+ into cell

A– Na+

 FIGURE 3–19.   Effects of concentration and electrical gradients on the motion of K+ through a passive K+ channel. A. Concentration gradient is dominant causing K+ efflux. B. Concentration and electrical gradients are balanced and acting simultaneously on K+.

our example and that gave our imaginary neuron its neutral membrane potential is now disturbed. In short, the number of negative charges on the inner membrane surface is rising because we’re losing positive charges as K+ moves outward. The motion of K+ out of the cell does not continue unabated, though. (Again, this is because ions are both a chemical and an electrical charge simultaneously, and as such can be placed into motion by both concentration and electrical gradients.) The increasingly negative electrical potential developing across the cell membrane begins to start slowing the removal

of K+ out of the cell and begins attracting K + BACK INTO the cell down a developing and growing electrical gradient. Remember that, unlike concentration gradients that operate on the principle of differences in the quantity of a substance across areas, electrical gradients develop due to attractive and repulsive forces between positive and negative charges. At some point in the battle between our opposing gradients (concentration vs. electrical), the strength of the concentration gradient moving K+ out of the cell will precisely balance the strength of the electrical gradient wanting to moving K+ back into the cell.

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Neuroscience Fundamentals for Communication Sciences and Disorders

At that precise moment, the net movement of K+ across the cell membrane will effectively be equal to zero. In essence, the two opposing gradients have reached a balanced condition and now exist in a state of relative equilibrium to each other (Figures 3–18C and 3–19B). If we measure Vm at this instant in time, the voltage value we will record is called the equilibrium potential for K+, abbreviated EK (Bear et al., 2016a; Koester & Siegelbaum, 2013a; Purves et al., 2012b). EK is the voltage that must exist across the neuron’s membrane to perfectly balance the driving forces of our two opposing gradients (concentration and electrical) acting on K+. In our imaginary neuron, that voltage would be approximately −75 mV. Now, rest assured, I didn’t just invent this number for potassium’s EK. The value of EK = −75 mV is based on a mathematical formula known as the Nernst equation. I’m not going to bother you with the details of the Nernst equation, because what is needed from your perspective is simply the intuitive understanding that we have developed on this concept so far using our imaginary neuron. But for your edification, in case you’re curious, the Nernst equation allows neurobiologists to calculate the individual equilibrium potentials for any ion acting on a neuron (Brown, 2018; Koester & Siegelbaum, 2013a). Much like we did by using an imaginary neuron with only one kind of ion channel to intuitively understand the idea of an equilibrium potential (see Figure 3–18), the Nernst equation makes the same basic assumptions, except mathematically. Using this equation and the assumption of a cell permeable only to Na+, neurobiologists have determined that the equilibrium potential for such a cell is ENa = +55 mV. One of the questions I’m often asked while teaching this subject is why one equilibrium potential is negative (EK = –75 mV) while the other is positive (ENa = +55 mV). This is not a trivial question, but one that helps shed light on the nature of the RMP in a fully functioning neuron. The answer to this often-asked question is a simple matter of the number of resting channels that exist on the cell membrane for K+ versus for Na+ ions. As alluded to earlier (but worth repeating), the negative value for EK stems from the fact that the concentration gradient for K+ is outward, resulting in a great loss of positive charges from the intracellular fluid through large numbers of resting K+ channels. On the other hand, the positive value for ENa stems from the fact that both the concentration and the electrical gradient for Na+ are inward. This results in an increase in the number of positive charges entering the cell via resting Na+ channels. Unlike our imaginary cell, though (see Figure 3–18), the real-world neuron possesses both types of resting channels on its membrane, with resting K+ channels far outnumbering resting Na+ channels (see Figure 3–21 for an example). Why this uneven number of K+ versus Na+ resting channels exists in a neuron is a question only nature can answer . . . it simply is what it is. Under normal conditions, the uneven number of resting channels makes a cell’s membrane far more permeable or leaky to K+ compared to Na+. The uneven distribution of

SECTION 1

K+ versus Na+ resting channels on the cell membrane is an important factor in understanding why a fully functioning neuron’s RMP is approximately −65 mV and not −75 mv (EK) or +55 mV (ENa) (Bear et al., 2016a; Koester & Siegelbaum, 2013a). Our next step is to convert our imaginary neuron in Figure 3–18 from one that was permeable to only one type of ion to a neuron that is now permeable to both K+ and Na+ simultaneously. We are getting closer and closer to understanding the real thing! Let’s keep going. Let’s go back to our imaginary neuron where we last left it (see Figure 3–18), possessing only K+ resting channels and sitting at an RMP of −75 mV. It’s time to make our imaginary neuron a bit more realistic by adding a handful of resting Na+ channels to its cell membrane. What do you think will happen when this occurs? Based on what you know so far, you can predict that Na+ will start leaking into the neuron down both its concentration gradient AND the negative electrical gradient. The influx of Na+ ions creates a slight depolarization (membrane potential shifts closer to 0 mV) of the intracellular space, shifting the RMP of this updated imaginary neuron from −75 mV to a value that is now slightly less negative in potential. Because very few passive Na+ channels are on the cell membrane of our current model cell, the amount of depolarization is small, approximately +10 mV. The significance of this slight Na+-driven depolarization is critical, because as the RMP of the entire neuron shifts away from −75 mV (the EK), the careful balance we first created between the concentration and electrical gradients for K+ is now completely disturbed. (Don’t you hate when someone messes up your equilibrium potential? I know I do! ) The K+ gradients, both concentration and electrical, are no longer in equilibrium relative to each other because of Na+ now leaking into the cell and depolarizing it. The depolarized state of the neuron operates to weaken the existing electrical gradient for K+. Because the electrical gradient for K+ is now weakened, the cell tries to compensate and restore the equilibrium of K+ ion motion by strengthening the K+ concentration gradient. If the influx of Na+ remains steady, the cell will seek out a new equilibrium point for its membrane voltage that now takes into account not only the effects of K +, but of Na + as well. The neuron’s new balance point will be equal to roughly −65 mV, a value close to EK, but very far away from ENa. A good way to think about this situation more visually is to imagine trying to keep a balance beam perfectly horizontal to the ground. Illustrated in the top panel of Figure 3–20 is a balance beam with a representation of both intracellular and extracellular K+ ions (our positive charges) present on each end (light blue–colored balls). The K+ ions are depicted as 10 balls held in boxes on each end of the beam. When the number of balls (positive charges) is the same on each side, the beam is perfectly horizontal; there is no difference between the number of K+ ions on each end (the concentration and electrical gradients for K + are balanced relative to each other). This state is a representation of EK indicating that the net number of K+ ions or positive charges flowing across the membrane (dashed

CHAPTER 3   Basics of Neural Signaling and Synaptic Function

Intracellular

61

Extracellular

K+ concent. gradient K+ elect. gradient

Events

EK maintained

• # of K+ ions moving out of cell via concentration gradient is equal to # of K+ ions moving into cell via electrical gradient (arrows are equal).

K+ concent. gradient K+ elect. gradient

EK disturbed

• Influx of Na+ disturbs EK. • Electrical gradient for K+ loses strength (smaller arrow). • Cell tries to compensate and restore EK by increasing concentration gradient for K+ (larger arrow).

K+ concent. gradient K+ elect. gradient

= K+

New RMP established

• RMP is no longer based upon influence of one ion, but rather based on effects of K+ and Na+ simultaneously. • K+ movement is rebalanced, but at a slightly different Vm due to presence of intracellular Na+.

= Na+

 FIGURE 3–20.   Balance beam analogy for understanding the effects of adding Na+ to a model neuron that is at EK.

line) is equal to zero (arrows are equal in size). Now, pretend that someone walks up to our perfectly balanced beam and adds two additional balls on the intracellular side of the beam (middle panel of Figure 3–20). These additional balls (shown in green) will represent Na+ ions that have been added to the intracellular side (you can think of these as the addition of two more positive charges intracellularly). The beam now tips downward toward that direction, indicating that we now have more positive ions on that side of the beam compared to the other (12 positive charges vs 10 positive charges). This is analogous to the case when a cell that was once permeable only to K+ and resting at EK (top panel condition) suddenly becomes permeable to Na+ (middle panel condition). This scenario represents the slight depolarization of the entire cell due to the addition of Na+ intracellularly. The problem with our new scenario, though, is that now EK has been disturbed because of the depolarization; K+ currents across the cell membrane are no longer in equilibrium (see the small and large arrows in the middle panel ). As stated earlier, the depolarization created by adding Na+ intracellularly causes the cell to try and restore

EK. Since the depolarization operates to decrease the effects of the electrical gradient on K+ (small arrow in middle panel of Figure 3–20), the concentration gradient for K+ becomes slightly stronger in response (larger arrow), operating to eject additional positive K+ ions out of the cell (see bottom panel of Figure 3–20). The removal of a couple of intracellular K+ ions is the cell’s attempt to reestablish the balance between the K+ concentration and electrical gradients we started with originally. Performing this action restores the balance beam to its perfectly horizontal condition again, but now the newly established RMP for our entire cell is no longer based on just the influence of one ion, but rather is now based on the effects of K + and Na + simultaneously. K+ movement across the cell membrane is rebalanced, but at a different membrane voltage than before, because of Na+ leaking into the cell and depolarizing it slightly. Stop here and make sure you understand everything that is happening up to this point. When you’re ready, continue with the final step in the RMP process. Our final step in understanding the establishment and maintenance of the RMP is to add the Na+-K+ pump to our

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Neuroscience Fundamentals for Communication Sciences and Disorders

imaginary neuron. This will be the last revision to our imaginary cell. This revision will finally convert our imaginary model into a realistic neuron that is functionally able to maintain the RMP (Figure 3–21). While establishing the RMP for a neuron depends on the passive motion of Na+ and K+ ions, the maintenance of the RMP rests squarely on the active operation of the Na+-K+ pump. The Na+-K+ pump, as discussed previously in the section on ion channels, uses ATP to move Na + and K + against their natural concentration gradients (see Figure 3–13 for a depiction of the pump in action). The pump moves two K+ ions into the cell and three Na+ ions out of the cell for every molecule of ATP metabolized (Bear et al., 2016a). At this ratio, the active operation of the Na+-K+ pump will exactly offset the passive leakage currents for each ion into and out of the cell. Without the existence of the Na+-K+ pump, the cell’s membrane voltage could not be maintained. In fact, given enough time without an active pump, the neuron would eventually lose all electrical potential and come to rest at 0 volts. This would obviously not be a good condition for the neuron to be in because it would mean that it was functionally dead. Let’s do a quick review of what we’ve learned thus far. In this section, we’ve seen how neurons develop membrane potentials (voltages) by taking advantage of the uneven distribution of ionic charges in the extra- versus intracellular fluids. These voltages are created and maintained through charge separation by the phospholipid bilayer of the cell. With the addition of ion channels selective for Na+ and K+, the neuron

SECTION 1

can now use passive ion currents to create a baseline resting membrane potential. By adding the operation of the metabolically active Na+-K+ pump, the neuron can maintain this RMP for long durations of time (see Figure 3–21). The RMP is effectively a “negotiated” value, lying much closer to the equilibrium potential for K+ than for Na+. The chief reason for this situation is because many more passive K+ channels exist on the cell membrane compared to passive Na+ channels (see Figure 3–21 to observe the differences in passive channel numbers for K+ versus Na+). Thus, the RMP is a “relative” equilibrium state for the neuron, one that is maintained by balancing the effects of both passive and active events to keep the neuron’s membrane potential hovering consistently at a steady value (approximately –65 mV). The RMP is a critical functional condition for a neuron and one that forms the baseline for all future forms of neural signaling. In the next section, we explore what happens when the membrane permeability of a neuron is rapidly and suddenly altered through the opening and closing of gated ion channels. Figure 3–22 provides a summary illustration of the elements and processes contributing to the development of the resting membrane potential in the neuron.

The Action Potential Considering that neurons must transmit electrical signals over relatively long distances via axons, what is required is a mechanism that can create an electrical signal that doesn’t

Na+ Na+

K+

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ATP

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 FIGURE 3–21.   Key passive and active elements needed to develop the resting membrane potential (RMP) are depicted in a model neuron.

CHAPTER 3   Basics of Neural Signaling and Synaptic Function

63

Resting Membrane Potential: Mechanism Extracellular

Intracellular

+ Vm = -65 mV + + + + + Di usion down [Na+] -gradient + + + + + + Active transport out + + AT + P + + Na+ - K+ + Pump + + + + ATP Active - transport + + + + + + + + Di usion down [K ] gradient+ + + + Phospholipid + Bilayer +

Na

+

ATP

Na+

K

K

in

+

 FIGURE 3–22.  Resting membrane potential is developed through the combination of active transport and passive gradient-dependent forces acting across a neuron’s cell membrane. In the illustration, active and passive movement directions for Na+ and K+ ions are shown by the labeled blue and yellow arrows, respectively. The Na+-K+ pump is depicted at the center of the figure.

decay or lose energy over time and distance. Luckily, the nervous system has evolved such a signaling mechanism: the action potential (AP). The action potential is an extremely rapid (approximately 1 ms in duration) change in a neuron’s RMP that briefly “flips” the intracellular charge or polarity of the neuron from negative to positive. The AP is initiated in the axon hillock region of the cell and, once triggered, moves in one direction down the length of the axon until it reaches the presynaptic terminal (see bottom of Figure 2–3 for example). The AP is a “potential” because it is a measurable voltage that the cell membrane possesses, if only for an instant in time. The “action” part of the term simply signifies that this potential is generated during periods of activity for a neuron. Hence, you can think of an action potential as a change in membrane voltage during active behavior of a neuron. Other

terms that you’ll find in the literature for an action potential include nerve impulse, spike, or neural discharge. No matter what it’s called, the mechanism is the same. Action potentials are known as all-or-none events, meaning that once an AP is generated, it cannot be stopped (Bear et al., 2016b; Koester & Siegelbaum, 2013b; Purves et al., 2012b). Think of firing a gun; once the trigger is pulled, there is no way to stop and retrieve the bullet. In fact, this analogy has been used so often for describing the all-or-none property of the AP that we often describe AP generation as a “firing.” The importance of the AP for signaling is further highlighted by the fact that AP generation requires a threshold for firing. This makes quite a bit of functional sense. Because the AP is the principal way of conveying information around the nervous system, the message being transmitted from one cell to

64

Neuroscience Fundamentals for Communication Sciences and Disorders

another must be important enough to warrant creating and sending it to other members of the neural population. Aside from its thresholding and all-or-none qualities, the AP is also a highly stereotyped signal, looking the same no matter where it is recorded from within the nervous system. The stereotyped nature of the AP indicates that the mechanism underlying its creation must be identical throughout our bodies and, in fact, this is exactly the case. The stereotyped nature of the AP, along with the idea that it is a means for conveying information over long distances, suggests that the generating mechanism must be self-regenerating. In other words, the AP must have a means of preserving its consistent shape and strength as it propagates (travels) over some distance.

Voltage-Gated Ion Channels Are Chiefly Responsible for AP Generation Let’s go back to the neuron that we created when discussing the RMP (see Figure 3–21). Recall that this neuron possessed resting (passive) ion channels for Na+ and K+, as well as a metabolically active ion pump. We’ve already seen how these factors interact to produce the RMP of a neuron (see Figure 3–22). What we need to realize, though, is that the

Na+

V

AP is a rapid and transient deviation of the resting membrane potential, suggesting that there must be other players present on the cell membrane to rapidly alter the cell’s permeability to Na+ and K+. As shown in Figure 3–23, if we look closely at the membrane of a typical neuron, what we observe is that sitting alongside the resting channels and ion pumps are voltage-gated ion channels specifically for (you guessed it! ), Na+ and K+. These voltage-gated channels form the underlying basis for the self-regenerating and stereotypical nature of the AP. We are already familiar with the general operation of voltage-gated ion channels from an earlier section of this chapter. These channels respond to a fluctuation in Vm by shifting the position of electrically sensitive proteins making up a channel’s subunits (see Figure 3–9). With the shifting of these subunits, the channel pore is opened, allowing for the diffusion of ions across the membrane (Bear et al., 2016b; Koester & Siegelbaum, 2013b; Purves et al., 2012b). Voltage-gated channels are closed when the cell is at RMP, which means that, for all intents and purposes, they play no role whatsoever in production of the RMP. In contrast, voltage-gated channels play a central role in development of the AP. Let’s spend a bit of time considering the functional characteristics of the voltage-gated channels for

V

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 FIGURE 3–23.   A model neuron is shown with the required elements needed to develop an action potential. Compare this figure against Figure 3–21 to observe the differences between the elements needed for developing the RMP versus those needed for action potential generation.

CHAPTER 3   Basics of Neural Signaling and Synaptic Function

Na+ and K+. (From now on, we’ll refer to voltage-gated channels using the following abbreviations: v-Na + and v-K + for voltage-gated Na + and K + channels, respectively.) Understanding their different operating dynamics will greatly facilitate your understanding of (1) why the AP has a stereotypical shape and form and (2) why the AP causes a polarity (electrical charge) reversal in the neuron.

Voltage-Gated Na + and K + Channels Differ in Their Opening Speed Voltage-gated Na+ (v-Na+) channels have three key operational features that influence the flow rate and quantity of Na+ that passes through the channel pore once it opens. First, v-Na+ channels open very rapidly with almost no delay upon a significant change in Vm. (Think of automatic sliding doors in a store that open and close rapidly.) The direction of electrical change necessary within the neuron to initiate the opening of this channel type must be a depolarizing one. Second, when v-Na+ channels open, they remain open for less than 1 ms in time before deactivating. Once deactivated, the channel cannot be triggered open again (generally speaking) until the membrane around the channel returns to its RMP. Finally, v-Na+ channels are present in higher quantities compared to other voltage-​ gated channels on the cell membrane. Functionally, these three factors all point to the following functional condition: When v-Na+ channels are activated, Na+ movement into the cell down its concentration and electrical gradients is very shortlived, but absolutely massive in magnitude (Bear et al., 2016b; Koester & Siegelbaum, 2013b; Purves et al., 2012b). If you needed a channel to operate in the opposite manner to the v-Na+ channel, the characteristics of the v-K+ channel would likely fit the bill. Unlike the v-Na+ channel, v-K+ channels open far more gradually to a depolarization, taking a little bit more than 1 ms to fully reach an open state. (Think of a rusty old yard gate slowly creaking open and closed.) Once open, this channel does not undergo inactivation, but rather remains mostly open for as long as the membrane is in a depolarized state. Functionally, these factors indicate that v-K+ channels are delayed in their full opening compared to v-Na+ channels. This suggests a different role for the motion of K+ out of the cell and down its own concentration gradient.

The Action Potential in “Action” With our understanding of the RMP and our new insights into the functioning of the voltage-gated channels for Na+ and K+, we are now ready to discuss two key issues: (1) the mechanism for generating an AP and (2) how the stereotypical shape and duration of the AP arises. As shown in the top panel of Figure 3–24, the characteristic spike-like signal of the action potential can be divided into four phases: (A) RMP transition to firing threshold period, (B) a rising depolarization phase, (C) a descending repolarization phase, and (D) a prolonged hyperpolarization/refractory phase. From start to

65

finish, an AP has a duration of a little less than 1 ms, with each phase of the action potential characterized by the opening and closing of different combinations of voltage-gated ion channels on the cell membrane. In Figure 3–24, the four rows of ion channels labeled A through D illustrate the different patterns of voltage-gated channel opening and closing corresponding to each of the four phases of the AP. Use Fig­ ure 3–24 to follow along as we begin our detailed description of AP generation. Let’s begin with our familiar neuron at the RMP and just at the moment before our neuron produces an AP (see Fig­ ure 3–24A, the first phase). With the neuron at the RMP, we know that the cell is passively very permeable to K+ and only slightly permeable to Na+ (illustrated in Figure 3–24A by the open passive resting channels). Observe that at RMP, all the voltage-gated channels are closed and thus do not contribute in any way to ion motion during the RMP. If you recall when we were first defining the AP, we stated that the AP is a rapid reversal of the cell’s inner polarity or charge from negative to positive. Because the RMP of a neuron is mostly accounted for by K+, a reversal of the cell’s inner polarity would require the influx of massive numbers of positive ions. This is where Na+ ions now become the stars of the show and take center stage. As discussed earlier, generating the AP requires enough depolarization (i.e., decrease in charge separation across the membrane) to cross a critical firing threshold to get the axon hillock to fire an AP. The axon hillock possesses the highest overall density of v-Na+ channels in the entire neuron. This makes the hillock exquisitely sensitive to depolarizing events, giving this region the lowest threshold for AP generation. Think of the firing threshold for a neuron as a tipping or destabilization point. Imagine yourself balancing on one foot. You can sway and get jostled around quite a bit and still have enough strength and balance to retain your upright posture. But at some critical angle of sway or with enough of a push, you simply can’t maintain your balance any longer and you fall over. A threshold is precisely this type of event. Regarding our neuron, depolarization events from various sources acting on the cell (typically input from a synapse) will build and add together. These early depolarization events trigger the opening of growing numbers of v-Na+ channels in the region around the axon hillock, rapidly increasing the influx (flowing inward) of Na+ and strengthening the ongoing depolarization. At a critical tipping point, depolarization becomes sufficient to initiate a sudden and rapid cascade of v-Na+ channel opening, leading to a massive influx of Na+ ions into the cell. The massive influx of Na+ is the result of the rapid way v-Na+ channels open in response to the threshold-level depolarizing event. This event is depicted in Figure 3–24B with the selective opening of all v-Na+ channels. (Personally, I always like to think of this moment in time in the process as looking like a ginormous tsunami wave of Na + crashing through the cell membrane to rapidly flood the intracellular space with positive Na + ions.)

+60 v-Na+ channels closed and v-K+ channels fully open

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 FIGURE 3–24.   Action potential is a rapid deviation of the neuron’s RMP, generated through the activation of voltage-gated Na+ and K+ channels. In the top of the illustration, the AP trace is shown color-coded and labeled to highlight the different phases of the signal. In the lower section are four panels whose backgrounds are color-coded to match the different phases of the AP shown in the top panel. Each panel (A through D) depicts the state of both the passive resting and voltage-gated ion channels during each AP phase. A. During the RMP phase, only passive ion channels are operational. B. During the depolarization phase, passive channels remain active, but are joined by the sudden opening of voltage-gated Na+. A small number of voltage-gated K+ channels begin to open. C. During the repolarization phase, voltage-gated Na+ channels are inactivated, while voltage-gated K+ channels are now fully opened. D. During the hyperpolarization phase, most voltage-gated K+ channels are closed, allowing for restoration of the RMP via passive channels and operation of the Na+-K+ pump. 66

CHAPTER 3   Basics of Neural Signaling and Synaptic Function

In the AP trace at the top of Figure 3–24, the massive influx of Na+ ions accounts for the rapid (,

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 FIGURE 16–5.   Summary of speech experiments using altered somatosensory feedback (panels A, B, C) and altered auditory feedback (panels D, E). Panel A is an illustration of the experimental setup for altering somatosensory feedback using a robotic device that changes the movement path of the lower jaw during speech-related movement. Panel B is a plot of sample jaw movement paths when there is no path alteration (black lines), when the path is robotically altered (blue lines), and after adaptation to the somatosensory disturbance (gray lines). Panel C is a plot of the perpendicular deviation of the jaw path at peak velocity (normalized to peak velocity) as a function of utterance sequence. The black symbols represent the period before the robot was altering the path of the jaw. The blue symbols represent the movement change during the robotically altered jaw motion. Note that, over time, the subject adapted to the disturbance and reduced the amount of path deviation. On the left side of panel D is a spectrogram for the word “head” spoken by an experimental participant. The white lines correspond to the first three formants of the vowel within the word. On the right side of panel D is a second spectrogram of the same word following processing that shifted the first formant to a lower frequency while leaving other formants unchanged (see red lines). This is the signal that is presented in near real time into the headphones of the participant. Panel E is a plot of the frequency of the first formant as a function of utterance sequence. The black symbols represent the first formant values during production, while the red symbols represent what the subject hears. The altered feedback begins approximately 75 utterances into the experiment. Over time, the subject systematically alters articulation so that the formant being heard is closer to an expected value. (Republished with permission of Society for Neuroscience. From Lametti, D. R., Nasir, S. M. & Ostry, D. J. [2012]. Sensory preference in speech production revealed by simultaneous alteration of auditory and somatosensory feedback. Journal of Neuroscience, 32, 9351–9358. Permission conveyed through Copyright Clearance Center, Inc.)

The gray traces represent the jaw paths after speaking the target word a few hundred times with the robot altering its motion trajectory (panel C). The new path trajectory looks similar to the jaw path observed in the robot-off condition.

This is because the sensorimotor control system of the person has adjusted the descending motor commands to the jaw to accommodate the altered sensations created by the imposed effects of the robot.

CHAPTER 16   Neural Substrate of Speech and Voice

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Auditory Processing System

“had”

Altered auditory feedback experiment design  FIGURE 16–6.   Altered auditory feedback experimental setup. Subject overtly produces a target word visible on a display (Step 1). The target word production is recorded by a microphone (Step 2). The recorded production is altered in real time by an auditory processing hardware system (Step 3) and fed back to the subject via headphones (Step 4). The subject hears something different from what they are reading from the display and producing.

Each of these examples is a clear demonstration of how altering the sensory feedback available to a person causes a systematic change in the person’s motor behavior (Lametti et al., 2012). In the altered auditory feedback condition, the participant is attempting to get the speech signal to “sound correct,” even if it means modifying his or her central motor commands related to voicing. In the altered somatosensory feedback condition, the person is attempting to get the movement path to “feel” correct. Results such as these have been used as evidence that speakers routinely use sensory information on an ongoing basis to fine-tune descending motor commands (Ito & Ostry, 2011; Lametti et al., 2012; Nasir & Ostry, 2006). What neural pathways would be involved in this fine-tuning? As we learned in the last section, these experiments most likely exploit the dorsal processing streams of the auditory and somatosensory systems. It is worth noting that participants do not respond uniformly to these altered feedback environments. A significant percentage either do not show the effect at all or exhibit marginal responses. There also seem to be some individual preferences toward sensory modality. In a study in which participants were exposed to both forms of altered feedback, it was found that some participants preferentially responded to altered auditory feedback, while others preferentially responded to the altered somatosensory feedback. In a separate study of postlingual deaf participants who were exposed to altered somatosensory feedback, 100% of the participants exhibited motor adaptation (Nasir & Ostry, 2008). Why would the response rate to somatosensory alterations be uniform for deaf individuals? Because these participants have no access to auditory information at all, so they were obliged to monitor the status of the somatosensory tactile system exclusively.

Putting It All Together:  Computational Models of Speech Production Do you remember discussing the model of the atom in introductory chemistry class way back in high school? The mental image of an atom with its nucleus at the center and electrons whizzing around it in different locations might be the only thing that stuck from that class for me. But what do scientists mean when they refer to a model? It can mean a lot of different things. But, in its simplest form, a model represents an effort to organize known data and phenomena into a logical framework. As you read this rather hefty textbook, you are likely accumulating an ever-growing collection of informational bits and pieces. Like the pieces of an incomplete jigsaw puzzle, these different informational bits may not have an immediate and obvious connection to one another. One aim of a scientific model is to arrange and organize all the available bits into some larger, hopefully more coherent structure. A jigsaw puzzle has a unique and final solution. Science, though, is not a jigsaw puzzle. Scientific models are, at best, approximations of reality, and therefore are always a work in progress. But this fact is not a shortcoming of scientific models. To the contrary, the process of developing, testing, and in some cases rejecting models leads us to a deeper understanding of the natural world around us. We have already examined at least one example of a model in this chapter — the dual-stream model of speech processing. Borrowing its basic structure from other sensory processing models, the dual-stream model organizes information from a wide range of experiment types into a cohesive, internally consistent framework. Even though the model is

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represented by just a set of boxes and arrows, it is sufficiently detailed to allow for the design of new experiments to test its assumptions. This section focuses on computational models of speech production. A computational model is a specific type of model that represents natural phenomena as a mathematical or computer-based process. For a multifaceted process such as the neural control of speech production, computational models tend to build a large complex structure from smaller, analytically tractable mathematical components that serve different subfunctions. A strength of computational models is that they can often provide specific predictions that can be subject to experimental verification in real humans. There are a growing number of computational models of speech production reported in the literature. We are focusing here on one such model as an example: Frank Guenther’s Directions Into Velocities of Articulators (DIVA) model of speech production (Ghosh et al., 2008; Guenther, 2016; Guenther & Vladusich, 2012).

The Directions Into Velocities of Articulators Model (DIVA) The DIVA model was chosen to include in this chapter for a variety of reasons. First, it just has such a cool name! How can you not include a model that declares itself to be a DIVA! (Just kidding.) The real first reason why it is included is because it is a relatively mature model. It was first introduced more than two decades ago and since then has undergone continuous refinement and extensive testing and validation. Second, the DIVA model provides a nice example of the components of an adaptive speech motor control system, which is described in some detail later. Finally, unlike other models, which focus on a specific aspect of the speech production process, the DIVA model is ambitious as heck! It is designed to model the following conditions: (a) speech development, (b) the normal mature speech motor system, and (c) specific predictions about the neural basis of a variety of speech disorders (Ghosh et al., 2008; Guenther, 2016; Guenther & Vladusich, 2012). Furthermore, the DIVA model’s elements map onto known neural structures, making it possible to test this model’s predictions directly using functional neuroimaging studies and other forms of direct assessment in real humans. As a bonus, within the model is an articulatory synthesizer that generates acoustic and kinematic data that can be compared to real speech behavioral data. Talk about a wickedly cool model, right? The organization of the DIVA model is illustrated in Figure 16–7. Rather than getting overwhelmed by the large number of components and connections, let’s first spend a bit of time on the broad aim of the DIVA model. An important goal of the DIVA model is to provide an explicit description of the processes involved in the control of the speech sensorimotor system (Ghosh et al., 2008; Guenther, 2016; Guenther & Vladusich, 2012). A key word in the last sentence was “control,” and we need to define this term carefully

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here. A system is in “control” if there is a match between the intended and actual output of the system. For example, if the intended output of the speech sensorimotor system is to produce the word “special” and the articulatory and acoustic patterns produced look something like those in Figure 16–1, we could say that the nervous system exerted adequate “control” over the speech sensorimotor system. However, if the intended word was instead, let’s say, “Canada,” and the resultant patterns still looked like those in Figure 16–1, there would be cause for concern about the nervous system’s “control” over the speech sensorimotor system. To understand how DIVA and models like it exercise control, we need to define some additional basic terms. Simple motor control systems can fall into one of two distinct categories. The first category is termed a feedforward control system (see Chapter 15 to review the discussion on feedforward systems in motor control theories) (Seidler, Noll, & Thiers, 2004). Feedforward, or open-loop, control systems send a stored command to the motor system (see Figure 15–6 for reference). The commands are essentially previously learned and memorized instructions of how a task is to be completed. Feedforward systems are not able to monitor whether the real-world output matches the intended output. For example, you could imagine that feedforward control would be well suited for producing highly familiar words or phrases such as your name, cell number, and email address. However, with just a few minutes of reflection, problems become apparent. First, this strategy would not be foolproof to errors or unexpected changes that would affect performance. For example, it would be highly inconvenient if you happened to have your jaw wired shut and someone asked for your name. Those stored instructions for your name probably did not ever include or anticipate such a dramatic situation and drastic change in your anatomy. Second, how did you come to learn the instructions associated with saying your name in the first place? Did you just fumble around with a variety of sound patterns until you happened to stumble on the right one? This is highly unlikely. So, a strict feedforward control strategy alone leaves us wanting quite a bit. A second simple motor control strategy is a pure feedback or closed-loop control system (see Chapter 15 to review the discussion on feedback systems in motor control theories). Within such a system, feedback control closely monitors the actual output of the motor system using continuous real-time sensory information (see Figure 15–7 for an example) (Seidler et al., 2004). The difference between the intended and actual output yields an “error” signal, which can be used to update motor commands to converge on the target with increasing accuracy. For example, if the intended output is the production of an “/i/,” the auditory system would guide the speech motor system until the actual sound produced matches the intended sound. Clearly, a feedback control system does not share the problems of a strict feedforward system when dealing with novel situations. It can easily adapt to changing environmental conditions, and its use of sensory guidance negates

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 FIGURE 16–7.   Overview of the Directions Into Velocities of Articulators (DIVA) model of speech production. Lines with arrows represent excitatory connections between regions. Lines with circles represent inhibitory connections between regions. Abbreviations: vPMC = ventral premotor cortex; vMC = ventral motor cortex; SMA = supplementary motor cortex; pAC = posterior auditory cortex; vSC = ventral somatosensory cortex; GP = globus pallidus; SNr = substantia nigra pars reticularis; VA = ventral anterior nucleus of thalamus; VL = ventrolateral nucleus of thalamus; VPM = ventroposteromedial nucleus of thalamus; MG = medial geniculate nucleus of thalamus; Cb = cerebellum. (Guenther, F. H., Neural control of speech [Figure 3.5, p. 103]. © 2016 Massachusetts Institute of Technology, used by permission of The MIT Press.)

the need for storing specific motor commands internally. However, a feedback control system presents its own unique issues. For example, the controller cannot operate without a feedback signal, which is inconsistent with research studies showing that short-term loss in sensory input does not eliminate the ability to produce speech (e.g., you can still speak after visiting the dentist, right?). In addition, feedback systems are slow and, in fact, far too slow to support novel speech production in real time. So, a pure feedback control strategy also leaves us wanting. Given these limitations, it is unlikely that a speech motor control system would employ strictly feedforward or purely feedback-driven control strategies. The DIVA model is an example of an adaptive control model that combines the use of both feedforward and feedback control strategies to achieve its goals (Ghosh et al., 2008; Guenther, 2016; Guenther & Vladusich, 2012). Within these models, the motor command to the speech sensori­ motor system is the summed output of the commands from

feedforward and feedback controllers operating at the same time. The relative contribution or weighting of the feedforward and feedback controllers can vary and will so depending on the performance details of the task and the skill level of the individual. For example, when learning a novel motor skill, the motor control method will be heavily weighted toward feedback-based control because there was no prior opportunity to store feedforward commands for production of the new skill. However, with each opportunity to execute the new motor skill (what we call “practice”), feedforward commands start becoming established and stored internally (what we refer to as “remembering”). Furthermore, the feedback controller can send a copy of its commands directly to the feedforward controller to help further refine the commands that are being stored and remembered (what we refer to as “teaching”). Alternatively, with highly practiced movements, such as those involved in saying your name, the command to the speech motor system will be more heavily weighted

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toward feedforward control. Adaptive systems are highly flexible and can maintain a high degree of control across a range of experiential and environmental circumstances. The feedback controller can adjust the motor command in response to unexpected changes in the environment, such as speaking with a pencil clenched between your teeth or speaking while chewing gum. More slowly occurring changes such as those related to growth and anatomical development in vocal tract size will be accommodated by ongoing adjustment of the feedforward controller by the feedback system.

DIVA—Feedfoward and Feedback Control System Operation With these basic definitions in mind, let’s turn our attention back to Figure 16–7 and walk through the essential elements and connections of the DIVA model (Guenther, 2016). Use Figure 16–3 with the DIVA model illustrated in Figure 16–7 to connect in your mind the elements of DIVA model to the basic neuroanatomy of speech. Within the DIVA illustration shown, the shaded light brown region demarcates structures within the feedforward control system, while the shaded blue region shows structures within the feedback control system. The DIVA feedforward control system includes (a) the speech sound map, proposed to be located within the left ventral premotor cortex, which includes Broca’s area; (b) the articulator map, presumed to be located bilaterally in the ventral primary motor cortex; and (c) the initiation map, presumed to be housed within the supplementary motor area, including neural loops through the basal ganglia. The decision to initiate production of a particular speech sound is first mediated through the neural network formed by the initiation map and the basal ganglia. This element of the system sends a cue to the speech sound map, which contains a set of stored and previously learned motor commands for each speech sound (e.g., phoneme, syllable) within the language. Note that the speech sound map sends a feedback signal to the basal ganglia circuitry that presumably helps refine the initiation map’s activity over time. Once the speech sound is selected, the remembered motor commands are directed down the pathway labeled feedforward commands, which interconnects the speech sound map with the articulator map. The speech sound command is also shared with a cerebellar circuit that projects to the articulator map as well and assists in movement coordination. Note that the articulator map is reciprocally connected with the basal ganglia system. This should not be a surprise given what you have already learned about the basal ganglia’s role in motor control from Chapter 14. The DIVA model’s feedback control system (blue shaded area) is more complex, containing separate auditory and somatosensory feedback control subsystems. This feature allows for both auditory and somatosensory information to be used for driving the feedback controller and for helping fine-tune the feedforward system. Components of the feedback system include (a) the speech sound and articulator

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maps; (b) all the somatosensory mappings (target, state, error), located in the ventral somatosensory cortex on the post-central gyrus; (c) all the auditory mappings (target, state, error), located within the posterior auditory cortex on the superior temporal gyrus; and (d) the feedback control map, located in the right ventral premotor cortex. When a speech sound is selected by the speech sound map for production, an efference copy signal (see Chapter 14 to review the discussion on efference copy) is sent to the separate somatosensory and auditory target maps, where the efference copy will be compared with real-time sensory inputs produced during speech. The afference produced during speech goes to the auditory and somatosensory state maps. Viewed more simply, what is happening and being set up by the feedback systems in this section of the model is a means for comparing the intent of an action (speech sound map efference copy) with the real-time sensory consequences of that action (feedback inputs to the auditory and somatosensory state maps). The comparison between the two forms of information (intent vs. actual ) is performed and output through the somatosensory and auditory error maps. Output error signals converge onto the more general feedback control map, which then sends corrective movement commands to the articulator map in the motor cortex via the pathway labeled feedback commands and via a pathway through the cerebellum once again. The feedback controller effectively identifies the error in either the acoustic or somatosensory channels and makes corrective adjustments to compensate for any unexpected sensory information generated during performance. Lastly, the feedforward and feedback commands join each other within the articulator map. Once the articulator map in the ventral primary motor cortex processes these two major inputs, descending signals will be transmitted to lower motoneurons to initiate muscle contraction of vocal tract systems. The DIVA model is very robust and can account for a wide range of known experimental phenomena, including adaption to altered auditory and somatosensory feedback conditions as previously illustrated and discussed in Fig­ ure  16–5. (For further information on the DIVA model for speech, see review articles or books by Dr. Frank Guenther.) One question that we’ve left unresolved is, how does the feedforward system come to learn and contain speech sound gestures in the first place? Recall that one of the major goals of the DIVA model is to understand the development of speech. Also recall that adaptive motor systems operate to balance the use of feedforward and feedback control depending on how skilled a person is at an action. As an infant, who is unskilled in speech sound production, the hypothesis is that the feedback control system is dominant for quite some time to help the baby learn the relationships between articulator motion and the sounds and feel of the infant’s native language. Can you guess what this period is called? That’s right, the babbling phase! Babbling IS the trial-and-error process generated by the feedback system to refine and better approximate speech sound perception with production. With continued babbling and speech production practice, the infant’s feedforward

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Box 16–3. Clinical:  Producing Speech Using Implantable Brain-Machine Interfaces As we have learned, damage to neural structures underlying speech and voice production can leave a person silent despite preserved cognitive and language abilities. Many of these individuals also exhibit significant limb motor deficits that limit the viability of spoken word alternatives such as writing or typing. Imagine not being able to share a simple greeting or comment, let alone engage in an extended discussion on a topic. The social isolation can be devastating. Such individuals need an alternative and augmentative communication (AAC) system to help them speak again. This is one area of communication sciences and disorders in which advances have been heavily influenced by technological progress. Low-technology AAC solutions typically involve a process whereby messages are built by directing the listener to charts of organized letter/word groupings, and then signaling the desired letter/word through nonverbal actions such as an eye blink or small movement of a body part. While such systems provide a method for communication, it is not without its obstacles. Building even a simple message is slow and tedious, and limits communication to partners highly familiar with the selection and signaling strategies. The ubiquity of portable, powerful, and inexpensive computer technology has allowed for great advances in current AAC options. Today, control switches specially selected to match a user’s motor ability, combined with sophisticated interfaces, allow control over portable computers and tablets that can generate highly natural, synthetic speech. More recent advances now allow the quality of the synthetic speech to be customized to a person’s age, gender, geographic locale, and so forth. As a result, modern AAC systems allow for much greater independence and flexibility for communication across a variety of situations. Despite ongoing advances, the speed and efficiency of communication using these devices continues to pale in comparison to the natural spoken word. What does the future hold for those in need of an alternative means to speak? The last two decades have seen a rapid expansion of research focused on using brain activity to directly control external devices. The development of so-called brain-machine interfaces (or BMIs) promises to have far-reaching implications for a wide range of rehabilitation issues, including improving prosthetic limb function, environmental control systems, and AAC device development (Brumberg, Nieto-Castanon, Kennedy, & Guenther, 2010; Guenther et al., 2009). Some research efforts in AAC have focused on using neural signals, recorded using noninvasive techniques such as electroencephalography, to directly control the utterance selection interface of otherwise conventional computerized AAC devices. While this holds some promise to hasten the retrieval of sounds,

words, and phrases stored in the computer, access speed will always be an issue. In the past 10 years or so, an intriguing series of studies has been published that has taken a different tack on the problem. These studies report on a single research participant with locked-in syndrome (Brumberg, Wright, Andreasen, Guenther, & Kennedy, 2011). Locked-in syndrome is a condition typically associated with bilateral damage to the brainstem resulting in complete paralysis of all voluntary muscles except for selected eye movements. Cognition is preserved, but the individual is left unable to move or speak. In these studies, the participant consented to have a small array of recording electrodes surgically implanted over the speech motor area of the frontal lobe. The activity of these electrodes was wirelessly transmitted across the scalp and routed to a system that processed the neural activity. This neural activity was then used to directly control a speech synthesizer that could produce a variety of vowel sounds. The participant could systematically alter the formant values of the vowels produced by the speech synthesizer by consciously altering the activity in the speech motor cortex. The delay time between the activation of the recording electrodes and the production of the vowel sound was about 50 milliseconds, which is like the response delay from motor cortex to the speech articulators under healthy conditions. After about two dozen short training sessions over a 5-month period, the participant demonstrated significant improvements in learning to produce three different vowels by consciously altering his brain activity. Note that directly synthesizing speech sounds from brain activity is qualitatively different from using brain activity to control the selection of sounds and words within a traditional AAC device. Although there is a big gap between reliably producing a closed set of vowels and connected speech, these studies serve as an important “proof of concept.” This is an area that is rapidly developing, and it will be exciting to see the direction of progress in this area. Resources Brumberg, J. S., Nieto-Castanon, A., Kennedy, P. R., & Guenther, F. H. (2010). Brain-computer interfaces for speech communication. Speech Communication, 52, 367–379. Brumberg, J. S., Wright, E. J., Andreasen, D. S., Guenther, F. H., & Kennedy, P. R. (2011). Classification of intended phoneme production from chronic intracortical microelectrode recordings in speech-motor cortex. Frontiers in Neuroscience, 5, 1–12. Guenther, F. H., Brumberg, J. S., Wright, E. J., Nieto-Castañón, A., Tourville, J. A., Panko, M., . . . Kennedy, P. R. (2009). A wireless brain-machine interface for real-time speech synthesis. PLoS One, 4(12), e8218, 1–11.

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system is effectively “taught” how to perform the repertoire of sounds for a given language. In developmental time, these speech gesture representations become increasingly refined and reliably performed (you learn how to speak).

The Development and Refinement of Speech Motor Abilities While infants are not born talking, they are certainly born vocalizing. One of the first signs that a newborn is in good health is that he or she lets out a sharp, loud cry. Any new parent will confirm that crying is one of the most frequent infant vocal behaviors, but it is certainly not the only one. Even though a newborn’s first words are more than a year away, infants typically pass through a common sequence of vocalization milestones characterized by increasingly complex and varied sounds. In the first couple of months of life, the newborn is largely producing reflexive phonations such as coughing, sneezing, and, of course, crying. Between 1 and 3 months, infants transition into a cooing stage in which vowel-like sounds are produced. This is also the time when the infant cry differentiates from one stereotypical acoustic pattern to many nuanced and more acoustically complex crying patterns. In other words, infants develop many different types of cries that become easily identifiable by the caregiver. There are fussy cries, hungry cries, really mad cries, the “I’m bored and need entertainment” cries, and of course, everyone’s favorite, the “I pooped and need a change” cry. New parents are rapidly taught by their bouncing infant the relevance and importance of each newly emerging cry pattern. Between 3 and 8 months is the expansion phase of vocalization when the infant sharpens his or her vowel clarity and broadens the sound repertoire to include behaviors like yells, whispers, squeals, laughter, and raspberries (Oller, 2000). Between 5 and 10 months, infants also begin to produce strings of uniform consonant-vowel syllables (e.g., ba-ba-ba). This is referred to as canonical babbling. Within a few short months, the child begins to produce more variable syllable sequences (e.g., ba-da-ga) as well as evidence of the child’s first meaningful protowords. While the earliest stages of vocalization are considered universal to all linguistic environments, language-specific sounds begin to emerge during this transitional period. The ubiquity of these early vocal behaviors suggests that they may be a necessary antecedent to subsequent speech development. One hypothesis is that these behaviors allow the infant to explore the vocal sensorimotor space and make connections between a given articulatory configuration of the vocal tract and the resulting sound (Fagan, 2015). This hypothesis is consistent with the predictions of the DIVA model reviewed in the previous section. Sensorimotor exploration, combined with frequent auditory exposure to native language sound systems, helps

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the child prepare for the transition to forming language-​ specific sounds themselves. Consistent with this view, a study of infant nonspeech oral motor movements revealed that during their first year of life, infants do systematically alter the kinematic characteristics of these early nonspeech movements (Green & Wilson, 2005). Even though the first meaningful speech erupts near a child’s first birthday, it still takes most children many years to master all the sounds of their native language. Studies have established general patterns for the emergence and mastery of various speech sounds for a given language. However, many of these studies rely on phonetic transcriptions, which are prone to rater bias and may fail to discern smaller and more subtle phonetic differences that may reflect finer incremental changes in skill development. Fortunately, technical advances over the last couple of decades have made it much easier to collect detailed acoustic and articulatory kinematic data on children of all ages (Green & Nip, 2010). This allows for multilevel analysis of speech motor skill that can provide a more in-depth understanding of changes in speech sensorimotor behavior over the course of development. To date, articulatory kinematic studies have revealed several interesting findings. First, articulatory variability, which is a commonly used metric considered to reflect speech motor stability and possibly speech motor skill, is generally greater in children compared to adults (Goffman & Smith, 1999). While this fact is not that surprising, what does come as a surprise is that children as old as 16 years of age continue to exhibit greater articulatory variability compared to adults, despite producing fluent well-articulated speech for years. This result suggests that even though we can’t hear a difference, teens may still be fine-tuning their speech sensorimotor systems. Articulatory variability studies have also revealed that speech sensorimotor development, like sensorimotor development in general, progresses in a nonlinear fashion that can include intermittent periods of rapid development, plateaus in performance, and slow steady changes (Green & Nip, 2010; Vick et al., 2012). For example, one study reported a somewhat counterintuitive finding that articulatory production variability is surprisingly greater in 2-year-old children compared to 1-year-old children producing similar tasks. The study hypothesized that the increase in articulatory variability in the older children may be due to the rapid expansion of their lexicon given their age. Additional studies in older children have reported similar findings. Thus, as children age, articulatory variability may get smaller, then larger, and then smaller again, depending on the language competency of the child at that moment in time. Young children and adults appear to use different multi-articulator strategies to produce speech and speech-like movements (Green & Nip, 2010). Infants less than 1 year of age tend to rely more on jaw movement to produce early bilabial speech sounds than do older children and adults, who routinely use a combination of the upper lip, lower lip, and

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jaw. When infants do use a combination of articulators, the pattern tends to be asynchronous and spatially different from mature productions. Examination across age groups suggests that a stable, mature pattern of bilabial closure emerges around 6 years of age. Together these findings suggest that careful, instrumented study of speech sensorimotor behavior across development can provide information about differences that are not otherwise currently available through more perceptual (listening-based) means. One challenge for researchers is to understand why patterns of speech motor development are so complex. One perspective suggests that the speech motor skill developmental process is dynamically shaped by two potentially opposing influences: constraints and catalysts (Green & Nip, 2010). Constraints are factors that may serve to limit the rate of skill development. Examples of constraints include (a) cognitive constraints that could limit the rate at which ideas are formulated, (b) linguistic constraints that may limit speed of planning of utterances, and (c) motor constraints of immature motor systems that limit the range of possible patterns of action available (Green & Nip, 2010). Catalysts are factors that can serve to facilitate speech motor skill development. Exam-

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ples of catalysts include (a) the child’s willingness to engage in vocal play; (b) the richness of the communication environment (e.g., parental modeling of speech); and (c) factors such as expressive vocabulary, which is reported to be correlated with phonological development (Green & Nip, 2010). If the child knows more words, he or she is more likely to attempt to say them, facilitating mastery of the speech sound system. This perspective predicts that the specific constraints and catalysts will vary across the developmental timeline. Furthermore, what might be a catalyst at one point in time may serve as a constraint at another point in time. For example, we know that children are tasked with learning to speak using vocal tract structures that undergo continual physical change during their growth. One might consider this to be a constraint because the neuromotor system must constantly be accommodating these small, but significant changes in vocal tract geometry. However, during the first 6 months of life, the vocal tract undergoes rather dramatic changes, from a shape that is quite similar to a nonhuman primate (a somewhat flat 120-degree angle) to a shape that is more similar to the adult human (close to 90-degree angle). Though the rate of this shape shift is rapid, it allows the

Box 16–4. Further Interest:  The Bouba-Kiki Effect The bouba-kiki effect has been used for several decades to argue that auditory characteristics of words may have evolved from the physical characteristics of objects humans interact with visually and/or by touch. The bouba-kiki effect is typically shown in the following manner. An individual is given two novel objects, one of which is soft with rounded edges and a second object that is more angular with sharper or pointy features. The individual is then asked to match each object to a corresponding pseudoword for the object. The individual is not told which term belongs to which object; they must guess simply by using the visual and tactile features of the objects being manipulated. Most English-speaking test subjects will choose the pseudoword “bouba” for the round, soft object and “kiki” for the sharp, pointy object. This effect is robust and, in fact, has been demonstrated across numerous cultures and age groups. The question is, what underlies the ability to match a pseudoword to an object’s physical features? Numerous investigators have hypothesized that the bouba-kiki effect is based on the capacity of the brain to detect similar global features of sensory inputs across different sensory modalities, a mechanism referred to as cross-modal correspondence. Think about articulating the pseudowords “bouba” and “kiki.” Bouba is produced using a lip rounding gesture with a plosive release of air that tends to highlight lower frequencies in the acoustic

signal. Kiki, on the other hand, is created with an angular spread lip posture and an articulation that highlights higher frequencies in the acoustics. It is reasoned that most speakers match bouba to rounded shapes, and kiki to objects with sharp corners or edges, because both the tactile and visual physical features of rounded and sharp objects mimic the acoustic properties of the spoken pseudowords, respectively. Interestingly, children with autism spectrum disorder (ASD) perform poorly on the bouba-kiki effect with response rates that are barely above chance, a striking contrast to neurotypical children who respond correctly at rates close to 90%. This finding suggests that children with ASD are not using feature correspondences to make a match between the pseudowords and the manipulated objects, but instead are guessing randomly when tested. It is hypothesized that poor performance on this task reflects deficits in the ability of children with ASD to use multisensory integrative processes, suggesting impairment in brain systems that support these behaviors. Resource Oberman, L. M., & Ramachandran, V. S. (2008). Preliminary evidence for deficits in multisensory integration in autism spectrum disorders: the mirror neuron hypothesis. Social Neuroscience, 3(3–4), 348–355.

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infant the capacity to produce a much richer repertoire of sounds. In this context, vocal tract growth serves as a catalyst to speech motor skill development (Green & Nip, 2010).

Selected Neurological Disorders of Speech and Vocalization Throughout this chapter, there have been numerous references to communication deficits associated with nervous system damage. Such damage can cut a broad or narrow swath of impairment ranging from the physical execution of speech/voice motor actions to the coordination and planning of utterances, to the comprehension and expression of the spoken and written word, to the marshalling of necessary cognitive resources to meet the demands of communication. Although this chapter is focused on the sensorimotor elements of speech, it is important to recognize that speech production is a physical manifestation of linguistic, cognitive, and social goals. In the real world of speech-language pathology, communication deficits seldom respect the organizational boundaries we impose on them academically. Table 16–4 provides a handy summary of select neurological disorders related to speech and vocalization.

Aphasias An impairment in the comprehension and expression of oral and written language due to neurological damage is termed aphasia. Typically, aphasia arises due to focal damage in the dominant (usually left) hemisphere. Persons with aphasia usually have preserved cognition, meaning that memory, attention, and problem-solving skills are mostly unaffected. The primary issue in aphasia is using the language system to express thoughts, feelings, and opinions. Symptom presentation can be variable, and a large classification scheme has been developed to organize the range of aphasic conditions (see Chapter 17 for specific details on aphasia classifications). Two examples illustrate this variability. Individuals with expressive or Broca’s aphasia struggle to speak in phrases or do so using a telegraphic style of speaking. Their speech has a notable absence of grammatically necessary words, yet they retain relatively good comprehension of what is said by themselves and/or others. Broca’s aphasia typically results from damage in the region of the left inferior frontal gyrus. On the other hand, damage to the temporoparietal region of the left hemisphere often results in receptive or Wernicke’s aphasia. Individuals with Wernicke’s aphasia often struggle to understand the spoken and written word. Verbal expression is often fluent, yet devoid of meaning due to the frequent use of jargon, nonsense words, incorrect words, or words with significant sound substitutions. When neurological damage preferentially affects cognitive processes such as memory, attention, and reasoning,

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individuals are said to have a cognitive communication dis­ order. Although speech and language abilities may not be directly impaired, cognitive limitations can affect the individual’s ability to maintain attention during a conversation, remember relevant information, hold a topic, and respect general social rules of communication. Such disorders can arise from a wide range of neurological events, including nondominant hemisphere damage, traumatic brain injury, and dementia.

Motor Speech Disorders:  Dysarthrias Neurological damage that affects some aspect of the planning and execution of the speech production process is termed a motor speech disorder. Motor speech disorders form a large class of communication disorders. Dysarthria is a general name given to a group of neurologic speech disorders that result in weakness, spasticity, incoordination, involuntary movements, or altered tone of the muscles controlling respiratory, phonatory, resonance, articulatory, and prosodic aspects of speech production. Like aphasia, there is a wide range of subtypes of dysarthria. For dysarthria, the Mayo Clinic classification scheme was developed several decades ago to help systematize the diagnosis of dysarthric conditions. The Mayo Clinic system is based on the assumption that damage to neuromotor structures will affect speech motor control in reliable and distinct ways and that these differences will be reflected in the perceptual characteristics of speech (Duffy, 2013). In other words, the naming scheme used to classify dysarthria reflects the assumption that speech features are related to an underlying pathophysiology. Different types of dysarthria are based on location of damage within the CNS, with each subtype exhibiting a distinguishable and specific set of speech characteristics (Duffy, 2013). Common subtypes of dysarthria include: • flaccid dysarthria (due to damage to the lower motor neuron system), • spastic dysarthria (due to bilateral damage to the upper motor neuron system), • ataxic (cerebellar) dysarthria (due to damage to the cerebellum), • hypokinetic dysarthria (due to basal ganglia disorder), and • hyperkinetic dysarthria (due to basal ganglia disorder). Flaccid dysarthria arises from damage to the lower motor neuron system. This type of dysarthria typically results from damage to the peripheral nerves associated with speech production or the ventral spinal cord/brainstem nuclei from which they arise (Duffy, 2013). Flaccidity results from lower motor neuron damage and is characterized by muscle weakness, loss of muscle tone, atrophy, and absence of stretch reflexes. The specific speech deficits associated with flaccid dysarthria depend heavily on the specific nerves and

 TABLE 16–4.   Summary of Select Neurological Disorders Related to Speech and Vocalization Disorder Type

Disorder Form

Lesion Site and Effects

Expressive (Broca’s)

• Damage to inferior frontal gyrus • Struggle to speak in phrases, telegraphic speaking, absence of grammatically necessary words, retain relatively good comprehension

Receptive (Wernicke’s)

• Damage to temporoparietal junction • Fluent speech devoid of meaning, frequent use of jargon, sound substitutions

Flaccid

• Damage to LMN • Muscle weakness, loss of muscle tone, atrophy • Ipsilateral effects

Spastic

• Damage bilaterally to UMN • Increased muscle tone and paresis • Slow labored speech rate, a monotone and strained/strangled voice quality, pronounced hypernasality, and imprecise articulation • Common after stroke

Ataxic

• Damage to cerebellar system • Dyscoordination and slower reaction times • Low-frequency rhythmic articulator oscillation, loudness variations such as explosive speech • Excess and/or equal syllabic stress and imprecise articulation

Hypokinetic

• Damage to basal ganglia motor circuit • Reduced movement, bradykinesia, muscle rigidity, and resting tremor • Hoarseness, low volume, hypernasality, monotone voice quality, difficulty initiating speech, and imprecise articulation, vocal tremor

Hyperkinetic

• Damage to basal ganglia motor circuit • Excessive movements, misdirected and ballistic actions, discrete body movements overlaid onto otherwise purposeful voluntary movements • Strained/strangled voice, misdirected articulations, atypical respiratory patterns

Apraxia

• Damage to inferior premotor cortex of the frontal lobe and/or insula • Impaired capacity to plan or program sensorimotor commands necessary for phonetically and prosodically normal speech • Consonant and vowel distortions, distorted substitution of phonemes, slowed rate, and unusual stress patterns

Mutism

• Absence of speech due to damage to systems such as frontal lobe, anterior cingulate, and cerebellum • Forms include locked-in syndrome, akinetic and cerebellar mutism

Dysphonia

• Many different systems can be affected • Broad class of disorder signifying alterations in voice production impacting effective communication • Includes vocal fold paralysis, spasmodic dysphonia, and dystonias

Aphasia

Dysarthria

Other types

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nuclei involved. For example, if the hypoglossal nerve is involved, the affected individual will struggle to produce precise articulation of lingual sounds, while respiratory, phonatory, velopharyngeal, and labial function would be preserved. Alternatively, flaccid dysarthria secondary to a more general disease, such as Bell’s palsy or the autoimmune disorder Guillain-Barré syndrome, can cause paresis across all speech subsystems, resulting in a more complex presentation. In the case of Bell’s palsy, for example, this disorder specifically affects the facial nerve, resulting in a partial or complete paralysis of the facial muscles ipsilateral to the diseased nerve (see Figure 14–8C for reference). Individuals with Bell’s palsy exhibit a pronounced facial droop on the affected side, and often struggle to produce speech sounds involving the lips and express emotion through facial expressions. For most cases, the cause of Bell’s palsy is unknown, though viral infection has been implicated. Prognosis for a full recovery from Bell’s palsy is usually good, and resolution of symptoms often begins within a few weeks of onset. Spastic dysarthria typically occurs as the result of bilateral damage to the upper motor neuron system. The upper motor neurons are mostly located in the corticospinal and corticobulbar tracts that project from ventral cortical motor areas to synapse onto the lower motor neurons in the brainstem and spinal cord. Upper motor neuron damage often leads to spasticity, a clinical condition that includes muscle paresis, increased muscle tone, and exaggerated stretch reflexes. It is presumed that spastic paresis underlies some of the key perceptual characteristics of spastic dysarthria, which include a slow labored speech rate, a monotone and strained/strangled voice quality, pronounced hypernasality, and imprecise articulation. Common causes of spastic dysarthria include stroke (often multiple strokes), cerebral palsy, and amyotrophic lateral sclerosis (Lou Gehrig’s disease) (Duffy, 2013). Ataxic dysarthria is a term reserved for dysarthria secondary to lesions within the cerebellum. As noted earlier, damage to the cerebellum typically results in ataxia, a condition that includes dyscoordination, poor skilled motor control, and unsteady gait. Intentional tremor, a low-frequency rhythmic oscillation of articulators during active skilled voluntary movement, is also characteristic of cerebellar damage. Speech characteristics include large variations in loudness, poor regulation of one’s pitch, excessive and/or unequal syllabic stress, and imprecise articulation (Duffy, 2013). Causes of ataxic dysarthria include stroke, cerebellar tumors, head trauma to the back of the skull, and degenerative cerebellar diseases such as Friedreich’s ataxia. Hypokinetic dysarthria arises primarily in individuals who suffer from Parkinson’s disease, which is related to the degeneration of dopamine-producing cells within the substantia nigra, a key functional part of the basal ganglia. Primary characteristics of Parkinson’s disease include hypokinesia or reduced movement, bradykinesia or slow movement, muscle rigidity, postural instability, and a rest­ ing tremor. These disturbances are realized in the speech

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motor system as hoarseness, low volume, monotone voice quality, difficulty initiating speech, frozen facial expressions, and imprecise articulation (Duffy, 2013). (See Table 14‒2 to review the general characteristics of hypokinetic conditions related to basal ganglia dysfunction.) Hyperkinetic dysarthria can also result from damage to basal ganglia structures. Hyperkinesia is a term used to describe the general presence of excessive, abnormal, or unintended movements and is observed in neurological conditions such as Huntington’s disease, an adult-onset degenerative neurological condition. Clinically, individuals with hyperkinesia will exhibit random, discrete body movements overlaid onto otherwise purposeful voluntary movements. As a result of the hyperkinesia, voluntary movements often do not reach their intended target. The characteristics of hyperkinetic dysarthria can be quite variable, depending on the degree to which involuntary movements are superimposed onto goal-directed actions (Duffy, 2013). (See Table 14‒2 to review the general characteristics of hyperkinetic conditions, related to basal ganglia dysfunction.) While these five types of dysarthria are thought to be distinct from each other, not all individuals with dysarthria fall neatly into these categories. In many cases, disease processes such as multiple sclerosis may cause damage to many regions of the brain at once, resulting in a “mixed ” dysarthria with features coming from more than one category (e.g., mixed spastic-ataxic dysarthria).

Other Speech Production Deficits Apraxia of speech is a type of motor speech disorder that is distinct from dysarthria. It is characterized by an impaired capacity to plan or program sensorimotor commands necessary for phonetically and prosodically normal speech. Apraxia of speech typically results from acquired damage to the inferior premotor cortex of the frontal lobe and/or insula. Speech characteristics typically include consonant and vowel distortions, distorted substitution of phonemes (e.g., “momato” for “tomato”), slowed rate, and unusual stress patterns. It is not uncommon for apraxia of speech to co-occur with expressive aphasias (Duffy, 2013). Mutism is a general term that means the absence of speech. Individuals who are mute are unable to generate the body movements necessary to produce speech. Individuals can be mute for a variety of reasons. In cases such as selective mutism, the cause is presumed to be psychological in origin. However, mutism can also be the result of a wide range of neurological conditions. These include but are not limited to (a) locked-in syndrome, associated with severe damage to the direct motor system; (b) akinetic mutism, associated with frontal lobe damage or damage to the anterior cingulate cortex; and (c) cerebellar mutism, which is usually a transient result of damage to the cerebellum (Duffy, 2013). Dysphonia is broadly defined as an alteration in voice production that impairs the effectiveness of communication (Stemple et al., 2014). Not all dysphonias are the consequence

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Box 16–5. Clinical:  Types of Apraxia of Speech (AOS) There are two main types of AOS: acquired apraxia of speech and childhood apraxia of speech. • Acquired AOS can affect someone at any age, although it most typically occurs in adults. Acquired AOS is caused by damage to the parts of the brain that are involved in speaking and involves the loss or impairment of existing speech abilities. It may result from a stroke, head injury, tumor, or other illness affecting the brain. Acquired AOS may occur together with other conditions that are caused by damage to the nervous system. • Childhood AOS is present from birth. This condition is also known as developmental apraxia of speech, developmental verbal apraxia, or articulatory apraxia. Childhood AOS is not the same as developmental delays in speech, in which a child follows the typical

of neurological abnormalities. Structural changes to the vocal folds and functional impairments can also result in dysphonia. When the cause is neurogenic, the term dysphonia is usually reserved for conditions in which the other speech motor systems are intact. Otherwise, the condition would be considered a dysarthria. One common neurogenic dysphonia is vocal fold paresis/paralysis, which arises from damage to

path of speech development but does so more slowly than is typical. The causes of childhood AOS are not well understood. Research studies have not been able to find evidence of brain damage or differences in the brain structure of children with AOS. Children with AOS often have family members who have a history of a communication disorder or a learning disability. This observation and recent research findings suggest that genetic factors may play a significant role in the expression of this disorder in children. Resource Edited from public domain material by the U.S. Department of Health and Human Services. (2016, September). Apraxia of speech. National Institute of Deafness and Other Communication Disorders. Retrieved January 11, 2022, from https:// www.nidcd.nih.gov/health/apraxia-speech

the peripheral nerves that synapse onto the intrinsic muscles of the larynx. Unilateral vocal fold paresis/paralysis results in a soft, breathy voice quality, respiratory stridor, and the aspiration of liquids due to poor airway valving during swallowing. Bilateral vocal fold paralysis can also result in voice and swallowing difficulties. However, for some, the paralyzed vocal folds are fixed in a near fully adducted position,

Box 16–6. Clinical:  Types of Spasmodic Dysphonia (SD) • Adductor spasmodic dysphonia is the most common form of spasmodic dysphonia diagnosed. In this form of the disorder, spasms cause the vocal folds to powerfully approximate together and stiffen. These spasms make it difficult for the vocal folds to vibrate normally and produce sound. The voice of someone with adductor spasmodic dysphonia may perceptually sound strained and strangled. A person’s speech may also sound choppy, with words often cut off. Individuals with SD may also have difficulty initiating speech because the muscle spasms prevent the initiation of vocal fold vibration. Interestingly, spasms are usually absent while laughing, crying, or whispering. • Abductor spasmodic dysphonia is less commonly diagnosed. In this form of the disorder, muscle spasms cause the vocal folds to remain open. Vocal folds cannot vibrate and generate sound when they are open and unable to contact each other. The open position

of the folds also allows a great deal of air to escape from the lungs during speech. As a result, the voice of someone with abductor SD often sounds weak and breathy. As with adductor spasmodic dysphonia, the muscle spasms are often absent during activities such as laughing, crying, or whispering. • Mixed spasmodic dysphonia is a combination of the previous two types and is very rare. Because the muscles that open and the muscles that close the vocal folds are not working properly, it has behavioral features of both adductor and abductor spasmodic dysphonia. Resource Edited from public domain material by the U.S. Department of Health and Human Services. (2020, March). Spasmodic dysphonia. National Institute of Deafness and Other Communication Disorders. Retrieved January 11, 2022, from https:// www.nidcd.nih.gov/health/spasmodic-dysphonia

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compromising the integrity of the airway and requiring procedures to restore a patent airway. Another neurogenic type of dysphonia is spasmodic dysphonia (Stemple et al., 2014). Spasmodic dysphonia is characterized by sudden intermittent spasms of the laryngeal muscles, resulting in a tight and highly strained vocal quality. The spasmodic episodes can affect the muscles of adduction,

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abduction, or both. Spasmodic dysphonia is an example of a dystonia, which is a family of neurological conditions with the shared sign of sustained or intermittent uncontrolled muscle contractions (Hintze, Ludlow, Bansberg, Adler, & Lott, 2017). While the neurological substrate of spasmodic dysphonia is only vaguely known, dysfunction of the basal ganglia appears to be a likely location for its emergence.

Box 16–7. Clinical:  You’re Going to Use a Neurotoxin to Improve My Voice?! Tens of thousands of North Americans suffer from a neurologically based voice disorder called spasmodic dysphonia (SD). SD typically erupts in adulthood, most often in middle age, and tends to affect more women than men. Persons who suffer from SD typically have a voice that sounds tight and strained and that will often break into a whisper. SD is part of a family of more general neurological disorders called dystonias. Dystonias are characterized by sustained or intermittent uncontrolled muscle contractions that are often intensified by physical activity. Other examples of dystonia include writer’s cramp and blepharospasm (rapid eye blinking). While the neural substrate of SD has not been clearly identified, the basal ganglia have been implicated. SD tends to be associated with spasmodic contractions of the intrinsic muscles of the larynx. The disease process can selectively affect the muscles that adduct (move toward the midline) the true vocal folds, the muscles that abduct (move away from the midline) the true vocal folds, or both muscle groups. The details of the symptom complex will vary depending on the affected muscles. There is not a known cure for SD, but there are treatment approaches that can help alleviate many of SD’s symptoms. The most common treatment approach surprisingly involves the use of a neurotoxin that in large quantities would most certainly kill you! Botulinum toxin (Botox) is a neurotoxin produced by the Clostridium botulinum species of bacteria. The toxin prevents the release of the neurotransmitter acetylcholine from the axon terminals of motor neurons that form a syn-

apse onto muscle fibers. Blocking neurotransmitter release prevents the generation of muscle action potentials necessary for contraction. The result is a flaccid paralysis of the muscle. Botox is one of the most lethal toxins known, and persons infected with Clostridium botulinum due to food poisoning or an exposed wound are at a significant health risk, particularly if the toxin reaches and paralyzes the respiratory muscles. However, the field of medicine has found that in extremely small, controlled dosages, Botox can be a safe and effective treatment for excessive muscle activation, as is seen in SD. Botox is injected directly and locally into those intrinsic laryngeal muscles determined to be excessively active. The result is a diminished capacity for the target muscle to contract. The effect typically lasts from weeks to months, necessitating repeated injections. In the first few days after injection, the voice may be weak and breathy, and the client might occasionally experience choking on liquids because the laryngeal muscles are at their weakest. After a few days, though, laryngeal function stabilizes, and the spasmodic muscle contractions that characterize SD diminish. This is a great example of how knowledge of disease mechanisms may be exploited to improve, rather than impair, human health and well-being. Resource Stemple, J. C., Roy, N., & Klaben, B. K. (2014). Clinical voice pathology: Theory and management (5th ed.). San Diego, CA: Plural Publishing.

The Top Ten List 1. Vocalization is the term used to characterize any complex pattern of sound production, while speech refers to the verbal expression of thoughts and feelings using time-varying sound patterns decodable by listeners who share a common reference language. Like many animals, humans possess a wide repertoire of innately specified vocalizations, including laughter, crying,

grunting, singing, and speech. Speech, however, must be actively learned to generate the sound patterns associated with our language. Speech production is the single most complex sensorimotor behavior in which humans engage. 2. Human speech and vocalization is generated from a wide array of anatomical subsystems that include the

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The Top Ten List  continued

respiratory, laryngeal, pharyngeal, velopharyngeal, oral, dental, mandibular, lingual, nasal, and labial systems. These systems are regulated by efferent and afferent pathways with origins and destinations within the cranial nerve nuclei of the brainstem and within motor and sensory gray matter of the spinal cord. 3. Aside from the direct regulation of speech systems by primary cortical areas, several different subcortical areas are also active in the regulation of human vocalizations. The reticular formation of the brainstem appears to be the lowest structure capable of coordinating muscle activity underlying vocalization. The periaqueductal gray is a midbrain structure that plays an important role in nonhuman animal vocalization and is hypothesized to also play a role in human vocalization. The thalamus is also known to be a key structure for speech and hearing behaviors. Key thalamic nuclei such as the VPM and medial geniculate body are responsible for relaying somatosensory and acoustic signals from the periphery to central locations. Lastly, the motor circuit through the basal ganglia is known to have, at a minimum, general influences on speech production. 4. Neuroimaging studies indicate that cerebellar activity is associated with the production of covert or silent speech tasks. It has been hypothesized that the cerebellum may play a role in mental rehearsal of motor acts, speech motor planning, and verbal working memory. Functional neuroimaging studies indicate a convergence of articulatory behavior within the paravermal region of the cerebellum. Activity in the superior portion of the paravermal region appears to code for the degree of syllable complexity, while inferior paravermal regions are more sensitive to changes in syllable sequencing. 5. Key cortical structures associated with speech production are in the temporal, parietal, and frontal lobes. The temporal lobe is active for representing and processing information from the auditory system. The parietal lobe represents and processes tactile and proprioceptive signals generated during speech. Lastly, the frontal lobe operates to produce motor plans and is active for higher-level decision-making and language formulation that is output by speech production. 6. The dual-stream processing models of speech and language, such as the one by Hickok and Poeppel (2007), hypothesize distinctive roles for a dorsal and a ventral speech processing stream. In this model, auditory-​ conceptual ventral streams are involved in linking meaning to a sound sequence. The auditory-motor dorsal stream is tasked to determine how to reproduce sounds we hear using our own vocal tracts. The ventral stream includes structures within the middle and

inferior temporal lobes, while the dorsal stream includes structures at the junction of the parietal and temporal lobes and the motor association cortices of the frontal lobe. 7. Sensory motor adaptation studies are investigations that systematically alter auditory and somatosensory information to assess their change on speech motor control mechanisms. Auditory perturbation studies demonstrate that subjects will adjust their speaking patterns to adapt to a variety of altered auditory conditions. Perturbation studies that instead have used altered somatosensation during speech conditions also show that subjects respond and modify central motor commands to imposed sensory conditions. Thus, speakers use sensory information on an ongoing basis to fine-tune descending motor commands during speech production. 8. The DIVA model is a computational model that is designed to test several speech-related conditions, including (a) speech development, (b) normal speech production, and (c) the neural foundations of many speech disorders. The DIVA model is an example of an adaptive control system that balances the use of feedforward and feedback control during the learning and performance of speech. The DIVA model uses known neuroanatomical structures that participate in speech, making it possible to test the model’s predictions against data from real humans. 9. While humans can vocalize from the first moments of life, speech development requires years to mature. Speech development begins in infancy with largely reflexive phonations. Between 3 and 8 months, infants begin to sharpen their vowel clarity and broaden their sound repertoire to include behaviors like yells, whispers, squeals, laughter, and raspberries. By 4 to 6 months, infants begin to produce strings of uniform consonant-vowel syllables called canonical babbling. These behaviors allow the infant to explore the vocal space and make early connections between a given articulatory configuration and its resulting sound. 10. Neurological damage that affects the planning and execution of the speech production process is termed a motor speech disorder. Motor speech disorders form a large class of disorders that result in weakness, spasticity, incoordination, involuntary movements, or altered tone of the muscles controlling respiratory, phonatory, resonance, articulatory, and prosodic aspects of speech production. The Mayo Clinic classification system, developed to systematize the diagnosis of dysarthric conditions, assumes that damage to neuromotor structures will affect speech motor control in reliable and distinct ways. Other forms of speech disorders include apraxia of speech, mutism, dysphonias, and dystonias.

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Chapter 16 Abbreviations A1 — Primary auditory cortex aINS — Anterior insula aITS — Anterior inferior temporal sulcus aMTG — Anterior middle temporal gyrus aSTG — Anterior superior temporal gyrus ACC — Anterior cingulate gyrus AOS — Apraxia of speech Cb — Cerebellum CMA — Cingulate motor area CN — Cranial nerves CNS — Central nervous system DIVA — Directions Into Velocities of Articulators model dSTG — Dorsal superior temporal gyrus eSLN — External branch of SLM F1 — First acoustic formant of speech GP — Globus pallidus GPe — Globus pallidus external GPi — Globus pallidus internal Hz — Hertz IFGop — Inferior frontal gyrus pars opercularis

IFGorb — Inferior frontal gyrus pars orbitalis IFGtri — Inferior frontal gyrus pars triangularis ILM — Intrinsic laryngeal muscle kHz — Kilohertz LMN — Lower motoneuron M1 — Primary motor cortex MG — Medial geniculate nucleus MRI — Magnetic resonance imaging PAG — Periaqueductal gray

S1 — Primary somatosensory cortex SLN — Superior laryngeal nerve SMA — Supplementary motor area SMG — Supramarginal gyrus Spt — Sylvian parietotemporal junction STG — Superior temporal gyrus STS — Superior temporal sulcus SN — Substantial nigra SNpc — Substantia nigra pars compacta

PD — Parkinson’s disease

SNpr (SNr) — Substantia nigra pars reticulata

pAC — Posterior auditory cortex

UMN — Upper motoneuron

pIFG — Posterior inferior frontal gyrus

VA — Ventroanterior nucleus of thalamus

pITS — Posterior inferior temporal sulcus pMTG — Posterior middle temporal gyrus pSTG — Posterior superior temporal gyrus preSMA — Pre–supplementary motor area

VL — Ventrolateral nucleus of thalamus vPoCG — Ventral postcentral gyrus vPrCG — Ventral precentral gyrus VPM — Ventroposteromedial nucleus of thalamus

PM — Premotor cortex

VPL — Ventroposterolateral nucleus of thalamus

PN — Pharyngeal nerve

vMC — Ventral motor cortex

RetF — Reticular formation

vPMC — Ventral premotor cortex

RLN — Recurrent laryngeal nerve

vSC — Ventral somatosensory cortex

Study Questions and Activities • Compare and contrast the terms speech and vocalization. • List and describe the ways used by scientists to learn about the neural foundations of speech and vocalization. • Review and memorize the peripheral nerves involved in speech and vocalization. Use the referenced illustrations to help you develop this review.

• Summarize the descending inputs to speech-related motor neuron pools in the brainstem and spinal cord. • Summarize the ascending sensory inputs from speech-related structures. • Describe the role of each subcortical structure that is active during vocalization. Organize this material in a chart for easy reference.

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Study Questions and Activities  continued

• Describe the role of each cortical structure that is active during vocalization. Organize this material in a chart for easy reference. • Explain the idea that “we are listeners before we are speakers.” What are the implications of this idea for human communication? • Explain the dual-stream sensory processing model developed by Hickok and Poeppel. • What are the functional differences between the ventral and dorsal stream in the Hickok and Poeppel model? • What processing stages in the Hickok and Poeppel model are shared between the dorsal and ventral streams? • Create a flowchart that traces the dorsal and ventral processing streams of the Hickok and Poeppel model. • Summarize your understanding of sensorimotor learning in the context of speech production and perception. Use the study by Lametti and colleagues (2012) to help you develop your summary. • Summarize your understanding of the DIVA model. • Why is the DIVA model different from other computational models of speech production and perception?

References Ambalavanar, R., Tanaka, Y., Damirjian, M., & Ludlow, C. L. (1999). Laryngeal afferent stimulation enhances Fos immuno­ reactivity in periaqueductal gray in the cat. Journal of Comparative Neurology, 409(3), 411–423. Ardila, A., Bernal, B., & Rosselli, M. (2016). How localized are language brain areas? A review of Brodmann areas involvement in oral language. Archives of Clinical Neuropsychology, 31(1), 112–122. Bass, A. H., Gilland, E. H., & Baker, R. (2008). Evolutionary origins for social vocalization in a vertebrate hindbrain-spinal compartment. Science, 321, 417–421. Carey, D., Krishnan, S., Callaghan, M. F., Sereno, M. I., & Dick, F. (2017). Functional and quantitative MRI mapping of somatomotor representations of human supralaryngeal vocal tract. Cerebral Cortex, 27(1), 265–278. DeLong, M. R., & Wichmann, T. (2007). Circuits and circuit disorders of the basal ganglia. Archives of Neurology, 64(1), 20–24. Devinsky, O., Morrell, M. J., & Vogt, B. A. (1995). Contributions of anterior cingulate cortex to behaviour. Brain, 118, 279–306. Duffy, J. R. (2013). Motor speech disorders (3rd ed.). St. Louis, MO: Elsevier Mosby. Fagan, M. K. (2015). Why repetition? Repetitive babbling, auditory feedback, and cochlear implantation. Journal of Experimental Child Psychology, 137, 125–136. Flinker, A., Korzeniewska, A., Shestyuk, A. Y., Franaszczuk, P. J., Dronkers, N. F., Knight, R. T., & Crone, N. E. (2015). Redefin-

• What was the DIVA model intended to accomplish regarding the development and production of speech? • Explain the goal of the feedforward system in the DIVA model. What anatomical structures are associated with this segment of the model? • Explain the goal of the feedback system in the DIVA model. What anatomical structures are associated with this segment of the model? • How does the DIVA model fit into the concept of an adaptive control system? • Explain and outline the development of vocal control and speech in the human. • What is meant by the terms constraints and catalysts? How are these terms applied in the context of speech motor development? • Create a summary chart that lists the different classes of neurological disorders related to speech and vocalization. Break down each class into the specific disorders discussed in the text. For each disorder, provide a brief synopsis of the signs and symptoms that characterize each condition.

ing the role of Broca’s area in speech. Proceedings of the National Academy of Sciences, 112(9), 2871–2875. Fried, I., Katz, A., McCarthy, G., Sass, K. J., Williamson, P., Spencer, S. S., & Spencer, D. D. (1991). Functional organization of human supplementary motor cortex studied by electrical stimulation. Journal of Neuroscience, 11(1), 3656–3666. Ghosh, S. S., Tourville, J. A., & Guenther, F. H. (2008). A neuroimaging study of premotor lateralization and cerebellar involvement in the production of phonemes and syllables. Journal of Speech, Language, and Hearing Research, 51(5), 1183–1202. Goffman, L., & Smith, A. (1999). Development and phonetic differentiation of speech movement patterns. Journal of Experimental Psychology: Human Perception and Performance, 25(3), 649–660. Golfinopoulos, E., Tourville, J. A., Bohland, J. W., Ghosh, S. S., Nieto-Castanon, A., & Guenther, F. H. (2011). fMRI investigation of unexpected somatosensory feedback perturbation during speech. NeuroImage, 55(3), 1324–1338. Green, J. R., & Nip, I. S. B. (2010). Some organization principles in early speech development. In B. Maassen, & P. van Lieshout (Eds), Speech motor control: New developments in basic applied research (pp. 171–190). London, UK: Oxford University Press. Green, J. R., & Wilson, E. M. (2005). Spontaneous facial motility in infancy: A 3D kinematic analysis. Developmental Psychobiology, 48(1), 16–28. Green, J. R., Wilson, E. M., Wang, Y.-T., & Moore, C. A. (2007). Estimating mandibular motion based on chin surface targets during speech. Journal of Speech, Language, and Hearing Research, 50(4), 928–939.

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Guenther, F. H. (2016). The neural control of speech. Cambridge, MA: MIT Press. Guenther, F. H., Brumberg, J. S., Wright, E. J., Nieto-Castañón, A., Tourville, J. A., Panko, M., . . . Kennedy, P. R. (2009). A wireless brain-machine interface for real-time speech synthesis. PLoS One, 4(12), e8218, 1–11. Guenther, F. H., & Vladusich, T. (2012). A neural theory of speech acquisition and production. Journal of Neurolinguistics, 25(5), 408–422. Haines, D. E. (2013). Fundamental neuroscience: For basic and clinical applications (4th ed.). Philadelphia, PA: Elsevier Saunders. Hickok, G., Okada, K., & Serences, J. T. (2008). Area Spt in the human planum temporale supports sensory-motor integration for speech processing. Journal of Neurophysiology, 101(5), 2725–2732. Hickok, G., & Poeppel, D. (2007). The cortical organization of speech processing. Nature Reviews Neuroscience, 8(5), 393–402. Hickok, G., & Poeppel, D. (2015). Neural basis of speech perception. In G. Hickock & S. L. Small (Eds.), Neurobiology of language (pp. 299–308). San Diego, CA: Academic Press. Hintze, J. M., Ludlow, C. L., Bansberg, S. F., Adler, C. H., & Lott, D. G. (2017). Spasmodic dysphonia: A review, Part 1: Pathogenic factors. Otolaryngology–Head and Neck Surgery, 157(4), 551–557. Hixon, T. J., Weismer, G., & Hoit, J. D. (2013). Preclinical speech science (2nd ed.). San Diego CA: Plural Publishing. Hoit, J. D., Banzett, R. B., Lohmeier, H. L., Hixon, T. J., & Brown, R. (2003). Clinical ventilator adjustments that improve speech. Chest, 124(4), 1512–1521. Holstege, G., & Subramanian, H. H. (2015). Two different motor systems are needed to generate human speech. Journal of Comparative Neurology, 524(8), 1558–1577. Houck, B. D., & Person, A. L. (2013). Cerebellar loops: A review of the nucleocortical pathway. Cerebellum, 13(3), 378–385. Ito, T., & Ostry, D. J. (2011). Speech sounds alter facial skin sensation. Journal of Neurophysiology, 107(1), 442–447. Iyengar, S., Qi, H. X., Jain, N., & Kaas, J. H. (2007). Cortical and thalamic connections of the representations of the teeth and tongue in somatosensory cortex of New World monkeys. Journal of Comparative Neurology, 501(1), 95–120. Joshi, A., Jiang, Y., Stemple, J. C., Archer, S. M., & Andreatta, R. D. (2011). Induced unilateral vocal fold paralysis and recovery rapidly modulate brain areas related to phonatory behavior: A case study. Journal of Voice, 25(2), e53–e59. Jürgens, U. (2002). Neural pathways underlying vocal control. Neuro­science and Biobehavioral Reviews, 26(2), 235–258. Jürgens, U. (2009). The neural control of vocalization in mammals: A review. Journal of Voice, 23, 1–10. Kaas, J. H., Qi, H. X., & Iyengar, S. (2006). Cortical network for representing the teeth and tongue in primates. Anatomical Record, 288(2), 182–190. Krainik, A., Lehéricy, S., Duffau, H., Capelle, L., Chainay, H., Cornu, P., . . . Marsault, C. (2003). Postoperative speech disorder after medial frontal surgery: Role of the supplementary motor area. Neurology, 60(4), 587–594. Kuhl, P. K., & Meltzoff, A. N. (1996). Infant vocalizations in response to speech: Vocal imitation and developmental change. Journal of the Acoustical Society of America, 100, 2425–2438. Kuhl, P., & Rivera-Gaxiola, M. (2008). Neural substrates of language acquisition. Annual Review of Neuroscience, 31(1), 511–534.

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Lametti, D. R., Nasir, S. M., & Ostry, D. J. (2012). Sensory preference in speech production revealed by simultaneous alteration of auditory and somatosensory feedback. Journal of Neuroscience, 32, 9351–9358. Lisberger, S. G., & Thach, W. T. (2013). The cerebellum. In E. R. Kandel, J. H. Schwartz, T. M. Jessell, S. A. Siegelbaum, & A. J. Hudspeth (Eds.), Principles of neural science (5th ed., pp. 960– 981). New York, NY: McGraw-Hill. Lu, M., Preston, J. B., & Strick, P. L. (1994). Interconnections between the prefrontal cortex and the premotor areas in the frontal lobe. Journal of Comparative Neurology, 341, 375–392. Ludlow, C. L. (2005). Central nervous system control of the laryngeal muscles in humans. Respiratory Physiology & Neurobiology, 147(2–3), 205–222. Lüthe, L., Häusler, U., & Jürgens, U. (2000). Neuronal activity in the medulla oblongata during vocalization: A single-unit recording study in the squirrel monkey. Behavioural Brain Research, 116(2), 197–210. Manto, M., Bower, J. M., Conforto, A. B., Delgado-García, J. M., da Guarda, S. N. F., Gerwig, M., . . . Timmann, D. (2011). Consensus paper: Roles of the cerebellum in motor control: The diversity of ideas on cerebellar involvement in movement. Cerebellum, 11(2), 457–487. Mariën, P., Ackermann, H., Adamaszek, M., Barwood, C. H. S., Beaton, A., Desmond, J., . . . Ziegler, W. (2013). Consensus paper: Language and the cerebellum: An ongoing enigma. Cere­ bellum, 13(3), 386–410. McClean, M. D., Dostrovsky, J. O., Lee, L., & Tasker, R. R. (1990). Somatosensory neurons in human thalamus respond to speech induced orofacial movements. Brain Research, 513, 343–347. Miyamoto, J. J., Honda, M., Saito, D. N., Okada, T., Ono, T., Ohyama, K., & Sadato, N. (2006). The representation of the human oral area in the somatosensory cortex: A functional MRI study. Cerebral Cortex, 16(5), 669–675. Murray, S. S., & Guillery, R. W. (2006). Exploring the thalamus and its role in cortical function (2nd ed.). Cambridge, MA: Massachusetts Institute of Technology. Nasir, S. M., & Ostry, D. J. (2006). Somatosensory precision in speech production. Current Biology, 16(19), 1918–1923. Nasir, S. M., & Ostry, D. J. (2008). Speech motor learning in profoundly deaf adults. Nature Neuroscience, 11(10), 1217–1222. Oller, D. K. (2000). The emergence of the speech capacity. Hillsdale, NJ: Lawrence Erlbaum. Picard, N., & Strick, P. L. (1996). Motor areas of the medial wall: A review of their location and functional activation. Cerebral Cortex, 6, 342–353. Price, C. J. (2012). A review and synthesis of the first 20 years of PET and fMRI studies of heard speech, spoken language and reading. NeuroImage, 62(2), 816–847. Rauschecker, J. P., & Scott, S. K. (2009). Maps and streams in the auditory cortex: Nonhuman primates illuminate human speech processing. Nature Neuroscience, 12(6), 718–724. Roux, F.-E., Djidjeli, I., & Durand, J.-B. (2018). Functional architecture of the somatosensory homunculus detected by electrostimulation. Journal of Physiology, 596(5), 941–956. Schuenek, M., Schulte, E., & Schumacher, U. (2007). Thieme atlas of anatomy: Head and neuroanatomy. New York, NY: Thieme. Scott, S. K., & Johnsrude, I. S. (2003). The neuroanatomical and functional organization of speech perception. Trends in Neuroscience, 26, 100–107.

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CHAPTER 17 Neural Substrate of Language Jessica D. Richardson and Sarah Grace H. Dalton Introduction and Learning Objectives

will involve learning about the brain and language so that you can educate patients, families, and communities, and so you can provide the most effective treatment, or even develop new and improved treatments of your own. So, as Fräulein Maria in the Sound of Music famously sang, “Let’s start at the very beginning, a very good place to start.” After completing this chapter, you should be able to meet the following learning objectives:

Road signs, books, menus, medicine labels, tweets, Facebook posts, I love you’s, goodbyes, debates, rituals, job applications. The value of words is not fully realized until the ability to rely upon them, as naturally as one would breathe, is diminished. So, take a moment with us to think about this scenario: What would your world be like if you woke up one morning and couldn’t say “I love you”? What would life be like if you had difficulty reading the menu at your favorite restaurant, or telling the server your order? What would happen if you couldn’t read medicine labels? What would your relationships be like if you never developed the vocabulary to express your emotions to your loved ones? What would happen to your career options, your income, if the words you needed to say, that you could clearly think of in your head, would not exit your mouth? Where would you be right now, this very second, if you never developed the ability, or if you lost the ability, to decode the letter strings on this page to make sense of this chapter? One or more of these scenarios may be the reality for someone who did not develop language normally. It can also happen to anyone with a damaged language system following stroke, brain injury, or progressive brain disease. Odds are that you either know someone who has difficulty speaking, comprehending, reading, or writing because of a brain difference, or you know someone who knows someone. Perhaps you are even that someone yourself. Our communities, and our society at large, are ill-equipped to handle this quandary. Think about it. Where are the “sidewalk ramps” for language difficulty? Where are the “communication-accessible” restaurants, theaters, places of worship? What would serve similarly as a “wheelchair” or a “cane” for communication? Where are the people that can identify language difficulty and lend a hand or voice, just like someone who sees a person with a paralyzed arm and jumps in to action to help open a door? Language is not simply used for survival, at least in the more primitive use of the word; we do not need language only to meet basic wants and needs for nutrition, safety, and so forth. Language is also used for fellowship, to establish relationships and rapport, to engage in societal rituals and community, and to participate in this thing we call life. To truly understand the impact of diminished language abilities in everyday life is an important first step in your clinical training. This training lays the groundwork for your motivation to do something to lessen the impact that a deficit in language will have in someone’s everyday life. Doing that something

• Describe the function of language and why it is important for survival. • Identify and characterize gray and white matter brain areas important for language processing. • Describe current models of language processing and their importance. • Identify and discuss language errors that are made in certain clinical populations. • Describe ways that principles of neuroplasticity are incorporated into language rehabilitation. • Explain the relationships between language features and processes, and their clinical application.

Language:  What Is It Really? Many species have highly developed communication abilities that are essential not just for their survival, but also for the species as a whole to thrive and evolve. However, the ability to communicate via “language” is unique to humans. There are probably as many different definitions of language as there are people who study it. For the purposes of this chapter, we will define language as a finite set of arbitrary symbols, agreed upon by a community or society, which can be combined to communicate an infinite number of concepts between community members for social cooperation (for further details on defining language, see Hoff, 2005; Justice & Redle, 2014; Nelson, 1998; Plante & Beeson, 2008). These symbols can be a string of letters on a page, a string of phonemes passing from mouth to ear, or a sequence of handshapes passing from hand to eye. The key notion is that all these symbols express a concept such as your favorite pet (we all have one), your favorite child (we are not supposed to have one of these), your favorite expletive (your go-to word when really frustrated ), your favorite place to visit (just give us any beach), and so on. As long as the phonemes (or letters, handshapes, etc.) are assembled in a socially agreed-upon manner, their

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meaning will be understood, and the communicative exchange will be successful. For example, if you are an English-speaking person, your favorite expletive cannot be “Bmoung! ” because it begins with an unacceptable initial phoneme cluster /bm/, /ŋ/ cannot follow the diphthong /aʊ/, and well, it just doesn’t seem “expletive-y” enough. If you violate or do not adhere to the agreed-upon symbols and constraints of a given language, as in our “Bmoung! ” example, then you are literally not speaking the same language. You may have to resort to more universal ways of expressing yourself. This example, while silly, also oversimplifies language. Language is not only the tying of a mental concept to an arbitrary collection of sounds or symbols to represent that single concept; it is so much more than that. It is knowing how to put these strings of sounds, symbols, or handshapes together into phrases, sentences, and narratives to express our thoughts and beliefs, opinions, and preferences. Language is not simply used for the most basic survival purposes — to avoid danger or acquire food. If that were the case, language would be superfluous, because basic signaling, gestures, and primitive vocalizations would easily suffice. But in this modern fast-paced day and age, language is literally required for survival, and certainly for thriving in our society — keeping that job, navigating society, and being involved in some type of relationship that fulfills our human needs. The fact that we are able to accomplish communicating with language, with such speed and with little to no formal instruction, is pretty special indeed. How exactly do we come to have and understand the use of language? Unfortunately, if you think we are going to give you the answer to this question, then you’re going to be disappointed. This question remains open, and is hotly debated and studied in language science. One of the most often presented ideas is that humans are born with brains that have genetically specified and specialized language areas. These specialized areas are said to contain some innate knowledge (set of rules) of language that then sets the stage for our ability to learn language, given the proper environmental stimulation. In other words, nature provides us with some innate linguistic framework and the analytical abilities to fill out that framework, and all that is needed is a little nurture to begin the building process. This linguistic framework and language-​learning ability has been described using such terms as “universal grammar,” “language acquisition device,” “nativism,” and “linguistic universalism” (Chomsky, 2005; Cowie, 2017; Traxler, 2012). The language stimulation we need “nurtured” must occur during certain developmental periods, described as critical periods or sensitive periods (Johnson & Newport, 1989). A critical period is when: there is a maturational change in the ability to learn, with a peak in learning during some maturationally definable period . . . and a decline in the ability to learn, given the same experiential exposure, outside of this period. (Newport, 1991, p. 112)

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Similarly, a sensitive period is a timeframe in development when learning is vulnerable to harmful stimuli. For example, in the case of language development, vulnerability could be manifested as isolation from language models and adult caregivers. I know you are already thinking, “Great! Let’s find this language acquisition device in the brain and fix it when it isn’t working!” or asking yourself, “Which genes do we target with gene therapies to ensure everyone starts off with the same linguistic slate, even if they have some sort of developmental difference?” Unfortunately, life is not that simple. While those who proposed strictly innate language abilities have developed extensive theoretical constructs to explain the emergence of this uniquely human ability, without some sort of real-world biological underpinning to their ideas, their constructs hold little weight or value. Simply put, the genes and/or anatomical substrates to support innate theories of language have never been identified, making a discussion of language’s neural substrate impossible from a nativist or Chomsky-ian perspective.

Neuroscience and Language Acquisition Okay, we can agree that language is not innate. But where does that leave us? Let’s turn to research in language that does have well-characterized brain responses and anatomical locations to help us find a direction. First, while language itself is not innate, it is important to appreciate that the structural and functional underpinnings of language do begin well before we take our first breaths. For example, infants in utero can detect the stress, intonation, and prosody of their native language from those of other languages with very different prosodic patterns (Mehler et al., 1988). After birth, this detection process is further enhanced and refined by exposure to clear visual and auditory signals, as well as social interactions with other humans. Second, also appreciate that the study of language and language acquisition is not for the faint of heart. As anyone who spends a lot of time with small children knows, getting infants and small children to cooperate with anything is challenging at the best of times. And if they are not cooperating, is it because they don’t understand what you are asking them to do, because they can’t do what you’re asking, and/or because they don’t want to do what you’re asking them to do? Thanks to advances in neuroimaging technology such as functional magnetic resonance imaging (fMRI), electroencephalography (EEG), and especially magnetoen­ cephalography (MEG), developmental language researchers are now able to reliably determine how children process language, without relying on them specifically to cooperate or perform a certain response (e.g., button press, hand raise). This is achieved by playing recordings of tones, harmonics, syllables, sentences, and other environmental sounds, to the child during assessment. This approach is effective because there is no way to “turn off” hearing at will; the child’s brain will process auditory information even if there is no overt behavior to observe (see Box 17–1).

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Box 17–1. Further Interest:  Electroencephalography Analyses Methods Electroencephalography, commonly referred to as EEG, is a noninvasive brain imaging tool that researchers routinely use to investigate how the brain works. EEG records the electrical activity of the brain using small electrodes that are placed on the scalp. These electrodes are very sensitive and can pick up the tiny electrical signals that neural populations in the brain use to communicate. EEG has been used for decades to investigate language processing and development. Two forms of EEG analyses are commonly employed today: event-related potential (ERP) and quantitative electroencephalographic analyses (qEEG). Researchers such as Patricia Kuhl of the University of Washington, Seattle use ERPs to understand how the brains of children and adults respond to language-related stimuli. In Kuhl’s (2010) ERP research study, stimuli such as words, sounds, or pictures are presented to the participant. The participant is asked to complete a task, such as deciding whether a string of letters is a real word or nonword. Brain activation can then be measured from the time the stimulus appears on a screen until a response is made. ERP studies use large numbers of trials averaged across many participants to extract the nuances of how the brain completes a task. This pattern of activity is compared to the pattern found in individuals with different brain injuries or disorders to understand how the brain changes in response to these conditions. ERP research has shown that individuals with brain differences (e.g., schizophrenia, stroke, Parkinson’s, and Alzheimer’s) respond to stimuli differently compared to healthy individuals. A less widespread method of analyzing EEG data is referred to as quantitative EEG (qEEG) (Finnigan et

The results of this neuroimaging research have been no less than groundbreaking. Spoken language learning has been found to start at birth with the sounds or phonetics of the language. Right after birth, infants can detect small differences in the way phonemes are produced and, in fact, are much more sensitive to these differences than adult speakers of their native language (Eimas, 1975; Eimas, Siqueland, Jusczyk, & Vigorito, 1971; Lasky, Syrdal-Lasky, & Klein, 1975; Werker & Lalonde, 1988). For example, adult speakers of English can hear the difference between /r/ and /l/ because switching these sounds changes the meaning and intelligibility of many words in the English language (e.g., “right” to “light”). However, adult speakers of Japanese cannot hear the difference between /r/ and /l/ because switching these sounds in Japanese does not change the meaning of a word. According to EEG research, up until about 8 to 10 months of age, infants in English-speaking and Japanese-speaking homes are

al., 2004; Tong & Thakor, 2009). Unlike ERP analysis, qEEG does not rely on time-locking brain activity to the presentation of a stimulus. Instead, qEEG measures the frequency with which neurons are communicating. The qEEG signal is divided into frequency bands (delta, theta, alpha, beta, and gamma). Low-frequency delta and theta activity is associated with sleep in healthy adults. The higher frequencies (alpha, beta, and gamma) are associated with on-task behaviors. Like ERP analysis, qEEG analysis may provide insights into differences that arise because of brain injury or disease (Finnigan, Walsh, Rose, & Chalk, 2007). For example, stroke researchers have reported that low-frequency activity is increased after a stroke compared to individuals with healthy brains. Increased alpha activity (e.g., hyperactivity, hypersynchrony) in the contralateral hemisphere to the lesion site has also been observed and is correlated with poorer function. Resources Finnigan, S. P., Rose, S. E., Walsh, M., Griffin, M., Janke, A. L., McMahon, K. L., . . . Brown, J. (2004). Correlation of quantitative EEG in acute ischemic stroke with 30-day NIHSS score. Stroke, 35(4), 899–903. Finnigan, S. P., Walsh, M., Rose, S. E., & Chalk, J. B. (2007). Quantitative EEG indices of sub-acute ischemic stroke correlate with clinical outcomes. Clinical Neurophysiology, 118(11), 2525–2532. Kuhl, P. K. (2010). Brain mechanisms in early language acquisition. Neuron, 67(5), 713–727. Tong, S., & Thakor, N. V. (2009). Quantitative EEG analysis methods and clinical applications. Boston, MA: Artech House.

both able to hear the difference between the two sounds. As discovered by Patricia Kuhl and colleagues, at around 10 to 12 months, infants in Japanese-speaking homes begin to lose their ability to recognize /r/ and /l/ as different and unique sounds, while infants in English-speaking homes maintain the distinction (see Kuhl, 2010, for review). While maintaining that particular distinction, infants in English-speaking homes instead lose the ability to distinguish between nasal and nonnasal vowels at around 10 months, because the presence of nasality in vowels does not change the meaning of words in English. Thus, the salience of an input, its importance or value to the infant brain for communication, plays a huge role in determining our perceptual categorizations and the phonemic boundaries necessary for future language development. During this same period, from birth to about 12 months, infants show a remarkably similar change in the way their brains respond to different auditory signals. At birth, the

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temporal lobe, which you have learned already is crucial for receptive language abilities, activates strongly and equally to pitch tones and syllables, while areas responsible for motor speech production (i.e., inferior frontal lobe) remain inactive (Imada et al., 2006). Using fMRI, we know that by 3 months, the infant brain begins to show activity in the inferior frontal areas in response to sentences produced by adult speakers, even though babies have generally not even started babbling at this age yet (Dehaene-Lambertz et al., 2006). Using MEG, researchers have discovered that by 6 to 12 months, inferior frontal lobe activation is present when infants listen to syllables, but not tones (Imada et al., 2006). Importantly, activation in the inferior frontal (related to speech production) and superior temporal (related to receptive language) regions appears to be coupled for speech stimuli only. In other words, both motor and sensory-related brain areas demonstrate activation at the same time in response to the same auditory input. Additional studies have shown that at 7 months — before infants become native speech specialists — infants listening to syllables in native and nonnative languages show activation in both superior temporal and inferior frontal regions. However, by 11 to 12 months, after becoming uniquely attuned to their own native language, listening to syllables in the native language results in greater activation of superior temporal areas, while listening to syllables in a nonnative language results instead in greater activation in the inferior frontal area — a brain activation pattern that mirrors what has been seen in adult research subjects (Kuhl, Ramírez, Bosseler, Lin, & Imada, 2014). Clearly, infants can determine, in a remarkably short amount of time, the sounds of their own language, and this process can be characterized by changes in brain activation patterns. Furthermore, infants focus on the sounds specific of their native language to such a degree that they lose their sensitivity to sounds in other languages. But why do infants do this? Why don’t they just keep that sensitivity? How are they able to learn these relationships so quickly with the limited information provided by adult speakers? It’s not like adults sit down and actively teach children each different sound and how it relates to all the other sounds in their language. According to Kuhl and her colleagues, the “why” may be based on the idea that giving up the ability to recognize small distinctions between sounds frees up other brain resources needed to learn the native language more efficiently (see Kuhl, 2010). Infants that are more sensitive to the sounds of their native language, and less sensitive to the sounds of nonnative languages, have better language abilities later in life than infants who are sensitive to all sounds. These differences persist up to at least age 5, suggesting that the ability to focus neural and cognitive resources early in one’s life is critical for successful language learning (Kuhl et al., 2008; Kuhl, Conboy, Padden, Nelson, & Pruitt, 2005). Of course, as with anything worth understanding, how infants do this is still not entirely clear. There seem to be two critical processes interacting to give infants the capacity for

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rapid learning. It turns out that infants and young children are very sensitive to frequency distributions and probabilities in language. At some point, many of us learn that the letters “s,” “t,” and “r” are frequently used in English, and therefore make excellent guesses when trying to solve a word puzzle. When you first learned this information, it may have felt completely new, like something you just discovered; however, your brain likely “knew” about this fact long before you were consciously aware of it. That is because your brain is able to pick up on regularities that exist in the world even when you are not consciously aware of them. This is one of the brain’s extraordinary “superpowers,” the ability to detect and extract patterns and regularities from streams of incoming information. This ability is what is referred to as statistical learning: the general brain process that allows infants to learn language so quickly from a small and relatively underrepresentative sample of auditory inputs (Saffran, Aslin, & Newport, 1996). But statistical learning alone cannot account for how infants learn language. This was elegantly demonstrated in a series of experiments where 9-month-old infants being raised in English-speaking homes were exposed to Spanish or Mandarin adult speakers for several weeks (Conboy & Kuhl, 2011; Kuhl, Tsao, & Liu, 2003). Using EEG, the researchers found that brain activation when listening to the sounds of Spanish and Mandarin was the same for the infants who spent time with Spanish and Mandarin speakers as it was for infants raised in Spanish- or Mandarin-speaking homes since birth. Critically, brain activation in infants who watched videos or heard audiotapes of Spanish and Mandarin speakers, and did not directly interact with these adults, did not show this pattern. Their brains responded to Spanish and Mandarin sounds in the same way that the brains of infants from English-​ speaking homes who had never been exposed to those languages responded. Face-to-face social interaction seems to be a key trigger for infants to engage in statistical learning processes for language. This research was supported further by the finding that the infants who were more engaged with the adult nonnative speaker had greater brain activation to the nonnative sounds than infants who had been less engaged. From this work, Kuhl developed the Social Gating Hypothesis, which suggested that social interaction creates a critical change in the environment that influences how learning occurs by increasing attention, improving the quality of information available for learning, allowing for a sense of relationship to develop between partners, and bringing online neural systems that link our perception of language to our production of language.

Neuroscience and Language Evolution Humans are social creatures, and we have been since the dawn of our species. We work together not just to survive, but to push the limits of what is currently possible. Social cognition, or what is more accurately characterized as Theory of Mind (ToM), is the ability of humans (and maybe, to a lesser

CHAPTER 17   Neural Substrate of Language

extent, other species) to understand how another being thinks or feels, and to imagine ourselves as someone else (Corballis, 2017). Social cognition is the basis upon which human society developed. Researchers have argued that social cognition paved the way for the evolution of language. The logic is as follows. Humans needed to develop effective and efficient communication that could be transmitted across distances while also leaving our hands free to complete other tasks. As our communication system evolved, human society became more complex, leading to further advances in language, which again allowed for societal advances until the present day. According to this theory, language evolved incrementally out of the need to communicate more clearly with other members of our species, rather than as a quantum leap from the kinds of communication systems observed in other animals (Corballis, 2017; Seyfarth & Cheney, 2014). As evidenced in our definition of language, one of the features that makes human language different from other animals’ communication systems is our ability to generate an infinite number of new utterances that have never been imagined before in the history of humankind. For example, “My dogs Zed and Koshari like to chew on bones while sitting in front of the pellet stove while I write about the neural substrates of language” is a highly novel utterance, because (a) it is unlikely that there is another person on earth besides the second author who owns two dogs that happen to be named Zed and Koshari; (b) if such a person did exist, it is highly unlikely that the person would also live in the southwestern United States where pellet stoves are often used instead of fireplaces (go ahead and Google “pellet stove” if you’re curious); and (c) it would be beyond belief that such a doppelgänger would also be writing about the neural substrate of language. This generativity of novel utterances is in stark contrast to the limited number of vocalizations, calls, and/or gestures utilized by all other mammals and avian species. According to the famous linguist Noam Chomsky, this generativity is a hallmark of language and operates as the precursor to other advanced abilities, such as thought (Chomsky, 2005). The sudden appearance of this ability is why there seems to be no evolutionary chain to explain human language. But it only seems this way. Other language theorists lay out an alternative path — one in which thoughts first became generative, and language developed to facilitate expression of these generative thoughts. This alternative path has the benefit of a much more straightforward evolutionary chain. At the heart of generative thought lies mental time travel, or the ability to think about something other than the present moment, which happens to also be a precursor of ToM (Suddendorf & Corballis, 1997, 2007; Tulving, 1985). This ability has been observed in rats that have learned and remember the path through a maze; this ability is similar to humans’ ability to retrace or plan a route to a desired location (Moser, Rowland, & Moser, 2015). In both humans and rats, it is the hippocampus that supports this ability. ToM is another potentially later-​

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developing aspect of generative thought. ToM is most highly developed in humans, but there is a great deal of debate about its existence in chimpanzees, who evolutionarily are closely related to humans. Chimpanzees do seem to exhibit aspects of ToM, such as understanding the goals and knowledge of others, although not everyone is convinced about this idea (for opposing arguments, see Call & Tomasello, 2008; Penn, Holyoak, & Povinelli, 2008). Because chimpanzees are capable of learning sign language and demonstrate some limited ability to combine signs into novel utterances, their emerging ToM might represent the key to understanding why all mammals, up to and including primates, rely on fairly limited communication systems, while humans have developed language. In other words, it was the social impetus — our ability to understand how others think and feel, to consider others’ wants and needs — that may have provided the evolutionary pressure or “spark” for the development of our sophisticated language system. From our clinical perspective, rarely do discussions of language evolution take place in clinical practice. A basic appreciation of this topic, though, is important for your clinical toolbox in the future. This appreciation will be especially important as you read research articles to keep up with evidence-based practice recommendations, because understanding the theoretical perspective of the researchers who author these studies is important for interpreting their results and conclusions. If you think authors are approaching a question from a flawed theoretical perspective, you may want to be cautious in how you apply their discussion to your therapy decisions. Additionally, information about language acquisition must be constantly taken into consideration, regardless of the age of your population. While this may seem to have most application to a younger population who are still developing language, we encourage you to also diligently include this in your assessment and treatment of adults. Questions about language acquisition and development should be addressed during preassessment (e.g., case history, records review, screening) and assessment, and this information should be incorporated into the selection of treatment approaches and the setting of realistic expectations for therapeutic outcomes.

Brain Areas Involved in Language Processing In most typical adults (>90%), processing for language production and comprehension occurs primarily in the left hemisphere of the brain (see Box 17–2), specifically in areas around the lateral sulcus (sylvian fissure) that separates the frontal, temporal, and parietal lobes and lies over the insular lobe. This area is often referred to as the perisylvian lan­ guage area or zone (Figure 17–1). Although the right perisylvian area has the same anatomical structures as the left, they are functionally different, with the right not activated as extensively for language compared to the left. We pres-

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Perisylvian & Subcortical Language-Related Areas Ventral precentral gyrus

Ventral postcentral gyrus

Superior frontal gyrus

Inf. parietal lobule: Supramarginal gyrus Angular gyrus

Middle frontal gyrus Prefrontal cortex

Visual association cortex

Inf. frontal gyrus: Pars triangularis Pars opercularis Pars orbitalis

Frontal operculum

Primary visual cortex

(deep to lateral sulcus & near anterior insula)

Superior temporal gyrus Inferior temporal gyrus Middle temporal gyrus

Anterior temporal lobe

Caudate nucleus

Ve

ntr

Cerebrocerebellum

Pulvinar

ola

ter

al

Tie

rN

uc

lei

Putamen

Centromedian nu.

Thalamus

Striatum

Cerebellum

 FIGURE 17–1.   Perisylvian and subcortical language areas. Primary and associated language processing areas are shown for the left hemisphere of the cerebrum (top), the thalamus (bottom left ), the basal ganglia (bottom center), and the cerebellum (bottom right).

ent language areas by location and their contribution to language in Table 17–1. This is not an exhaustive list of all potential areas or all potential functions, but it does include key subcortical structures like the thalamus and cerebellum ​ — structures that are also highlighted along the bottom of Figure 17–1. Note that to simplify and limit the scope of the chapter, right hemisphere cortical structures are not included in this table or in Figure 17–1. Rather, this table is representative of those areas and functions that are most frequently discussed and those that are hot topics of current research. In addition, some of the functions may overlap; however, there are enough differences of opinion in the literature to warrant careful treatment and separation. Please bookmark Figure 17–1 and refer to Chapter 6 for in-depth descriptions of the neuroanatomical structures of the cerebral hemispheres as we start to cover the neuroanatomical foundations of language processing.

Language areas that have been most frequently or notably associated with cognitive-executive control of language, which includes behaviors such as new learning, language switching, and contextual considerations, are the frontal operculum (FOP), prefrontal cortex (PFC), insular lobe, basal ganglia, and cerebellum. Areas associated with the role of emotion in language and arousal include the anterior temporal lobe (ATL), insula, thalamus, and PFC. (Please make a note in the margin that while right hemisphere areas are not listed in our summary tables, we know that right hemisphere structures are heavily involved with emotional processing as it pertains to language production.) Areas associated with lexical/ semantic processing include the inferior frontal gyrus (IFG) pars triangularis and pars orbitalis, ventral precentral gyrus (vPCG), ventral premotor cortex (vPMC), middle frontal gyrus (MFG), inferior parietal lobule (IPL) including the angular gyrus, superior temporal gyrus (STG), middle

 TABLE 17–1.   Language-Related Brain Areas Organized by General and Specific Structures General Brain Region

Left frontal lobe

Left parietal lobe

Left temporal lobe

Specific Brain Structure

Contribution to Language

Inferior frontal gyrus pars opercularis (IFG)

• Phonological processing • Spoken language preparation (motor) • Syntax • Verbal working memory

Inferior frontal gyrus pars triangularis (IFG)

• Lexical, semantic, and comprehension • Spoken language preparation (motor) • Syntax

Inferior frontal gyrus pars orbitalis (IFG)

• Lexical, semantic, and comprehension • Syntax

Ventral precentral gyrus (vPCG)

• Lexical and semantic • Spoken language preparation (motor)

Ventral premotor cortex (vPMC)

• Lexical and semantic • Phonological processing • Spoken language preparation (motor)

Superior frontal gyrus (SFG)

• Verbal working memory

Middle frontal gyrus (MFG)

• Lexical, semantic, and comprehension

Frontal operculum (FOP) Deep and near anterior insula

• Cognitive-executive control of language • Phonological processing • Spoken language preparation (motor) • Syntax

Prefrontal cortex (PFC)

• Cognitive-executive control of language • Emotion

Inferior parietal gyrus (IPG) Supramarginal gyrus

• Phonological processing • Sound-to-articulation mapping

Inferior parietal lobule (IPL) Angular gyrus

• Phonological processing • Lexical, semantic, and comprehension • Sound-to-articulation mapping

Superior temporal gyrus (STG)

• Lexical, semantic, and comprehension • Phonological processing • Semantic • Sound and acoustic • Verbal working memory

Middle temporal gyrus (MTG)

• Lexical, semantic, and comprehension • Sound and acoustic

Inferior temporal gyrus (ITG)

• Lexical, semantic, and comprehension • Sound and acoustic

Anterior temporal lobe (ATL) Temporal pole

• Emotion • Lexical, semantic, and comprehension • Syntax continues

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 TABLE 17–1.   continued General Brain Region

Specific Brain Structure

Contribution to Language

Left insula lobe

Anterior insula (AIns) Posterior insula (PIns)

• Cognitive-executive control of language • Emotion • Spoken language preparation (motor)

Occipital

Primary visual cortex (V1) Visual association areas

• Visual representations • Visual identification

Left basal ganglia

Striatum

• Cognitive-executive control of language • Spoken language preparation (motor) • Syntax

Thalamus

Ventrolateral tier nuclei (VL) Centromedian nucleus Pulvinar

• Lexical and semantic • Control-gating of language access and ability according to arousal states

Cerebellum

Cerebrocerebellum Lateral hemisphere

• Cognitive-executive control of language • Language production (motor) and monitoring • Syntax

Box 17–2. Clinical:  Lateralization of Language Function In roughly 90% of adults, processing for language occurs in the left cerebral hemisphere. For the remainder of the population, language processing may be lateralized to the right hemisphere, or it may be distributed evenly across both hemispheres. You might be wondering what determines whether language processing will be left or right lateralized, or bilaterally distributed. While we don’t know the whole answer to that question, we do know that language lateralization is related to our handedness, but not in a reliable or consistent manner. During conditions when brain surgery needs to be performed, language lateralization becomes critically important to know. Why is this the case? Individuals who have uncontrollable seizures often undergo brain surgery to remove areas responsible for the seizures. Similarly, individuals with brain cancer also require surgery to remove the tumor. Because language is such an integral part of life and so critical to maintain intact, surgeons must know the lateralization status of the patient so that they can try and avoid tissue removal from critical language processing zones. Physicians will carefully seek to preserve language ability whenever possible.

Because it is possible for language to be lateralized to either the left or right hemisphere, relying on one’s handedness seems like a risky way of determining the exact location of language processing in a patient. As such, physicians use an additional procedure to quantitatively determine an individual’s language lateralization prior to surgery. This procedure is called the Wada test and uses an injection of sodium amobarbital into either the left or right carotid artery to “paralyze” that side of the brain, producing a temporary inability to process or produce speech and language (Binder et al., 1996). This procedure allows surgeons to determine which half of the brain is clearly responsible for language processing in each patient. The effects of the Wada are relatively short-lived, and the procedure is safe to perform. Resource Binder, J. R., Swanson, S. J., Hammeke, T. A., Morris, G. L., Mueller, W. M., Fischer, M., . . . Haughton, V. M. (1996). Determination of language dominance using functional MRI: A comparison with the Wada test. Neurology, 46(4), 978–984.

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temporal gyrus (MTG), inferior temporal gyrus (ITG), ATL, and thalamus. Areas associated with phonological processing include the frontal lobe (IFG pars opercularis, vPMC, FOP), inferior parietal gyrus (IPG) including the supramarginal gyrus, IPL, and STG. Areas associated with motor preparation and related components of spoken language include the IFG pars triangularis, vPCG, vPMC, FOP, insula, basal ganglia, and cerebellum. Areas strongly associated with sound-to-​ articulation mapping and/or the acoustic properties of incoming spoken language include the IPG, IPL, STG, MTG, and ITG.

Areas associated with syntax include the IFG pars opercularis, IFG pars triangularis, IFG pars orbitalis, FOP, ATL, basal ganglia, and cerebellum. Areas associated with verbal working memory include the IFG pars opercularis, SFG, and STG. Finally, the occipital lobe is associated with the visual aspects of language including acquisition, learning the linkage between visual representations and semantic concepts, and gestural and orthographic language processing. All these language functions and their related neuroanatomical structures are summarized for you in Table 17–2.

 TABLE 17–2.   Key Language-Related Brain Structures Organized by Function Language Processing Function

Key Language-Related Brain Structure

Cognitive and executive control

• FOP and PFC • Insula • Basal ganglia and cerebellum

Emotion and arousal

• PFC • ATL • Insula • Thalamus

Lexical and semantic processing

• IFG (pars triangularis and orbitalis), vPCG, vPMC, MFG • IPL (angular gyrus) • STG, MTG, ITG, ATL • Thalamus

Phonological processing

• IFG par opercularis, vPMC, FOP • IPG and IPL (supramarginal gyrus and angular gyrus) • STG

Spoken language preparation (motor)

• IFG par triangularis and opercularis, vPCG, vPMC, FOP • Insula • Basal ganglia and cerebellum

Sound-to-articulation mapping

• IPG and IPL (supramarginal and angular gyrus) • STG, MTG, ITG

Syntax

• IFG (pars opercularis, triangularis, and orbitalis), FOP • ATL • Basal ganglia and cerebellum

Language production and monitoring

• Cerebellum

Control/gating of language access and ability according to arousal states

• Thalamus

Verbal working memory

• IFG pars opercularis, SFG • STG

Visual aspects of language

• Visual cortical and association areas of occipital lobe

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Explanations of language processing have long focused on gray matter hubs or modules and have ignored the importance of the connections between these areas and the extensive distribution of language-associated brain activations (Catani & Mesulam, 2008). White matter connectivity and integrity are increasingly recognized as vital to understanding how language is learned developmentally and how it emerges in real time during novel speech production. We are long overdue for an expansion and/or shift in focus of our research from localization to connectivity factors (see Box 17–3 for an example of advances in charting brain network connectivity). This can be understood easily by simply viewing the amount of brain “real estate” devoted to white matter versus gray matter (Figure 17–2) and by visualizing the exuberant white matter tracts for information flow (Figure 17–3). When looking at the entire brain (see Figure 17–2, top row), appreciate the pervasiveness and extent to which white matter is distributed throughout the brain (see areas highlighted in purple in last row). Without the white matter, complex behaviors that require high degrees of timing and input integration would be virtually impossible to generate. Keeping in mind the same

SECTION 4

disclaimers when discussing gray matter regions underlying language, we present the most-often discussed white matter tracts associated with language processing by their connections and hypothesized functions in Table 17–3. Table 17–4 has a summary of the same tracts, except organized by their function. A tract that has been associated with cognitive-executive control of language is the arcuate fasciculus (AF). It should be noted that not everyone is convinced that the AF is an independent pathway in the human. Many anatomists consider the AF to simply be an offshoot of the much larger and extensive superior longitudinal fasciculus. Although these differences in opinion exist, we will consider the AF as a separate pathway in this chapter for the sake of clarity in describing the underlying organization of language network connections. Tracts associated with lexical/semantic processing (retrieval and/or comprehension) include the AF, extreme capsule (EmC), frontal aslant tract (FAT), middle longitudinal fasciculus (MLF), inferior frontal occipital fasciculus (IFOF), inferior longitudinal fasciculus (ILF), and uncinate fasciculus (UF). Tracts associated with phonological processing

Whole Brain

CSF

CSF + Gray matter

CSF + Gray matter + White matter  FIGURE 17–2.   Segmentation of the human brain into its constituent tissues. For each row of MRI images, the brain is shown in five axial sections that correspond to their location indicated by the blue lines (from bottom to top) on the midsagittal view of the cerebrum at the end of each row. The topmost row is a standard anatomical MRI sequence of these brain sections. The second row depicts the same brain sections, but with the cerebrospinal fluid (CSF) highlighted in an aqua shading. The third row depicts the brain sections with the CSF highlighted and with the cortical and subcortical gray matter highlighted in red. Lastly, row four has white matter highlighted in purple in addition to the previously highlighted brain segments.

Commissural Fibers

Projection Fibers

 FIGURE 17–3.   Diffusion tensor image (DTI) of commissural and projection axon fibers of the cerebrum white matter. Both panels show a coronal section of the cerebrum and brainstem with the DTI composite figures (colored segments) superimposed at a normal anatomical position.

 TABLE 17–3.   Cerebral White Matter Tracts Supporting Language Processing Functions Organized by Brain Structure White Matter Tract

Connected Cortical Areas

Arcuate fasciculus (AF) [Sometimes listed as part of SLF]

Frontal–Temporal Frontal–Parietal Temporal–Parietal

• Cognitive (language learning) • Lexical and semantic • Phonological processing • Syntax

Extreme capsule (EmC) [Sometimes listed as part of IFOF and UF]

Frontal–Temporal

• Lexical, semantic, and comprehension

Frontal aslant tract (FAT)

Frontal–Frontal

• Lexical and semantic • Spoken language preparation (motor) • Syntax

Middle longitudinal fasciculus (MLF)

Temporal–Parietal

• Lexical, semantic, and comprehension

Inferior frontal occipital fasciculus (IFOF)

Frontal–Occipital

• Lexical, semantic, and comprehension • Visual representations • Visual identification

Inferior longitudinal fasciculus (ILF)

Temporal–Occipital

• Lexical, semantic, and comprehension • Visual representations • Visual identification

Superior longitudinal fasciculus (SLF)

Frontal–Temporal Frontal–Parietal Temporal–Parietal

• Phonological processing • Syntax • Sound-to-articulation mapping

Uncinate fasciculus (UF)

Frontal–Temporal

• Lexical, semantic, and comprehension • Syntax

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Function in Language

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 TABLE 17–4.   Cerebral White Matter Tracts Supporting Language Processing Operations Organized by Function Language Processing Function

White Matter Tract

Cognitive (language learning)

• Arcuate fasciculus (AF)

Lexical, semantic, and comprehension

• Extreme capsule (EmC) • Arcuate fasciculus (UF) • Frontal aslant tract (FAT) • Middle longitudinal fasciculus (MLF) • Inferior frontal occipital fasciculus (IFOF) • Inferior longitudinal fasciculus (ILF) • Uncinate fasciculus (UF)

Spoken language preparation (motor)

• Frontal aslant tract (FAT)

Phonological processing

• Superior longitudinal fasciculus (SLF) • Arcuate fasciculus (AF)

Syntax

• Superior longitudinal fasciculus (SLF) • Frontal aslant tract (FAT) • Arcuate fasciculus (AF) • Uncinate fasciculus (UF)

Sound-to-articulation mapping

• Superior longitudinal fasciculus (SLF)

Visual representations and visual identification

• Inferior frontal occipital fasciculus (IFOF) • Inferior longitudinal fasciculus (ILF)

include the AF and superior longitudinal fasciculus (SLF). A tract associated with motor preparation and related components of spoken language is the FAT. The tract strongly associated with sound-to-articulation mapping is the SLF. Tracts associated with syntax include the AF, FAT, and the UF. Finally, the tracts associated with the visual aspects of language include the IFOF and ILF. For a review of the location of the major association pathways in the cerebrum, see Figures 17–3, 17–4, and 17‒5. From our clinical perspective, understanding the relationship among language, brain areas, and tracts is critical for (a) understanding reports from other health professionals (neurology, neuroradiological, neuropsychological), (b) educating patients and their families about the nature of their deficits, and (c) making the most informed assessment and treatment decisions for your clients. We routinely incorporate brain models, brain drawings, and brain imaging into assessment or education sessions with patients and families. For many — even those who have had brain injury and subsequent imaging — it is the first time anyone has discussed their brain with them. We have found that this simple practice empowers patients to be better self-advocates. Unlike a

broken leg in a cast, brain injury is not visible to the naked eye, making it difficult to explain the impact of the injury. By showing patients and family members the injury, it is made real to them, which often helps decrease frustration related to questions like, “Why am I not getting better?” or “Wouldn’t she be able to do this if she just tried harder?”

Models of Language Production For the most part, the brain seamlessly processes sensory information and programs actions, implementing these without difficulty. Occasionally, errors occur during processing or production that cause a momentary problem, like having a word on the “tip of your tongue” and not being able to get it out. A great deal of our knowledge about what the brain does, how it does it, and which areas are responsible or involved is derived from these momentary breakdowns in otherwise healthy individuals, as well as from the more serious and long-lasting difficulties resulting from stroke, traumatic brain injury, and neurodegenerative diseases such

CHAPTER 17   Neural Substrate of Language

as multiple sclerosis, Alzheimer’s disease, Parkinson’s disease, vascular dementia, and more. Doctors and scientists have studied the damaged brain for centuries to gain insight into human behavior, and specifically language. To those individuals who have shared their lives and struggles with scientists over the years, we owe a huge debt of gratitude for our fund of knowledge today. Much of what we know about lexical access comes from patients with brain injuries who produce speech errors and incorrectly retrieve words. We can also study errors that occur in healthy adults, such as the tip of the tongue (ToT) phenomenon mentioned earlier. We have all probably experienced ToT — that moment when the word we want is in our brain, but just out of our reach. It happens often with names of casual acquaintances, or low-frequency object labels that you know but don’t often use. ToT errors were one of the first indicators that lexical items have rich representations in the brain, and that access to these representations does not have to come through the lexical item itself. For example, early research demonstrated that when you experience ToT, you can often identify the letters it starts and ends with, how many syllables it has, synonyms of the word, and words that sound the same, even when you still cannot retrieve the word itself (Brown & McNeill, 1966). We know that lexical items have rich representations, that they are accessible from

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many levels, and that retrieval errors occur in both healthy and brain-injured people. So, what exactly is happening in our brain during all of this, and during other errors we may make, such as saying, “Hand me the wrench” instead of “Hand me the pliers,” or saying “Shinderlella” for “Cinderella”? The short answer is, we’re not exactly sure yet. The longer answer is, scientists have been trying to determine this for centuries and have generated some pretty good working theories and models. Let’s review some of the most influential models that have been used to explain how the brain “does” language.

The “Classic” Language Model: Wernicke-Geschwind Model The classic language model, still presented in medical textbooks and relied upon heavily by researchers and clinicians alike, is based on a series of observations and theories made by several different clinician scientists from 1861 to 1970. These individuals were the famous Paul Broca and Carl Wernicke, as well as the less famous Ludwig Lichtheim and Norman Geschwind. As illustrated in Figure 17–4, the now classic Broca-Wernicke-Lichtheim-Geschwind (BWLG) language model (or most often simply referred to as the Wernicke-Geschwind [WG] model) highlights several primary language areas, including (a) Broca’s area (red), located

Wernicke-Geschwind Model Arcuate Fasciculus

Primary Motor Cortex

Supramarginal Gyrus Angular Gyrus

Primary Visual Cortex Broca’s Area Wernicke’s Area Primary Auditory Cortex

 FIGURE 17–4.   Wernicke-Geschwind language processing model. Auditory speech inputs arrive at the primary auditory cortex (blue), where they are passed onto Wernicke’s area (yellow). From Wernicke’s, inputs are shuttled to Broca’s area (red ) via the arcuate fasciculus, with final output from Broca’s to the ventral primary motor cortex (pink). Orthographic language-related inputs are transduced by visual cortices and project to the angular gyrus (green) in the inferior parietal lobule.

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somewhere in the posterolateral inferior frontal lobe and operating as the center for spoken language articulation and production; (b) Wernicke’s area (gold), located somewhere in the posterior superior temporal lobe and operating as the center for spoken language comprehension; and (c) the arcuate fasciculus (curved line) that serves as the white matter connection between these two language-processing centers (Catani & Mesulam, 2008; Damasio & Damasio, 1980; Geschwind, 1970; Hagoort, 2013; Tremblay & Dick, 2016). Our use of imprecise language, such as “somewhere,” is very deliberate, because even today, there is little to no consensus regarding the exact anatomical locations for these areas (Tremblay & Dick, 2016). Other components incorporated into various versions of the WG model include (a) an anatomically unspecified area of the temporal lobe containing semantic concepts that are linked to both Broca’s and Wernicke’s areas, (b) auditory input from the primary auditory cortex to Wernicke’s area, (c) integrative areas such as the supramarginal and angular gyri, and (d) verbal output pathways from Broca’s area to the ventral primary motor cortex. As shown in Figure 17–5, use of the WG model has helped us develop and envision the essential traffic flow needed for different forms of language processing, such as spoken, lexical, and graphical forms. For example, generating novel speech entails activating Wernicke’s area, followed by Broca’s, which then projects speech gestural instructions to the ventral primary motor cortex (location of vocal tract representation), ultimately affecting the activity of lower motoneurons to vocal tract musculature. To produce and understand written forms of language, a slightly different pathway is delineated through the model. This pathway originates in

Hear speech

Area 41

Cognition

Wernicke’s area

Writing

Area 17

the primary visual cortex and visual association areas with projections to the angular gyrus, followed by inputs to Wernicke’s area for reading comprehension. Finally, listening to speech follows a route from the primary auditory cortex to Wernicke’s area. The WG model was helpful for very early investigations of relationships between brain and language behaviors and has served as a foundation for model updates facilitated by advances in brain mapping and brain imaging. For example, during the 1980s and 1990s, Damasio and Damasio built upon the classic WG model by including more perisylvian brain areas in the language model and identifying more convergence hubs or zones for linguistic processing — even specifying zones for processing certain word categories such as nouns, verbs, and color adjectives (Damasio & Damasio, 1980, 1992; Damasio & Geshwind, 1984; Small & Hickok, 2015). The more recently introduced Memory, Unifica­ tion, Control (MUC) model proposed by Hagoort (2013) is another improvement upon the classic WG model, and includes the following features: (a) temporal and parietal areas storing memory of knowledge pertaining to phonology, morphology, syntax, and semantics; (b) frontal areas important for the unification and assembly of these different pieces into larger coherent structures (e.g., phrases, sentences); and (c) frontal areas needed to control the selection and usage of these unified structures. Frontal lobe areas are also necessary to account for (a) the context of the communication exchange, (b) the selection of the correct language, (c) turn taking, (d) adherence to social mores, and (e) attention to salient information. Major cortical zones along with interconnecting white matter pathways of the MUC model are

Wernicke’s area (contains auditory map of phonemes)

Broca’s area (stores speech motor gestures)

Area 18, 19

SECTION 4

Area 39 (angular gyrus)

Hear and understand speech

Vocal tract areas of motor cortex

Wernicke’s area

Cranial nerves

Speech

Read

 FIGURE 17–5.   Information processing flow through Wernicke-Geschwind language areas for behaviors related to auditory comprehension of speech (green boxes), the novel generation of language and speech (gold boxes), and the comprehension of written language (blue boxes).

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highlighted in Figure 17–6. Be sure to note the similarities and difference between the WG model (see Figure 17–4) and the MUC model (see Figure 17–6). There remains a strong legacy of topological and localizationist approaches to categorizing language disturbances. Investigators have long wanted to identify a specific brain region or structure that can explain everything about language disturbances. However, the classic model and many of its descendants often lack the anatomical precision needed to explore with any great fidelity and resolution the neuroanatomical bases of language. Furthermore, these types of models are often too narrow in scope, which is immediately apparent if you glance at Tables 17–1 and 17–3 and count how many structures and pathways are mentioned. Models consistently leave out many cortical areas that we know are involved in language, most importantly the numerous white matter connections between the many different gray matter areas that support language (Catani & Mesulam, 2008; Tremblay & Dick, 2016). Progress in understanding how the brain “does” language will necessitate a widening of our investigative lens to include more brain areas. Crucially, this should involve movement away from gray matter–centric

approaches to consider both gray and white matter contributions, so that connectivity, strengths of connections, and their functional dynamics become primary players in the language modeling game.

Dual-Path Models of Language Processing The most promising models currently in development involve dual paths, routes, or loops of processing through cortical regions related to language. Collectively, these approaches are referred to as dual-path models (DPM) (Figure 17–7). While a variety of DPMs of language exist (for an excellent example of a DPM, see Hickok & Poeppel, 2007, 2015), in this section, we’ll highlight two models that more explicitly focus on language. Importantly, these two models emphasize the importance of white matter connections between gray matter processing hubs. In our first model, proposed by Dorothee Saur and colleagues (see Kümmerer et al., 2013; Saur et al., 2008), advances in neuroimaging, specifically fMRI and diffusion tensor imaging (DTI), have been leveraged to identify (a)  which brain areas show activation changes during certain spoken

MUC Model

Arcuate Fasciculus & Sup. Long. Fasc. Supramarginal Gyrus

Ventral M1

Angular Gyrus

Prefrontal Cortex A1

Primary Visual Cortex Broca’s Area Wernicke’s Area

Uncinate Fasciculus Extreme Capsule

Inf. Long. Fasciculus

Temporal Association Area

 FIGURE 17–6.   Memory, Unification, Control (MUC) model of language. Major cortical zones along with interconnecting white matter pathways of the MUC model are highlighted. The model is an expansion of the Wernicke-Geschwind model to include temporal and parietal areas storing knowledge of phonology, morphology, syntax, and semantics (light red shading) and frontal areas for unification and assembly of communication output (purple shading). Greater detail about the MUC model can be found in Hagoort (2013).

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Dorsal Pathway

Auditory-Motor Integration

 FIGURE 17–7.   Dual-path model for language processing. Language processing entails the use of dorsal and ventral processing pathways. Both paths originate from inputs arising out of the auditory cortices (green arrows). Dorsal path brain areas (blue arrows) include the superior temporal gyrus, inferior parietal lobule, and frontal lobe areas. The dorsal path operates to integrate auditory and motor inputs. Ventral path brain areas (deep red arrows) include the auditory cortex, the middle and inferior temporal lobe areas, and the frontal lobe regions rostral to the premotor cortex. Ventral pathway function is strongly associated with semantic and syntactic processing. The white shaded region on the lateral cerebrum demarcates the approximate location of the peri­ sylvian language processing zone.

Ventral Pathway

Semantic & Syntactic Language

language comprehension and repetition tasks (with fMRI) and (b) which white matter tracts provide links between these areas of activation (with DTI). Their findings are consistent with more speech production and perception-based models developed by Hickok and Poeppel (2007, 2015), and they present a dorsal-ventral brain network organization that supports both comprehension and repetition language tasks. For the purposes of this discussion, dorsal brain areas include the parietal lobe and frontal lobe zones posterior to and including the premotor cortex, whereas ventral brain areas include the middle and inferior temporal lobe areas and the frontal lobe regions anterior to the premotor cortex. Looking at Figure 17–7, the dorsal pathway is implicated in repetition tasks and originates in the superior temporal gyrus and the auditory cortex. Signals from the superior temporal gyrus (green arrow pathways) flow through the inferior parietal lobule and toward their principal destination in premotor areas of the frontal lobe (blue arrow pathway). These elements are interconnected via the AF and SLF. The dorsal path operates to integrate auditory-motor information. So, repeat these words after us (pretend you hear us saying these words, and then repeat them in the following order): firefly, toothache, drattle, necklace, trakite, stalentay, tomato. Congratulations! You just activated your dorsal pathway, some parts more than others depending on whether you were repeating real words or pseudo words. Alternatively, the ventral pathway (dark red arrow pathway) is active during semantic and syntactic processing and

is thus implicated in language comprehension activities. The ventral path originates from the auditory cortex, and then projects (green arrow pathway) to the middle and inferior temporal lobe, with eventual output to the inferior frontal lobe, including the pars triangularis and pars orbitalis. The ventral pathway relies on connections that pass through the extreme capsule (see Figure 6‒5 for location of extreme capsule next to the insular cortex). So, pretend you are hearing these sentences: The man was driving too fast. The splack prought a prifony. The woman should run for president. Ipicam was gragio lan prathy. Congratulations again! Now, you just activated your ventral pathway, especially when producing the real sentences and not the jargon. Another gap in our knowledge, beginning to be addressed by these model developers, relates to the role of the insular lobe in language (see Figures 6‒5 and 6‒12 for location). According to various investigations, it appears that the anterior portion of the insular (AIns) lobe may support comprehension, while the posterior portion of the insula (PIns) may support repetition. This model has been used to theorize about where breakdowns in the dorsal-ventral network could occur and how it may result in comprehension and/or repetition impairments observed in different subtypes of aphasia. In our second model, developed by Weiller and colleagues (2015), these investigators based their dual-loop model on the vast knowledge of language disorder data. For the purposes of their modeling, dorsal streams or tracts refer to those that are generally oriented above the lateral sulcus,

CHAPTER 17   Neural Substrate of Language

whereas ventral streams or tracts refer to those oriented below the lateral sulcus (see Figure 17–7). The dorsal stream is responsible for analyzing and ordering of information (sensory, phonological, etc.) in time and space. This stream is therefore involved in correctly parsing phonology when heard (e.g., hearing each phoneme in the order in which it was produced, such as “scream” — /s/ then /k/ then /r/ then /i/ then /m/) and stringing these phonemes together correctly for purposes of spoken language production. The structures involved in the dorsal stream in this model are the inferior parietal lobule and ventrolateral frontal lobe, connected via the SLF. Included also are the superior temporal lobe and ventrolateral frontal lobe, connected via the AF (Weiller et al., 2015; Weiller et al., 1995). In Weiller’s model, the ventral stream is concerned with semantic meaning as well as the relationships between different phonological, morphological, syntactic, and semantic elements. The structures involved are the anterior temporal lobe (or pole) and ventrolateral frontal lobe — specifically the IFG pars orbitalis, connected via the uncinate fasciculus. The ventral stream also includes connections between middle and posterior temporal lobe structures and the ventrolateral frontal lobe, specifically the IFG pars triangularis and pars orbitalis, via the IFOF and EmC. In Weiller’s dual-loop model, the middle longitudinal fasciculus (MLF) seems to be associated with both streams, which was similarly hypothesized by Saur and colleagues. This model has been used to theorize about where breakdowns in the dual loops could occur, leading to

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aphasias marked by agrammatism and/or Broca’s aphasia, apraxia of speech, conduction aphasia, Wernicke’s aphasia, and primary progressive aphasias. Similarities between these two dual-loop models are apparent — not only similarities in function (e.g., comprehension and meaning), but also in gray matter areas and white matter tracts (e.g., IFG, SLF). There are also some important differences (e.g., UF), and much more research is warranted. Be mindful of the limitations of these models, in that they are based on very simple speech tasks or word-level errors, which may not accurately predict the scope and magnitude of the processing that takes place in real-world language tasks such as conversations and narratives. Factors such as attention to communication context, salience of information, and social mores need to be more regularly considered when developing language models. Additionally, as is likely clear to you by now, much of what we know about language is about spoken language — the understanding and processing of it. We have not even scratched the surface for language expressed through other modalities, such as gesture, orthography, and tones, nor have we begun to satisfactorily address what is happening in the brain of multilingual populations. As you can readily appreciate by this brief tour of current language models, we are only at the very start of our journey toward fully appreciating and understanding the neural complexity of language expression and reception in the human. If you have any interest in becoming a language scientist at some point in your future career, we could sure use the help!

Box 17–3. Further Interest:  The Human Connectome Maps of the brain’s wiring and connectivity are nothing new; they have been around for decades. These maps have been limited to small and discrete regions of the nervous system using mostly electrophysiological methods and/or existing brain imaging technologies. These maps are, and continue to be, important ways in which neuroscientists understand the network properties, structure, and function of the brain. Now, imagine the existence of a map so precise and so comprehensive that it would literally reveal the way in which every area of the brain communicates with every other area, and how every neuron within a neural network is connected to other members of the network. You don’t have to imagine this any longer because neuroscientists are hard at work today creating such a complete mapping of the brain under the umbrella of a massive federally funded project called the Human Connectome. The Human Connectome’s goal is no less than uncovering and understanding the physiological and structural basis of neural information processing and our mental

representation of behavior and cognition (which includes language!). Spearheaded by theorist Olaf Sporns (2011) of Indiana University and his colleagues across several national laboratories, the Human Connectome project is attempting to make sense of the vast neuroanatomical and functional data that currently exist. Neuroscience is often criticized for being excellent at producing reams of data about the nervous system, but poor at putting those pieces of information together to see how the nervous system operates in a living and conscious being. While still in its infancy, the Human Connectome project is already changing the way neuroscientists conceive of the brain and is pushing the boundaries for the creation of new analytical methods to accelerate our discoveries even further. Resource Sporns, O. (2011). Networks of the brain. Cambridge, MA: MIT Press.

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Models of Communication, Language Evolution, and Development Language is an incredibly complex behavior, and the preceding models most assuredly represent an oversimplification of the neural substrates that allow us to produce and comprehend language. Advances in structural MRI have allowed us to identify white matter connections and interconnected gray matter regions that, beyond just the AF, may contribute to language. In addition, integrating these white matter pathways and the areas they connect provides an avenue for understanding how language may have evolved incrementally in humans. So, now that you are more familiar with language anatomy and some language models, we can revisit our origin of language discussion with a more neuroanatomical perspective. The Social Communication and Language Evolu­ tion and Development (SCALED) model is a key theoretical model that currently attempts to explain how language evolved in humans, and how language develops or is learned in children. As summarized in Table 17–5, SCALED suggests five levels of language evolution and development, from primitive to highly advanced (Catani & Bambini, 2014). Level 1, recognizing informative actions by others, is both the first language precursor to evolve in mammals (especially primates) and the earliest developing aspects of language in human infants. This level is supported by frontal and parietal

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regions connected via the anterior AF. Level 2 is related to the ability to recognize communicative intentions in others, and requires use of the inferior frontal gyrus and dorsomedial frontal regions connected through the FAT. This tract and its connections are also present in macaque monkeys, who can recognize communicative intent in other members of their species. As the precursors to what is commonly recognized as language, Levels 1 and 2 develop in human infants within the first year of life. Level 3 represents lexical and semantic processing and has the most complex neural substrates. These substrates consist of (a) the superior, middle, and anterior temporal regions connected via the MLF and ILF; (b) the anterior temporal and inferior frontal regions connected via the UF; and (c) the inferior frontal and superior and middle temporal regions connected via the EmC and the IFOF. Level 4 characterizes one’s ability to parse syntax and is supported by activity of the inferior frontal and superior and middle temporal regions interconnected via the long segment of the AF. Levels 3 and 4 also represent the first levels where humans and closely related primates substantially diverge. While primates can learn lexical and semantic information, and combine lexical items, as demonstrated by chimpanzees learning sign language, they have a relatively small vocabulary made up of concrete items and a limited ability to combine elements to generate novel, syntactically complex utterances. Consistent with these differences, primates have less developed networks and are even missing some critical areas, such as the middle

 TABLE 17–5.   SCALED Model Levels Level

Features

Cortical Correlate

Level 1

Recognizing informative actions by others

• Frontal and parietal areas via AF

Level 2

Ability to recognize communicative intentions in others

• Inferior frontal gyrus and dorsomedial frontal areas connected through FAT

Level 3

Ability to use lexical and semantic processing

• Superior medial and anterior temporal areas connected via the MLF and ILF • Anterior temporal and inferior frontal areas connected via UF • Inferior frontal and superior medial temporal areas connected via EmC and IFOF

Level 4

Ability to parse syntax

• Inferior frontal and superior medial temporal areas interconnected via long segment of AF

Level 5

Ability to integrate pragmatic information from communication partners to understand meaning

• Superior medial temporal areas connected to inferior parietal lobule via posterior segment of AF

CHAPTER 17   Neural Substrate of Language

temporal gyrus, that support language abilities. In human children, the abilities described by Levels 3 and 4 develop over the course of several years during early childhood. Level 5, the final level of language evolution and development according to the SCALED model is the ability to integrate pragmatic information from communication partners in order to understand their meaning. This process is sustained by the superior and middle temporal region connected to the inferior parietal lobule via the posterior segment of the AF. This level of pragmatic integration requires a highly developed Theory of Mind (ToM) that is absent in other species, perhaps due to a minimally present posterior segment of the arcuate fasciculus. This is also the latest developing skill in children and continues to develop into adolescence. From our clinical perspective, we have had front-row seats to a constantly changing landscape of models and can share this truism with you: Models will, and should, always change and be updated. This is a great thing because it represents progress and advancement in knowledge (although it can be a bit frustrating when using up brain space to store this information for exams). Another truism is that models are, by necessity, simplifications of much more complex systems. This means that they will always fall a bit short in characterizing all the relevant features and characteristics of a phenomena. Given that there are many different models of speech and language processing, and considering also that they will change, it is difficult to know which will stand the test of time. Our own approach is to survey those models that have the most and highest quality evidence in their support, and to identify the similarities. For example, we might identify which gray and white matter areas seem to be shared across different models, and appear to support the same type of behavior. But even after we narrow it down to one or two, how or why should these models be incorporated into clinical practice? From our perspective, using theoretical models helps us to look at brain injury and predict areas of deficits for the purposes of improving our diagnostic processes. Through the use of models, language scientists have created a profile of deficits with corresponding predicted regions where we should see brain injury or atrophy in both acute and progressive disease states. This knowledge, and of course your theory of intervention, can also inform treatment decisions. For example, given damage to the dorsal stream, do you target therapeutic tasks to the more intact ventral stream, or do you directly target the residual dorsal stream for best outcomes? (Hmm, that’s a good research question. Time for us to get back to work!)

Neurological Factors and Correlated Features of Language Disorders Language is a complex brain-based behavior. As such, it should be of no great surprise that disorders affecting the brain often cause breakdowns in language. These disorders

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provide golden opportunities for us to study the relationships among brain structure, function, and language ability, but more importantly, they allow us to apply our knowledge of brain structure and function to improve habilitative and rehabilitative approaches. This section of the chapter focuses on disorders of language acquired in a fully developed language system, briefly summarizing the nature of each brain injury as well as its associated language deficits. Please keep in mind that each disorder is deserving of its own textbook, and we are not even scratching the surface of the complexities of language in these populations! From our clinical perspective, if you work with the adult population, persons with the diagnoses we briefly review here will absolutely be on your caseload. Knowledge of brain injury and behavioral symptom associations will be essential as you engage in the differential diagnosis process. In many cases, your in-depth language assessment will be used to help other health professionals, including neurologists, arrive at a correct patient diagnosis. It is important for you to advocate and to teach your patients and families to advocate for clinical attention to language and communication deficits. These can often be overlooked or put aside because other issues (e.g., paralysis, incontinence, impulsivity) may be taking center stage. While other co-occurring deficits are indeed important, the ability to communicate is equally important, if not more so than any other brain injury–related outcome.

Aphasias Aphasia is an acquired language disorder with many subtypes. The most commonly discussed and researched definition is that of an impaired language processing system that can affect speech production as well as auditory comprehension, thus inhibiting verbal communication. Deficits in the production and understanding of other communication modalities (e.g., gesture, writing, reading) are also present (Douglas, Brown, & Barry, 2002; Goodglass & Kaplan, 1983; McNeil & Pratt, 2001). Aphasias are most frequently discussed according to the subtypes that are associated with cerebrovascular damage (Tippett & Hillis, 2015), specifically to the left middle cerebral artery, which is the primary supplier of blood to perisylvian regions (see Figures 7‒15 to 7‒22 to review the cerebral vascular system). Following stroke localized to the perisylvian zone, speech and language deficits are likely to occur, and these range in their variety and severity. The amount of accurate content words produced and the rate at which they are produced can be impaired in aphasia, as well as the appropriate use of syntactic structures to link these content units. Word-level errors, called paraphasias, may also be produced. For example, someone may want to say “cracker” but produces “bread” instead, generating what is referred to as a semantic paraphasia. Perhaps a person intends to say, “stop sign” and says, “spot sign” or “tops sign.” In this case, the individual is demonstrating a phonological paraphasia. The person may even make up a new word — a neologism — that follows the

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phonological rules of his or her language, but is not actually a word, such as “apishade” or “frealth.” A person with aphasia may also have a difficult time repeating words and sentences he or she hears. Finally, the person’s comprehension of language, whether through reading language or hearing it, may also be impaired. This comprehension impairment can also impact the monitoring of spoken language output, so that the person does not detect his or her own errors. This condition is often associated with semantic jargon — real words in sentences, spoken with regular stress and intonation, that do not make much sense or express the intended message. This deficit is often described among practicing therapists as the individual producing a “word salad.” As illustrated in Figure 17–8, many different forms of aphasia can emerge depending on where the damage is done by a stroke (ischemic or hemorrhagic) or where other similarly related neurotrauma is localized. As alluded to earlier, different forms of aphasia can be segregated from one another based on a patient’s ability to produce speech fluently, to comprehend language, and to repeat what is spoken to that person. Each form of aphasia is correlated with damage to a specific region of the perisylvian language zone. The decision tree in Figure 17–8 is provided as a handy general reference to quickly determine different variants of aphasia based

Fluency Comprehension Repetition

on your assessment of a patient’s fluency, comprehension, and repeating abilities as either functional or poor. More specific details for each form of aphasia are summarized in Table 17–6. Please note that the decision tree in Figure 17–8 ignores reading and writing of language, which is commonly affected in persons with aphasia, although Table 17–6 does include some mention of reading and writing deficits by aphasia subtype. Research and clinical practice for acquired deficits of reading (alexia) and writing (agraphia) lag far behind that for spoken language deficits, a situation that we sincerely hope will improve in years to come. Furthermore, the decision tree, while useful for many different presentations of aphasia, will not be helpful for detecting very mild aphasic deficits that are still quite debilitating. In those cases, assessment of comprehension and production of narratives is needed (see Box 17–4 for a brief discussion on the difference between fluent and nonfluent aphasias). To give you an idea of how a person with expressive aphasia may sound, the following is a spoken language sample obtained from a patient with Broca’s aphasia. The patient had a stroke to the left middle cerebral artery, causing damage to the left hemisphere perisylvian areas, primarily in the frontal lobe region, but also including temporal and parietal lobe areas. This person is describing the “firemen” picture

Aphasia

Poor Poor Poor

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Functional

Global

Functional Functional

Poor

Functional

Broca’s

Mixed Transcortical

Poor Poor

Functional

Wernicke’s

Transcortical Motor

Functional Poor

Functional

Conduction

Transcortical Sensory

Anomic

 FIGURE 17–8.   Aphasia decision tree. Variants of aphasia can be determined based on assessment of a patient’s fluency, comprehension, and repeating abilities. Each form of aphasia is correlated with damage to a specific region of the perisylvian language zone.

 TABLE 17–6.   Major Forms of Aphasia and Associated Characteristics Aphasia Type

Fluency

Broca’s (expressive)

Nonfluent

Transcortical motor (expressive)

Nonfluent

Auditory Comprehension

Repeat

General Characteristics

Within functional limits (WFL) to mildly impaired

Impaired

• Often associated with apraxia

WFL to mildly impaired

WFL

• Telegraphic, sound distortions, agrammatism, word errors (paraphasias) • Significantly reduced length of utterances • Poor conversational partners, lack of ability to initiate and maintain exchanges • Retention of attention skills • Paraphasias and perseveration

Mixed transcortical (expressive)

Nonfluent

Wernicke’s (receptive)

Fluent

Mildly impaired

WFL

• Rare form of aphasia • Severe deficit producing propositional speech • Damage thought to isolate Broca’s, Wernicke’s, and arcuate fasciculus from one another

Impaired

Impaired

• Empty/nonsensical speech, with paraphasias and neologisms • Use of grammatically correct sentences that lack any meaning, and often lacks awareness of deficit • Reading/writing is severely impaired • Logorrhea

Transcortical sensory (receptive)

Fluent

Impaired

WFL

• Much similarity to Wernicke’s • Empty/nonsensical speech, with paraphasias and neologisms • Presenting with strong compulsion to echo speech and repeat • Lexical and semantic processing impaired, but phonological processing remains present

Conduction (receptive)

Fluent

WFL to impaired

Impaired

• Hallmark characteristic: inability to repeat • Avoidance of repetition by paraphrasing • Auditory comprehension, grammatical and syntactical production remaining mostly intact • Speech is sensical with paraphasias

Anomic (expressive or other)

Mostly fluent

WFL to mildly impaired

WFL

• Milder form of aphasia • Speech is sensical with category-specific wordretrieval deficits • Often complaint of “tip of the tongue” feelings • Speech filled with vague words and a great deal of circumlocution

Global (expressive and receptive)

Nonfluent

Impaired

Impaired

• Most severe form • Produces few words • Inability to read or write • If language is present, paraphasias and verbal stereotypies are noted

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Box 17–4. Clinical:  Fluent Versus Nonfluent Aphasias Although there is no universally agreed-upon classification system for aphasia subtypes, there is general agreement that most presentations of aphasia can be described as either fluent or nonfluent. Wernicke’s, transcortical sensory, conduction, and anomic aphasias fall under the umbrella of fluent subtypes, whereas global, mixed transcortical, Broca’s, and transcortical motor aphasias are considered nonfluent subtypes. Examples of aphasia subtypes that do not fit neatly into this classification scheme include (a) crossed aphasia, which occurs in a right-handed person because of a right hemisphere lesion; (b) atypical aphasia, which has a mixed constellation of language deficits attributed to premorbid idiosyncratic cortical organization; and (c) aphasias that arise secondarily to subcortical damage (e.g., thalamus, basal nuclei) (Brookshire, 2007). The terms “expressive” and “receptive” are also used to characterize aphasias and are meant to capture the deficits that are most prominent in that subpopulation (Brookshire, 2007). For example, the greatest challenge for a person with “expressive aphasia” would be expressing thoughts through spoken (and/or written) language, and a person with “receptive aphasia” would have the most difficulty understanding language presented through auditory and/ or visual modalities. These terms can be somewhat misleading, as they can lead to the assumption in the case of expressive aphasia, for example, that receptive abilities are intact. While receptive abilities may indeed be a relative strength compared to expressive abilities in this case, it is unlikely that they are completely intact or normal.

from Nicholas and Brookshire (1993) (Figure 17–9). Take a moment to appreciate this language sample. One children, yes, girl. Girl, two braids, yes. Uh, long hair, yes, dress and loafers. Wike (intended: white) socks. Tri . . . tricycle seat. Handles. A ladder. Tree leafing. A leaf. A leaf. Cat. Dog. One is up high. One up high. Shirt, pants, and loafers. Hair, hair, combing hair. Okay. “Ruff ruff.” Yes, trees. Fire stason (intended: station). Fire stason. Two ladders, uh, spenders (intended: suspenders). Four boots, four tires, sireen (intended: siren). Engine. Pants, shirt, yes. Rescue fire. And rescue. (Total time producing sample: 3 minutes, 18 seconds) Questions to ask yourself to help guide your exploration of this sample include: Are the utterances or sentences long or short? Are the sentences grammatically correct? Because most words were accurate and depicted in the picture scene, were you able to determine the “gist” of this story? What compensatory strategies does the person seem to be employing to describe the picture? Was the

It is common for an individual’s aphasia subtype to evolve over time during recovery (Brookshire, 2007). Most individuals with aphasia participate in language therapy with a speech-language pathologist at some point in their recovery, and it is generally accepted that those who participate in therapy demonstrate better outcomes than those who do not. Therapy targets depend on your approach to rehabilitation: compensation or remediation. Perhaps you assume that the central areas responsible for aspects of speech and language (e.g., syntax, semantics) cannot be retrained. Your rehabilitation may then be compensatory in nature, and you may focus on areas of strength or language abilities that were preserved. Alternatively, you may be convinced that discrete language deficits can be targeted directly and that the intact brain can reorganize to support those tasks, even if those central areas were altered by the brain injury. Your rehabilitation may then be remediative in nature, and you may target those language deficits directly. Current behavioral and neuroimaging evidence, as well as best practice recommendations, support both remediative and compensatory approaches to treatment, as well as both in combination, to meet the needs of the individual patient. Resource Brookshire, R. H. (2007). Introduction to neurogenic communication disorders (7th ed.). St. Louis, MO: Mosby-Elsevier.

person’s communication efficient if you compare the output to the total time spent producing it? In this next example, we have a spoken language sample of someone with conduction aphasia following a stroke. The stroke was a left middle cerebral artery occlusion that caused damage to left hemisphere perisylvian areas, primarily temporal and parietal lobe regions. This person is describing the “broken window” picture sequence from Menn and colleagues (1998) (Figure 17–10). Take a moment to appreciate this sample. With a trouble ’o been around messing around with a pes pes. That’s about uh one ball and one thing happened happened with the the ball with the blades and I going kabush off over on toward the wall and its min there’s a obviously and hits somewhere hits there and to to the house for the was sitting and then wondering for and the one that’s going on I had hole up up the bo the po into the house and that’s when cuz wants to some pillows over to some pillows some other people are lookin’ at at what’s on this lot . . . this scal a on.

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 FIGURE 17–9.   Firemen picture. (Republished with permission of the American Speech-Language-Hearing Association. From Nicholas, L. E., & Brookshire, R. H. [1993]. A system for quantifying the informativeness and efficiency of the connected speech of adults with aphasia. Journal of Speech, Language, and Hearing Research, 36(2), 338–350. Permission conveyed through Copyright Clearance Center, Inc.)

 FIGURE 17–10.   Broken window picture. (Reprinted from Menn, L., Reilly, K. F., Hayashi, M., Kamio, A., Fujita, I., & Sasanuma, S. [1998]. The interaction of preserved pragmatics and impaired syntax in Japanese and English aphasic speech. Brain and Language, 61(2), 183–225, with permission from Elsevier.)

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Questions to help guide your exploration of this sample include: Are the utterances or sentences long or short? Are the sentences grammatically correct? Are there word-level errors? What ratio of real words to pseudo words do you observe? Were you able to determine the “gist” of this narrative?

Dementia Dementia, or neurocognitive disorders (NCD), according to the fifth edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-5) published in 2013 by the American Psychiatric Association, is a term referring to a wide variety of chronic and progressive brain diseases or differences. For this diagnosis, memory and at least one other cognitive function (such as language) must be impacted. A key diagnostic factor in the classification of NCDs is that they must arise gradually and not acutely. Memory and other cognitive functions are important for language and, as such, there is a wide variety of language signs, symptoms, and breakdowns that can be observed with this broad diagnosis. Some forms of dementia are characterized by impairment in semantic memory or conceptual knowledge, resulting in semantic breakdowns and semantic paraphasias being produced. Language may also often lack semantic content and be nonspecific or impoverished. Some with dementia may present with aphasia-like symptoms, as described earlier. There is a special type of dementia where language is actually the primary complaint, as opposed to memory or other cognitive factors. This disorder is referred to as primary progressive aphasia (PPA). PPA does not arise from stroke or other cerebrovascular etiologies. As such, the brain areas involved in PPA may differ from those usually impacted by an MCA stroke. For PPA, the constellation of symptoms does not fit neatly within those categorizations associated with stroke, resulting in unique subtypes for PPA. Historically, PPA was not recognized as a specific type of dementia, and individuals with what we now call PPA were likely diagnosed with Pick’s or Alzheimer’s dementia. PPA is unique among the different types of dementia because it primarily impacts language abilities rather than cognitive functions like memory, attention, visuospatial processing, and executive functions. There are currently three widely recognized PPA variants, although several other forms have been proposed by various language scientists. The semantic variant is characterized by a progressive loss of word meaning without reduced speech output. The logopenic variant is characterized by deficits in phonology and moderately reduced speech output due to word-finding difficulties. The nonfluent/agrammatic variant is characterized by severely reduced speech output, agrammatism, and/or motor speech errors (Figure 17–11). PPA offers scientists a unique opportunity to further our understanding of how language is processed and produced in the brain by relating performance on in-depth language testing to the areas of the brain that show degeneration on neuro-

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imaging. So far, studies of the neurodegeneration patterns caused by PPA have helped to confirm insights about the role of specific brain regions for certain aspects of language. For example, individuals with semantic variant PPA show localized damage to the temporal poles in both the left and right hemispheres (see pink zone in Figure 17–11). This confirms previous research that suggested that unlike many other language aspects, semantic representations are organized bilaterally, and damage to both hemispheres is necessary for semantic deficits to be observed behaviorally. Similarly, investigations of logopenic and nonfluent (agrammatic) variants have confirmed much of our knowledge regarding the areas of the brain responsible for speech production, phonological processing, motor planning, and grammatical knowledge (see green and blue areas in Figure 17–11, respectively). In addition to confirming previously theorized brain-​ language relationships, PPA offers the chance to extend our knowledge of this relationship. Historically, the conclusions researchers have been able to make regarding brain areas specialized for language have been limited by the kind of damage caused by a stroke. Because a stroke is caused by disruption of blood flow in the brain, damage occurs where blood vessels are. This means that certain brain regions are highly likely to be damaged together when a stroke occurs because they are fed by the same blood vessel. Because these areas are almost always damaged together, it can be difficult, if not impossible, to determine and tease out the exact function of one or the other of those regions. On the other hand, PPA is a neurodegenerative disorder that does not follow the vascular system. It may be possible for the function of brain regions commonly damaged together in stroke to be elucidated and studied independently because of the unique patterns of damage found with PPA. To give you an idea of how a person with PPA may sound, the following is a spoken language sample of someone with logopenic PPA. Brain atrophy to the left hemisphere perisylvian area was suspected. This person was asked to describe how to make a peanut butter and jelly sandwich. [Wife’s name] really likes them. I don’t like them. Okay so I’ve got I’ve got to figure this thing out. A s- s- say one more time what you said th- peanut butter and j-jelly a- and you need to know. How to make- okay. The situation of making a peanut butter and jelly sandwich is a very incredibly complex sandwich. One has to go ahead and have the right house, have to have the right place, y- have to have the right sugar, it has to have the right uh wheat, it has to have incredible number of things in order to have a a jelly and peanut sandwich. Now, there’s only it’s only be can be accomplished by a person that has two kids and a husband and this lady that can do this is one knows a great deal about speech work and she has this incredible talent to put together this beautiful thing in a very special place. And she puts these things together. And when she gets done with this, there’s nothing better in the world than this peanut butter

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Primary Progressive Aphasia Peak Damage Areas PPA Logopenic Variant

PPA Agrammatic Variant

PPA Semantic Variant

 FIGURE 17–11.   Deficit regions correlated to different forms of primary progressive aphasia (PPA). Semantic PPA is correlated to deficits in the anterior temporal lobe (pink shading). Logopenic PPA is correlated to deficits in the temporoparietal junction region (green shading). Lastly, nonfluent PPA (agrammatic variant) primarily arises from deficits in the frontal lobe rostral to the precentral gyrus (blue shading).

and jelly sandwich given by this beautiful, beautiful fine nice wonderful lady. There. Questions to help guide your exploration of this language sample include: Are the sentences grammatically correct? Are there word-level errors? If you were from another country where people did not eat peanut butter and jelly sandwiches (sacrilege!), would you be able to construct a PBJ from this description?

Traumatic Brain Injuries Traumatic brain injury (TBI) generally involves more diffuse damage (except in cases of penetrating head injury) and particularly affects white matter tracts in a broader manner, known as diffuse axonal injury (DAI). The cause of DAI is related to differences in the inertial properties of different types of brain tissues, and the shearing and tearing forces that these inertial differences generate on white matter tracts during rapid acceleration and deceleration forces experienced by the brain (Figure 17–12, bottom panel). Note that not only are axons sheared during these events, but capillary structure too! Disruption of capillary networks leads to pinpoint focal damage (think of this damage as extremely tiny and localized strokes) to both white matter and cortical elements. The most frequently documented and researched brain areas affected by

DAI and capillary damage are the frontal lobe areas. Injury to this brain region subsequently affects higher-level cognitive functions. Impact force or rapid deceleration types of injuries also result in a characteristic coup-contrecoup damage pattern, whereby the brain undergoes a forceful impact into the skull (coup injury) followed by forceful recoiling of the brain that leads to additional damage (contrecoup injury) on the opposite side of the brain (see Figure 17–12, top panel). While not represented well in most language models, language relies heavily on cognition. It is certainly understandable that language abilities will be impaired following TBI, given the extensive damage caused to interconnecting white matter axon pathways. TBI populations are less likely to have aphasia, which is more closely associated with focal damage to perisylvian areas on the lateral cortical surface. Rather, TBI patients are more likely to demonstrate difficulty using the aforementioned dorsal and ventral streams efficiently, functionally, or in socially appropriate ways. This difficulty arises primarily because of attentional, memory, social cognition, or other executive functioning deficits caused by structural damage to both cortical and white matter pathways. This collection of deficits is thus referred to as cognitive communication disorders (McDonald, Code, & Togher, 1999). Deficits are particularly apparent in narratives and conversations, and include (a) reduced coherence and

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Acceleration Forces

Recoil forces

Coup

Normal Axon Myelin sheath Axon

Contrecoup

Shearing of Axon Forces applied to brain cause axons to twist & tear

Post-trauma state

Neurons die

Cell body

 FIGURE 17–12.   Coup and contrecoup brain injury and diffuse axonal injury (DAI). Impact or deceleration forms of injury produce characteristic coup-contracoup patterns of damage to large surfaces of the cortex. These patterns (top of figure) arise because the brain undergoes forceful acceleration-related impact into the skull (coup), followed by forceful recoiling of the brain to produce additional cortical damage (contrecoup injury) opposite to the initial site of injury. DAI results from shearing forces acting on white matter tracts during rapid acceleration and deceleration forces. Shearing (bottom of figure) effectively twists and rips apart axon structure as well as presynaptic terminal attachments. With this much damage, the tissue eventually dies.

cohesion of language, (b) poor organization of the content presented, (c) poor initiation of communication and/or difficulty maintaining communication intent or topic, (d) social inappropriateness, (e) excessive tangential discussions, and (f ) reduced ability to use and understand abstract or figurative language. The following is a spoken language sample from someone with a traumatic brain injury following a motor vehicle accident. The accident caused diffuse white matter damage as well as additional focal damage to left hemisphere areas because of brain swelling and subsequent surgical intervention — a frequent secondary consequence following an initial

injury. This person was asked to describe part of the event and the recovery. So I remember up to an hour before [the accident] and then the first memories that . . . are close to two months un. . . . So for the first two months, I was here in [name of town] and I have a total of . . . (long pause). For some reason I’m thinking it’s four, but I can only think of three right now um . . . memories in [name of town] and then it comes back up in [name of state where received acute treatment]. When I first went up there, I was. . . . We’re in the home that um . . . I wasn’t even in a wheelchair I was

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basically in the bed and that was pretty much it um . . . I moved over to a wheelchair, um . . . did a lot of things in occasional therapy and um played a lot of uh, just secret board games are fantastic for helping people, they really are um . . . yeah, no cuz um. . . . My main SLP up in [name of state], she gave me an assignment where each week I had to choose two board games and learn to play them at in spare time, you know . . . aaaand uummm. Yeah that and then I went out to [name of city] after that um . . . to uh over there and um that’s where I . . . They taught me walking in [name of state] as part of PT and the very last session I ever had was uh walking through the halls with a shopping cart to keep my balance but um. . . . And [name of city] is when I started uh not using the wheelchair and just started walking (a)gain and they had me uh practice on grass, which you don’t really see here but grass is a lot better than rocks or a lot tougher I mean . . . you know, if there’s holes you don’t necessarily see them or you know . . . yeah. You know it’s [speech] definitely gotten better. It’s done more than it was, um. . . . You know I’m definitely a lot more social now and so, uh, talking with other people helps improve it too um . . . but yeah, I mean . . . (shrugs) seems to be doing okay, you know? Questions to help guide your exploration of this language sample include: What are your thoughts and impressions about this language sample? Are the utterances or sentences long or short? What is the ratio of complete sentences to incomplete sentences? Were you able to determine the “gist” of this narrative? How does this sample differ from the previous samples? What are some similarities?

Right Hemisphere Much of our discussion up until now has ignored or downplayed the role of the right hemisphere in language, primarily because models have yet to adequately incorporate this hemisphere into the grand scope of language processing. It should be clearly understood that language is much more than just finding the right phonemes, words, and sentences. It is also about using prosody (stress and intonation) appropriately to convey the intended meaning by “knowing your audience,” navigating communication rules, and altering the intent of the spoken word. When these things go wrong, miscommunications are likely to occur, and it can be difficult to maintain relationships. The right hemisphere plays a critical role in these and other language and communication abilities. Broadly speaking, right hemisphere deficits can be divided into three major categories: communication difficulties, attention deficits, and cognitive effects (Blake, 2016). To limit the scope of our discussion, we focus here on the communication difficulties observed after right hemisphere damage, but keep in mind that attention and cognition factors may cause issues that present as communication impairments while having a different underlying neural substrate

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and cause. For example, difficulty sustaining attention could lead to a person’s mind wandering during a conversation so that the person misses important details. This could lead to inappropriate responses to the topic at hand that might appear to be auditory comprehension difficulties. Right hemisphere communication deficits may include, but are not limited to, difficulty processing emotion, impaired prosodic abilities, disrupted content and organization of connected speech, impaired comprehension of connected speech, difficulty with abstract language, problems identifying and using relevant information in narratives and conversations, and other pragmatic impairments that may impede appropriate language use (for an excellent discussion on right hemisphere deficits, see Tompkins, 2012). Impairments of prosody, affect, and pragmatics can be receptive (i.e., difficulty understanding the cues provided) and/or expressive (i.e., difficulty using cues to support the communication partner) in quality. Individuals with receptive deficits may have trouble picking up on extralinguistic and paralinguistic cues such as facial expressions, body posture, tone of voice, volume, and speech rate used by communication partners, or may not be able to use those same cues themselves to signal their feelings about the communicative interaction effectively. While these kinds of miscommunications happen to non-brain-injured speakers on occasion without lasting harm, their continued presence may leave some potential communication partners reluctant to engage in communicative exchanges out of fear or potential discomfort. It is unclear what percentage of individuals with right hemisphere damage experience prosodic and affective deficits. Perhaps the core communication deficit observed in right hemisphere disorders is that of inferencing. Research has shown that individuals with right hemisphere damage are able to make inferences, but that they do so less accurately and have more difficulty revising inferences than healthy control subjects. Inferencing difficulties may have two separate sources. In healthy control subjects, when a sentence is processed, all possible semantic meanings and inferences based on the nature of the sentence are activated. As processing advances, inappropriate meanings and inferences are inhibited or deactivated until the correct interpretation of the sentence remains. Individuals with right hemisphere damage may present with a coarse coding deficit, in which all possible meanings or inferences are not initially activated (the right hemisphere is implicated in activating more distant meanings of words), or a suppression deficit, in which inferences are not adequately inhibited once they are identified as clearly inappropriate. Difficulty with inferencing leads to difficulty understanding humor or abstract language like metaphors and similes, and identifying the most salient information in narratives and conversations. Together, these factors may lead to difficulty with comprehension, especially in connected speech. Expressive aspects of communication deficits in individuals with right hemisphere damage are related to discourse

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production and comprehension. Individuals with expressive issues may produce discourse that is poorly organized, contains tangents or non sequiturs, and is inefficient. Narratives and conversations may be difficult to understand because a great deal of nonessential information is produced (like talking about a really great restaurant across town when asked to give directions to a different restaurant), or because too little detail is given with critical information absent (such as using pronouns without first introducing the subject to which they refer). Generally, narrative and conversation deficits are related to the inferencing issues mentioned earlier, or perhaps to attention or cognitive deficits that overlap with language. The discourse-based deficits seen in individuals with right hemisphere damage are highly variable and can be subtle. As such, we caution you to recognize that each patient may present differently, and that deficits may not always be easy to recognize — which doesn’t mean that they are not negatively impacting communication.

Harnessing the Ability of the Brain to Change for Language Rehabilitation Rehabilitation is described as “the provision of planned experience to foster brain changes leading to improved daily life functioning” (Robertson, 1999, p. 385). If rehabilitation truly aims to provide experience to produce structural brain changes that lead to functional brain and behavioral changes, then it must take into account the neurosciences. Integrating neuroscientific methods with rehabilitation approaches led to the emergence of the field of study termed neurorehabilitation, an approach seeking to regain brain function following injury or maintain brain function in the face of progressive disease (Berthier & Pulvermüller, 2011; Kaas, 2002; Khan, Amatya, Galea, Gonzenbach, & Kesselring, 2017; Nadeau, 2002). Research in neurorehabilitation seeks to discover ways to manipulate the system such that plastic mechanisms can be triggered, enhanced, disrupted, reversed, and/or prolonged. Understanding these mechanisms and how to manipulate them can then lead to the development of more effective, efficient, and efficacious neurorehabilitation procedures to bring about the desired change and/or prevent undesired patterns from being established. Activity-dependent plasticity (also known as experiencedependent, or use-dependent, plasticity) refers to the ability to alter structure and function within the nervous system as a result of voluntary experience. Activity-dependent plasticity begins in utero, operates during development, and is maintained throughout the life span (Hafström & Kjellmer, 2000; Hübener & Bonhoeffer, 2014; Zhang & Wang, 2007). This is crucial, because organisms constantly experience new events and must have a nervous system that can adapt to these events within the context of a limited set of brain resources (Edelman, 1987; Nudo, Wise, SiFuentes, & Milliken, 1996;

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Singer, 1994; Thelen & Corbetta, 1994; Turkstra, Holland, & Bays, 2003). Furthermore, we are always learning — from our first sounds, to a new sport, to a second language, to operating new machinery or tools — and relying on brain plasticity to accomplish these behaviors. Activity-dependent plasticity occurs as a result of use and everyday experience, and is very much dependent on the nature and form of input a person is experiencing. But it can also be a mechanism that is manipulated via treatment programs to bring about specific and desired changes to improve a patient’s performance on a given task. The neural system or behavior in which change is desired must be engaged in training; otherwise, the brain networks that support that behavior will be retasked (pulled away for use in another network for another behavior) to other functions. In other words, if you do not use those brain networks for that behavior, you lose them to another process. For rehabilitation purposes, this would mean that we need to know the area of the brain we are wishing to train (our target) and what types of tasks will strongly engage those areas. The language rehabilitation literature currently lacks much in the way of target engagement knowledge, making this topic a focus of research for years to come. The brain is more likely to change in response to training tasks that involve some level of challenge, complexity, learning, and, most critically, attention. Training tasks are also likely to be more effective in changing brain structure and function if they are not trivial to the individual, but instead are relevant for everyday functioning. In these ways, the nature of our therapeutic task matters immensely. When selecting a therapeutic task, we can abide by what we term the “Goldilocks rule”: The task can’t be too easy so that the person “checks out” of the activity, but it can’t be so difficult that the person gives up in frustration. Instead, the task needs to be just the right mixture of complexity. This is demonstrated time and again in human and other animal research, where skilled versus unskilled, enriched versus mundane, challenging versus unchallenging activities result in more brain changes and more behavioral benefits than passive or simple behaviors. Furthermore, the training task must engage the specific areas of the brain you are attempting to change. Working on tasks that engage only visual cortex or motor cortex, for example, is unlikely to lead to demonstrable changes in language-related brain regions. If you want to get better at something, you must practice doing that something. It is no surprise then that large amounts of practice and repetition of training tasks are an important requirement for activity-dependent plasticity. Repetitive engagement of brain networks during the target task increases the ability of brain cells within that network to communicate more effectively and efficiently, facilitating learning and/or behavioral improvement. In the motor learning literature, massed practice refers to the blocked repetition of a single task so that focus can be maintained and exposure to irrelevant stimuli or activities avoided (Nadeau, Gonzalez

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Rothi, & Rosenbek, 2008; Schmidt & Lee, 2005). It is often discussed in contrast to distributed practice, which is the same amount of total practice time, but with frequent and longer rest periods between repetitions (Nadeau et al., 2008; Schmidt & Lee, 2005). These labels are not entirely clear or absolute, as they are often used as relative terms to describe practice schedules within a specific experiment. They are also somewhat difficult to apply to a language treatment, because it is a bit difficult to picture how one would adhere to the idea of blocked repetition of a single task in language treatment that may involve a combination of sending and receiving messages, performing speech gestures with varying articulations, and utilizing varied stimuli. Perhaps this is one of the reasons why therapeutic practices in speech-language therapy do not adhere to traditional notions of massed practice. Other terms frequently used alongside massed practice are those such as “intense” or “intensive.” In the aphasia treatment literature, practice schedules described as intense have ranged anywhere from 3 to 20 hours a week. In the motor learning literature, “intensity” refers to the number of repetitions per unit of time; so, the translation of this definition to speech-language interventions would require investigators to focus on how many speech acts were produced per unit of time, instead of reporting on the overall number of hours spent in treatment. Still, the terms “massed practice,” “intense,” and “intensive” are often used interchangeably to describe the practice schedules of both motor and speech-language interventions. Recently, attempts to operationally define these ideas in hopes of creating uniformity in research and reporting suggest use of the term intensity to discuss the frequency of intervention (e.g., number of intervention hours per week), whereas quantity was suggested as a term reflecting the number of repetitions per unit of time (Raymer et al., 2008).

Neuroplasticity and ConstraintInduced Therapy Approaches In this next section, we discuss two rehabilitation approaches ​ — one for motor deficits and the other for language deficits — ​ that very nicely incorporate the aforementioned activity-​ dependent plasticity principles into their treatment procedures. Why is it necessary to discuss a motor deficit approach in a chapter on language? Discussion of the motor deficit treatment program is needed first because it will facilitate your understanding of the logic behind the new language treatment approaches that are being developed. The basic assumptions and logic are shared among the two different approaches. In the 1960s through the 1980s, a great deal of work was performed to test the hypothesis that forced use of a weak or paralyzed (affected) limb (Taub, Ellman, & Berman, 1966; Taub, Perrella, & Barro, 1973; Wylie & Tyner, 1981, 1989) and/or restraint of an unaffected limb could result in significant restoration of function of the affected limb (Ostendorf & Wolf, 1981; Taub & Berman, 1968; Wolf,

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Lecraw, Barton, & Jann, 1989). These approaches — forced use and restraint — were frequently used as separate treatment regimens for improving limb motor function. Eventually researchers realized the value of combining these approaches and developed a treatment protocol for physical rehabilitation designed to induce individuals to use their affected limbs poststroke (Kunkel et al., 1999; Miltner, Bauder, Sommer, Dettmers, & Taub, 1999; Taub, 1980; Taub et al., 1993; Taub, Crago, & Uswatte, 1998; Taub, Uswatte, & Pidikiti, 1999). This approach is known today as constraint-induced movement therapy.

The Original Idea:  ConstraintInduced Movement Therapy Constraint-induced movement therapy (CIMT) was developed by Taub and colleagues following work with primates and humans on a phenomenon called learned nonuse (Taub et al., 1994; Taub, 2004). Research demonstrated that primates and humans with brain damage that caused movement deficits to one or more limbs experienced pain, discoordination, and/or lack of success when trying to use the affected limb, leading to the avoidance of use of that limb. It was presumed that learned nonuse emerged because the behavior in question was associatively punished (via pain, lack of success), resulting in limb movement suppression. In addition, when success was achieved without the use of the affected limb, it was also thought that avoidance behavior was further reinforced. Thus, primates and humans learn, via classical associative conditioning, not to use the affected limb despite the availability of residual function. The essential premise to CIMT is that once constraint of the unaffected limb is introduced, the reinforcement contingencies or rewards are altered to give the primate or human two choices: (a) attempt to use the affected limb to try to meet basic needs as well as participate in everyday activities or (b) forgo eating, grooming, and mobility. Because the preference to meet basic survival needs and participate is strong in mammals, this change in contingencies overpowers the strength of the learned nonuse, and the animal is forced to use the affected limb with greater frequency and intent (Taub et al., 1994). CIMT typically involves constraint of an unaffected limb via hand splint, using an oven mitt, arm sling, and/or verbal instruction not to use the unaffected limb(s), accompanied by forced use of the affected limb(s) during functional tasks (e.g., meal preparation, eating) for most of the individual’s waking hours (Taub, 2004; Wittenberg et al., 2003). The overarching objective is twofold: (a) to increase the amount of time the individual uses the affected limb, and (b) to shape the movement of that limb so that it is used as normally as possible (Taub, 2004). CIMT outcomes research consistently reports increased use of the affected limb, transfer of skills to real-world settings, and retention of treatment effects for at least 2 years posttreatment in a variety of clinical populations with motor deficits. Many studies have demonstrated that

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behavioral improvements are accompanied by cortical reorganization, in which increased neuronal activity (functional changes) and expansion of cortical areas devoted to the operation of the affected limb (structural changes) are observed following therapy (Kelly et al., 2014; Liepert, Bauder, Miltner, Taub, & Weiller, 2000; Miltner et al., 1999; Plummer, 2003; Taub, 2004; Wittenberg et al., 2003).

Constraint-Induced Language Therapy Following the success of CIMT, language researchers took this lead and began exploring the use of these principles within the context of speech and language (Pulvermüller et al., 2001). Because individuals with aphasia often live through negative experiences that lead to learned nonuse of communication, the application of constraint-induced approaches is a logical next step. For example, many individuals with aphasia report emotions such as frustration, anger, and helplessness during and following failed communicative acts that involve spoken language (Brookshire, 1997). These negative emotions, accompanied by the person’s frequent lack of success, can punish the speech production behavior, resulting in the individual with aphasia being more likely to rely on other nonverbal methods of communication (e.g., writing, gesturing, telegraphic speech) (Brookshire, 1997; Pulvermüller et al., 2001). If communication attempts with alternative methods are successful, avoidance of spoken language is further reinforced. A reasonable hypothesis is that pushing individuals with aphasia to use their impaired spoken language production system, and constraining or reducing their use of alternative methods of communication, may have an impact similar to those noted for CIMT in motor deficits (Pulvermüller et al., 2001). This is part of the logic of translating CIMT principles to language therapy, and part of the foundation of constraint-induced language (or aphasia) therapy (CILT or CIAT). CILT or CIAT development was heavily influenced by pragmatic approaches to aphasia therapy. For example, Wittgenstein (1953) introduced a “builder’s game” that required communicative interaction between a builder and an assistant (i.e., clinician and client) to successfully complete a construction or craft project. In this game, communicative acts had a clear purpose and led to observable actions. He believed that language was systematically linked to actions. These beliefs have since been confirmed with neurophysiological evidence that demonstrated functional linkages in the cortex between linguistic areas and primary motor areas during language processing tasks (Hauk, Johnsrude, & Pulvermüller, 2004; Pulvermüller, 2017; Pulvermüller, Hauk, Nikulin, & Ilmoniemi, 2005; Pulvermüller, Shtyrov, & Ilmoniemi, 2005). Following the introduction of these groundbreaking concepts, other pragmatic approaches that involved role-playing and scripted social communicative situations (e.g., shopping and dining) increased in popularity (Aten, Caligiuri, & Holland, 1982; Bollinger, Musson, & Holland, 1993; Schlanger & Schlanger, 1970). In the early 1980s, Davis and colleagues introduced an

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approach to aphasia therapy known as promoting aphasics’ communicative effectiveness or PACE (Davis, 2005; Davis & Wilcox, 1981, 1985; Li, Kitselman, Dusatko, & Spinelli, 1988). PACE is an approach that requires individuals to take turns sending and receiving messages in any communication modality (e.g., written, gestural, spoken). As long as the message is successfully conveyed, the communicative exchange is considered successful. In other words (excuse the pun), communication by any means possible is the name of the game. The earliest study in the aphasia literature related specifically to the development of CILT is that of Pulvermüller and Roth (1991), who introduced a modification to PACE and coined the new approach communicative aphasia treat­ ment (CAT). Their study used a requesting-style game for the PACE treatment with a physical barrier or screen placed between the patients and clinicians. All participants in the game received identical picture stimuli and were required to communicate the content of the picture to another individual via any modality. If the receiver was able to identify which picture the sender was describing, then the turn was judged successful. This foundational therapeutic task was put together with insights taken from the motor learning and rehabilitation literature to refine this approach and create CILT. The principles of CILT can be summarized as follows: (a) a focus on spoken language, sometimes facilitated via constraint of alternative methods of communication (and therefore forced use of spoken language); (b) shaping; (c) participation in behaviorally relevant group activities; and lastly (d) mass practice over a short period of time (usually 3–4 hours/day for 10 consecutive weekdays, though different schedules have been utilized) (Difrancesco, Pulvermüller, & Mohr, 2012; Pulvermüller & Berthier, 2008; Pulvermüller et al., 2001). These principles are implemented to obtain the objective of increasing spoken language output. This is a departure from many current methods of therapy, which consist largely of working in a 1:1 sterile clinical setting for one or two sessions per week, learning compensatory strategies or participating in traditional stimulus-response activities. During a typical CILT session, a frequent activity is a modified form of “Go Fish” played with picture cards (Difrancesco et al., 2012). Other activities include 20 questions, Memory, joint activity planning, scripted communication activities of daily living, and other narrative production tasks (Difrancesco et al., 2012; Goral & Kempler, 2008). Participants request, answer, or deny requests during the card game, in which the goal is to match picture cards. Barriers are placed between patients so that they are unable to view each other’s cards. As therapy progresses, individuals are required to gradually increase the syntactic complexity of utterances, moving from single words (or approximations thereof ) to sentences of varying complexity. In addition, clinicians provide as much cueing as possible to enable participants to eventually produce target productions correctly, and gradually reduce the amount of support provided. Sometimes an error-reduction approach is also taken, in which participants

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are encouraged to produce a response only when they are confident it will be correct. Thus, CILT involves rule constraints that facilitate shaping, as participants are required to move from a low-​ complexity syntactic structure to a high-complexity syntactic structure throughout the course of treatment (Difrancesco et al., 2012; Pulvermüller et al., 2001). For example, if the individual is able to produce only the name of the picture (e.g., scarf ) in an attempt to request, this is acknowledged positively, and the card is given. However, participants are required to produce more complex utterances (e.g., “green scarf,” “I want the scarf ”) as the therapy progresses. Material constraints are also introduced so that participants are initially dealing only with high-frequency vocabulary targets, but once they achieve mastery with these targets, they are moved to those that are lower in frequency and more challenging to produce (Difrancesco et al., 2012; Pulvermüller et al., 2001). Finally, to assist this overall shaping process, the level of individualized support is adjusted according to the level of performance, gradually reducing the level of scaffolding provided by the clinician so that participants experience greater independence (Difrancesco et al., 2012; Pulvermüller et al., 2001). Early forms of CILT required that all communication be in the form of spoken words or sentences. No pointing, writing, or gesturing was allowed. Meinzer, Streiftau, and Rockstroh (2007) conducted a study where they assumed constraint was not a necessary part in the rehabilitation approach, drawing from research in which constraint was believed to make only a small contribution to treatment outcomes in CIMT (Sterr & Freivogel, 2003) and also from the knowledge that gestures, drawing, and other compensatory communication efforts often facilitate spoken language. As such, their 2007 study did not concentrate on preventing gestures; rather, spoken communication was simply reinforced, and gesturing was allowed if it was not the primary mode of communication and it facilitated language output. Even with this variation, the treatment was deemed successful, as 19 of the 20 individuals in their study demonstrated improvement on overall aphasia severity and aphasia profile scores. These findings led to an update in CILT principles, where the concept of “constraint” was replaced with the broader idea of “focusing.” This focusing principle was subsequently described as a means of helping patients intentionally use their remaining language abilities, especially those being avoided (Pulvermüller & Berthier, 2008). Treatment studies that compared the effectiveness of CILT and traditional therapy approaches often find significant differences between the two methods on standardized language measures and measures of functional communicative behavior, transfer to narrative discourse, and long-term retention of treatment effects. Behavioral improvements are also accompanied by changes in brain activity, though interpretation and application of the varied findings often prove rather difficult (Kurland, Stanek, Stokes, Li, & Andrianopoulos, 2016; Maher

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et al., 2006; Meinzer, Djundja, Barthel, Elbert, & Rockstroh, 2005; Meinzer et al., 2007; Pulvermüller, Hauk, Zohsel, Neininger, & Mohr, 2005; Stahl, Mohr, Dreyer, Lucchese, & Pulvermüller, 2016; Szaflarski et al., 2008). From our clinical perspective, neuroplasticity is central to rehabilitation and is the key reason why therapy works. The rehabilitation specialist’s job is to direct the experience of a patient in such a way as to promote brain rewiring. We focused on CILT in the latter part of this discussion because it incorporates well-known principles of neuroplasticity within the treatment package. (Principles of neuroplasticity as they relate to another treatment, script training, have also recently been detailed in Hubbard, Nelson, & Richardson, 2020.) CILT is considered one of the most effective treatments supported by empirical research (Allen, Mehta, McClure, & Teasell, 2012; Cherney, Patterson, Raymer, Frymark, & Schooling, 2008; Shrubsole, Worrall, Power, & O’Connor, 2017; Watila & Balarabe, 2015). However, CILT may not result in significantly better outcomes compared to traditional speech-language therapies, especially if treatment intensity is accounted for (Brady, Kelly, Godwin, Enderby, & Campbell, 2016; Zhang et al., 2017). There is much research to be conducted in the field of language neurorehabilitation. Regardless, our current schedules of treatment delivery and service reimbursement are not compatible with neuroplasticity principles. This is a fundamental clinical practice condition that must be addressed and changed if we want to improve treatment outcomes above the levels they have been hovering at for the past several decades.

Neural Substrate of Language Recovery Following Stroke Converging clinical and imaging evidence suggests that neural recovery of language is often characterized by the following features: (a) activation of brain areas immediately surrounding the damaged, or lesioned brain (referred to as the perile­ sional areas); (b) increased activation in undamaged speech and language association areas in the language-​dominant hemisphere; and (c) activation of homologous areas in the nondominant hemisphere that mirror the location of the perisylvian language areas (Calvert et al., 2000; Cao, Vikingstad, George, Johnson, & Welch, 1999; Harvey et al., 2017; Martin et al., 2005; Mattioli et al., 2014; Meinzer & Breitenstein, 2008; Mohr et al., 2016; Thompson, 2000). A regional hierarchy of aphasia recovery poststroke has been proposed to describe the nature of language recovery (Cornelissen et al., 2003; Heiss & Thiel, 2006; Hillis, 2006; Rosen et al., 2000). Complete brain recovery, which is possible only following extremely transient and minor neural damage, represents the first tier of the hierarchy and the best possible behavioral outcomes for language performance. The second tier in this regional hierarchy may arise from

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the emergence or restoration of perilesional function in the language-dominant hemisphere. This outcome likely involves recruitment of areas that were associated with language production and processing before the stroke. This outcome may also entail the co-opting of nonlanguage left hemisphere structures to take over the role of language areas now that the original language processing regions are damaged. The third tier of the hierarchy involves recruitment of homologous speech and language areas (e.g., right temporoparietal areas), as there is evidence that such recruitment correlates with improvements in language performance, though often not to the degree of perilesional restoration of function. Consistent with the regional hierarchy, the presence of intact language areas in the left hemisphere has proven time and again to be incredibly important for aphasia recovery (Fridriksson, 2010; Heiss & Thiel, 2006; Mohr et al., 2016). Interestingly, damage to some language areas (e.g., posterior language areas) seems to result in worse overall outcomes (Fridriksson, 2010). However, just because tissue is intact, defined operationally here as readily identified white or gray matter in MRI images (see Figure 17–2), does not mean that it is functioning normally. Previous work has revealed that perilesional tissue may be receiving reduced blood flow (i.e., reduced cerebral perfusion) in chronic stroke even though the tissue remains intact (Fridriksson, Richardson, Fillmore, & Cai, 2012; Richardson et al., 2011). Blood flow levels in left hemisphere language areas have been found to correspond well with improvements related to treatment (Fridriksson et al., 2012). Also, the greater the number of spared and connected residual language processing areas that exist, the better the outcomes (i.e., reduced aphasia severity) (Gleichgerrcht et al., 2015). Visualization of patient lesion,

a.

Gray matter damage

b.

White matter damage

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connectivity, and blood flow images can help drive home this point. As is apparent in Figure 17–13, the fluid-filled hole in the brain caused by a stroke not only causes damage to those critical gray matter areas (see Figure 17–13A), but also significantly damages the underlying white matter tracts (see Figure 17–13B). Furthermore, blood flow is clearly reduced around the lesion space (see Figure 17–13C). Current research emphasizes the importance of restoration and/or normalization of function in the recovering stroke brain. In a typical brain, the dominant language areas in the left hemisphere inhibit right hemisphere homologues via transcallosal inhibition, where fibers from the left hemisphere cross over to the right hemisphere to excite cortical interneurons that then inhibit activation of the right hemisphere. A lesion in the language areas of the brain disrupts this structural connectivity and functional balance, resulting in the release of the nondominant right hemisphere from its normal state of inhibition (Thiel et al., 2015). In other words, in a healthy brain, the right hemisphere is “quieted” during language processing, but in the stroke brain, the “quieting” mechanism is not working correctly, so the right hemisphere operates without restraint and turns “on” with great frequency. While the right hemisphere does contribute to normal language and communication (e.g., prosody, emotion, concepts), as discussed previously, it is minimally redundant with left hemisphere specializations for language. So, the right hemisphere does perform some language jobs, but does not perform all of the left hemisphere’s language operations. For those it does perform, it does not perform them nearly as well. A closer look at aphasia recovery, though, reveals more complexities. Saur and colleagues (2006) conducted a lon-

c. Reduced blood flow

 FIGURE 17–13.   Representative MRI axial and coronal images of gray matter damage, white matter damage, and blood perfusion changes in an individual poststroke. A. In both the axial and coronal image, significant cortical tissue is absent and replaced by fluid (red arrow location). B. Note the expanded ventricles and the infiltration of fluid into areas that should be comprised of white matter (red arrow location). C. Perfusion of the brain tissue with blood is shown by the orange/red/yellow/ green color overlay. Note that in the region of damage (red ovals), blood profusion is clearly curtailed and/or absent.

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gitudinal brain imaging study to clarify the reorganization process and revealed different types of language recovery curves for the left versus the right hemispheres. For the right hemisphere, response activity first showed an initial increase, followed by a decrease during the more chronic phases of language recovery. Simultaneously, left hemisphere activation poststroke was characterized by a more linear relationship, with left hemisphere activity gradually increasing over time. Saur and colleagues (2006) concluded that as the left hemisphere activity began improving and restoring itself to near-normal levels, this change may have had the restorative effect of increasing inhibition to the right hemisphere back to near prestroke levels of activity. This evidence suggests that the left hemisphere was once again taking over its normal language processing role and was starting to quiet the right hemisphere back to its normal state. The degree of this normalizing shift in interhemispheric activity was associated with the extent of language function recovery. This finding, on the importance of restoring the balance of activity between the left and right hemispheres during language recovery, has led to new developments in treatment research (Barrett & Hamilton, 2016; Fernandez et al., 2004; Heiss, Kessler, Thiel, Ghaemi, & Karbe, 1999; Heiss & Thiel, 2006; Saur et al., 2006; Szaflarski, Allendorfer, Banks, Vannest, & Holland, 2013). Still, research continues to show us that the right hemisphere should not be discounted and also is not a monolith — some areas in the right hemisphere seem to be

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particularly helpful for recovery after brain injury, while others are not (Cocquyt et al., 2017; Kiran, Meier, & Johnson, 2019; Turkeltaub et al., 2012). In summary, the following brain states have been identified as consistent predictors of better language recovery outcomes: a) the presence of intact and connected (structurally and functionally) language areas on the injured side; b) reduced inhibition from the healthy right hemisphere to the injured left hemisphere, allowing the left hemisphere to begin reassuming normal language operations; c) greater inhibition from the injured left hemisphere to the healthy right hemisphere, which operates to quiet the right hemisphere back to pre-stroke levels; and d) coordinated functional activity between left and right hemisphere language and cognitive areas. As you can see, restoring activation balance between the left and right hemispheres should be a key goal for treatment. Many new methods are currently under development that are taking advantage of technological advances in noninvasive brain stimulation approaches to help drive the restoration of balanced activity between the two hemispheres. While the early data on these approaches and their effects on language recovery are promising, much work remains to be done until they become first-line therapeutic approaches.

Box 17–5. Clinical:  What Is a Clinical Trial? Clinical trials are part of clinical research and at the heart of all medical advances. Clinical trials look at new ways to prevent, detect, or treat diseases. Treatments might be new drugs or new combinations of drugs, new surgical procedures or devices, or new ways to use existing interventions. The goal of clinical trials is to determine if a new test or treatment works and if it is safe. Clinical trials can also look at other aspects of care, such as improving the quality of life for people with chronic illnesses. Many different types of people participate in clinical trials. Some are healthy, while others may have illnesses. A healthy volunteer is a person with no known significant health problems who participates in clinical research. Research procedures with healthy volunteers are designed to develop new knowledge, not to provide direct benefit to the study participant. A patient volunteer has a known health problem and participates in research to better understand, diagnose, treat, or cure that disease or condition. Although studies may provide direct benefits to patient volunteers, the main aim is to show, by scientific means, the effects and limitations of the experimental treatment.

Consequently, some patients serve as controls by not taking a test drug or by receiving test doses of the drug large enough only to show that it is present in their system, but not at a level that can treat the condition. People participate in clinical trials for a variety of reasons. Healthy volunteers say they participate to help others and to contribute to moving science forward. Participants with an illness or disease also participate to help others but usually do so to receive the newest treatment and to have the additional care and attention from the clinical trial staff. Clinical trials offer hope to many people and are an opportunity to discover better treatments for others in the future. Resource Edited from public domain material by the U.S. Department of Health and Human Services. (2016). Clinical research trials and you: Questions and answers. National Institute of Neurological Disorders and Stroke. Retrieved January 20, 2022, from https://www.nimh.nih.gov/health/publications/ clinical-research-trials-and-you-questions-and-answers

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Parting Thoughts on the Neurorehabilitation of Language A very wise colleague and friend once told us to never practice “random acts of therapy,” and to always have a purpose and deep intent when treating patients. We have taken this motto to heart and have made it a part of all our clinical and research endeavors, ensuring that we are intentional about each session, each task, each stimulus set, each homework assignment, and each research design we employ. It is obvious that atypical brain development or acquired brain injury can impact language ability. It is clear that neurorehabilitation can be administered in such a way that those language abilities are improved, with improvements accompanied by changes in the brain. It is also obvious that we have yet to reach the full potential of neurorehabilitative recovery in these areas: • brain health (e.g., perfusion and connectivity of the intact brain) is not fully incorporated into our plasticity and recovery discussions or investigations, • schedules of treatment in both real-world and research

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settings are pitifully sparse when you consider principles of neuroplasticity and the need for chronic and consistent experience to drive plastic brain changes, • most investigations are still conducted using outcome measures (e.g., naming, reaction time, repetition) that are unlikely to impact real-world functioning (e.g., discourse, conversation, participation, quality of life), and • we know next to nothing about target engagement in language rehabilitation; caseloads are too full to allow time to study and incorporate the best of the evidence or whole-patient outcomes. We do not list these glaring gaps to discourage you, but rather to invite you to come along and join us for the ride. There is much work to be done, and we can certainly use the help! This chapter has taken you on a journey though the neural foundations of language — from the beginning of language acquisition to a fully developed system, to brains with some dings and scratches, to what we believe is a message of hope for the future of language rehabilitation and the professionals who seek it as a career.

The Top Ten List 1. Language is a finite set of arbitrary symbols, agreed upon by a community or society, which can be combined to communicate an infinite number of concepts between community members for social cooperation. These symbols can be a string of letters on a page, a string of phonemes passing from mouth to ear, or handshapes passing from hand to eye. The key idea is that all these symbols express a concept. As long as the phonemes are assembled in a socially agreed-upon manner, their meaning will be understood, and communication will be successful. Language is also about knowing how to put strings of sounds, symbols, or handshapes together into phrases, sentences, and narratives, to express our thoughts and beliefs, opinions, and preferences. 2. The results of neuroimaging research in infants have demonstrated that spoken language learning starts at birth with the sounds or phonetics of the language. Right after birth, infants can detect small differences in the way phonemes are produced and, in fact, are much more sensitive to these differences than adult speakers. By 7 months, infants become native speech specialists and, by 11 to 12 months, become uniquely attuned to their native language. Two critical processes interact to give infants the capacity for rapid learning. They are very sensitive to frequency distributions and

probabilities in language and pick up on regularities in the language and speech they are hearing. This ability is referred to as statistical learning, a process that allows infants to learn language quickly from a small and underrepresentative sample of auditory inputs. 3. Social cognition paved the way for the evolution of language. Humans developed effective and efficient communication that could be transmitted across distances while also leaving their hands free to complete other tasks. As our communication system evolved, human society became more complex, leading to further advances in language, which again allowed for societal advances until the present day. It may have been this social impetus — our ability to understand how others think and feel, to consider others’ wants and needs — that provided the evolutionary spark for the development of our sophisticated language system. 4. In most typical adults (>90%), processing for language production and comprehension occurs primarily in the left hemisphere of the brain, specifically in areas around the lateral sulcus. This area is referred to as the perisylvian language area. Although the right perisylvian area has the same anatomical structures as the left, it is not activated as extensively for language. Explanations of language processing have ignored the importance of the connections between language-​associated

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The Top Ten List  continued

brain areas. It is increasingly recognized that white matter connectivity is vital to understanding how language is learned developmentally and how it emerges in real time during novel production. 5. The classic Wernicke-Geschwind language model highlights several primary language areas, including (a) Broca’s area, (b) Wernicke’s, and lastly (c) the arcuate fasciculus, the pathway that serves as the white matter connection between these two language processing centers. 6. A more recent language model called the Memory, Unification, Control model is an improvement upon the classic model and includes the following features: (a) temporal and parietal areas storing memory of knowledge pertaining to phonology, morphology, syntax, and semantics; (b) frontal areas important for the unification and assembly of these different pieces into larger coherent structures (e.g., phrases, sentences); and (c) frontal areas involved in the control of the selection and usage of these unified structures. Frontal lobe areas are needed for determining the context of the communication exchange, the selection of the correct language, turn-taking, adherence to social norms, and attention to salient information. 7. Dual-path models of language are the most promising models currently in development and generally consist of dual paths or loops of processing through cortical regions related to language. A dorsal-ventral brain network organization is proposed that supports both comprehension and repetition tasks. Dorsal brain areas include the parietal lobe and frontal lobe areas posterior to and including the premotor cortex. This stream is responsible for analyzing and ordering of informa-

tion in time and space. Ventral brain areas include the temporal lobe and frontal lobe areas anterior to the premotor cortex. This stream is generally concerned with semantic meaning as well as the relationships among different phonological, morphological, syntactic, and semantic elements. 8. Disorders affecting the brain often cause breakdowns in language. These disorders provide golden opportunities to study the relationships between brain structure, function, and language ability. They also allow us to apply our knowledge of brain structure and function to improve rehabilitative approaches. Knowledge of brain injury and behavioral symptom associations are essential for the differential diagnosis process. 9. The brain can change in response to training tasks that involve some level of challenge, complexity, learning, and attention. Training tasks are likely to be more effective in changing brain structure if they are meaningful and relevant for everyday functioning. In these ways, the nature of our therapeutic task matters immensely. This is demonstrated in human and animal research where skilled, enriched, and challenging activities result in greater brain changes and more behavioral benefits than passive or simple behaviors. 10. New rehabilitation approaches to language are taking advantage of neuroplasticity mechanisms and noninvasive brain stimulation methods. Taking cues from the neuroplasticity literature on constraint-induced therapy approaches in physical therapy, along with pragmatic approaches in aphasia therapies, a new model of language treatment called constraint-induced language therapy has emerged.

Chapter 17 Abbreviations AF — Arcuate fasciculus AIns — Anterior insula ATL — Anterior temporal lobe CAT — Communicative aphasia treatment CIMT — Constraint-induced movement therapy CILT — Constraint-induced language therapy

CIAT — Constraint-induced aphasia therapy

FAT — Frontal aslant tract

CSF — Cerebrospinal fluid

fMRI — Functional magnetic resonance imaging

DAI — Diffuse axonal injury

FOP — Frontal operculum

DSM-5 — Diagnostic and Statistical Manual of Mental Disorders–Fifth edition

IFG — Inferior frontal gyrus

EEG — Electroencephalography EmC — Extreme capsule

IFOF — Inferior frontal occipital fasciculus ILF — Inferior longitudinal fasciculus

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Chapter 17 Abbreviations  continued

PACE — Promoting aphasics’ communicative effectiveness

TBI — Traumatic brain injury

ITG — Inferior temporal gyrus

PFC — Prefrontal cortex

V1 — Primary visual cortex

MEG — Magnetoencephalography

PIns — Posterior insula

VL — Ventrolateral tier nuclei

MFG — Middle frontal gyrus

PPA — Primary progressive aphasia

vPCG — Ventral precentral gyrus

MLF — Middle longitudinal fasciculus

SFG — Superior frontal gyrus

vPMC — Ventral premotor cortex

MTG — Middle temporal gyrus

SLF — Superior longitudinal fasciculus

WFL — Within functional limits

NCD — Neurocognitive disorders

STG — Superior temporal gyrus

IPG — Inferior parietal gyrus IPL — Inferior parietal lobule

UF — Uncinate fasciculus

Study Questions and Activities • What is language in its simplest and most complex form? • Explain the idea that language is not innate. • Describe the results of advanced neuroimaging methods used in infants and toddlers to address questions related to language acquisition. • What has research using advanced neuroimaging methods taught us about language emergence? • What is meant by statistical learning and how does this concept apply to language acquisition? • Why are face-to-face interactions so vital for language learning? • Explain Theory of Mind and how this concept applies to processes in language. • Briefly summarize the operation of each brain area known to participate in language. • Practice identifying brain areas known to participate in language on figures of the cerebrum. • What is the significance of the white matter in language processing? • Which association pathways are vital for language processing and identify each pathway’s location? • Describe the classic language model. • Create a flowchart that lays out the processing pathway for language inputs from the auditory (spoken) and visual (reading) systems. • Compare and contrast the Wernicke-Geschwind model with the Memory, Unification, Control (MUC) model. • Summarize the characteristics of the MUC model. • Compare and contrast the Wernicke-Geschwind model with dual-path models.

• Summarize the characteristics of dual-path models. • What is the SCALED model, and what is it designed to explain? • Summarize the five levels of the SCALED model and relate each to language production. • What is the value of theoretical language models clinically? • Define aphasia and provide several examples of characteristic deficits associated with expressive and nonexpressive forms of this condition. • Define dementia. How is dementia different from aphasia? • Describe the nature of primary progressive aphasia (PPA). • How has PPA helped to confirm hypotheses related to normal language processing? • Define traumatic brain injury. • How do language deficits in traumatic brain injury (TBI) patients differ from those in other disorders or acquired conditions? • Explain diffuse axonal injury and why it is so problematic to deal with in patients with TBI. • Explain the critical role of the right hemisphere to language processing. • What is activity-dependent plasticity and how is it related to learning and rehabilitation? • Explain the basic premise behind constraint-induced therapy approaches for aphasia. • Describe the evidence underlying the neural profile for language recovery following stroke.

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CHAPTER 18 Neural Substrate of Hearing:  Central Auditory Pathway and the Auditory Cortices Anne D. Olson

Introduction and Learning Objectives

tory cortex located in the temporal lobe on both sides of the brain. Traditionally, the left hemisphere was thought to house the primary auditory cortex where sounds are received for processing biologically important inputs; however, auditory information is processed to some degree by both hemispheres. Information is extensively shared between the hemispheres via transcallosal connections (axon pathways across midline), with eventual relay to higher-order auditory processing regions across the cortex (Dallos & Oertel, 2008). In Chapter 10, you were introduced to the details underlying the function of the inner ear and the early transformations of acoustic energy that must take place to successfully code this input into electrochemical signals understood by the nervous system. As outlined in Chapter 10, acoustic sound pressure variations undergo numerous transduction steps as they are rapidly transferred through the outer, middle, and inner ear organs before reaching the auditory nerve and, ultimately, the central auditory pathway. The central neural systems required to preserve the features of an incoming auditory stimulus event in terms of frequency, intensity, and timing must possess multiple and parallel information processing features, be highly efficient, and be exquisitely accurate in its responsiveness to sound. The goal of this chapter is to familiarize you with the structures and operations of this fascinating central processing system. The elements and systems that lie beyond the cochlea and the auditory nerve are crucial for successful human communication. As such, by the end of this chapter, you should be able to accomplish and perform the following learning objectives:

The ease and speed with which humans perceive auditory information from their environment is quite remarkable. We can locate sounds rapidly and with great accuracy. We can understand conversations even when multiple people are talking in the background, as well as follow the lyrics of our favorite song. While this might seem like its no big deal simply because it happens so effortlessly, the truth could not be more different. For optimal function, our auditory system must operate with a seemingly flawless capacity to an ever-fluctuating stream of acoustic information. The auditory system must respond to extremely short-duration timing cues to process details about where a sound is, what it is, and what that sound means to the individual. You might be asking yourself, “What is required for this function to occur?” The answer is a very sophisticated and complex system that involves multiple stages of transduction and extensive computations across many neural structures. For decades, computer science has been attempting to build an artificial system that is capable of accurate and consistent speech recognition, and while significant strides have been made toward that goal, the outcomes still aren’t as great as we had expected. While many of you may be thinking that Siri or Alexa or any other voice-recognition system does a pretty good job with the task, the speech recognition capabilities of those systems are still far from those capacities possessed by humans, even young children. Try speaking to Siri or Alexa with a foreign accent or a heavy regional dialect, and you will fast discover their “perceptual” limitations. Appreciating the auditory spectral (frequency) and temporal (timing) information of a signal has been shown to be essential for successful speech recognition (Anderson, Parbery-​Clark, White-Schwoch, & Kraus, 2013). All auditory information from the cochlea is processed via the cen­ tral auditory pathway (CAP) and, ultimately, the central auditory representation in the cerebral cortex. The CAP has evolved to accomplish this feat through the emergence of a series of brainstem structures that are interconnected via nerve pathways that arise from both ears. Acoustic inputs begin their travel from the right and left ears, and eventually project to both cerebral hemispheres. A pattern of crossed and uncrossed information transmission streams is present, the significance of which will become more apparent later in this chapter. Ultimately, acoustic inputs reach the audi-

• Describe and identify the major components that comprise the central auditory pathway. • Identify, describe, and trace the connection patterns between CAP structures. • Explain the functional importance of CAP connection patterns to the process of hearing. • Describe and explain the early acoustic processing performed by the cochlear nucleus and its various cell types. • Explain the processes that underlie our ability to localize acoustic information in the environment. • Characterize the acoustic processing operations of each component along the CAP in the brainstem. • Describe and explain the organization and repre­ sentation of acoustic inputs in the primary auditory cortex. 697

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• Identify and describe the secondary and higher-order acoustic processing locations that receive inputs from the primary auditory cortex. • Describe the significance and contribution of efferent inputs in auditory processing.

Central Auditory Pathway Supports Auditory Skills We Use Daily As shown in Table 18–1, the central auditory pathway (CAP) processes auditory information and supports several auditory skills that we use daily. We perform these skills so rapidly and effortlessly that we often do not even realize we are using these abilities. While the external ear is important for receiving sound information, without the CAP, we would not have the ability to process the sounds coming from our environment. The nervous system is the central processor for incoming acoustic information and is responsible for transforming inputs into the cognitive appreciation of sound. For example, if someone were to suddenly bang on a pot, this loud signal would travel through the peripheral and central systems, and typically make us jump with a startle. The auditory startle reflex originates within the CAP (in lower-level brainstem structures) and immediately alerts us to the existence of potentially important acoustic signals. Similarly, whenever

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we turn to search for a sound, we are relying on localization cues that are generated by the CAP structures to tell us where some sound is emanating in space. Other important auditory skills include attending to sounds (such as when someone calls our name) and integrating sound inputs with other parts of the brain, such as visual areas, to create a more complete mental representation of what we just heard (Pickles, 2008). While these skills are accomplished unconsciously, they rely on a complex and integrated system of neural structures and interconnected axon pathways that extend from the cochlea through and beyond the primary receiving area of the cerebral cortex. Thus, the CAP functions to support both simple listening tasks related to sound detection and frequency analysis, as well as higher-level and more abstract listening tasks such as speaker recognition or the selection of a specific sound in a complex auditory environment (Popper & Fay, 1992). Each structure in the system makes a unique contribution to the overall meaning we perceptually place on incoming acoustic inputs. The next time you are sitting in your favorite restaurant or coffee shop, stop a moment and notice the acoustic “view” and sound environment swirling around you. You’ll soon start appreciating the enormity of the task that the CAP must continually perform to allow a person to navigate around the acoustic world successfully. Figures 18–1 and 18‒2 provide you with two illustrations of the neural components that comprise the CAP. Figure 18–1 provides an anatomically accurate depiction of the CAP, while

 TABLE 18–1.   Essential Central Auditory Processing Skills and Examples of How Each Skill Is Used in Everyday Listening Activities Central Auditory Processes

Description of Skill

Listening Activity Example

Sound localization or lateralization

• Determining whether sounds are coming from the right or left, or front or back

• Is the siren coming from the right or the left of the intersection ahead of me?

Auditory discrimination

• Determining differences in loudness and frequency between sounds

• Did the pharmacist say something related to the “pill” or the “bill”?

Auditory pattern recognition

• Identify short versus long sounds or a melody

• Was that my mother’s cell phone ringtone or my friend’s?

Temporal (timing) aspects of hearing

• Identifying differences between two consecutive stimuli • Discriminating differences between phoneme and word length

• Your grandmother says that children speak too quickly these days • Your child can nod his head with the rhythm of a nursery rhyme

Auditory performance with competing signals

• Comprehension of sentences or words when other acoustic signals are present in the opposite or same ear

• Can you hear your friend sitting next to you in a noisy restaurant?

Auditory performance with degraded acoustic signals

• Comprehension of sentences or words when the signal is not clear

• Can you hear recorded information on public transportation?

CHAPTER 18   Neural Substrate of Hearing:  Central Auditory Pathway and the Auditory Cortices

Right

Left

Primary auditory cortex

Acoustic radiations

Medial geniculate nucleus

Rostral midbrain

Inferior colliculus

Caudal midbrain

Nucleus of lateral lemniscus

Lateral lemniscus Dorsal acoustic stria Intermediate acoustic stria Dorsal cochlear nucleus

Rostral pons

Middle pons Superior Olivary Complex (medial & lateral divisions) Medial nu. of trapezoid body Ventral acoustic stria

CN VIII

Rostral medulla Right cochlea

Ventral cochlear nucleus (AVCN & PVCN) Spiral ganglion

 FIGURE 18–1.   Central auditory pathway. Major elements of the central auditory pathway at different representative locations in the brainstem, thalamus, and cerebrum. Only the right central auditory pathway is shown for clarity. Note the binaural representation of sound beginning at the superior olivary complex and continuing through to the auditory cortex.

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Internal capsule

Lateral lemniscus

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Internal capsule

Lateral lemniscus

 FIGURE 18–2.   Simplified schematic illustration of the main elements comprising the central auditory pathway.

Figure 18–2 provides you a quick and easy to use schematic representation of the CAP’s major elements. We will return to these figures time and again during this chapter, so it might be a good idea to bookmark them right now. Before launching into the CAP, let’s first review the characteristics of the acoustic signal. You should already have a sense from previous coursework in speech science that the physical characteristics of an acoustic cue relate to its fre­ quency (low vs. high), intensity (loud vs. soft), and timing (duration or gaps between signals) parameters. When these features combine, as they do during a dynamic conversation, alterations of the speech signal occur across each of these physical domains. During connected speech, the acoustic signal passes rapidly in time. Speech sounds are produced at a rate of approximately four syllables per second in English, translating to about 140 to 160 words per minute. Thus, in a fraction of a second, our CAP is presented with auditory information that must be accurately detected, differentiated, and interpreted. The CAP must determine small timing, intensity, and spectral differences among phonemes (i.e., /v/

vs. /f/) and syllables (i.e., /pat/ vs. /bat/). The rapid fluctuations in the timing, intensity, and frequency of speech sounds are all behaviorally important to appreciate because they reflect factors such as the intent, emotional state, and linguistic competency of the speaker. For example, rapid fluctuations in signal amplitude, what we perceive as changes in “loudness,” form the basis for prosodic features of running speech (Schreiner & Malone, 2015). Rapid fluctuations in frequency (spectral shifts) provide the listener with critical contextual and coarticulatory cues to distinguish among competing sound inputs. For example, the formant fre­ quency of a vowel occurring before a voiced consonant (as in the syllable /ibi/) will contain a formant frequency shift, a necessary and critical spectral acoustic cue for humans to discern voiced consonants and their place of articulation. There are many more examples that can be produced, but suffice it to say that the acoustics of speech are a rich and multidimensional source of information that can provide the listener with cues on a wide range of contextual (location and acoustic environment in which speech is produced) and speaker

CHAPTER 18   Neural Substrate of Hearing:  Central Auditory Pathway and the Auditory Cortices

Box 18–1. Clinical:  An “Acoustic Gap” for Premature Babies Researchers have described the peripheral mammalian ear as being mature at birth, but the brain itself is not. This means that the central auditory pathways (CAP) from the brainstem to the auditory cortex continue to develop together for a longer time period. The amniotic fluid of a mother’s womb provides a safe auditory environment for most of the prebirth development and maturation of the central auditory pathway. However, preterm infants (2000 Hz) use interaural intensity differences (IID) between the ears to localize a source. The differences between the use of these two processes has much to do with the physical nature of sound wavelengths for low versus high frequencies and (believe it or not) the size of a person’s head (Geisler, 1998; Pickles, 2008; Popper & Fay, 1992).

Low-Frequency Sound Localization Is Processed in the MSOC Imagine you are listening to an audio speaker, positioned on your right side that is broadcasting a pure-tone pitch of 225 Hz. The effective sound wavelength of this pitch would be approximately 152 cm. If the diameter of your head is 20 cm, there would a time delay of approximately 0.5 milliseconds for the sound to reach your left ear compared to your right. As illustrated in Figure 18–7B, the sound’s location from your right would result in a short travel distance for the speaker sound to reach the right ear, but a longer distance for the same sound to reach the left ear. This difference would effectively produce a short time delay in receiving the sound across the two ears. Although sound detection may seem instantaneous to you perceptually, there are always delays in the time of arrival for a sound to each ear depending on the origin of its location, except in one condition. If the audio speaker were moved to directly and exactly in front of you, you would then detect no delay in the sound reaching each ear. Sounds that project

CHAPTER 18   Neural Substrate of Hearing:  Central Auditory Pathway and the Auditory Cortices

Interaural Intensity Differences

A.

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Acoustic shadow of head Rt.

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 FIGURE 18–7.   Interaural intensity (IID) and interaural time difference (ITD) are used for sound localization. A. For high-frequency sounds, localization is accomplished though the detection of subtle changes in the intensity of a sound between the near (right ) and far (left ) ear. When a high-frequency sound is broadcast from a speaker positioned to the right of a person, intensity decreases for high-frequency sounds for the far (left ) ear because of the acoustic shadow cast by the listener’s head. Changes in intensity for each ear are schematically shown in the waveforms (bottom). B. For low-frequency sounds, localization is accomplished through the detection of small changes in the time delay for sound arriving at the near (right ) versus the far (left ) ear. For a low-frequency sound broadcast from the right side of a person (red speaker), the sound to the far ear must travel a longer distance and, as such, arrives slightly later in time compared to the arrival of the same sound to the near ear. Changes in timing for each ear are schematically shown in the waveforms (bottom).

from such a location would have no time delay differences because the distance being traveled by the sound to each ear would be identical. So, if a sound’s wavelength is longer than the diameter of your head, you can take advantage of interaural time differences to localize a sound. As noted earlier, the MSOC receives low-frequency inputs from the CN, suggesting that the circuitry required to differentiate time difference between the right and left ear exists within this nucleus. The MSOC circuitry is organized to detect the differences in the time it takes for a sound coming from a given location in space to reach the right versus the left ear (Geisler, 1998; Popper & Fay, 1992).

In the SOC, the MSOC is the larger of the two nuclei in humans and receives most of its input via the ventral acoustic stria (see Figure 18–4). Given that cells in the MSOC receive projections specifically from the large spherical bushy cells via the ventral acoustic stria, it is not surprising that the cells of the MSOC are uniquely sensitive to timing cues for low-frequency inputs. The convergence of neural inputs from both ears within the MSOC permits this structure to analyze the timing characteristics of low-frequency sounds. This is accomplished through a system of neural delay lines that are present within the nucleus. As illustrated in a simplified form in Figure 18–8, delay lines are a system of axon

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 FIGURE 18–8.   Circuitry for detecting interaural time delays (ITDs) in the medial superior olive complex (MSOC). Delay lines to the MSOC make up a system of axons that differ in length as they emerge from each ear. These delay lines converge onto an array of cells in the MSOC (labeled A through F) such that they create an orderly series of coincidence detectors. By taking advantage of the different axon lengths coming from the right (red ) and left (blue) ears, relative to how they converge onto a given cell in the MSOC, coincident arrival of an input onto a given cell in the MSOC provides the localization cue that will be transmitted to higher segments of the CAP. Numbered boxes outline the sequential order of steps for sound localization in the MSOC.

pathways of differing lengths originating from each ear and projecting to the MSOC. These pathways converge upon a collection of cells in the MSOC (labeled A through F) in such a way as to effectively produce a series of coincidence detectors. What is formed is a clever way of mapping interaural time differences by taking advantage of the different axon lengths coming from the right and left ears relative to how they converge onto a given cell in the MSOC. The coincident arrival of inputs onto a given cell in the MSOC is the localization cue that is transmitted to higher segments of the CAP. Using Figure 18–8, let’s walk through the basic steps involved in detecting a low-frequency sound that is coming from your left-hand side. Because the sound reaches the left ear first by some fraction of time compared to the right, signal transmission toward the MSOC from the left begins slightly before signal transmission originating from the right ear. Remember, to detect a location, MSOC cells must be activated by arrival of the left and right ear inputs simultaneously.

In the example shown in Figure 18–8, the axon coming from the left toward the MSOC is longer than the axon coming from the right. As a result, neuron F in the MSOC is ideally positioned to receive the coincident input from both ears. Neuron F is the site of convergence, because even though the sound originated in the left ear first, this input had to travel a longer distance than the signal coming from the right ear. In other words, time delays in sound reaching a given ear are compensated for by the signal having to travel a shorter distance in the far ear compared to the closer ear that first received the sound. This effectively allows for the “calculation” (to use this term loosely) of interaural timing difference between the ears and thus facilitates our localization ability for low-frequency inputs. If you imagine taking the speaker illustrated in Fig­ ure 18–8 and gradually moving it toward the right, what will occur is the following: As you shifted the position of the speaker, neuron E, then D, and then C would receive the coincident input in that order. Coincident input to cells

CHAPTER 18   Neural Substrate of Hearing:  Central Auditory Pathway and the Auditory Cortices

C or D would indicate that the position of the speaker was just about right in front of you. As you continued shifting the speaker toward the right, neuron B and lastly A would be excited by coincident input from the left and right ear. Such a condition would tell the brain that the sound has shifted and is now coming from the far right-hand side. ITD as brief as 10 microseconds, which is shorter than the time it takes to snap your fingers, can be detected by the MSOC and illustrates how truly sophisticated this segment of the auditory system is (Pickles, 2008). Evolution is indeed a marvelous engineer!

High-Frequency Sound Localization Requires Action of the LSOC and MNTB Different from low-frequency inputs, the localization of high frequencies cannot depend on time delay differences, simply because the wavelengths for these types of inputs are much shorter than the diameter of your head. For example, if you are listening to a speaker playing a 10,000 Hz pure tone to your right ear, the wavelength of this sound would be approximately 3.5 cm, much shorter than the distance of approximately 25 to 30 cm between your ears. As such, the auditory system needs to use a different method to determine the location of high-frequency sound inputs. For high-frequency sounds, the auditory system uses interaural intensity differences instead of time delay differences. As illustrated in Figure 18–7A, interaural intensity differences are the result of your head casting what is referred to as an acoustic shadow. An acoustic shadow effectively lowers the intensity of an incoming sound slightly as it crosses over the top and around your head to reach the opposite ear. The difference in sound intensity between the two ears is the cue provided to auditory perceptual centers when localizing high-frequency signals (Pickles, 2008). As was the case for interaural time differences, if there are no detectable changes in sound intensity reaching each ear, the sound must be coming from a point directly in front of you (or directly behind). If intensity differences are large, though, then sound must be coming from one of your two sides. The LSOC receives projections specifically from the small spherical bushy cells via the ventral acoustic stria originating from the AVCN. As such, it is not surprising that the cells of the LSOC are uniquely sensitive to cues for high-frequency inputs because small spherical bushy cells themselves receive auditory nerve inputs from the high-frequency range of the basilar membrane. This pattern of input suggests that the circuitry required to differentiate interaural intensity differences for high-frequency inputs exists within the LSOC (Geisler, 1998; Popper & Fay, 1992). Aside from the LSOC, the MNTB also participates in the process of high-frequency sound localization. The MNTB receives inputs from the globular bushy cells of the AVCN. Like the small spherical bushy cells, globular cells also receive inputs from auditory nerve fibers transmitting

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high-frequency signals from the cochlea. The MNTB is connected to the LSOC via interneurons and operates as an inhibitory influence on the LSOC. Now that we have a good appreciation of the key players in localizing high-frequency sounds, let’s use Figure 18–9 to review the steps involved in this process. Consider a condition where a high-frequency sound is delivered to the left handside of the head. The input transduced by the left cochlea is transmitted to the ipsilateral LSOC (green) and the contralateral MNTB (blue), where it provides excitatory drive to these different cell populations (see red pathway). Excitation of the contralateral MNTB by the left CN functionally operates to inhibit the contralateral LSOC (remember that activation of MNTB interneurons produces inhibition upon its target). In other words, what is accomplished overall through this circuitry is an interplay of inhibitory versus excitatory effects between the left and right LSOC. Sounds that arise from the left (as shown in Figure 18–9) generate greater net excitation to the ipsilateral LSOC but cause a greater net inhibition of the contralateral LSOC through the connection of the left CN to the contralateral MNTB. Thus, differences in the location of a high-frequency sound source create changes in the relative balance of excitatory versus inhibitory activity from within the LSOCs bilaterally (Pickles, 2008).

SOC Allows for the Integration of Sounds From Both Ears Even though the SOC is best appreciated for localization, other functional benefits also arise out of the binaural inputs directed to this structure. In addition to localization, a key benefit of binaural hearing is that persons with normal hearing and a healthy CAP up through the SOC can fuse or merge information from both ears. This idea has been termed binaural fusion and relates to how you integrate auditory information from both ears. For example, if you’re in a line for coffee and you’re talking on the phone in one ear and the barista is talking toward your other ear at the same time, how does your brain interpret these conflicting auditory inputs? This scenario is termed dichotic listening and is defined as the ability to take information from both ears and attend to one input, while inhibiting the other (Hugdahl & Westerhausen, 2016). If you heard “meet me at four fifteen this afternoon” in the right ear from your friend and “that’ll be three forty-five” in the left ear from the barista for your coffee, you would need to make sure that you separated these two numbers accurately and didn’t pay $4.15 for the coffee and meet your friend at 3:45 p.m. The ability to start separating and integrating this type of information begins at the SOC. But this task is more difficult than it sounds (no pun intended). In fact, many children with auditory processing difficulties present with deficits in dichotic listening tasks. Because of the significant convergence of neural information from both ears, the SOC contributes to our ability to integrate such information. Since the SOC is the first structure receiving bilateral inputs, this suggests

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Lt. ear stimulus also inhibits right LSOC via 2 MNTB interneuron

Stronger stimulus to left ear excites left LSOC 1

xcitation Net excitation to brain

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Excitation from left ear is greater than inhibition from right ear, resulting in overall excitation to brain on left side 3

Inhibition from left ear is greater than excitation from right ear, resulting in overall inhibition on 4 right side and no signal to brain

 FIGURE 18–9.   Circuitry for detecting interaural intensity difference (IID) in the lateral superior olive complex (LSOC) and medial nucleus of the trapezoid body (MNTB). With a sound presented to the left side, the stronger stimulus from the left cochlea will excite the left LSOC (red pathway). Simultaneously, the left ear signals (red pathway) from the cochlear nucleus (CN) cross midline to also inhibit the right LSOC via MNTB inhibitory interneuron activity. Excitation from the left ear is greater than the inhibition stemming from the right ear for the same sound, resulting in overall greater excitation to the auditory cortex from the left LSOC. Numbered boxes outline the sequential order of steps for sound localization in the LSOC. Identifying colors for nuclei: LSOC = green; MNTB = blue; CN = yellow and red.

that the SOC is the point where we begin extracting and integrating auditory information to enhance our auditory skills. Auditory skills become increasingly refined with each processing step along the CAP as different populations of neurons are tasked with integrating acoustic information in different ways (Hugdahl & Westerhausen, 2016). So, the next time you encounter a child in a classroom with a unilateral hearing loss or with an auditory processing disorder, don’t underestimate the difficulties the child may be encountering in school. The child may very well be able to hear some sounds, but unable to understand connected speech or follow multistep directions.

Lateral Lemniscus:   Anatomy and Physiology The lateral lemniscus (LL) is often characterized as a ribbon of axons (lemniscus is Latin for “ribbon”) spanning through the pons and midbrain (see Figure 18–1). It is the primary ascending auditory pathway connecting lower CAP struc-

tures with the midbrain. Specifically, it connects the SOC with the inferior colliculus and is composed of both afferent and efferent nerve fibers. Two important nuclei are part of this pathway: the ventral nucleus of the lateral lemniscus (VNLL) and the dorsal nucleus of the lateral lemniscus (DNLL). As the names suggest, signals transmitted through the ventral acoustic stria (which pass through the MSOC described earlier) travel through the VNLL, while signals from the dorsal and intermediate acoustic stria (which pass through the LSOC and MNTB) continue ascending via the DNLL. Thus, the processing streams that were established at the level of the CN continue to exist so that timing information is preserved within the VNLL (ventral stream) and intensity/spectral information is preserved within the DNLL (dorsal stream). The take-home point to appreciate is that the integrity of the auditory signal continues to be preserved within the LL as it travels from the lower brainstem to the midbrain where auditory inputs synapse onto the next obligatory relay along the CAP, the inferior colliculus (Haines, 2013; Pickles, 2008).

CHAPTER 18   Neural Substrate of Hearing:  Central Auditory Pathway and the Auditory Cortices

n

Go Big BLUE

vat io

The inferior colliculus (IC) is one of the most prominent structures in the midbrain and represents the third obligatory synapse relay station of the CAP (see Figures 18–1 and 18–2). The IC is easily recognizable as the lower pair of mound-like projections on the dorsal surface (tectum) of the midbrain (see Figure 4–31). The IC has several divisions, but it is the central nucleus that is of greatest interest to us. The central nucleus of the IC receives input from essentially all lower CAP structures, including the CN, SOC, DNLL, and VNLL. The central nucleus of the IC is regarded as a laminar nucleus, which means simply that it is comprised of layers of cells (like a stack of pancakes) with different inputs and outputs. The cell’s layers differ in their activity, with some cells responding in a graded manner to specific frequencies, some firing spontaneously yet inhibited with sound input, and yet others that are able to track a moving sound source (Oertel & Wang, 2021). The layers of the IC central nucleus are tonotopically organized from low to high frequency in the dorsal to ventral direction. All cells within a given lamina (or layer) have similar best characteristic frequencies and are tuned more broadly spectrally (they respond to a wider range of frequencies) than neurons in lower segments of the CAP. In addition, IC cells are responsive to interaural time (ITD) and intensity differences (IID), and presumably aid in the process of sound localization. The IC is a main site of convergence for the ventral (timing) and dorsal (complex stimuli) streams mentioned earlier. This suggests that these streams converge in the IC, resulting in more complex processing and greater abstraction of acoustic information from lower levels of the CAP (Geisler, 1998; Pickles, 2008; Popper & Fay, 1992). Consider this dilemma for a minute: Three-dimensional space is not encoded in any way by the tonotopic arrangement of the basilar membrane (BM), or by the auditory afferent fibers that synapse onto the hair cells in the organ of Corti. In fact, you could argue that the BM is just a flat, two-dimensional sheet of tissue that maps frequencies from high to low along its base to apical length. Yet, we are quite adept at localizing sound in three-dimensional space. We can tell the difference between a sound played directly in front of us a meter away from our heads, compared to the same sound played directly in front of us, but this time 10 meters away from our ears. How is this possible? How does a two-dimensional representation of frequency on the BM become transformed into a signal that conveys the nature of our three-dimensional auditory space? The IC appears to be the location in the CAP that integrates auditory inputs from lower levels of the brainstem to synthesize our perception of auditory space. What emerges from the binaural integration of lower-​ level inputs into the IC is a calculated representation of the physical features of auditory space. Experiments in owls, whose echolocation skills to find prey in complex environ-

ments are legendary, demonstrate that IC neurons are active to sounds emanating from a preferred vertical (elevation) as well as horizontal (azimuth) location is space (Figure 18–10). The IC heavily processes and extracts critical information from sound inputs, including frequency features, timing, and intensity. The timing (via the ventral stream) and complex inputs related to frequency and intensity changes (via the dorsal stream) converge onto the IC from both the MSOC (ITD processing) and the LSOC (IID processing). This emphasizes the IC’s additional contribution to the processing of localization cues and its integral role in our binaural abilities (Dallos & Oertel, 2008; Elemans et al., 2015; Popper & Fay, 1992). Many lesion studies in animals have shown that when the IC on one side of the head is experimentally injured (for example, on the right side), the animal upon recovery is unable to localize sounds coming from the opposite side (Celesia, 2015). However, the animal is still able to localize sounds coming from the right side, because the ipsilateral pathway to the IC is still intact. These findings underscore the importance of the IC to our complex sound localization abilities. Frequency preservation in the IC has also been studied using electrophysiological approaches in animal models. Using

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Inferior Colliculus:   Anatomy and Physiology

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Az i m

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 FIGURE 18–10.  Cells of the inferior colliculus respond to sounds that come from a preferred vertical position (elevation) as well as a preferred horizontal (azimuth) location of auditory space.

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microelectrodes inserted into the central nucleus of the IC, tonotopic maps have been discovered in both rat and cat models. Together, these studies reveal a dorsal to ventral gradient of frequency mapping such that lower characteristic frequencies (CFs) are obtained from dorsal parts of the IC and higher CFs are obtained more ventrally located zones (Dallos & Oertel, 2008; Popper & Fay, 1992). More current noninvasive imaging techniques in humans show similar findings in relation to the tonotopic organization of the IC. It’s noteworthy that such tonotopic patterns are intact only if cochlear function is normal. Experiments in a variety of mammalian species have demonstrated that IC neurons are tuned to respond to frequency-modulated sounds or to sounds of certain durations (Dallos & Oertel, 2008; Popper & Fay, 1992). These acoustic factors are typical of environmental sounds that hold biological importance to animals (helping them find a mate, escape from predators, or communicate among their group). Unilateral cochlear ablation (purposeful removal or lesioning of the cochlea) in many types of mammals will result in a disruption of the frequency mapping described earlier for the IC. In other words, the retention of frequency information at the level of the cochlea and through to the IC will be important for later sound pattern identification in the auditory cortex. As communication sciences and disorders students, these two IC cell response features should jump out at you for one critical reason . . . both factors also underlie the acoustic properties of speech sounds. Thus, it appears that early stages of speech perception may occur within the IC even before acoustic inputs reach the auditory cortex. In terms of understanding speech, it is important for humans to have a system that preserves spectral (frequency-based) information so that we can make accurate distinctions between sounds. Lastly, spectral (frequency) cues from the dorsal cochlear nucleus project directly to the IC and are known to combine with somatosensory inputs from lower brainstem nuclei. Some have suggested that the IC may be part of a mechanism that suppresses or filters out self-generated sounds related to our own chewing, breathing, and vocalization though the integration of somatosensory and auditory inputs in the IC. Such a mechanism would presumably help us distinguish between sounds people commonly make and the less regular environmental sounds that could potentially be more important. Think of this as a mechanism that helps us pay attention to sounds with behavioral value and prevents us from wasting time or resources on auditory inputs related to our own actions. In other words, if we were walking down a busy street while chewing some bubble gum, paying attention to the environmental sounds around us would be much more important than attending to the snapping and popping sounds of our gum chewing.

Medial Geniculate Body:   Anatomy and Physiology The medial geniculate body (MGB) is the fourth and last obligatory subcortical relay station in the CAP (see Figures

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18–1 and 18–2). The word geniculate comes from the root word “genuflect,” which means to kneel (I used to do this a lot during my Catholic school days back in New Jersey). To early anatomists, the medial geniculate looked like a little “bent knee,” hence the use of this term. The MGB is located on the posterior and ventral part of the thalamus (see Figure 6–2 for its location on the thalamus). The MGB serves as the main thalamic relay between the IC and the auditory cortex. Much like the IC, the MGB is a laminar structure with a tonotopically arranged organization that mediates the transmission of intensity, frequency, and the appreciation of auditory space to the primary auditory cortex (Lee, 2013; Oertel & Wang, 2021). Projection neurons housed in the MGB carry acoustic sensory information directly to the auditory cortex in the superior temporal gyrus via the thalamic auditory radiations (see Figure 7‒7 for its location). The auditory radiations (also known as the inferior thalamic radiations) project through the internal capsule to the auditory cortex in the temporal lobe. The term “radiations” is used because this fiber tract fans out from the medial geniculate to different portions of the auditory cortex. This fan-like projection is the last link of the CAP pathway that first originated way back in the cochlea. Thus, the MGB, through its extensive projections, is actively involved in controlling the flow of information to the auditory cortex. The MGB also receives heavy descending projections from the auditory cortex itself, suggesting a regulatory or “gating” role of the auditory cortex for tuning the activity of this nucleus. The MGB is not a uniform structure, but rather a collection of smaller subnuclei grouped together. While there is a prominent auditory nucleus (the ventral division) in the MGB, there are also other recognizable divisions (dorsal and medial) that receive both auditory and nonauditory inputs. This organization suggests that a key function of the MGB may be to integrate auditory signals with other sensory systems such as vision and touch (Bartlett, 2013; Lee, 2013). For hearing, the ventral and dorsal segments appear to play the most significant roles. Projections from the ventral division of the MGB travel to the primary auditory cortex (A1) while projections from the dorsal division project to more diffuse areas such as the belt and the auditory association fields (to be discussed in a later section). Cell types in the MGB are like those previously described (i.e., bushy and stellate), with each type of cell responding differently to a stimulus; some respond to the onset of a sound, while others to the offset, and still others remaining active for the duration of an input. Tonotopy is primarily observed in the ventral division of the MGB as it is comprised of mostly auditory information. The ventral division projects to core regions of the auditory cortex, conveying timing and frequency-specific properties of sound inputs (Lee, 2013). Interesting findings continue to emerge about the MGB, particularly concerning how the dorsal division of the MGB is uniquely responsive to fluctuations in amplitude of a signal, which is a key characteristic of a complex signal such

CHAPTER 18   Neural Substrate of Hearing:  Central Auditory Pathway and the Auditory Cortices

as connected speech. Neurons in this division lack the frequency specificity of the ventral division and, as mentioned earlier, also project to different subareas of the auditory cortex. Together, these two characteristics indicate that the dorsal division of the MGB might play a role in human-specific auditory sound processing supportive of speech and language (Bartlett, 2013). MGB neurons in all divisions appear to preserve interaural timing and intensity differences first analyzed by the SOC. These inputs are widely dispersed to all auditory areas of the cerebral cortex, attesting to the importance of sound localization as we analyze auditory inputs for meaningful information that can be applied to our own perception of environmental sounds. The MGB receives almost exclusive input from the IC, with some lesser projections from lower CAP levels. The MGB is the first location in the CAP where neurons are activated by specific combinations of frequencies. Experiments in the echolocating bat suggest that the tonotopy of lower levels of the CAP is harnessed by MGB neurons to respond to sound patterns with unique spectral signatures (different combinations of frequencies). In addition, MGB neurons are responsive to different time intervals between the presentation of two different frequencies. Once more, echolocating bat experiments have demonstrated that these mammals assess distance to a target by calculating the time delay between the presentations of calls as the animal homes in on prey. Recordings from MGB neurons demonstrate a response preference to specific delays. When the entire population of time-sensitive neurons is considered, one can readily see that a whole series of delays is encoded through different neuron activity levels in the MGB. From the perspective of speech, formants are basically frequency patterns that encode and distinguish phonemes from one another. Furthermore, the ability to detect temporally related coarticulatory factors is critical for the segmentation (separation of a stream of sounds into meaningful units) and perception of running speech. Together, MGB spectral and temporal response characteristics suggest that these neurons may play an important role in facilitating speech perception (Pickles, 2008; Popper & Fay, 1992).

Auditory Cortical Areas We have finally reached the top of the ladder! The temporal lobe, distinctly separated from the frontal and parietal lobes by the lateral sulcus (also known as the Sylvian fissure), houses the auditory cortex (Figures 18–1 and 18–11). The auditory cortex, also known in older literature as Heschl’s gyrus, is located on the surface of the superior temporal gyrus (STG). The auditory cortex is divided into three major areas called the primary (A1), secondary (A2), and auditory association cortices (Haines, 2013). There is considerable variation in the boundaries of the primary, secondary, and auditory asso-

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ciation areas across species, so findings from animal studies contribute only to our partial understanding of the auditory cortex in humans. The primary difference is that the human auditory tracts are much longer than those of smaller mammals. So, while we can describe much of how the auditory cortex codes incoming information, our understanding of the auditory cortex in the human remains incomplete. That being said, there is an overabundance of data highlighting how auditory-related cortical structures connect with one another, thus setting the stage for us to derive meaning from sound.

The Primary Auditory Cortex The primary auditory cortex (A1) is often referred to as Brod­ mann’s area 41 (BA 41) based on the cytoarchitectural cortical mapping by Brodmann in the 1900s (see Figure 6–14). As illustrated in Figure 18–11A and B, the primary auditory cortex (BA 41) is located posteriorly on the dorsal surface of the superior temporal gyrus. A1 is considered the most sensitive cortical structure to auditory inputs. This helps explain why some researchers call this cerebral area the core auditory region (see rainbow-colored zones highlighted in Fig­ ure 18–11C) (Hackett, 2015). Given that the core is buried within the folds of the superior temporal gyrus, it cannot be viewed fully without a little manipulation. To observe the entirety of A1, you have to retract the frontal and parietal operculum upward to reveal the dorsal surface of the superior temporal gyrus, as shown in Figure 18–11A, or cut the cerebrum horizontally along the plane of the lateral sulcus, as shown in Figure 18–11B. Many of our neurophysiological descriptions of the auditory cortex come from studies in the cat, macaque monkey, and other mammalian models using microelectrodes to record A1 cell behavior in response to auditory stimuli (Dallos & Oertel, 2008; Geisler, 1998). These studies have shown that most of the projections into A1 originate from the ipsilateral ventral MGB and specifically synapse onto neurons in layer IV of the auditory cortex (see Figure 6–13 for cortical layers example). The primary auditory cortex possesses a tonotopic frequency representation of the cochlea’s basilar membrane (see Figure 18–11 for a visual depiction of this arrangement) (Hackett, 2015). Auditory cortical cells also possess very sharp tuning curves, indicating that different neurons in A1 respond best to specific characteristic frequencies (Schnupp et al., 2011). Auditory neurons appear to respond to stimulation from the ears in two different general patterns. In the first pattern, auditory cortical neurons are excited by inputs from both ears. These neurons are referred to as EE auditory neu­ rons. In the second pattern, cells are excited by one ear, but inhibited by the opposite. These cells are called EI auditory neurons. Alternating bands of EE versus EI cells within the auditory cortex have been found. Besides frequency, many other acoustic features are also mapped onto the activation of A1 cortical cells, including loudness changes, frequency

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 FIGURE 18–11.   Auditory cortical areas and organization of the auditory cortex. A. The frontal and parietal lobes are shown retracted from the temporal lobe to uncover the dorsal surface of the superior temporal gyrus (STG). In this perspective, the insula can be seen in the background. The primary auditory cortex (blue shading), secondary auditory cortex (red shading), and Wernicke’s area (green shading) are located on the posterior aspect and dorsal surface of the STG. B. Sectioning the cerebrum axially through the lateral sulcus (as shown by the line in A) allows a clear view of the dorsal surfaces of the STG, bilaterally. In this perspective, the primary auditory cortex (BA 41) can be easily seen. Also visible are the secondary auditory cortex and a segment of Wernicke’s area. C. The primary auditory cortex is shown in isolation. The sensitivity of A1 cells to frequency in the core region is represented by the rainbow coloring pattern. Cells in the A1 core region are tonotopically organized (see rainbow key) and possess very sharp tuning curves. The A1 core is surrounded by the second auditory cortex (A2). This region is referred to as the belt area. The parabelt region (adjacent to the belt) is considered an auditory association area and receives inputs from visual and somatosensory systems. Orientation legend signifies rostral, caudal, lateral, and medial directions.

modulation, and bandwidth characteristics of an input (Kaas, Hackett, & Tramo, 1999; Knudsen & Konishi, 1978; Oertel & Wang, 2021). As is evident by our brief review, it appears that auditory cortical neurons are processing many different aspects of an acoustic input simultaneously. For example, any given auditory cortical cell will process information related to the location of a sound, its frequency, intensity, and so forth. The ability to process multiple functional characteristics of a given auditory input allows for the auditory cortex to maximize its

processing power (Oertel & Wang, 2021). This organization also provides the system with a mechanism to more efficiently combine a wide range of auditory features to generate a unified perception of sound. Before moving on, it is important to also appreciate that A1, in addition to the processing described above, adaptively regulates and influences the activity of subcortical structures that are involved in the transmission of auditory signals to itself. The top-down control between A1 and auditory-related subcortical regions is believed to allow the cortex to

CHAPTER 18   Neural Substrate of Hearing:  Central Auditory Pathway and the Auditory Cortices

adaptively alter the nature and quality of incoming signals by influencing the processing occurring in lower areas of the CAP (Oertel & Wang, 2021). In other words, A1 is not a passive player that simply waits for subcortical areas to deliver information. A1 actively seeks out and dynamically adjusts or “tunes” the quality of the incoming input streams to refine the perceptual processing that it itself can perform. The capacity of the brain to adaptively regulate itself never ceases to amaze me.

Deeper Insights Into the Properties of the Primary Auditory Cortex As mentioned earlier, frequency mapping exists within the primary auditory cortex, with pronounced tonotopic patterning found on the cortical surface of the core region of A1. Unlike in other CAP structures, the term fields is used to describe cortical areas that are responsive to specific frequencies. These fields are also referred to as frequency strips. The multicolored core depicted in Figure 18–11C illustrates the tonotopic organization of these fields in A1. This frequency representational pattern in the core correlates with the same place organization observed at the level of the basilar membrane in the cochlea. When viewing the STG along the cortical surface of A1, neurons that respond maximally to low frequencies are located toward the poles of the core, while higher frequencies are generally localized more medially (Hackett, 2015). The normal tonotopic pattern of the core is significantly disrupted in persons with hearing loss, with neurons showing broader rather than sharp tuning curve responses. Tonotopic pattern disruption is very likely the result of changes to cortical processing related to prolonged auditory deprivation. This may help to explain why a person with a hearing loss will have great difficulty discriminating sounds and understanding speech. Several studies have examined the response properties of different layers of the primary auditory cortex in anesthetized cats by recording neuron activity during the presentation of pure-tone stimuli of varying frequencies. Results show that all six layers of the auditory cortex within a radial plane (a plane that is oriented 90 degrees relative to the cortical surface) of tissue have the same characteristic frequencies (Hackett, 2015; Kaas et al., 1999). Thus, the auditory core not only displays tonotopic organization, but also possesses a form of columnar organization whereby cells in a radially oriented column receive inputs from similar sources. We have encountered this type of cortical columnar organization in the past within the somatosensory and visual systems, suggesting that columnar organization of the cerebral cortex is a common structural theme for supporting and facilitating information processing in the brain. Recent experiments suggest that A1 activity is far richer than simply that related to processing frequency information. Given that the ventral stream of the CAP has significant projections into A1, it should not be surprising that A1 is also essential for sound localization. In cats, when both auditory

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cortices are experimentally removed, no sound localization abilities are observed even though subcortical structures remain intact. Interestingly, even with unilateral A1 lesions, cats still have significant difficulty with localization tasks, suggesting that the integrity and health of A1 bilaterally is critical for sound localization. Timing information is also retained within the auditory cortex through phase-locking, but it appears that the auditory cortex also uses an additional mechanism for representing the timing of sounds that go beyond the ability of phase-locking processes. In this different approach, the auditory cortex uses the response of populations of neurons to help distinguish between slowly and rapidly time-varying sounds. This approach relies upon two forms of neural coding, one that is based on the timing of action potentials from one moment to the next (a temporal coding approach), and a second that is based on the firing rate of the cells in the population (a rate coding approach) (Oertel & Wang, 2021). Together, all these mechanisms suggest that the timing characteristics of acoustic cues used for determining factors such as voice onset time and the rapid coarticulatory dynamics of connected speech are preserved in A1 for perceptual use. Lastly, the representation of intensity is not as clearly understood as frequency processing is in A1. However, observations that some groups of neurons respond preferentially to certain static intensity levels have been made. Other groups of A1 cells appear to increase their firing rate more dynamically with increasing intensities. This suggests that both static and dynamic mechanisms are likely present for the encoding of intensity at the level of the auditory cortex. These mechanisms suggest that intensity encoding is also achieved by the activity of populations of neurons rather than single cells (Micheyl, Schrater, & Oxenham, 2013).

Role of the Auditory Cortex in Speech and Vocalization When we are speaking to someone, there is not just one person listening. In fact, there are always two . . . the person you are speaking to and YOU! When we produce speech, we simultaneously hear our own speech during its production. The vexing problem that the auditory system has in this situation, though, is trying to figure out if the sound being received by the cortex is coming from you (self-generated) or from an outside source. Without a means of suppressing the sounds of our own speech, we would have a difficult time staying perceptually sensitive to externally generated sounds that may be carrying important information for our current situation. Evidence from both human subjects and nonhuman participants has demonstrated that auditory cortical cell activity is actively suppressed or gated by our own vocalizations (Eliades & Wang, 2003; Houde & Chang, 2015; Oertel & Wang, 2021). The auditory cortical cell suppression has been observed to start a few hundred milliseconds before voicing begins, indicating that this suppression must be coming from

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within the brain itself and not from an external source (Eliades & Wang, 2003; Houde & Chang, 2015). In humans, this suppression appears to originate within speech production regions of the frontal lobe, including the inferior frontal gyrus (Broca’s area), premotor cortex, and primary motor cortex. The suppression of auditory cortical cells is likely driven through the mechanism of corollary discharge (or efference copy) via white matter pathways interlinking these regions (see Chapter 15 for discussion on corollary discharge and its use during behavior). Suppressing our self-generated auditory inputs during communication helps us maintain the integrity of speech-related feedback to learn new languages and maintain our current speech production skills.

The Secondary Auditory Cortex The secondary auditory cortex (A2) has been described as a region that encircles the core of A1 and is sometimes referred to as the belt zone (see Figure 18–11C) (Kaas et al., 1999). The belt zone is highly responsive to auditory stimuli, as it has several interconnections with A1. However, its responses to auditory stimuli are not as robust or strong as those observed Box 18–3. Further Interest: Can I Hear Without an Auditory Cortex? W. D. Neff and colleagues in the late 1950s at the University of Chicago removed the auditory cortices of cats and reevaluated auditory skills that the cats had previously learned (Diamond & Neff, 1957). After ablations (cortical removal), the cats could still perform several auditory processing skills such as responding to the onset of a sound, or changes in location, frequency, or intensity of a sound. These classic experiments showed how important the auditory brainstem is for processing sound for simple auditory skills related to tones. Apparently, an auditory cortex may not be always required for some simple forms of sound processing in some species. However, humans as a species do need an intact auditory cortex, especially when processing the more complex speech signals we use and rely on during conversation. So, the next time a friend provides a verbal description for you about an event that occurred over the weekend, remember that you are engaging your auditory brainstem and cortical areas to create a mental image from that verbal information. Without your auditory cortex, you might not get the whole auditory picture! Resource Diamond, I., & Neff, W. D. (1957). Ablation of temporal cortex and discrimination of auditory temporal patterns. Journal of Neurophysiology, 20(3), 300–315.

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in the core. A2 is extensively connected via axon pathways to frontal and parietal lobes and ventral regions of the temporal lobe. Tuning curves obtained from A2 are much broader and not as well defined or as sharp as those obtained from A1. This responsiveness suggests that the belt may have some role in processing more complex auditory inputs that arise from naturalistic environments and behaviors (Kaas et al., 1999). The broader responsiveness of belt neurons may be related to the preferred response of these cells to more harmonically complex tones (like voices or sounds in nature) rather than pure tones (single-frequency pitches). Cortical areas surrounding A1 appear to be active during pitch perception both for musical purposes and more critically for vocalization and speech (Hickok & Poeppel, 2015). Pitch perception may play an important role in discriminating multiple speech sounds that possess similar signal frequency qualities and that are produced from the same location in space.

The Auditory Association Areas It is important to underscore that while A1 may be the official end of the CAP, it is certainly not the end of auditory processing. Besides A1 and A2 for that matter, numerous connections to other areas of the brain are essential in our receptive processing of language and salient environmental sounds. The auditory association areas are a diverse set of structures connected to A1 and A2 and are located within the temporal lobe, extending into the most ventral regions of the inferior parietal lobule (Smiley & Falchier, 2009). One such area is referred to as the parabelt region, a zone of tissue adjacent to the belt region around the core (see Figure 18–11C). It is the largest among the auditory cortical areas described thus far. It receives direct projections from the belt, but not from the core. The parabelt region also receives inputs from visual and somatosensory systems, suggesting that the parabelt operates to integrate auditory information with other incoming sensations. Another key structure in the auditory association area is the planum temporale, an area of tissue located directly posterior to A1 on the surface of the superior temporal gyrus and folded within the lateral sulcus (see Figure 18–11A and B). The planum temporale’s connectivity with auditory memory and language areas implies that its activity is important for word recognition and assigning word meaning. Furthermore, the planum temporale extends into the inferior parietal lobe, suggesting a role for this area in the conversion of lexical and graphical representations of language during reading and writing (Hickok & Poeppel, 2004). The planum temporale is often viewed as the central region of the broader zone classically defined as Wernicke’s area (see green region in Figure 18–11). Patients with lesions to Wernicke’s area often present with disturbances in auditory comprehension, yet they have relatively fluent speech production that is characterized by jargon and paraphasias (Hickok & Poeppel, 2015). This area has long been recognized as a key structure within the perisylvian language zone of the left hemisphere (see

CHAPTER 18   Neural Substrate of Hearing:  Central Auditory Pathway and the Auditory Cortices

Chapters 6 and 17 for more in-depth details about the role of Wernicke’s areas in receptive language processing). As shown in Table 18–4, auditory association areas differ along several other dimensions compared to A1 or A2, including input projections, the presence of tonotopy, and several response characteristics. The key difference upon which other distinctions are based is the source of input into each auditory processing zone. The ventral portion of the MGB projects to A1, whereas the dorsal division of the MGB projects to A2 and the auditory association areas. This projection pattern continues the overall theme of ventral (timing) versus dorsal (intensity and spectral) auditory processing streams that were first introduced at the cochlear nucleus. When comparing the general operation of A1 versus A2 and the

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association areas, what we notice is that A1 has sharply tuned and well-defined frequency representations, responds best to pure-tone signals, and is unimodal in its operation. A2 as well as the auditory association areas, on the other hand, are more broadly tuned, process more complex signals, and perform integrative operations with other sensory modalities (Kaas et al., 1999; Smiley & Falchier, 2009). Thus, the auditory association areas appear to be inextricably linked with other areas of the brain. These connections are thought to expand our auditory perceptual skills beyond simple auditory detection to higher forms of processing such as discrimination, identification, abstraction, and assignment of meaning to auditory cues. Damage to these areas will undoubtedly result in complex changes related to speech and language abilities.

Box 18–4. Further Interest:  “What” and “Where” Pathways in the Auditory System The use of imaging technology has provided greater detail for identifying what an object is and where it is located. For example, in visual systems, researchers have widely explored this idea since the mid-1980s to explain how the visual system separates relevant incoming sensory information. Essentially, spatial and object visual information was found to be processed in two anatomically discrete pathways or streams: the ventral stream, or “what” pathway, that projects to the middle and inferior temporal cortex, and the dorsal stream, or “where” pathway, that projects to the posterior parietal cortex. A similar processing scheme has been proposed for the auditory system such that directional information (where) and spatial information (what) are also processed in two discrete areas or streams (Hickok & Poeppel, 2004). The ventral auditory pathway is thought to facilitate our ability to identify sounds, while the dorsal pathway is believed to

support our ability to locate sounds. Both pathways arise from the superior temporal gyrus (STG) and project to distinct cortical areas. The auditory “where” pathway runs dorsally and passes through portions of the parietal lobe with eventual projection of information into the prefrontal cortex. The auditory “what” pathway projects ventrally (and laterally) from the temporal lobe to inferior frontal cortical areas. Interestingly, the dorsal stream is surprisingly activated earlier than the ventral stream, which may explain why we can often locate a sound well before we know exactly what that sound is. Resource Hickok, G., & Poeppel, D. (2004). Dorsal and ventral streams: A framework for understanding aspects of the functional anatomy of language. Cognition, 92(1–2), 67–99.

 TABLE 18–4.   Key Characteristics for Different Segments of the Auditory Cortical Areas A1

A2 and Auditory Association Areas

Input projections

Ventral MGB (timing)

Dorsal MGB (spectral/intensity)

Tonotopic organization

Yes

Some

Tuning curve response

Sharp and narrowly tuned

Broadly tuned

Stimulus response

Responds best to pure tone signals

Responds best to complex signals

Sensory response

Responds only to auditory stimulation

Responds to auditory, touch, and vision signals

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Another example of the complexity of auditory association area connectivity is the recognition that these regions are arranged into dedicated processing systems. Like the visual system, the cortical auditory processing areas appear to possess “what” and “where” information processing streams (see Figure 6–18) (Hickok & Poeppel, 2004). Although the details of these processing streams are still under investigation and debated, it appears as if a ventral stream (what is heard ), which passes through the temporal lobe to prefrontal cortical areas, may be involved in identifying auditory objects through spectral analysis. A dorsal stream (where the sound is located) obtains input from A1 and routes its processing through the inferior parietal lobule (includes the supramarginal and angular gyri), eventually reaching prefrontal cortical areas as well. At a minimum, the dorsal stream is likely specialized to locate sound sources, detect sound motion, and segregate sources of sound from one another (Romanski & Averback, 2009).

Neuroimaging of the Human Auditory Cortex Reveals Distinct Features Many technological and scientific advances have occurred in the past decade that allow for the direct examination of the central auditory system in humans. Brain imaging techniques such as functional magnetic resonance imaging (fMRI) require subjects to be placed in a machine that uses powerful magnetic fields to examine changes in neuron activity in the brain. There are several benefits of this method compared to the use of animal models. First, by examining human subjects with intact auditory systems, more precise inferences can be made about the human auditory cortex rather than trying to infer from simpler animal systems. Second, subjects can be engaged in the precise activity of interest, such as connected speech, and not just listening to simpler stimuli such as tones, clicks, or isolated phonemes. Lastly, imaging methods allow us to demonstrate cortical responses over longer periods of time so that the hierarchical steps involved in speech comprehension can be observed. In humans, imaging studies have confirmed that A1 is tonotopically organized as in other mammals (Brewer & Barton, 2016). Unique to humans, the auditory cortex of the left hemisphere has been reported to be up to 30% greater in volume compared to the homologous region on the right hemisphere. This increased size is consistent with the known left hemispheric dominance for speech and language. It is quite remarkable that several fMRI studies have confirmed what decades of animal electrophysiological research have suggested ​ — that sound comprehension involves activation among several cortical areas beginning in A1 with spectral (frequency) features of speech arising from the core, followed by spectral and articulation features of speech sounds coming from other areas of the superior temporal gyrus. Thus, A1 appears most sensitive to pure tones, while the belt and parabelt regions are more sensitive to more complex auditory stimuli such as speech.

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Imaging studies in humans have also demonstrated that projections from the primary auditory cortex are diffuse across wide expanses of the cerebral cortex. Such interconnections suggest that the auditory cortex interacts with virtually all lobes of the brain so that auditory information can be integrated with other sensory modalities. More recent imaging studies have shown that the left and right auditory cortices respond differentially to auditory stimuli, with the left showing more vigorous response for rapidly fluctuating sounds (i.e., pure tones or tone bursts), and the right responding preferentially to sustained complex sounds. These findings highlight how important both hemispheres are in terms of speech perception (Hugdahl & Westerhausen, 2016). This is logical given the dense number of circuits that are involved in speech and language throughout all of the cerebral cortex. Thus, while speech perception starts in the auditory cortex, much of the brain is involved in integrating this information with other sensory modalities to contribute to the full cognitive appreciation of experiences with significant auditory components. Additional differences in auditory processing between the left and right hemispheres indicate that individuals with a larger volume of gray matter in the left auditory cortex present with better language learning skills, particularly when learning a foreign language (Li, Legault, & Litcofsky, 2014). In contrast, persons with larger volumes of gray matter in the right auditory cortex show better pitch discrimination and higher musical aptitude scores (Janata, 2015; Kraus & Chandrasekaran, 2010).

Surprise! The Auditory System Has Efferent Pathways When you think about the auditory system, the last thing you would probably call to mind is efferent processing of any kind. Why would you even consider this idea? The auditory system is a purely sensory system anyway, right? Once again, the nervous system provides us with a twist and a bit of a surprise! The fact of the matter is that our auditory system does possess and use efferent descending pathways from higher-order regions of the CAP down to lower-level structures (Figure 18–12). There are two well-studied efferent pathways that we’ll mention to highlight this unique aspect of the auditory system: (a) a descending pathway that starts at the SOC and projects directly to the outer hair cells in the cochlea, and (b) another descending pathway that starts at the level of the auditory cortex with fibers projecting down through the auditory radiations and terminating in the MGB, IC, and SOC (Dallos & Oertel, 2008). Additionally, each relay along the CAP appears to also project to lower regions of the CAP as well, further adding to the complexity of auditory signal processing along the CAP. While the purpose of the afferent system is clearly well known, the efferent system’s operation in auditory processing has only recently been discovered. Generally, the efferent

CHAPTER 18   Neural Substrate of Hearing:  Central Auditory Pathway and the Auditory Cortices

Auditory Cortex

Corticofugal projections

Tectorial Membrane

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Outer hair cells

MGB

(descending)

IC

Inner Hair Cells

SOC Auditory Nerve

CN

Olivocochlear efferent axon bundle

Efferent axons going to outer hair cells

Basilar Membrane

 FIGURE 18–12.   Descending efference (motor) via corticofugal pathways from the auditory cortex to CAP locations modulates and gates signal transmission and processing in these lower areas. The superior olivary complex also projects efferent fibers via the olivocochlear bundle to the outer hair cells. Abbreviations: MGB = medial geniculate body; IC = inferior colliculus; SOC = superior olivary complex; CN = cochlear nucleus.

auditory system is geared toward providing regulatory feedback down to lower structures (see Figure 18–12). In other words, efferent mechanisms allow for central brain control and the self-regulation of afferent auditory information being obtained from the environment. Cortical areas that pro­ject descending efferent influences onto lower CAP structures effectively “gate” the transmission of afferent inputs through the relay locations of the CAP (Terreros & Delano, 2015). Efferent projections to the cochlea, though, have a more fundamental role in tuning or modifying the responsiveness of the BM through outer hair cell mobility (see SOC to outer hair cell connections in Figure 18–12) (Delano, Elgueda, Hamame, & Robles, 2007). The active tuning characteristics of the outer hair cells were discussed in Chapter 10.

Stapedial Reflex Response Is Mediated Through the SOC One of the primary responsibilities of the efferent auditory pathway that originates from the SOC is to provide protection to the cochlea, particularly in high-noise environments like those present during collegiate basketball game day matchups (it can get very loud in a basketball arena!). This mechanism is called the acoustic or stapedial reflex (AR) response (Pickles, 2008; Popper & Fay, 1992). The AR is an automatic and bilateral response that occurs when sound pressure levels (SPLs) exceed 85 dB SPL in persons with nor-

mal hearing. Attenuation of roughly 20 dB can be achieved when the AR is activated. AR activation results in a stiffening of the ossicular chain with the stapedius being pulled out of the oval window slightly, increasing the mechanical impedance of the middle ear (Pickles, 2008). The efferent signal responsible for the AR is mediated from the SOC through a branch of cranial nerve VII, ultimately resulting in stapedial muscle contraction. The bilateral nature of the AR is logical because if you are in an excessively loud environment, you want to have this attenuation action occurring in both ears. You really wouldn’t want to leave one ear unprotected, would you? Figure 18–13 lays out the basic circuitry of the acoustic reflex response when elicited by a tone click to one ear. Following along with this figure, auditory nerve input from the left cochlea arrives at the CN via cranial nerve VIII where it is then shared with the SOC bilaterally. To produce the ipsilateral stapedial response (shown with the heavy black arrows), the left facial motor nucleus (VII) receives excitatory inputs from the ipsilateral CN and SOC, which subsequently drive lower motor neurons of the facial nerve system to produce a contraction of the ipsilateral stapedial muscle of the middle ear. The contralateral stapedial response (shown with the gray arrows in Figure 18–13) is generated though the combination of (a) a contralateral projection from the right CN and (b) a bilateral projection of the SOC to the contralateral right facial motor nucleus, which in turn triggers the contraction of the contralateral stapedial muscle.

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Ipsilateral Response

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Contralateral Response

VII

VII

SOC

CN

SOC

CN

VIII Stapedius

Stapedius Middle Ear

Middle Ear Left

Right

Tone CLICK transduced by left cochlea

 FIGURE 18–13.  Stapedial reflex response pathway. To produce the ipsilateral response (dark black arrows), a tone click is presented to the left cochlea (blue). From the cochlea, auditory nerve fibers (VIII) project to the cochlear nucleus (CN). From CN, excitatory signals are routed to the facial motor nucleus (VII) and to the superior olivary complex (SOC). The SOC also projects to the facial motor nucleus. Facial motor nucleus activity driven by the ipsilateral CN and SOC leads to contraction of the stapedial muscle of the middle ear on the ipsilateral side. The contralateral response (light gray arrows) is generated through the combination of a contralateral projection from the CN receiving the sound input and a bilateral projection of the SOC to the contralateral facial motor nucleus. Identifying colors: right cochlea (red ); cranial nerve VIII (pink); CN (blue); VII nucleus (red ); SOC (yellow).

Function of the Olivocochlear Bundle Another well-identified efferent pathway is the olivocochlear bundle (OCB), which has both crossed and uncrossed fibers (Haines, 2013). The two divisions of this pathway are the medial and lateral OCB, with the medial OCB being the better understood of the two. The medial OCB pathway projects from the SOC to the CN, and then to the cochlea. At the cochlea, OCB fibers make direct connections to the outer hair cells (OHCs) and indirect connections to the inner hair cells via the auditory nerve (see schematic projection from the SOC to the OHC in Figure 18–12). The OCB is thought to have primarily inhibitory effects as discovered by American neuroscientist Robert Galambos in the early 1950s through the performance of several seminal studies in cats. In these studies, electrical stimulation was applied to the OCB, while recording from the auditory nerve to track any influences that the stimulation might be having on cochlear function. What was noted was that at low intensity levels (20  ms) reflect activation of the thalamocortical radiations from the MGB, the primary and secondary cortical areas, and in some cases even the auditory association areas. The presence, timing, and morphology of these evoked long-latency cortical auditory responses have been discovered to be effective predictors or biomarkers of the degree of cortical plasticity in children with profound congenital hearing loss. The importance of understanding the degree of cortical plasticity within auditory processing areas is directly related to the insertion of a cochlear implant at the optimal time so that it has the greatest positive effect on a child’s speech perception abilities (Ryugo, 2015). In groundbreaking work by Dr. Anu Sharma,

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Generator Sites for Auditory Brainstem Response 5.0

Distal portion of CN VIII

2.0

Proximal portion of CN VIII

CN

SOC LL

IC

Amplitude (microvolts)

1.0 0.5

I

0.2 0.1

II

III

V

IV

P0

VI

0.2 0.5

N0

1.0

Long latency thalamic & cortical responses

2.0 5.0

1.0

2.0

5.0

10

Latency (ms)

 FIGURE 18–14.   Representative auditory brainstem response (ABR) profile for different generator sites along the central auditory pathway. The ABR is a noninvasive electrophysiological assessment evoked by presenting a click to the ear to trigger an auditory nerve action potential that is transmitted to all auditory brainstem structures. The ABR waveform is comprised of six peaks (labeled I through VI) reflecting the evoked neural activity at different CAP locations. Measures of ABR amplitude, latency, and signal morphology (shape) are used to assess the health of the CAP generator sites.

the presence and morphology of the long-latency P1 cortical auditory evoked potential was used to identify the window of opportunity to provide a cochlear implant for maximum benefit to the child. In her work, Sharma demonstrated that providing a cochlear implant to congenitally hearing-impaired children any time before approximately 6 years of age provided the greatest benefit to the habilitation of functional hearing as assessed through speech recognition test scores (Glick & Sharma, 2017).

Conclusion We’ve seen that the central auditory system is a diverse collection of interconnected structures whose operation spans from sound localization to detection of spectral and timing-related

acoustic information. Acoustic inputs begin their travel from the right and left ears, and project to both cerebral hemispheres in a pattern of crossed and uncrossed information transmission streams (ventral and dorsal stream CAP pathways). Like other sensory systems, acoustic input processing is performed by a series of mechanisms that detect, filter, and integrate different aspects of sound along a collection of distinct pathways. Unlike other sensory systems, the central auditory pathway performs a great deal more sophisticated processing and abstraction before the signal even arrives at the auditory cortical areas in the cerebrum. This is likely a testament to the richness and density of information and cues carried by acoustic signals in nature. Such richness of information and its critical importance to our survival and enjoyment of life should motivate us all to protect and cherish this most special of sensory systems.

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The Top Ten List 1. Decussation occurs throughout the central auditory pathway (CAP) and represents a condition where auditory nerve fibers branch from one side of the auditory pathway to the opposite side. This results in a binaural representation of sounds that carry frequency, intensity, and timing information simultaneously to the brain. Given that we move through a three-dimensional world of sound, binaural processing is critically important for (a) correctly representing the sound field’s depth, (b) sound location, and (c) functionally appreciating frequency, intensity, and timing inputs from the environment. 2. Tonotopic organization refers to the notion that there is a systematic organization of frequency within a structure. In the auditory system, tonotopy originates at the basilar membrane where higher-frequency inputs respond optimally at basal ends of the BM and lower frequencies respond best at apical ends of the BM. The tonotopy of the central auditory pathway mirrors similar organizational schemes in the somatosensory and visual sensory systems. The place organization of the frequency components of any acoustic signal is observed at the level of the cochlea and is repeated throughout all key structures of the CAP. This systematic organization of sound frequency is essential for the discrimination of sounds. 3. Multiple processing mechanisms contribute to the abstraction of information in the central auditory pathway. These include processes such as detection, decoding, discrimination, and interpretation. Thus, when the term “processing” is used, be mindful that there are many underlying neurophysiological events that contribute to each of these processes. Each process performs a specific function and serves a different purpose during auditory perception. 4. Dorsal and ventral processing streams are a fundamental way in which incoming acoustic information is sorted and distributed to different regions of the CAP. The dorsal stream primarily carries frequency information, which helps a listener understand what was said (sound identification). The ventral stream primarily carries timing and intensity cues to help a listener identify where a sound is in space. These dorsal and ventral streams are preserved through the CAP and into the auditory cortices. 5. The central auditory pathway consists of multiple obligatory relay points, suggesting that auditory processing relies heavily on brainstem-level structures

to perform initial abstraction of sound inputs, even before reaching the cerebral cortex. These multiple relay points reflect the fact that there is not just one main pathway from the cochlea to the cortex. Several different nuclei make up these relay points, and all are connected to one another. Some of the relay points can be described as required synapse locations. The synapses that occur at these locations can be excitatory or inhibitory. There are five required synapse junctures in the CAP: the cochlear nucleus, superior olive, inferior colliculus, media geniculate body, and neurons of the auditory cortex. 6. Neurons in the CAP are unique and highly specialized to detect, transform, and integrate different aspects of incoming acoustic information. The auditory nerve, up until it enters the cochlear nucleus (CN), presents with virtually no specialization, except for some auditory nerve fibers having low versus high thresholds for sound. In contrast, the CN consists of many different types of cells that have different response properties and that operate to break down auditory nerve inputs and direct them to different locations in the CAP. 7. Temporal processing in the auditory system refers to the capacity to detect and interpret brief timing differences in a speech signal, a critical skill that underlies speech perception. For speech, this is an important idea because words are comprised of temporal gaps that convey critical information about word boundaries and voicing onset. In persons with hearing disorders, the ability to perceive these subtle timing cues is impaired, which makes speech difficult to understand. Another aspect of temporal processing is related to our ability to hear the difference between two different musical notes, such as middle C and two octaves above middle C. To hear this difference, the CAP displays evidence of preserving the temporal characteristics of sounds through a mechanism described as phase-​locking. In phase-locking, neurons fire only at a particular point in time for a periodic stimulus such as a musical tone. 8. Serial and parallel processing pathways found throughout the CAP contribute to the development of our appreciation of three-dimensional auditory space. Parallel paths reflect the idea that multiple processing routes exist simultaneously for a given input. In contrast, serial processing means that different types of information are processed from lower to higher structures, and thus processing becomes more enhanced

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The Top Ten List  continued

or abstracted as sounds travel from a lower to higher structure. Often serial and parallel pathways overlap and intersect one another in the CAP. 9. Unlike our intuitive belief, the auditory system possesses not only an afferent system, but an efferent system as well. Efferent pathways to the cochlea from brainstem areas, or to CAP nuclei from the cerebral cortex, are believed to tune the basilar membrane and regulate the transmission of incoming acoustic inputs, respectively. Essentially, the auditory efferent system is thought to be a feedback system. Many studies have suggested that this feedback is accomplished through inhibitory effects. While the precise nature of the interaction between afferent and efferent pathways is not completely understood, there must be a balance between them that contributes to optimal function.

Evidence for this lies in many clinical findings in persons with auditory disorders such as hyperacusis (hypersensitivity to sound), tinnitus, and auditory hallucinations, to name a few. 10. The acoustic reflex is an automatic contraction of the stapedius muscle of the middle ear that occurs in response to loud sounds. It is one of the hallmark functions of the efferent auditory system and occurs when excessively loud sounds (>90 dB) ensue. The contraction results in a significant reduction in intensity of sound input delivered to the cochlea. The process involves the propagation of sound through the peripheral hearing system and into the CN and SOC. From there, a motor response is triggered in an efferent nerve fiber that travels back through a branch of the facial nerve to cause contraction of the stapedius muscle.

Chapter 18 Abbreviations A1 — Primary auditory cortex

DCN — Dorsal cochlear nucleus

OAE — Otoacoustic emission

A2 — Secondary auditory cortex

EEG — Electroencephalography

OCB — Olivocochlear bundle

ABR — Auditory brainstem response

fMRI — Functional magnetic resonance imaging

OHC — Outer hair cell

AN — Auditory nerve AR — Acoustic or stapedial reflex response AVCN — Anterior ventral cochlear nucleus

Hz — Hertz IC — Inferior colliculus kHz — Kilohertz

BM — Basilar membrane

LSOC — Lateral superior olivary complex

CAP — Central auditory pathway

MEG — Magnetoencephalography

CAT — Computed axial tomography

MGB — Medial geniculate body

CF — Characteristic frequency

MNTB — Medial nucleus of the trapezoid body

CN — Cochlear nucleus CNS — Central nervous system dB — Decibel

MRI — Magnetic resonance imaging MSOC — Medial superior olivary complex

PET — Positron emission tomography PSTH — Poststimulus time histogram PVCN — Posterior ventral cochlear nucleus VCN — Ventral cochlear nucleus VNLL — Ventral nucleus of lateral lemniscus SL — Sensation level SOC — Superior olivary complex SPL — Sound pressure level STG — Superior temporal gyrus

CHAPTER 18   Neural Substrate of Hearing:  Central Auditory Pathway and the Auditory Cortices

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Study Questions and Activities • Summarize the basic features and characteristics of the acoustic signal. • Identify the major structures of the central auditory pathway (CAP). Create a table that lists the main structures of the CAP, their divisions, and the key features of each structure. • Sketch the general ascending pathway of sound once it enters the cochlear nucleus (from the right ear) and ends in the auditory cortex. Be sure to draw both the ipsilateral and contralateral pathways. Replicate this activity for the left ear. • What methods have been used to investigate the properties and functions of the CAP? • Describe the structure and general operation of the cochlear nucleus. • Create a table that lists the major features, functions, and cell types found within each subdivision of the cochlear nucleus. • Define the dorsal and ventral acoustic processing streams that originate in the acoustic stria exiting the cochlear nucleus. What is the significance of these streams? • Compare and contrast the functions and responses for the different cell types that populate the subdivisions of the cochlear nucleus. • Why are there so many cell and response types present in the cochlear nucleus? What purpose do they serve? • What is a characteristic frequency, and how is it used to characterize cells in the CAP? • Explain how timing and intensity are preserved in the cochlear nucleus. • Describe the structure and general operation of the superior olivary complex (SOC). • Create a flowchart that characterizes the pathway from the cochlea to the medial SOC (MSOC) responsible for low-frequency sound localization. • Explain the mechanism and circuitry for low-frequency sound localization in the MSOC.

References Anderson, S., Parbery-Clark, A., White-Schwoch, T., & Kraus, N. (2013). Auditory brainstem response to complex sounds predicts self-reported speech-in-noise performance. Journal of Speech Language and Hearing Research, 56(1), 31–43. Bartlett, E. L. (2013). The organization and physiology of the auditory thalamus and its role in processing acoustic features important for speech perception. Brain & Language, 126(1), 29–48.

• Create a flowchart that characterizes the pathway from the cochlea to the lateral SOC (LSOC) responsible for high-frequency sound localization. • Explain the mechanism and circuitry for high-frequency sound localization in the LSOC. • What is meant by binaural fusion and dichotic listening in the SOC? • Describe the structure and general operation of the inferior colliculus (IC). • What are the inputs to the IC and outputs from the IC? • Create a summary table that lists what research in animal studies has taught us about the IC’s operation on sound inputs. • Describe the structure and general function of the medial geniculate body (MGB). • What are the inputs to the MGB and outputs from the MGB? • Where is the primary auditory cortex, how is it organized, and what is its chief function? • How are the ventral and dorsal auditory processing streams represented in A1? • Create a simple table that lists the characteristics and functions of the core, belt, and parabelt regions of the auditory cortices. • How do the auditory cortical areas (A1, A2, association area) differ from one another functionally? • What role do the efferent projections from higher auditory processing zones play on the function and operation of lower CAP regions? • Explain the mechanism and function of the acoustic stapedial reflex. • What is the purpose of efferent signals along the olivocochlear bundle? • What is the auditory brainstem response, and how is it used diagnostically? • Describe the relationship between different waves in the auditory brainstem response (ABR) and the location of their generation.

Brewer, A. A., & Barton, B. (2016). Maps of the auditory cortex. Annual Review of Neuroscience, 39, 385–407. Carpenter, M. B. (1991). Core text of neuroanatomy (4th ed.). Baltimore, MD: Williams & Wilkins. Celesia, G. G. (2015). Hearing disorders in brainstem lesions. Handbook of Clinical Neurology, 129, 509–536. Christensen-Dalsgaard, J., & Carr, C. E. (2008). Evolution of a sensory novelty: Tympanic ears and the associated neural processing. Brain Research Bulletin, 75(2–4), 365–370. Dallos, P., & Oertel, D. (2008). The senses: A comprehensive reference. Volume 3: Audition. Boston, MA: Elsevier.

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Delano, P. H., Elgueda, D., Hamame, C. M., & Robles, L. (2007). Selective attention to visual stimuli reduces cochlear sensitivity in chinchillas. Journal of Neuroscience, 27(15), 4146–4153. Diamond, I., & Neff, W. D. (1957). Ablation of temporal cortex and discrimination of auditory patterns. Journal of Neurophysiology, 20(3), 300–315. Elemans, C. P. H., Rasmussen, J. H., Herbst, C. T., Düring, D. N., Zollinger, S. A., Brumm, H., . . . Švec, J. G. (2015). Universal mechanisms of sound production and control in birds and mammals. Nature Communications, 6, 8978. Eliades, S. J., & Wang, X. (2003). Sensory-motor interaction in the primate auditory cortex during self-initiated vocalizations. Journal of Neurophysiology, 89(4), 2194–2207. Emanuel, D. C., & Letowski, T. (2009). Hearing science. Baltimore, MD: Lippincott Williams & Wilkins. Geisler, C. D. (1998). From sound to synapse: Physiology of the mammalian ear. New York, NY: Oxford University Press. Gilroy, A. M., & MacPherson, B. R. (2016). Atlas of anatomy (3rd ed.). New York, NY: Thieme Medical. Glick, H., & Sharma, A. (2017). Cross-modal plasticity in developmental and age-related hearing loss: Clinical implications. Hearing Research, 343, 191–201. Hackett, T. A. (2015). Anatomic organization of the auditory cortex. Handbook of Clinical Neurology, 129, 27–53. Haines, D. E. (2013). Fundamental neuroscience: For basic and clinical applications (4th ed.). Philadelphia, PA: Elsevier Saunders. Hamill, T. A., & Price, L. L. (2019). The hearing sciences (3rd ed.). San Diego, CA: Plural Publishing. Hickok, G., & Poeppel, D. (2004). Dorsal and ventral streams: A framework for understanding aspects of the functional anatomy of language. Cognition, 92(1–2), 67–99. Hickok, G., & Poeppel, D. (2015). Neural basis of speech perception. San Diego, CA: Academic Press. Houde, J. F., & Chang, E. F. (2015). The cortical computations underlying feedback control in vocal production. Current Opinion in Neurobiology, 33, 174–181. Hugdahl, K., & Westerhausen, R. (2016). Speech processing asymmetry revealed by dichotic listening and functional brain imaging. Neuropsychologia, 93(Pt. B), 466–481. Janata, P. (2015). Neural basis of music perception. Handbook of Clinical Neurology, 129, 187–205. Kaas, J. H., Hackett, T. A., & Tramo, M. J. (1999). Auditory processing in primate cerebral cortex. Current Opinion in Neurobiology, 9, 164–170. Knudsen, E. I., & Konishi, M. (1978). A neural map of auditory space in the owl. Science, 200(4343), 795–797.

SECTION 4

Kraus, N., & Chandrasekaran, B. (2010). Music training for the development of auditory skills. Nature Reviews Neuroscience, 11(8), 599–605. Lee, C. C. (2013). Thalamic and cortical pathways supporting auditory processing. Brain & Language, 126(1), 22–28. Li, P., Legault, J., & Litcofsky, K. A. (2014). Neuroplasticity as a function of second language learning: Anatomical changes in the human brain. Cortex, 58, 301–324. Martinini, F. H., & Timmons, M. J. (1997). The nervous system: The brain and cranial nerves. In F. H. Martinini, & M. J. Timmons (Eds.), Human anatomy (8th ed.). Upper Saddle River, NJ: Prentice Hall. Micheyl, C., Schrater, P. R., & Oxenham, A. J. (2013). Auditory frequency and intensity discrimination explained using a cortical population rate code. PLoS Computational Biology, 9(11), e1003336. Narayanan, S., Majeed, K. A., Subramaniam, G., Narayanan, A. & Navaf, K. M. (2017). A case of cortical deafness due to bilateral Heschl gyrus infarct. Case Reports in Medicine, 2017, 6816748. Oertel, D., & Wang, X. (2021). Auditory processing by the central nervous system. In E. R. Kandel, J. D. Koester, S. H. Mack, & S. A. Siegelbaum (Eds.), Principles of neural science (6th ed., pp. 651–681). New York, NY: McGraw-Hill. Pickles, J. O. (2008). An introduction to the physiology of hearing (3rd ed.). Bingley, UK: Emerald Group. Popper, A. N., & Fay, R. R. (1992). The mammalian auditory pathway: Neurophysiology. New York, NY: Springer-Verlag. Romanski, L. M., & Averback, B. B. (2009). The primate auditory cortical system and neural representation of conspecific vocalization. Annual Review of Neuroscience, 32, 315‒346. Ryugo, D. (2015). Auditory neuroplasticity, hearing loss and cochlear implants. Cell & Tissue Research, 361(1), 251–269. Schnupp, J., Nelken, I., & King, A. (2011). Auditory neuroscience: Making sense of sound. Cambridge, MA: MIT Press. Schreiner, C. E., & Malone, B. J. (2015). Representation of loudness in the auditory cortex. Handbook of Clinical Neurology, 129, 73–84. Silva, J., Sousa, M., Mestre, S., Nzwalo, I., & Nzwalo, H. (2020). Cortical deafness of following bilateral temporal lobe stroke. Journal of Stroke and Cerebrovascular Diseases, 29(7), 104827. Smiley, J. F., & Falchier, A. (2009). Multisensory connections of monkey auditory cerebral cortex. Hearing Research, 258(1–2), 37–46. Terreros, G., & Delano, P. H. (2015). Corticofugal modulation of peripheral auditory responses. Frontiers in Systems Neuroscience, 9, 134.

Glossary

Numerals

occipital lobe, causing a loss of the perception of color vision despite the maintained health of the retinal input into the visual system. actin.  One of the principal constituent myofilaments in the myofibril. Also known as the thin filament. action potential (AP).  All or none electrical signal generated by a massive and rapid exchange of Na+ and K+ ions via voltage-regulated channels. Action potentials propagate down axons at differing speeds depending on the degree of myelination and thickness of the axon’s diameter. active zones.  Location on the presynaptic terminal membrane that operates as docking locations for filled synaptic vesicles. Active zones participate in the fusion and exocytosis of synaptic vesicles during synaptic transmission. activity-dependent plasticity.  Also known as experiencedependent or use-dependent plasticity. Structural and functional changes to the brain based on an individual’s experiences and interactions within an environment. acoustic reflex response. An automatic and bilateral response that occurs when sound levels exceed 85 dB SPL in people with normal hearing. Results in the stiffening of the ossicular chain and the stapedius being pulled out of the oval window slightly. acoustic shadow.  An area through which sound waves cannot propagate well because of the presence of an object and/or obstruction. adaptive control model.  Control model that makes use of both feedforward and feedback-based regulation. adenine.  An organic molecule that acts as a building block for DNA. Pairs with thymine. adenosine 3′, 5′-cyclic monophosphate (cAMP). Second messenger molecule created through G-coupled protein receptor activation. adenosine diphosphate (ADP). An organic chemical hydrolyzed from ATP that provides energy to cells for cellular processes. adenosine triphosphate (ATP).  Organic molecule that acts as a key unit of energy for cellular processes. Produced by mitochondria. adenylyl cyclase.  Membrane-bound enzymatically active proteins that drive the chemical reaction to create cAMP from ATP. Used in second messenger systems within a neuron. aerodigestive tract. The aerodigestive tract consists of the shared anatomy of the head, neck, and upper thorax that underlies the behaviors of breathing, swallowing, and vocalization.

Ia afferent.  Fast-conducting primary afferent that inner-

vates intrafusal fibers of the muscle spindle.

Ib afferent.  Fast-conducting primary afferent that inner-

vates the Golgi tendon organ.

A A-band.  Segment of the sarcomere comprised of actin and

myosin filament overlap.

abducens nerve (CN VI).  A general somatic efferent cra-

nial nerve innervating the lateral rectus muscle of the eye. Mediates the outward turning of the eye. abducens nucleus.  Originating nucleus of the abducens cranial nerve. Operates to control the motion and gaze position of the eye through innervation of the lateral rectus muscle. Nucleus is in the lower pons. absolute refractory period.  The period after an action potential during which the cell membrane of a neuron cannot be excited to generate a second action potential. absorption. The transfer of light energy to an object. Absorption depends on the electromagnetic frequency of the light energy. abstraction.  The process by which the brain discovers and distills the rules, generalities, and common features across and within a set of stimuli. acalculia.  An acquired impairment that leaves the individual with the inability to appreciate numeric sequences or perform simple arithmetic operations. accessory nucleus.  Motor nucleus of the lower medulla that houses lower motoneurons of the spinal accessory nerve (CN XI). Nucleus is increasingly considered a caudal extension of the nucleus ambiguus. accommodation response.  Response that rapidly adjusts the shape and focus of the lens to an object that is coming closer to you. acetylcholine (ACh).  A neurotransmitter involved in both parasympathetic nervous system and central nervous system operations. Also, the key neurotransmitter of the neuromuscular junction. acetylcholinesterase. Enzyme found in the junctional folds of the NMJ that degrades ACh to terminate NMJ transmission. achromatopsia.  A rare condition caused by cortical damage to the juncture of the posterior temporal lobe and the 731

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affective aggression.  A process in which the body under-

goes a slow and prolonged buildup of sympathetic nervous system activation. May result in behaviors such as growling, hissing, or taking a defensive body stance. A-alpha afferent fibers (Aα).  Largest diameter and most heavily myelinated primary afferent axons arising from the skin. Innervate cutaneous mechanoreceptors. A-beta afferent fibers (Aβ). Second form of heavily myelinated large primary afferent axons arising from the skin. Innervate cutaneous mechanoreceptors. A-delta afferent fibers (Aδ).  Small diameter and lightly myelinated primary afferent axons arising from the skin. Associated with thermal and nociceptors. afferent neurons.  Neurons that carry sensory information from the peripheral body toward the central nervous system. affordance.  The link between the contextual information from the environment and the action performed by the motor control system. Affordances are those behaviors “allowed” by the nature of the environment in which they are performed. agnosias.  A phenomena resulting from brain damage to association areas in which a patient has a profound inability to process sensory information and combine features into a unified cohesive whole. Often associated with a loss of ability to recognize objects, persons, and so forth. agraphia.  Acquired disorder that results in communication deficits through writing. Loss of writing skill is associated with deficits in other language disorders including alexia, aphasia, and agnosia. akinesia.  Inability to move or the absence of movement. akinetic mutism.  Loss of ability to produce speech despite having normal sensorimotor function. Caused by bilateral damage to the anterior cingulate gyrus. alar plate.  The dorsal embryonic spinal cord region that comes to house sensory-related elements such as the dorsal horns and afferent projection neurons. alexia.  Acquired disorder that results in communication deficits through reading. Loss of reading and lexical abilities is associated with deficits in other language disorders including alexia, aphasia, and agnosia. allodynia.  A condition in which injured tissues become exquisitely sensitive, triggering heightened pain responses to even nonnoxious forms of stimulation. alpha (α) motor neurons.  Lower motor neurons that specifically innervate extrafusal fibers. alpha-gamma coactivation.  Neuromotor mechanism that ensures that the muscle spindle in striated muscle remains sensitive to extrafusal changes in contraction state. Activation of the alpha motor neuron with intrafusal (gamma activation) contraction ensures that position and rate of length change proprioceptive signals are always available to the CNS. American Academy of Neurology.  A chief international professional association for neurologists and neuroscientists.

amines. A subgroup of neurotransmitters that includes

dopamine, serotonin, and norepinephrine.

amino acids. The building blocks of proteins that are

bound together at ribosomes during protein transcription. Can also be used as a CNS neurotransmitter. ampere.  The rate of electrical current flow measured in coulombs per second. ampulla.  Transducing structure at the base of the semicircular canals. The ampulla contains the hair cells of the semicircular canals and operates to detect rotational acceleration of the head. ampullary crista.  A sheet of thickened epithelium at the base of each ampulla into which vestibular hair cell stereocilia are embedded. amygdala.  Found in the medial temporal lobe anterior to the hippocampus. Considered a segment of the limbic system responsible for autonomic responses to fear and anxiety. amyloid plaques. Abnormal clusters of proteins that develop between nerve cells. Clumping proteins impair cell-to-cell signaling at central synapses and are thought to activate immune system and proinflammatory responses. Related to Alzheimer’s disease. androgen receptors. Receptors found in the preoptic nucleus of the hypothalamus that bind testosterone. aneurysms. Blood-filled balloon-like distensions of an arterial wall. Sudden rupture of an aneurysm can lead to hemorrhagic stroke. angular gyrus (ANG).  Prominent anatomical substructure of the inferior parietal lobe. Sits posterior to the supra­ marginal gyrus and extends to the imaginary border separating the parietal and occipital lobes. Active during reading tasks. anion.  A negatively charged ion. anopsias.  Visual deficit involving visual field losses. Can be total or partial. anosmia.  Denoting a complete loss of smell. ansa lenticularis.  One of two pathways that interconnect the GPi output nucleus to the ventroanterior and ventrolateral nucleus of the thalamus. anterior cerebral artery (ACA).  One of the two major cerebral arteries that bifurcate from the internal carotid. Supplies blood to the midline of the cerebral hemispheres and the frontal lobe pole. Major cortical areas supplied by the ACA include the cingulate gyrus, the corpus callosum, the superior frontal gyrus, the supplementary motor area, the medial extent of the primary motor and sensory cortices, and a portion of the superior parietal lobule. anterior cingulate gyrus (ACG).  Rostral segment of the cingulate gyrus involved in functions related to emotional regulation, affect, and executive function. Suggested to be involved with affect control and the assignment of emotions to cognitively attended sensory inputs. ACG is also active during voluntary initiation of vocalization behaviors in mammals.

GLOSSARY

anterior circulatory system.  Neurovascular arterial system

that originates from the common carotid and that supplies blood to the lateral and midline cortical areas. anterior commissure. A secondary commissural pathway characterized as a small, compact tract interlinking homologous regions of the middle and inferior temporal gyri across the midline. anterior communicating artery.  A short arterial bridge interconnecting the left and right anterior cerebral arteries. Part of the circle of Willis. anterior corticospinal tract.  Smaller division of the corticospinal tract accounting for less than 10% of the total descending corticospinal projections to the spinal cord. Pathway descends ipsilaterally through the medial aspect of the spinal cord’s anterior funiculus. Fibers decussate near their target location in the spinal cord. anterior fasciculus.  Anterior most region of white matter in the spinal cord. anterior hypothalamic nucleus.  Part of the thermoregulatory system that operates in a complementary manner to the posterior nucleus. Parasympathetic in function. Senses increases in body heat, triggering behaviors that can remove excessive body heat such as panting and sweating. anterior inferior cerebellar artery (AICA).  Artery that bifurcates from the basilar artery to supply blood to the central core and ventral regions of the cerebellum. anterior lobe of the cerebellum. The cerebellar lobe forming the upper third of the cerebellar mass in the rostral direction. anterior median fissure.  A prominent groove on the ventral surface of the medulla dividing it evenly into left and right halves. anterior middle temporal gyrus.  A cortical region in the temporal lobe associated with speech processing at the sentence level. anterior paracentral lobule.  Tissue on the medial surface of the frontal lobe that is the continuation of the precentral and postcentral gyri. anterior perforated substance. See olfactory tubercle. anterior spinal artery.  Relatively narrow artery found in the midline of the ventral medulla. Supplies blood to the tissues of the lower brainstem and ventral spinal cord. anterior thalamic nucleus (AN).  Forms the rostral tip of the thalamus and possesses profuse connections with several emotional regulatory system components of the limbic system including the mammillary bodies, hippocampus, and the anterior cingulate cortex. anterior tract of the anterolateral system.  Located in the ventral region of the spinal cord’s anterior funiculus. Conveys inputs related to crude touch and deep pressure from lamina IV and V to the thalamus and other subcortical locations. anterior ventral cochlear nucleus (AVCN).  The anterior subarea of the ventral cochlear nucleus.

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anterograde transport.  Movement of substances from the

cell body down an axon toward its terminal end.

anterolateral tract (ALS).  Somatosensory tract originating

in the spinal cord and passing through the brainstem en route to the thalamus. Anterolateral tract transmits nociceptive, thermal, and crude touch information from peripheral locations of the body (inferior to the neck) to the brain. anticodons.  The sequences of nucleotides on tRNA that are complementary to codons found on mRNA. aphasia.  Acquired language disorder most often caused by stroke. Impairment to the language processing system that can affect speech production and auditory comprehension. Deficits in the production and understanding of other communication modalities (e.g., gesture, writing, reading) can also be present. apneustic center.  A grouping of respiratory-related cells found in the pontine tegmentum that works with the pneumotaxic center to make up the pontine respiratory system. Apneustic center promotes inspiration by exciting cells of the medullary respiratory center. apoptosis.  Genetically triggered and purposeful mechanism of cell death that occurs naturally during embryological and postnatal development. apraxia.  Motor planning deficits characterized by an individual unable to perform voluntary activity. Apraxia is unrelated to deficits such as muscle weakness caused by lower motoneuron injury or spasticity resulting from upper motoneuron syndromes. Apraxia of speech is the speech-related variant of this disorder. apraxia of speech (AOS).  Motor speech disorder characterized by an impaired capacity to plan or program sensorimotor commands necessary for phonetically and prosodically normal speech. arachnoid layer. The middle of three meningeal layers. Consists of a barrier layer and the subarachnoid space. Circulation of cerebrospinal fluid occurs within the subarachnoid spaces. arcuate fasciculus (AF). Arched segment of the superior longitudinal fasciculus linking the superior temporal region with the inferior parietal lobule and the inferior frontal gyrus. Considered a central pathway interconnecting Wernicke’s and Broca’s areas. arcuate fibers.  Short association axon fibers that interconnect and link adjacent gyri to each other. arcuate hypothalamic nucleus. Nuclei in the tuberal region of the hypothalamus. Interlinks the lateral and ventromedial hypothalamic nuclei, allowing for the development of a baseline level for food and calorie intake for an animal. arteriovenous malformations (AVM).  Congenital tangle of arteries and veins within the cerebrum. Patients with AVMs may experience generalized seizures and debilitating migraine-like pain during activities that raise blood pressure levels. Transient changes to movement, sensation, and cognitive processes may also be noted.

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articulatory system. Set of oropharyngeal structures

including the lips, face, tongue, and mandible, which are positioned to form distinct sound patterns associated with a language. association cortices.  Large expanses of cortical tissue outside of the primary cortical areas corresponding to higher-order processing region. Chiefly responsible for the complex information processing that occurs between when an input arrives at primary cortical areas and the expression of a behavioral response. association fibers.  White matter tracts and pathways that interconnect cortical regions within a given cerebral hemisphere. Short and long association pathways are recognized. association thalamic nuclei.  Collection of thalamic nuclei that output to higher-order regions of the brain involved in integrating perceptual and motor activity with cognition. Outputs of association thalamic nuclei are distributed in a more widespread and diffuse manner than outputs of the specific class of thalamic nuclei. astrocytes. A type of glial cell, star-like in shape, and responsible for providing metabolic support to neurons in the CNS. Play an important role in creation of the bloodbrain barrier. ataxia.  A condition that includes dyscoordination, poor fine motor control, and unsteady gait. ataxic (cerebellar) dysarthria.  Speech motor disturbances arise from cerebellar lesions. Damage to the superior paravermal region underlies the most common cause of ataxic dysarthria, which results in imprecise articulation, prosodic excess (drunken-sounding speech), phonatory-prosodic insufficiency, and increased duration of speech elements. athetosis.  A slow and writhing form of involuntary movement. auditory agnosia.  Also known as cortical deafness. An inability to recognize, differentiate, and process sound meaning. Auditory agnosia is not related to peripheral deficits in the structure of the ear. auditory brainstem response (ABR).  Noninvasive electrophysiological method used routinely by clinical audiologists to objectively assess cochlear and neural function without the need for client participation. auditory nerve.  Primary afferent neuron from the organ of Corti in the cochlea to the cochlear nucleus in the brainstem. auditory radiations. Axon fibers originating from the medial geniculate nucleus of the thalamus to the temporal lobe. Fibers transmit acoustic information to the auditory cortical areas in the superior temporal gyrus. Also known as the inferior thalamic radiations. auditory startle reflex.  A reflex that immediately alerts us about the existence of a potentially important signal. Originates in the lower central auditory pathway. auditory-vestibular nerve (CN VIII). Special somatic afferent cranial nerve mediating the senses of hearing and balance.

autonomic nervous system (ANS).  A branch of the vis-

ceral motor PNS that regulates metabolism and homeostasis through activation of sympathetic and parasympathetic elements. aversion. Negative experience that results in stimulus avoidance. Opposite of reward state. axial section.  Anatomical reference plane running parallel to earth. Divides the cerebrum into dorsal and ventral parts. Divides the rest of the body into upper and lower half. Also known as horizontal or transverse section. axoaxonic.  A synapse between two axons. axodendritic.  A synapse between an axon and a dendrite. axon.  The cytoplasmic process of a neuron that extends outward and carries signals to other target neurons or glands. axon collaterals.  Small projections branching off an axon and usually found as the axon approaches the vicinity of a target site. axon hillock.  A region located at a point where the axon extends from the soma. Specialized to initiate action potentials. Rich in voltage-gated Na+ ion channels and sensitive to integrative excitability changes in the neuron. axoplasmic transport (flow). Mechanism responsible for the transport of materials between the cell body and its terminals. Can be described as fast or slow axoplasmic transport. axosomatic.  A synapse between an axon terminal and a cell body.

B Babinski response (sign).  Reflexive response character-

ized by flaring outward of the toes to a strong stroking of the foot sole. Key neurologic sign for upper motoneuron syndromes. baroreceptor reflex. An autonomic response helping maintain blood pressure to ensure continuous blood flow to the brain. baroreceptors.  A type of stretch-sensitive mechanoreceptor sensitive to contraction and expansion of blood vessels. Baroreceptor activity relays information about blood pressure. Key mechanism in mediation of the baroreceptor reflex. basal ganglia (BG).  Group of heavily interconnected subcortical nuclei in the cerebrum and mesencephalon. Operate as a “selector” to choose the appropriate action among many candidate actions that best satisfies the goals of a task and/or condition. Also operate to regulate the duration of a selected action, decide whether another action is of enough importance and value to interrupt the existing action, and choose when to terminate a current action. basal plate.  The ventral embryonic spinal cord region that comes to house motor-related elements such as the ventral horns and spinal motoneurons. basilar artery.  Artery running over the midline of the pons to the mesencephalon that is formed by the merging of the

GLOSSARY

right and left vertebral arteries. The basilar artery bifurcates rostrally into the posterior cerebral arteries and the superior cerebellar arteries. The anterior inferior cerebellar artery originates from the basilar artery caudally. The basilar gives rise to the pontine arteries. basilar membrane (BM).  Floor of the scala media. Varies from its base to its apex along three physical dimensions: thickness, stiffness, and width. Possesses tonotopy. basilar pontine region.  Ventral area of the pons. Contains the pontine nuclei. Bell’s palsy.  Disorder affecting the facial nerve that results in a partial or complete paralysis of the facial muscles ipsilateral to the diseased nerve. Patients exhibit a pronounced facial “droop” on the affected side. belt zone.  The region encircling the core of the auditory cortex. Also known as the secondary auditory cortex. benign paroxysmal positional vertigo (BPPV). Common cause of vertigo triggered through rapid changes in the position of one’s head. Believed to be caused by the dislodging and drifting of otoconia within the fluid-filled spaces of the semicircular canals. Nikolai Bernstein.  Russian physician and physiologist who published some of the most influential observations and theories about the principles of coordination and human movement. His theoretical work formed the foundation for modern conceptions of motor control in the 20th century through the present day. Bernstein’s problem.  A theoretical motor control dilemma discussed by Nikolai Bernstein. Bernstein asked how animals learn to control all the redundant and variant features available to produce a recognizable action. How do we learn to select or choose which collection of parts to use to accomplish a goal? How do we shape our movement-​ related intentions into observable actions? binaural fusion.  The fusion and integration of information from both ears. binocular visual zone.  Central portion of the visual field created by the overlap of left and right monocular visual hemifields. bipolar cells.  A cell type whereby two processes extend from opposite sides of the soma, one of which takes on the role of a dendrite and the other the role of an axon. bitemporal hemianopsia. Blindness in the temporal halves of the right and left visual fields. Lesion to the optic chiasm is most often associated with this deficit. blind spot.  Location on the retina that does not contribute to the input of an image due to the absence of photo­ receptors at that site. Origination point of the optic nerve. blood-brain barrier (BBB).  A protective barrier around the brain and spinal cord vasculature created by astrocytes. Astrocytes use tight junctions to prevent various agents and molecules that could potentially cause harm to neurons from passing though easily. body of corpus callosum.  Thickest region of the corpus callosum. Fibers within this section mostly interconnect

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homologous areas of the frontal and parietal lobes across the midline. botulinum toxin (Botox).  Neurotoxin from the Clostridium botulinum species of bacteria. The toxin prevents the release of the neurotransmitter acetylcholine from the axon terminals of motor neurons forming a synapse onto muscle fibers. Botox, as it is commonly referred to clinically, is used to treat a range of neuromotor conditions, including dystonia and spasticity. Bowman gland.  A secretory cell that plays an important role in generating mucus for the olfactory epithelium and aids in the maintenance of the ionic environment of the region. brachium.  Prominent fiber tract allowing communication between the superior colliculus and the lateral geniculate nucleus of the thalamus, and between the inferior colliculus and the medial geniculate nucleus of the thalamus. bradykinesia.  Slowed movement. Walter Russell Brain.  A British neurologist who described an odd condition in which patients with right-side dorsolateral parietal lobe lesions could no longer attend to any object on the left side of their visual space. He defined the cardinal features of the condition that would become known as “contralateral neglect” or “hemispatial neglect.” brain-derived neurotrophic factor (BDNF). Neurotrophic growth factor that operates on CNS neurons. Promotes growth of synapses and is active during learning and memory. brain lesions.  Any damaged region of brain tissue. brainstem. A key region of the central nervous system connecting the cerebrum, cerebellum, and spinal cord. The brainstem is comprised of the midbrain, pons, and medulla. branchial arches.  Embryologic structures that differentiate into parts of the lower face and neck. Paul Broca.  Famous pioneering French neurologist and physician who first identified the relationship between damage to the inferior frontal gyrus and deficits related to the expression and generation of spoken language. He also coined the term “limbic lobe.” Broca’s aphasia.  Aphasia characterized by a struggle to speak in phrases, with a notable absence of grammatically necessary words. People retain relatively good comprehension of what is said by themselves and others. Broca’s area.  Inferior frontal gyrus region formed by the pars triangularis and the pars orbitalis. Plays a role in language comprehension, semantic processing, and selection of competing semantic interpretations. Believed to coordinate the interactions between speech-related areas of the temporal lobe that encode the sensory representation of word production with their articulatory motor gestures within the frontal lobe. Broca-Wernicke-Lichtheim-Geschwind language model.

Classic language model that identifies areas in the inferior frontal and superior temporal lobes (connected by the

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arcuate fasciculus) as critical to language processing and production. Sometimes referred to just as the WernickeGeschwind (WG) model. Korbinian Brodmann.  German neurologist who was the first to generate a detailed cytoarchitectural characterization of the human cerebral cortex. Brodmann’s areas (BA).  One of the first cortical parcelization schemes developed for the human brain. Forty-seven distinct cytoarchitectural regions were described and characterized by Korbinian Brodmann in the late 19th century. Brodmann’s areas are still regularly used today to distinguish cortical areas from one another. Brodmann’s area 41.  The primary auditory cortex (A1). buccal facial nerve branch.  A principal branch of CN VII innervating muscles of the lower middle facial region. bushy cell.  Primary cell type of the anterior ventral cochlear nucleus. Spherical and globular subtypes are recognized.

C calcarine fissure.  A prominent sulcus found on the medial

aspect of the occipital lobe. The primary visual cortex is found in the region surrounding this fissure. calcium (Ca2+).  A positive ion that is essential to intracellular processes such as the initiation of synaptic transmission and the initiation of second messenger cascades. Also needed for muscle contraction. Intracellular calcium is extremely low in concentration, whereas extracellular levels are high. calcium pump.  Active ion transporter found in the cell membrane that is responsible for returning calcium to its initial location and reestablishing resting level ion concentrations. callosal transection.  Also known as corpus callosotomy. A surgical procedure whereby the corpus callosum is cut, disconnecting the cerebral hemispheres from each other. Often used to relieve certain forms of epilepsy. callosomarginal artery.  Branch of the pericallosal artery that runs along the cingulate sulcus in the midline. calvarium. The topmost part of the cranium. Can be referred to as the skull cap. canonical babbling.  Term used to characterize the production of strings of uniform consonant-vowel syllables in infants. capsule.  Collections of axons found in the CNS. Examples include the internal and extreme capsules of the cerebrum. cardiac muscle.  One of three main forms of muscle. Found only in the heart and consists of an array of interconnected fibers forming a mesh-like network. Contracts rapidly and forcefully in repeated contraction-relaxation cycles. carotid body reflex.  Reflex chemoreceptive response triggered by a decrease in oxygen levels in the bloodstream and/or an increase in carbon dioxide concentration. Reflex causes medullary respiratory centers to increase respiratory activity.

carotid sinus.  Bulb-like enlargement at the base of the

internal and external carotid arteries where they bifurcate from the common carotid in the neck. Houses baroreceptors for the detection of blood pressure changes. catalysts.  Factors that can serve to facilitate speech motor skill development. cauda equina.  A collection of nerve roots extending from the caudal endpoint of the spinal cord and extending inferiorly to innervate anatomical locations of the lower trunk and limbs. caudal.  Anatomical term meaning inferiorly oriented or toward the tail. caudate nucleus (CaudN).  One of two input nuclei of the basal ganglia system. Located in the central core of the cerebrum and forming the floor of the lateral ventricles. Forms the striatum with the putamen. cell body.  Also known as the soma. Region of cell that contains the major metabolic organelles and the nucleus for a typical cell. cell doctrine.  The theory that cells are the basic structural unit of all living organisms. center-surround.  A receptive field (RF) pattern produced by ON and OFF bipolar cells. The RF possesses two regions: a central area and a donut-like region surrounding the center. Center and surround elements of the RF are always in direct competition with each other for influence over the center’s bipolar cell activity. central auditory pathway (CAP).  Brainstem and diencephalon pathway that processes all auditory information from the cochlea en route to the auditory cortical areas. central control system.  The executive center within the motor control system responsible for developing and executing motor commands that are observable in the periphery. central nervous system (CNS). The first of two major divisions of the nervous system consisting of the brain, brainstem, cerebellum, and spinal cord. central pattern generators (CPG).  Neural networks that produce patterned outputs and form the neural basis of many fundamental brainstem reflexes such as the gag, laryngeal adductory response, swallow, and the suck. CPG networks are highly responsive to sensory inputs and are adaptable to environmental and task conditions. central sulcus.  Deep sulcus that divides the frontal lobe from the parietal lobe. Prominent landmark on the brain’s surface. cerebellar ataxia.  Cerebellar deficits including (a) impaired muscle synergy with disruption in error correction, (b) abnormal control of rate and range of movement, (c) delayed initiation of movement, (d) extended reaction times, (e) bradykinesia (slowness of motion), and (f ) subdivision of complex movements into smaller component elements. cerebellar cortex.  Outer layer of high convoluted gray matter of the cerebellum. cerebellar folia.  Intricate and highly stereotypical pattern of folds comprising the cerebellar cortex.

GLOSSARY

cerebellar mutism.  Mutism arising transiently from dam-

age to speech-related zones of the cerebellum. cerebellar peduncles.  Massive fiber bundles that interconnect the cerebellum with the brainstem. Divided into inferior, middle, and superior cerebellar peduncles. Inferior cerebellar peduncle is a mixed pathway for afferent and efferent signals to and from the cerebellar cortex. Middle cerebellar peduncle is an input pathway originating in the pontine nuclei. Superior cerebellar peduncle originates in the deep cerebellar nuclei and is an output pathway to higher CNS regions and to the brainstem and spinal cord. cerebellum.  Known as the hindbrain, the cerebellum is located directly ventral to the occipital lobe and dorsal to the pons. Considered a key structure of the motor control system involved in motor learning and motor coordination. Operates indirectly through primary motor cortical areas of the cerebrum and through descending efferent pathways of the brainstem and spinal cord. cerebral aqueduct.  Canal interconnecting the 3rd and 4th ventricles. Allows for the circulation of cerebrospinal fluid from the 3rd into the 4th ventricle. cerebral cortex.  A 2- to 4-mm layer of gray matter surrounding the entire cerebrum that serves as the information processing and integrative center of the nervous system. cerebral dominance. Also known as brain lateraliza­ tion. The propensity for one side of the brain to primarily activate for select neural functions compared to the other hemisphere. cerebral hemispheres. Two symmetrical regions that comprise the cerebrum and are joined together by the corpus callosum. cerebral peduncle.  Mass of fiber tracts found in the ventral midbrain region, bilaterally. Also consists of the substantia nigra nuclei located dorsally to these fiber tracts. cerebral perfusion.  Blood flow to and through the brain. If blood flow to an area is too low, it may cause dysfunction because of inadequate oxygen/glucose transport to neurons in the area. cerebrocerebellum. Comprises the lateral parts of the cerebellar cortex, receiving information almost exclusively from regions in the cerebral cortex via pontine gray matter. Active during a wide range of speech, language, and cognitive functions. cerebrospinal fluid (CSF).  Watery fluid produced by the gland-like choroid plexus found in the ventricles of the cerebrum. CSF contains small quantities of proteins, glucose, K+, and Na+ ions. CSF circulates around and through the entire CNS via the ventricular system and the subarachnoid spaces. cervical facial nerve branch.  A branch of CN VII innervating superficial muscles of the lower face and jawline. cervical region of the vertebral column.  Vertebral column region that consists of vertebrae C1 to C7. Forms the topmost region of the vertebral column.

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C-fibers. Thin and unmyelinated primary afferent axons

arising from the skin. Associated with thermal and nociceptive receptors. channel gating.  The regulatory mechanism by which ion channels are opened or closed in response to a controlling signal. Gating regulates ion movement and current flow across the cell membrane. characteristic frequency. Best response of an auditory nerve fiber to a given frequency. Response sensitivity can be displayed as a tuning curve. Lowest intensity level where cell firing is triggered 50% of the time is the neuron’s threshold. chemoreceptors.  Primary receptors responsible for encoding information regarding smell, taste, and pain information. Receptors are responsive to the presence of chemical agents. chemosensation.  The sensing and transduction of chemical stimuli from the environment. Necessary for mediating taste and smell. chloride ion (Cl–).  Negatively changed ions that are high in concentration externally and low internally for a typical neuron. Plays a role in neuron hyperpolarization. chopper PSTH response pattern.  A repetitious response pattern of activation for T-stellate and D-stellate cells of the cochlear nucleus. chorda tympani.  Facial nerve branch that innervates the taste buds of the anterior tongue. chorea.  Hyperkinetic movement disorder characterized by rapid, jerky, and involuntary movements. Often described as being “dance-like” in quality. choroid plexus.  Gland-like structure within the ventricles of the cerebrum that is responsible for secreting approximately half a liter of cerebrospinal fluid daily. chromatic vision.  Color vision using cones. chromosome.  Thread-like and compact element that contains DNA. Located in the cell nucleus. cingulate gyrus (CG).  Gyrus comprising one of the largest segments of the limbic system. Lies on the medial aspect of the cerebrum, overlying the corpus callosum. Supports a variety of functions such as attention, affect, vocalization, motor control, and emotion. Comprised of functionally distinct areas known as the anterior and posterior cin­ gulate gyri. cingulate motor areas (CMA).  Areas found in the anterior cingulate gyrus having direct connections to the spinal cord and reciprocal connections with the primary motor cortex and supplementary motor areas of the frontal lobe. cingulate sulcus.  The sulcus separating the cingulate gyrus from the frontal and parietal lobes on the medial surface of the cerebrum. cingulum.  White matter tract that lies deep within the cingulate gyrus. Tract forms a functional connection between the hippocampus, parahippocampal gyrus, and anterior cingulate gyrus. circadian rhythms.  Biological processes displaying predictable oscillations tied to a 24-hour timeframe. Used

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in endocrine systems and for establishing the sleep-wake cycle. circle of Willis.  An easily identifiable landmark of the ventral cerebrum consisting of a circular pattern of arteries. The circle of Willis is hypothesized to allow for circular blood flow through these circularly interconnected arteries. The system consists of the left and right anterior arteries, middle and posterior cerebral arteries, and anterior and posterior communicating arteries. cisternae.  A reservoir for calcium ions that is within the sarcoplasmic reticulum. Forms a segment of the triad. When electrically stimulated, the cisternae release calcium into the intracellular spaces of the muscle cell. cisterns. Enlarged CSF-filled areas of the subarachnoid space usually found near the junction of major CNS elements such as the medulla, pons, and the cerebellum. closed-loop system.  A system that uses feedback to direct and correct movements during goal-oriented actions. coarse coding deficit.  Condition in which individuals with right hemisphere damage present with an inability to inhibit or deactivate inappropriate meanings and inferences when a sentence is processed. coccyx.  Small vestigial bony structure making up the lowest segment of the vertebral column. cochlea.  Consists of three fluid-filled tubes or chambers that are coiled to resemble the shape of a snail shell. Houses the primary sensory receptors for sound. cochlear amplifier.  Positive feedback neural mechanism that provides the outer hair cells with the ability to amplify the amplitude and frequency selection of sound vibrations. cochlear implant.  Neuroprosthetic sensory device that is surgically placed with the cochlear duct to directly stimulate auditory nerve afferents. Consists of an external and wearable sound-processing unit with a microphone, a transmitter coil placed below the skin of the skull, and an implantable lead of electrodes that are threaded into the cochlea. cochlear nuclei (CN).  First location along the central auditory pathway. Principal target for auditory nerve afferents. Located in the dorsolateral medulla and consisting of a ventral and dorsal division. codon.  A sequence of three nucleotides on mRNA that code for a specific amino acid. cognitive communication disorder.  Acquired language disorder often caused by traumatic brain injury. Difficulties arise primarily because of attentional, memory, social cognition, or other executive functioning deficits rather than through language itself. color blobs.  Color-sensitive cell clusters in the cortical layers of the primary visual cortex. commissural fibers. Collection of axons found in the CNS that interconnect homologous brain regions across the midline. common carotid artery (CC).  Large arterial branch of the neck stemming directly from the aortic arch. The CC is

the origination point of the anterior arterial system of the brain and gives rise to the internal carotid artery. Communicative Aphasia Treatment.  A treatment approach developed by Friedemann Pulvermüller and colleagues through modification of the PACE (Promoting Aphasics Communicative Effectiveness) approach. computed axial tomography (CAT).  A noninvasive imaging procedure used to produce scans of the inside of a body through the use of specialized x-ray equipment that takes measurements from different angles to produce cross-​ sectional slices of the body. concentration gradients. The uneven distribution of a substance in a given volume or space. Concertation gradients create driving forces. cones.  Photoreceptors of the eye responsible for high resolution and color vision in daylight. Three variants are recognized, each responsible for transducing different wavelengths of light corresponding to green, blue, and red spectral sources. confluence.  The junction of the superior sagittal, inferior sagittal, straight, and transverse sinuses of the cerebral venous system. The confluence is located at the posterior midline situated between the cerebellum and the occipital lobe tissues. conformational state.  Three-dimensional shape assumed by a structure. Regarding proteins, changes in conformational shape due to binding, enzymatic action, and electrical changes underlie a protein’s basic operation and function. conjugate deviation.  A condition caused by injury to the frontal eye fields of the frontal lobe. Results in a person’s visual gaze directed to the side without any real intent for looking that direction. Key sign of lateral frontal lobe damage consequent to stroke. connexons.  A structure created by six connexin proteins forming the pore of a gap junction. Also referred to as a connexon hemichannel. constraint.  A feature or characteristic within the organism and/or environment that dictates the motor control system’s organization around a movement goal. constraint-induced aphasia/language therapy (CIAT/ CILT). Language therapy that developed partially in

response to CIMT outcomes. Participants are encouraged to focus on the use of verbal communication during completion of language activities. Nonverbal communication attempts such as writing or gesturing are not the focus, but may be used as cues to prompt verbal communication. Other principles include an intensive practice schedule, participation in activities that are behaviorally relevant, and shaping of spoken language behaviors via contingencies and scaffolding. constraint-induced movement therapy (CIMT). Physical therapy method that constrains patients to use a weakened limb during functional tasks for most of the patient’s waking hours. Constraint is forced via hand splint, mitt,

GLOSSARY

or sling used to secure the unaffected limb and/or verbal instruction not to use it. Developed out of the principles of learned nonuse, massed practice, and activity-dependent plasticity. contextual shift.  A change in perceptual threshold detection due to factors such as prior experience with a task, practice, fatigue, and context of the stimulus presentation. contralateral neglect syndrome.  A complex phenomenon in which a person is unable to attend to any object on the left side of the visual field. Neglect syndromes result from specific damage to the right dorsolateral parietal lobe. coordinative structures.  Flexible, highly adaptable action synergies that allow the organism to accomplish the same movement goal with different combinations of movements and muscle activation patterns. See synergy. cornea.  Transparent covering of the eye that behaves as a first-line lens to help focus light into the inner eye chamber. Continuous with the tough outer wall of the eye called the sclera. corollary discharge. See efference copy. corona radiata.  A massive fan-like white matter structure in the cerebrum that contains projection fibers. Dorsal continuation of projection fibers comprising the internal capsule. coronal plane.  The anatomical reference plane that runs vertically to the earth and is oriented at a 90-degree angle to the sagittal plane. Divides the brain into rostral and caudal halves. Divides the body into dorsal and ventral halves. Also referred to as a frontal plane. corpus callosum.  The massive tract of commissural axons at the bottom of the longitudinal cerebral fissure that joins the cerebral hemispheres and allows for communication and coordination between the left and right hemispheres. cortex.  A sheet-like collection of neuronal cell bodies in the nervous system. cortical column.  The modular organization of the horizontal cortical layers into cylinder-like collections of neurons spanning the entire radial (vertical) dimension of the cortex. cortical deafness.  Rare form of deafness resulting from damage to the primary auditory cortex. cortico-basal ganglia-thalamo-cortical circuits. Complex neural circuits formed by connections running from the cerebral cortex, through the basal ganglia, into the thalamus, and then back to those same cortical structures. corticobulbar.  Key descending pathway transmitting motor signals from primary motor areas of the cerebral cortex to lower motoneurons of the brainstem and cranial nerve nuclei. Active during skilled and precision forms of action. cortico-cerebellar-cortical loop.  Processing loop or pathway that interlinks the cerebral cortex and the cerebellum, with a return pathway from the cerebellum back to the point of the loop’s origin in the cerebrum. corticocortical connections.  Short or long axon connections that arise specifically between the cortical layers from different regions of the brain. Corticocortical connections

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can exist between gyri in the same hemisphere or across hemispheres. corticofugal fibers.  Projection fibers that transmit information from the cortex down to brainstem and spinal targets. corticomotoneuronal projections.  Subsets of projection neurons belonging to the corticospinal and corticobulbar systems that monosynaptically innervate lower motor neurons in the spinal cord and brainstem. corticopetal fibers.  Projection fibers that transmit information from the spinal cord and brainstem to the cerebral cortex. corticopontine.  Descending fiber tract from sensorimotor areas of the cerebrum to the pontine nuclei in the basilar pons. corticoreticular tract.  Tract primarily responsible for locomotion and postural control. Comprised of the medial (pontine) tract and the lateral (medullary) tract. Controls activity of alpha and gamma motor neurons and is active during the control of breathing. corticospinal tract.  Key descending pathway transmitting motor signals from primary motor areas of the cerebral cortex to lower motoneurons of the spinal cord. Active during skilled and precision forms of action. corticostriatal projections.  Descending fibers interconnecting cortical areas of the cerebrum with the striatum. corticothalamic projections (fibers).  Reciprocal axonal connections or feedback projecting from the cerebral cortex back to the thalamus. corticotrophin-releasing factor (CRF).  A neuropeptide hormone playing a role in response to stress. Has strong correlations to behavioral disorders involving stress and anxiety. cortisol.  A stress-related hormone released by the pituitary gland. coulomb (Q).  A standard unit of electrical charge. coup-contrecoup.  Pattern of head injury where the brain is damaged at the point of impact (coup site), and then again at a location opposite the point of impact (contrecoup site). Contrecoup injury results from tissue recoil. cranial fossa.  Depressions on the floor of the cranial vault that support the mass of the frontal, temporal, and occipital lobes of the cerebrum. cranial nerves.  Twelve pairs of nerve fibers projecting from the brainstem, ordered from rostral to caudal, and numbered with Roman numerals. Cranial nerves mediate the transmission of sensory and motor information and control autonomic behaviors of the visceral organs. cranial vault.  The volume that houses the brain and most of the brainstem. Formed by the connection of the cranial plates. cranium.  Portion of the skull made up of plate-like and irregularly shaped bones. Cranium consists of the frontal, parietal, occipital, temporal, sphenoid, and ethmoid bones. Bone elements are connected by suture joints.

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crescent monocular zones.  Extreme region of the visual

field visible only monocularly by the retina of the ipsilateral eye. Can be seen only by the nasal retinas for each eye. cribriform plate. Porous region of the ethmoid bone through which axons of the olfactory receptors project. critical period.  Period during development when an individual is primed to learn language effectively and efficiently, and after which language learning is diminished. cross-bridge.  The binding complex formed by the interaction of myosin and actin. Cross-bridge formation is key to developing force and tension in the sarcomere. crus cerebri.  The most ventral area of the midbrain (mesencephalon) consisting of descending motor fibers from the cerebrum to the brainstem and spinal cord. cuneate fasciculus. Dorsal column white matter tract that houses primary afferents of the somatosensory system from the upper trunk and upper extremities. Axons of the cuneate fasciculus transmit tactile and proprioceptive inputs from their peripheral innervation zones. cuneate nucleus. Nucleus in the lower medulla that receives primary afferent inputs from the upper trunk, arms, and hands. The cuneate nucleus houses second-order neurons that project contralaterally to the ventroposterior lateral nucleus of the thalamus. Nucleus mediates tactile and proprioceptive sensory information. cuneus.  Wedge-shaped area dorsal to the calcarine fissure on medial aspect of the occipital lobe. cupula. A gelatinous sail-like structure that crosses the lumen (inner opening) of the ampulla. Stereocilia of semicircular canal hair cells are embedded within the cupula. Bending of the cupula results in shearing of the stereocilia and depolarization/hyperpolarization of vestibular hair cells. current (I).  The rate of flow or the quantity of charged particles passing a set point per second. cyclic AMP (cAMP). See adenosine 3′, 5′-cyclic monophosphate. cyclic GMP (guanosine 3', 5'-cyclic monophosphate). A common second messenger organic molecule created through G-coupled protein receptor activation. cytoarchitecture.  Referring to the composition and morphology of cells of the nervous system. cytokine.  Small proteins necessary for cell signaling. Triggers immunological responses. cytology.  The biological study of the structure and functioning of cells. cytoplasm.  The cytosol within a cell that contains the cell’s organelles, except the nucleus. cytosine.  A base organic molecule that acts as a building block for DNA. Pairs with guanine.

D dark current.  Chronic inward depolarizing current of Na+

and Ca2+ for photoreceptors.

deep cerebellar nuclei (DCbN).  Set of bilateral nuclei

found in the central region of white matter beneath the cerebellar cortex. Consist of the dentate, fastigial, emboliform, and globose nuclei. default-mode network (DMN). A collection of brain regions found to be more active when a person is not undergoing cognitive processing, such as when daydreaming and mind-wandering. DMN also activates when a person is thinking about others, himself or herself, or past events. DMN elements are localized in the medial region of the cerebrum. degrees of freedom (dF).  The component parts of the motor control system that can be dynamically organized into a variety of solutions for performing goal-oriented actions. Deiters’ cells.  Structural support cell of the organ of Corti. Believed to participate in the mechanical responsiveness of the organ of Corti to acoustic inputs. delay lines.  A system of axon pathways of differing lengths originating from each ear and projecting to the medial superior olivary complex where they converge on an array of cells in the MSOC, producing a series of coincidence localization detectors. dementia. See neurocognitive disorders. dendrite (soma)–axon–dendrite. The essential neural organization for information flow from a transmitting neuron to a receiving neuron. dendrites.  Short, branch-like processes projecting from a neuron’s cell body. Chief receptive and input site of the neuron. dendritic spines.  Small projections from a dendrite that form critical structural supports for synapse formation. dentate gyrus.  Medial segment of the hippocampal formation within the medial temporal lobe. Contributes to the development of new declarative (episodic) memories. dentate nucleus (DN).  One of the four deep cerebellar nuclei. Receives afferent signals from premotor cortex and supplementary motor area via pontocerebellar fibers. Dentate is active during the planning, initiation, and control of voluntary movements. denticulate ligaments.  Flattened bands of reticular and elastic fibers from the upper layer of the pia mater surrounding the spinal cord and suspending it from the dura. deoxyribonucleic acid (DNA). Self-replicating chains of nucleotides that carry genetic instructions for protein synthesis. depolarization.  Decreasing charge separation across a neuron’s membrane. Generated by Na+ ion influx. dermatome.  A specific zone or discrete area of the body innervated by a pair of spinal nerves or one-spinal segments. deterministic patterns.  A pattern that is highly predictable and therefore highly recognizable. diabetes insipidus.  A condition due to damage to the supraoptic or paraventricular nuclei of the hypothalamus.

GLOSSARY

Characterized by the desire for increased fluid intake and increased urination. dichotic listening. The ability to obtain acoustic information from both ears, but attending to one input while inhibiting the other. diencephalon.  Core region of the cerebrum enveloped by the telencephalon. Consists of the thalamus, hypothalamus, epithalamus, and 3rd ventricle. Important in sensory transmission, sensory gating, and metabolic homeostasis. diffuse axonal injury (DAI).  Hallmark damage caused in traumatic brain injuries where the head is struck in such a way that the brain accelerates (in linear and/or angular directions) within the bony cranial vault. White matter tracts across the brain experience mechanical stretching and shearing forces that cause diffuse damage, injury, and eventual cell death. diffusion.  The flow of a substance across a permeable membrane or volume of media. diffusion tensor imaging (DTI).  A magnetic resonance imaging (MRI) technique developed to statistically track the motion of molecules of water to estimate the route of axons in white matter. diplopia.  A condition of double vision. Directions Into Velocities of Articulators (DIVA) model.

A well-established neuroanatomically based computational (mathematical/computer) model of speech production and perception developed by Frank Guenther (Boston University) and colleagues. Also known as the DIVA model. direct motor systems.  Major elements of the motor control system that directly influence LMN activation. Include the premotor cortex, primary motor cortex, and select descending brainstem systems. direct pathway of the basal ganglia.  Pathway consisting of the striatum and the GPi/SNr output nuclei. Direct pathway operation will typically inhibit the output nuclei. distributed practice.  Completion of many trials of a single activity produced over a span of time. Blocks of trials are separated by other activities. dopamine (DA).  An amine neurotransmitter that plays a role in executive control, movement, reinforcement, and motivation. Expressed by neurons of the substantia nigra. dorsal.  Anatomical terminology referring to a position that is posterior or toward the back. dorsal acoustic stria.  Dorsal pathway fibers projecting from the cochlear nucleus. dorsal auditory stream.  Functional pathway through the entire auditory system that transmits and preserves intensity and spectral features of sound. dorsal cochlear nucleus (DCN).  Smallest division of the two major cochlear nuclei. DNC is a laminar structure that receives inputs from somatosensory, vestibular, and acoustic sources that are integrated within the DNC. dorsal column.  Also known as the posterior funiculus. The dorsal white matter section of the spinal cord divided

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into the somatotopically organized gracile and cuneate fasciculi. dorsal column–medial lemniscal system (DCML). Soma­ tosensory pathway in the CNS that conveys information related to touch and proprioception from all parts of the body through the spinal cord. dorsal column nuclei.  Nuclei of the lower medulla that house second-order neurons for tactile and proprioceptive somatosensory inputs. Consist of the gracile and cuneate nuclei. dorsal fasciculus.  Dorsal white matter region of the spinal cord that consists of the gracile and cuneate fasciculi. Also known as the posterior fasciculus or dorsal columns. dorsal horn.  Gray matter region located in the dorsal half of the spinal cord. Home to cells mediating sensory inputs from the periphery. dorsal motor nucleus of vagus.  Found in the dorsal medulla and considered a chief parasympathetic nucleus of the brain. Interconnections between the solitary nucleus and the dorsal motor nucleus of vagus allow for blood pressure monitoring and the slowing of cardiac rate. dorsal nucleus of the lateral lemniscus (DNLL). A nucleus of the lateral lemniscus that is part of the ascending central auditory pathway. Operates to connect the superior olivary complex and the inferior colliculus. dorsal processing pathways.  Processing pathways of the cerebral cortex that are active during spatial behaviors. In the visual system, the dorsal stream originates in the visual cortex and runs through the visual association areas to the parietal lobe for integration with other forms of sensation. Dorsal processing pathways usually terminate in the prefrontal cortex. Dorsal processing pathways have been identified for other sensory modalities and language processing. dorsal respiratory group.  Part of the medullary respiratory center. These collections of cells modulate the depth of breath through the monitoring of (a) stretch-sensitive baroreceptors in the respiratory vasculature and (b) chemoreceptors. dorsal root ganglion (DRG). Collection of nerve cell bodies belonging to spinal primary afferents. Ganglion is located at the point where the ventral and dorsal roots of the spinal cord join to form the spinal nerve. dorsal roots.  Bilateral pairs of fibers of the dorsal spinal cord consisting of nerve roots (axons) that extend from the dorsal root ganglion to the dorsal gray of the spinal cord. Transmit sensory information centrally. dorsal stream.  Processing pathway of the visual system that originates with M-type retinal ganglion cells and projects through the primary visual cortex and visual association areas. Pathway terminates in the posterior parietal association area. Dedicated to processing inputs related to direction of motion, visually guided movement, and positional relationship between elements of a visual scene. dorsal superior temporal gyrus (dSTG).  Primary auditory cortex that engages in initial stages of sound processing.

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dorsolateral prefrontal cortex (DLPFC).  General func-

tional zone of the lateral prefrontal cortex. Chief cortical region underlying executive function and working memory. dorsomedial hypothalamic nucleus. Nuclei in the tuberal region of the hypothalamus. Active in feeding behavior and satiation. dorsomedial thalamic nucleus.  The major component of the medial thalamic region containing streams of input from the emotional limbic system including the amygdala, anterior cingulate cortex, olfactory-related areas, and prefrontal cortex. Chief output is to the hypothalamus. driving forces.  Physical forces that result in particle motion. Can be chemically based or electrical in nature. D-stellate cells.  Smaller population of stellate cells found in the posterior ventral cochlear nucleus. Display “chopper” PSTH response pattern. Project inhibitory inputs to the ipsilateral dorsal cochlear nucleus and contralateral cochlear nucleus. dual-path models (pertaining to language processing). Models that have two primary cortical paths, routes, or streams of processing. Ventral stream is implicated in language comprehension tasks, semantic meaning, and the relationships between different phonological, morphological, syntactic, and semantic elements. Dorsal stream is implicated in repetition tasks and analyzing and ordering information in time and space such as that necessary for ordering phonemes to produce words. dual-stream sensory processing model.  Model of speech processing that proposes separate streams for linking sensory experience to meaning, and for linking sensory experience to motor output. Related to dual-path language models. dura mater.  The outermost meningeal layer of the CNS. The dura consists of an outer periosteal layer and an inner meningeal layer. Dural tissue is leather-like in texture and unyielding to stretching forces. duration (timing). The length of time during which an event is happening or has occurred. dynamic systems theory (DST).  A meta-theory used in experimental psychology and neuroscience based on the science of nonlinear chaotic and complex systems. DST emphasizes the self-organization and emergent properties of complex systems. dysarthria.  A general class of motor speech disorders caused by damage to the sensorimotor control system underlying speech. Characterized by differing levels of speech intelligibility deficits. Specific characteristics of speech dysarthria are dependent on the lesion site, but can include weakness, spasticity, incoordination, involuntary movements, or altered tone of the muscles controlling respiratory, phonatory, resonance, articulatory, and prosodic aspects of speech production. dysdiadochokinesia.  Feature of cerebellar ataxia whereby a patient cannot perform rapidly alternating actions. In

speech applications, cerebellar ataxic patients cannot produce the syllable train /pa/-/ta/-/ka/ at fast articulatory speeds. dyskinesia.  General classification of movement disorders characterized by unintentional muscle movements and diminished voluntary motion control. Dyskinesia can be classified as hypokinetic or hyperkinetic in quality. dysmetria.  Feature of cerebellar ataxia whereby a patient cannot accurately judge distances between himself or herself and a target he or she is reaching toward. Results in under- and overshooting of the target. dysosmia.  The perception of a different smell than is physically presented or a distortion in smell perception. dysphagia.  Disorders related to eating and swallowing. dysphonia.  An alteration in voice production that impairs the effectiveness of communication. dystonia.  Sustained or intermittent uncontrolled muscle contractions.

E eccentricity graph. The measure of an object’s distance

in a spherical or conical context from a central reference location. ectoderm.  The outermost cell layer making up the early human embryo. Differentiates to become the skin and nervous system. Edinger-Westphal nucleus.  Autonomic system nucleus innervating the pupillary and ciliary muscles of the eye, controlling the pupillary light reflex. Part of oculomotor system of CN III. EE auditory neurons.  Neurons in the auditory cortex that are excited by both ears. effector enzyme.  Enzyme that responds to the presence and the binding of a regulatory factor (such as G-protein). Response is typically activation of the enzyme to generate second messengers in the neuron. effector organs.  Structures, typically muscles and glands, that are activated by motor commands to produce movement or the expression of a substance. efference copy.  An internal model that is created by the motor system and used as a comparator signal for openloop and feedforward control systems. Efference copy reflects the intent of an action. efferent neurons.  Neurons that carry descending motor information from the central nervous system to the periphery. EI auditory neurons.  Neurons in the auditory cortex that are excited by one ear, but inhibited by the opposite ear. electrical gradient.  The driving forces created through differences in charge separation across a membrane or barrier. electricity. Form of energy created by the motion of changed particles. electroencephalography (EEG).  Neuroimaging method used to record electrical activity in the brain using small

GLOSSARY

electrodes placed directly on the scalp. Has very good temporal resolution, but poor spatial resolution. electromagnetic energy.  Radiant energy characterized as a wave and described in terms of its wavelength, frequency, amplitude, phase, and period. EM spectrum ranges from 1 picometer (1 trillionth of a meter) to 1 megameter (106 km). In the human, what we appreciate as light forms the part of the EM spectrum between approximately 400 and 780 nanometers. electromotility (pertaining to outer hair cells). Rapid cell shape changes in response to electrical stimulation. Conversion of electrical energy into mechanical forces by the outer hair cell. electromyography (EMG).  Assessment method designed to record electrical signals and potentials directly from muscle tissues. EMGs can be recorded using surface electrodes placed on the skin over the muscle of interest, or through the use of fine-wire implantable electrodes placed directly into the tissue. electronystagmography (ENG).  A specialized exam of the vestibular system used to uncover inner ear dysfunction. Involves the recording of eye motion to detect the presence of nystagmus. embolic stroke.  Also known as an ischemic stroke. Form of stoke resulting from the blockage of blood flow, generally due to a blood clot or the development of arteriosclerotic plaques. emboliform nucleus. One of the four deep cerebellar nuclei located medial to the dentate nucleus. Together with the globose nucleus, forms the interposed nucleus. Key nucleus of the spinocerebellar system. embolus.  A free-floating fragment of some substance in the bloodstream. The blockage of an arterial blood vessel by an embolus is referred to as an embolism. emergent phenomenon.  The notion that a complex system can produce stable output patterns from the interaction of its components within a given real-time context. endocochlear potential. The electrical potential maintained in the cochlea through ionic concentration differences between the endolymph of the scala media and the perilymph within the scala media and tympani. This potential is critical to maintaining the sensitivity and responsiveness of the hair cells. endocrine processes.  Processes carried out by the endocrine system related to growth, reproduction, immunity, and homeostasis. endoderm.  The innermost cell layer making up the early human embryo. Matures to become the internal organs and visceral linings. endolymph.  Fluid that fills the scala media of the cochlea. Endolymph has low concentrations of Na+, but high concentrations of K+. endomysium.  Deepest layer of connective tissue in a muscle bundle. Encapsulates and binds together individual muscle cells/fibers.

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endoneurium.  A layer of connective tissue surrounding

axons. Endoneurium groups axons into nerve fascicles.

endoplasmic reticulum (ER).  An organelle with mem-

branous channels specialized for protein modification and transportation, ion storage, and metabolism of substances in a cell. engram. The stored representation of a movement goal, which can be used to direct future goal-oriented actions. enteric system.  Branch of the visceral motor system of the peripheral nervous system that mediates gastrointestinal functioning. Also known as the intrinsic nervous system. entorhinal cortex. Multimodal limbic association area found in the medial temporal lobe. Receives projections from limbic structures and projects robustly to dentate gyrus and hippocampus. Entorhinal cortex plays a critical role in memory. environmental constraints. The factors in nature that govern how we can perceive ourselves within the surrounding space in which a movement goal will be organized. enzymatic degradation.  The process of enzymes altering a neurotransmitter’s structure to prohibit binding to a receptor site. One of the methods used to remove neurotransmitter from the synaptic cleft after synaptic transmission has ended. enzyme.  A macromolecular catalyst used to alter reactions or to convert substances into other molecular forms and products. Enzyme labels always end with the suffix, “-ase.” epimysium.  Topmost layer of connective tissue. Encapsulates collections of muscle fascicles into a muscle bundle. Closely attaches to the overlying fascia. epinephrine. A hormone neurotransmitter essential for activation of the sympathetic nervous system. Also known as adrenaline. epineurium.  A layer of tough connective tissue encapsulating an entire peripheral nerve. equilibrium potential (Ex).  Membrane voltage required to balance the motion of a given ion through an open ion channel. Ex is created by the opposing effects of concentration and electrical gradients across a cell membrane. For example, EK is achieved when the net flow of K+ ions across a neuron’s cell membrane is equal to -75 millivolts. On the other hand, ENa is achieved when the net flow of Na+ ions across a neuron’s cell membrane is equal to +55 millivolts. estrogen.  Female sex hormone that maintains female body features and plays a major role in the maintenance of the reproductive system. ethmoid bone.  Walnut-sized bone of the cranium separating the nasal cavity from the calvarium of the cranium. Contributes to the medial wall of the eye orbits. Houses the olfactory afferents. excitation-coupling.  The process by which NMJ activity leads to the onset of sarcomere contraction. excitatory.  The state in which an increased probability for action potential generation exists. Also characterizes the state of a neuron undergoing depolarization.

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Neuroscience Fundamentals for Communication Sciences and Disorders

excitatory postsynaptic potentials (EPSP).  Local depo-

larizing change in membrane voltage created through the opening of postsynaptic ion channels that allow for the influx of positive ions. excitotoxicity.  The maladaptive process in which neurons are damaged or killed due to excessive exposure to high concentrations of excitatory neurotransmitters such as glutamate. executive function.  The sum of cognitive processes allowing for the control of behavior in humans and select nonhuman primate species. Functions include control of attention, inhibition of cognition, working memory, cognitive flexibility, future planning, sense of purpose in an action, notion of personal responsibility, and adherence to social norms and constructs. exons.  The segments of DNA sequences responsible for the coding of amino acids. Exons are joined together to create the final mRNA strand after introns have been removed. expansion phase.  Phase of vocal development in which the infant sharpens vowel clarity and broadens sound repertoire to include behaviors like yells, whispers, squeals, zerberts, and raspberries. experience-dependent cortical reorganization.  A subtype of neuroplasticity that entails changes to widespread behavioral representations in the cerebral cortex as a function of voluntary action and functional use of a body part. Also known as activity-dependent or use-dependent cor­ tical reorganization/plasticity. Typically associated with changes in primary sensory and motor cortical areas. expressive (nonfluent) aphasia.  Deficits related to the expression of language, including slow and labored speech, degraded articulation, and telegraphic sentence structure. Related to damage to the posterior inferior frontal gyrus. Referred to as Broca’s aphasia after Paul Broca, who first characterized the neuroanatomical basis of this syndrome. external carotid artery.  Branch of the common carotid. Supplies blood to the face, pharynx, and tongue. external granular layer.  Layer II of the cerebral cortex. external pyramidal layer.  Layer III of the cerebral cortex. external superior laryngeal nerve (eSLN).  Nerve branch of the superior laryngeal nerve of the vagus system that innervates intrinsic laryngeal muscles except the crico­ thyroid. exteroception.  The ability to sense stimuli that arises from outside the body. extrafusal fibers.  Another term for skeletal muscle fibers. Stands in contrast to the intrafusal fibers of the muscle spindle. extraocular muscles.  Skeletal muscles of the eye that insert into the sclera and are responsible for the eye’s rotation and motion. extrapyramidal system.  Older generic term used in neurology to describe those descending systems that have indirect and modulatory influences on medial and axial body systems.

extrastriate cortex.  Region of the occipital cortex located

beyond the primary visual cortex. Higher-order visual processing areas (visual association areas) are found in this region. extreme capsule.  A long association tract associated with lexical/semantic processing. Connects the occipital and posterior temporal areas with the inferior frontal lobe.

F facial nerve (CN VII).  Mixed (sensory and motor) cranial

nerve innervating the muscles of the face, the taste buds of the anterior two thirds of the tongue, and the salivary and lacrimal glands. Exists laterally from the brainstem at the junction of the pons and medulla. facial nucleus.  Collection of lower motoneurons in the pontine tegmentum whose axons form CN VII. Projections from the facial nucleus innervate the muscles of the face, the stapedius, and the salivary glands. falx cerebelli.  Thick dural fold found within the calvarium, extending caudally from the midline of the tentorium cerebelli and situated between the hemispheres of the cerebellum. falx cerebri.  Thick dural fold found within the calvarium that separates the left and right cerebral hemispheres. fascicles.  A collection or grouping of muscle cells encapsulated by perimysium. fasciculus(i).  A term for describing a large bundle of axon fibers in the CNS. Key examples include the cuneate and gracile fasciculi in the spinal cord. fast-fatigable fiber. Striated muscle fiber that sustains force for brief periods of time. fast-fatigue resistant fiber.  Striated muscle fiber that sustains force for intermediate periods of time. fast-glycolytic fiber.  Striated muscle fiber that sustains force for brief periods of time and that uses glycogen as its chief energy source. fastigial nucleus.  One of the four deep cerebellar nuclei. Most medial of the deep cerebellar nuclei. Receives input from Purkinje cells in the vermis subdivision of the cerebellum, and possesses efferent connections to the vestibular nuclei in the medulla and pons. fast-oxidative fiber.  Striated muscle fiber that sustains force for intermediate periods of time and that uses aerobic respiration to produce ATP is its chief energy source. fast-twitch (fast fiber).  Striated muscle fiber that possesses rapid cross-bridge cycling and contraction rates. feedback.  Information arising from the interaction between peripheral receptors and the environment that guides error detection and improved performance during closed-loop system control of goal-oriented action. feedback control system.  Control system in which the actual output of the motor system is carefully monitored with differences between the intended and actual output yielding an “error” signal. Error signals can be used to

GLOSSARY

update motor commands to converge on the intended target. Also known as a closed-loop control system. feedforward control.  The type of motor control in which motor commands are not influenced by resultant sensory information. Rather, the resulting sensory information is used to fine-tune future planning. feedforward control system.  Stored or memorized commands sent to the motor system with no ability to monitor the results of the output. Also known as an open-loop control system. festination of gait.  A characteristic acceleration and shortening of normal walking gait patterns in patients with Parkinson’s disease. Often described as a “shuffling” type of walking pattern. fiber.  A generic term referring to an axon. fiber tracts.  A generic term referring to a collection of axons in the CNS. first (1st) pain.  Sharp, stabbing pain that is first perceived after an acute injury. Short duration perception. first-, second-, and third-order afferent neurons. Designations applied to the set of neurons comprising the dorsal column–medial lemniscal and in the anterolateral systems. First-order neurons are the primary afferent. Second-order neurons shift stimulus transmission from the ipsilateral to the contralateral side of the neuroaxis. Lastly, third-order afferents transmit sensation to the cerebral cortex from the thalamus. flaccid dysarthria.  Form of speech dysarthria caused by lower motor neuron damage resulting in weak and hypotonic musculature. Affects respiration, phonation, resonance, and articulation. Speech is characterized by hypernasality, inaccurate consonant productions, and breathiness. flaccidity.  Condition resulting from lower motor neuron damage, characterized by muscle weakness, loss of muscle tone, atrophy of the muscle, and an absent stretch reflex. flavor.  The combination and interaction of senses including gustation, olfaction, and somatosensation. flocculonodular lobe.  A deep lobe of the cerebellum with direct inputs from the vestibular nuclei via the inferior cerebellar peduncle. Outputs project back to the vestibular nuclei. foliate papillae.  Ridge-like papillae found on the posterior and lateral edges of the tongue body. Taste buds of this structure are innervated by CN IX. foramen magnum.  Large foramen found in the occipital bone that allows for passage of the brainstem out of the cranium. foramen of Luschka.  Laterally positioned ports connecting the caudal aspect of the 4th ventricle to the subarachnoid cisterns and spaces. foramen of Magendie.  Central port connecting the caudal aspect of the 4th ventricle to the subarachnoid cisterns and spaces. foramen of Monro.  Conduit that interconnects the lateral ventricles with the 3rd ventricle.

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forceps major.  Fibers of the corpus callosum (splenium)

that interconnect the posterior-most areas of the cerebrum, specifically the temporal and occipital regions. forceps minor.  Fibers of the corpus callosum (rostrum and genu) that interconnect the anterior-most areas of the left and right frontal lobes. formant frequency.  A concentration of acoustic energy localized about a particular frequency within the sound signal of speech. Formant frequencies form the acoustic signature of a given speech sound. formant frequency shift.  A spectral acoustic cue used by humans to discern voiced consonant place of articulation. fornix.  Major afferent pathway emerging from the hippocampus. Projections terminate in a variety of limbic-related structures, including the anterior nucleus of the thalamus, mammillary bodies, prefrontal cortex, septal nuclei, and several nuclei of the hypothalamus. forward model.  Model that uses efference copy as a comparator signal for anticipated sensory information and the actual changes in movement-related sensory information executed in feedforward conditions. fourth (4th) ventricle.  One of the four major segments forming the ventricular system. Comprises the space between the dorsal brainstem and the ventral cerebellum. Connected to the 3rd ventricle via the cerebral aqueduct. fovea.  Center of visual gaze on the retina and home to a dense concentration of cones. This location receives the greatest concentration of light when viewing an image. foveola.  Centermost zone of the fovea where the retinal ganglion and bipolar cell layers are shifted aside to allow for light to fall directly upon the photoreceptive layer. The foveola possesses only cones. frequency. Number of cycles per second of a periodic energy source. Measured in hertz (Hz). frontal aslant tract (FAT).  Association pathway directly connecting Broca’s area with the anterior cingulate and pre-SMA. Tract is left lateralized, suggesting a possible role in language. frontal association areas (FAA). Association cortical regions of the frontal lobe that mediate executive function behaviors and working memory. FAA receives and integrates information from primary sensory and motor areas, as well as from parietal and temporal association areas. Deficits in FAA are noted as changes to personality. frontal bone.  Curved, plate-like bone that comprises the anterior-most region of the cranium. Frontal bone also forms the superior wall of the orbits. frontal eye field (FEF).  Region of the lateral frontal lobe projecting to the oculomotor, trochlear, and abducens motor nuclei. Responsible for regulation of conjugate saccades of the eyes. frontal lobe.  Rostral area of the cerebrum from the fontal pole to the central sulcus. Key location for the planning and execution of movement. Operates as the integrative center of neural signals related to our cognitive abilities,

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Neuroscience Fundamentals for Communication Sciences and Disorders

higher-level decision-making, and language formulation skills. frontopontine fibers.  Axon tracts originating from motor regions of the frontal lobe that innervate the pontine nuclei of the basilar pons. Considered a critical pathway for efference copy from motor cortical regions of the frontal lobe to the cerebellum. functional magnetic resonance imaging (fMRI).  A form of magnetic resonance imaging technology that measures small changes in blood oxygenation levels in the brain to build maps of task-dependent cerebral activity. functional variability. The ability to flexibly adapt to changing constraints and still accomplish the same movement goal. See motor equivalence. fungiform papillae.  Covers the majority of the anterior two thirds of the tongue surface. Taste buds of this structure are innervated by CN VII. fused tetanus.  Contraction state where individual twitches are not visible and all signs of relaxation in the muscle are absent. fusiform gyrus. See occipitotemporal gyrus. fusion pore.  Opening that emerges after the joining of a synaptic vesicle with the presynaptic terminal membrane. Pore allows for exocytosis of neurotransmitter into the synaptic cleft.

G G-actin.  Subunit of actin that possesses the myosin binding

site.

Phineas Gage.  Nineteenth-century railroad worker who

is remembered in the annals of neuroscience for having survived a massive injury to his frontal lobe caused by the impalement of an iron tamping spike through his skull. Through his survival, his case fostered the emerging view that the brain plays a critical role in the establishment of one’s personality and that damage to specific brain areas produces specific and replicable personality changes. gamma (γ) motoneuron.  Motoneuron innervating the intrafusal fibers of the muscle spindle. Gamma motoneurons are activated synchronously with alpha motoneurons innervating extrafusal fibers. Gamma motoneurons are part of a servo-mechanism that adjusts the sensitivity of muscle spindles during muscle contraction. gamma-aminobutyric acid (GABA).  Principal inhibitory amino acid neurotransmitter found in the central nervous system. Associated with hyperpolarizing events. ganglion (plural, ganglia).  A collection of cell bodies (gray matter) in the peripheral nervous system. Parallel term to “nucleus” for the central nervous system. gap junction.  Specialized synaptic structure that links the cytoplasm of two cells, allowing for direct and virtually instantaneous transmission of ionic current. gases.  One of the four fundamental states of matter. In the CNS, nitric oxide gas may operate as a nonclassical neurotransmitter involved in retrograde synaptic transmission.

gate theory of pain.  A central mechanism that under-

lies the phenomena of pain suppression through tactile stimulation. gating.  The processes and mechanisms by which the nervous system filters and selects salient inputs from the environment to inform adaptive behaviors. gene expression.  The process by which information encoded within a gene is used to create a functional protein product. Requires a two-step process known as transcription and translation. general motor programs.  Stored general rule set for coordinating degrees of freedom into functional synergies for accomplishing a movement goal. general motor program theory.  Motor control theory suggesting that higher centers of the motor control system store neural representations of a given movement goal. Within the stored representation are the general sets of rules for coordinating degrees of freedom into functional synergies for accomplishing the goal. general nerves.  A generic classification of nerves that are distributed throughout the body and not restricted to any certain areas. general somatic afferent (GSA). Nerves arising from ganglia outside of the brainstem that convey somatosensory information related to touch, proprioception, pain, and temperature. Includes the sensory aspects of CN V, VII, IX, and X. general somatic efferent (GSE). Nerves arising from brainstem motor nuclei that project outward to innervate the skeletal muscles of the head and neck. Includes CN III, IV, VI, and XII. general visceral afferent (GVA).  Nerves arising from the pharynx and larynx that transmit information about general sense of pain and temperature as well as sensations related thirst and hunger. Includes CN IX and X. general visceral efferent (GVE).  Nerves arising from cranial nerve motor nuclei that project outward to innervate smooth muscle tissue and glands. Includes the autonomic components of CN III, VII, and X. genes.  Chromosomal units of DNA carrying genetic information that play an essential role in the expression of biological traits. genu of the corpus callosum.  Anterior bend of the corpus callosum. Genu is derived from the Latin word genuflect, meaning to “bend at the knee.” Norman Geschwind.  American neuroanatomist who was one of the first to argue that behavioral disorders must be analyzed by developing explicit hypotheses as to their underlying neural mechanisms. He developed one of the first connectionist models for language based on the work of Carl Wernicke. The Wernicke-Geschwind model is regarded as one of the foundational scientific models in language science. glabrous skin.  A form of skin that does not possess any hair follicles. Examples include the vermilion of the lip, palms of the hand, and soles of the feet.

GLOSSARY

glial cells (plural, glia).  Neuronal support cells providing

structure, protection, and insulation to neurons. glial progenitor cell.  A cell that can differentiate into astrocytes and oligodendrocytes after cortical development is complete. Matures from radial glia. globose nucleus.  One of the four deep cerebellar nuclei. Together with the emboliform forms the interposed nucleus. globular bushy cells. A subcategory of bushy cells of the anterior ventral cochlear nucleus. Part of the neural circuitry highlighting interaural intensity differences for high-frequency sound localization. globus pallidus (GP).  One of the key nuclei comprising the basal ganglia. Located medial to the putamen and lateral to the internal capsule, possessing a characteristic wedgelike shape. Globus pallidus is functionally subdivided into an external and internal segment. Internal segment of the GP (GPi) projects to the thalamus and comprises one of the chief output sites of the basal ganglia system. External segment of the GP (GPe) projects to the subthalamic nucleus and is a part of the indirect pathway in the basal ganglia system. glomerulus (plural, glomeruli).  Clusters of neural endings of olfactory nerve axons and second-order olfactory neurons that lie within the layers of the olfactory bulb. Glomeruli are the target locations for ORN nerve fiber innervation. glossopharyngeal nerve (CN IX). Cranial nerve that projects out from the lateral junction of the pons and the medulla. Glossopharyngeal system is comprised of numerous sensory and motor functional components, including SVE and GVE motor elements and three different sensory elements (GVA, SVA, GSA). glutamate (Glu).  An excitatory amino acid neurotransmitter. Regarded as one of the most important neurotransmitters for brain function. In excess, the excitatory property of glutamate can become toxic to neurons themselves. glycine (Gly).  An amino acid that also has a role as an inhibitory neurotransmitter. Most commonly found in the retina, spinal cord, and brainstem. glycogen.  Polysaccharide (a long chain of simple carbohydrates) of glucose that forms an energy storage or reserve substance in the muscle cell. glycolysis.  Process of using glycolytic enzymes to produce glycogen. goal-oriented actions. See motor skill. Golgi apparatus.  Multistacked organelle responsible for receiving and processing proteins for further distribution to other regions of the cell. Golgi tendon organ (GTO).  Proprioceptive receptors in tendons that detect changes in the tension or force of a contracting muscle. Innervated by group Ib afferents. G-protein.  Intracellular proteins associated with metabotropic receptors. Becomes associated with membrane-​bound effectors that generate second messengers. G-protein coupled receptors.  A family of metabotropic receptors that transduce signals from a primary neurotrans-

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mitter to activate second messenger pathways that will drive structural, metabolic, and genetic changes in the cell. gracile fasciculus.  Dorsal column white matter tract that houses primary afferents of the somatosensory system from the lower limbs and lower trunk. Axons of the gracile fasciculus transmit tactile and proprioceptive inputs from their peripheral innervation zones. gracile nucleus.  Nucleus in the lower medulla that receives primary afferent inputs from the lower trunk and legs via the gracile fasciculus. The gracile nucleus houses second-order neurons that project contralaterally to the ventroposterior lateral nucleus of the thalamus. Nucleus mediates tactile and proprioceptive sensory information. granule neurons.  Cells that comprise the densely packed granular layer of the cerebellum. gray matter.  Neural tissue of the nervous system consisting of neuronal cell bodies. group I fibers.  Axon classification of the musculoskeletal system. Fibers are large in diameter and heavily myelinated. Possess fastest conduction velocities. group II fibers.  Axon classification of the musculoskeletal system. Fibers are large in diameter and well myelinated. Possess second fastest conduction velocities. group III fibers.  Axon classification of the musculoskeletal system. Fibers are small in diameter and lightly myelinated. Possess the second slowest conduction velocities. group IV fibers.  Axon classification of the musculoskeletal system. Fibers are small in diameter and unmyelinated. Possess slowest conduction velocities. GTP and GDP. G-proteins that are used as chemical “switches” or sources of activation within biochemical reactions in a cell. GTP (guanosine triphosphate) is hydrolyzed to GDP (guanosine diphosphate) to create a driving source of energy for a given reaction. guanine.  A base organic molecule that acts as a building block for DNA. Pairs with cytosine. gustation.  The psychological perception and appreciation of taste. gustatory center. The rostral segment of the solitary nucleus. Afferent information related to taste terminates in this area. gustatory system.  Neural system that can detect, transduce, and perceive a tastant. gyrus.  The smooth “hill-like” ridges of the cerebral and cerebellar cortices. (plural, gyri) gyrus rectus.  A prominent structure of the ventral frontal lobe that is medial to the orbital gyri and directly in the midline. Olfactory bulb and tract lie directly over the gyrus rectus.

H hair cell (HC).  Mechanoreceptive cells with bundles of ste-

reocilia on their top surfaces. Found in the cochlea and vestibular system. Produce graded receptor potential changes when stimulated.

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Neuroscience Fundamentals for Communication Sciences and Disorders

hair follicle endings.  Nontraditional cutaneous mechano-

receptors found only on nonglabrous skin innervated by free nerve endings. Respond to bending, pulling, or any other form of deflection of the hair shaft. helicotrema.  The apical end of the cochlear spiral where the scala vestibuli and scala tympani meet and communicate. hemiballismus.  Hyperkinetic movement disorder that generates sudden, flailing, and ballistic involuntary movements. hemichannels.  A structure formed by connexin proteins that are paired to form gap junctions. Also known as connexons. hemifield.  The portion of the visual field mediated and seen by one retina. hemorrhagic stroke.  Any neurovascular condition leading to bleeding within the brain. Examples include rupture of an aneurysm or head injuries leading to tearing of neurovascular elements. Also known as an intracerebral hemorrhage. Hensen’s cells.  Support cells within the organ of Corti for the outer hair cells. Believed to mediate ion metabolism and maintain the electrical environment of the region about the outer hair cell. herniation syndromes.  Condition whereby compressive forces and intracranial pressures become great enough to cause a displacement of brain tissue from its normal position within the calvarium. Heschl’s gyrus.  A gyrus located on the dorsal surface of the superior temporal gyrus. Also known as the primary auditory cortex. heteronomous hemianopsia. See bitemporal hemian­ opsia. hierarchical processing.  The flow and processing of information from lower-order primary areas to successively higher-order secondary and tertiary processing areas of the cortex. Also known as serial processing. hippocampal formation.  A core processing area of the limbic system, active during conscious associative learning and episodic/declarative memory formation. hippocampus.  Lies within the parahippocampal gyrus of the medial temporal lobe. Considered a central element of the limbic system. Key structure in explicit (declarative) associative learning. histology. The anatomical study of tissues and cellular structure. Gordon Holmes.  British neurologist best known for critical research on World War I veterans who experienced cerebellar injury. He discovered key operations of the cerebellum. homonymous hemianopsia.  A condition that eliminates all retinal inputs from the entire contralateral binocular visual hemifield due to optic tract damage. homonymous hemianopsia with macular sparing. A pattern of visual field loss in which the center area of the visual field is preserved while the rest of the hemifield is absent. Macular sparing is a common outcome to cortical damage.

homonymous quadratanopsia.  A condition in which a

quarter of an entire visual field is lost due to damage to the ventral or lower segment of the optic radiations. homunculus.  A visual analogy of how cortical neurons are arranged and apportioned to different segments of the body. horizontal and amacrine cells.  Cells involved in modulating output between photoreceptors, bipolar cells, and retinal ganglion cells. horizontal plane. The anatomical reference plane that divides the brain into dorsal and ventral segments. Divides the body into upper and lower halves. Runs perpendicular to the sagittal and coronal planes. Also referred to as transverse or axial planes. Huntington’s disease.  Hereditary degenerative disease of the basal ganglia that results in excessive abnormal and uncontrolled body movements. hydrolysis.  Organic chemical reaction in which a water molecule is used to break chemical bonds. The reduction of ATP to ADP is a classic example of hydrolysis at work to release energy. hydrophilic.  The chemical property of being attracted to water. hydrophobic.  The chemical property of being repelled by water. hyperalgesia.  The abnormal or extremely heightened sensitivity to pain. Results from damage to nociceptive receptors and to the peripheral nerves. hypercapnia. Elevated or excess levels of CO2 in the bloodstream. hypercolumn.  A three-dimensional processing unit in the visual cortex consisting of a collection of ocular dominance columns, orientation columns, and blobs/interblobs. hyperkinesia (hyperkinetic dyskinesias). Disorders characterized by the presence of excessive abnormal or unintended movements. hyperkinetic dysarthria.  Speech dysarthria associated with a wide range of positive signs (excessive and abnormal movements) and associated with lesion to the basal ganglia. hyperpolarization.  Increase in membrane potential due to a greater degree of charge separation across a membrane. Results from an influx of negative ions or efflux of positive ions. hypertonia.  Increased muscle tone. hypoglossal nerve.  CN XII that innervates the intrinsic and extrinsic muscles of the tongue. hypoglossal nuclei.  Motor nucleus in the dorsal medulla forming the origination location of the hypoglossal nerve (CN XII). Axons of CN XII innervate the intrinsic and extrinsic muscles of the tongue. hypokinesia (hypokinetic dyskinesias).  Disorders causing reduced movement. hypokinetic dysarthria.  Speech dysarthria type associated with Parkinson’s disease and degeneration of the dopaminergic system. Characterized by hoarseness, breathiness,

GLOSSARY

reduced pitch, low intensity, and mumbled and slurred consonant production and distorted vowels. hyposmia.  The medical term for a decreased sense of smell. hypothalamic-pituitary-adrenal (HPA) axis. Complex set of neuroendocrine pathways that operate as feedback loops to maintain physiological homeostasis of the body. hypothalamus.  A region in the diencephalon located rostral to the thalamus, functioning as the “chief executive officer” for maintaining homeostasis and autonomic functions of the body. H-zone.  Location on either side of the M-line. The H-zone contains only myosin.

I I-band.  Light striation of the sarcomere. Comprised of actin

only.

ideomotor apraxia.  A condition characterized by patients

unable to perform voluntary movements, but able to perform the same actions if triggered as part of a habit or rote cue. immunoglobulins (Ig). Antibodies of immune system responsible for neutralizing pathogens. indirect motor systems.  Elements of the motor control system that influence LMN activity through the primary motor cortex and the premotor cortex. Indirect systems include the basal ganglia and the cerebellum. indirect pathways of the basal ganglia.  Organization of interconnected nuclei that leads to suppression of motion. Consists of the striatum, globus pallidus external, subthalamic nucleus, and the complex of the globus pallidus internal and the substantia nigra pars reticulata. infarct.  Cell or tissue death/injury related to a loss of blood supply. inferior cerebellar peduncle (ICbP).  One of three massive fiber tracts connecting the cerebellum with the brainstem. Transmits inputs to the cerebellum from the spinal cord and medulla. inferior colliculus (IC).  Located in the midbrain tectum, the inferior colliculus receives input from the superior olivary complex and the cochlear nucleus. Active in the development of auditory space and serves an integrative function to detect sounds of different time durations and frequencies. inferior frontal gyrus (IFG).  Broadest and most ventral of the three horizontal frontal gyri. Subdivided into the pars triangularis, pars orbitalis, and pars opercularis. Also known as the third frontal convolution in older terminology. Houses Broca’s area, a region associated with syntactic and semantic processing of language, reading, and speech motor control. inferior longitudinal fasciculus (ILF).  Association fiber tract within the occipitotemporal gyrus that interconnects the temporal and occipital lobes. inferior occipital gyrus.  The ventral set of gyri found on the lateral aspect of the occipital lobe.

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inferior occipitofrontal fasciculus (IOF). Association

fiber tract extending the entire ventral length of the hemisphere and interconnecting the frontal and occipital regions. inferior olivary complex (IOC).  Complex of several nuclei in the ventral medulla. Located dorsal to the pyramids. Major output is to the cerebellum. Also known as the infe­ rior olive. inferior parietal lobule (IPL).  Subdivision of the parietal lobe that is caudal to the postcentral gyrus and ventral to the superior parietal lobule. Comprised of the supramarginal and angular gyri. inferior sagittal sinus.  A venous system sinus created by the dural folds. Sinus runs along the inferior edge of the falx cerebri and drains into the straight sinus. inferior temporal gyrus (ITG).  Ventral-most temporal gyri. Processes information about the shape, color, and form of visual objects and combines this with somatosensory inputs to recognize complex objects in the environment. inferior temporal sulcus (ITS).  A cortical region in the temporal lobe associated with speech processing at the sentence level. inferior thalamic radiations. See auditory radiations. informed consent.  A critical ethical research standard in which an experimental procedure is performed only with full disclosure and permission of the patient or study participant. infratentorial.  Structures or lesions that occur in the brainstem or cerebellum because of their location below the tentorium of the dura mater. infundibulum.  The narrow stalk of tissue connecting the pituitary gland to the hypothalamus. Allows for movement of secreted substances between the hypothalamus and the pituitary gland. inhibitory.  A neuron cell state in which there is decreased probability for action potential generation. Also related to an increase in charge separation across the cell membrane. inhibitory interneuron.  An interneuron class that expresses inhibitory neurotransmitter, resulting in inhibition of the target postsynaptic neuron. inhibitory postsynaptic potential (IPSP).  Local hyperpolarizing events in the postsynaptic cell created through the opening of postsynaptic ion channels that allow for the influx of negative ions or efflux of positive ions. inner hair cell (IHC).  Three to four thousand cells forming a single row down the length of the organ of Corti. Cells are positioned closest to the central axis of the cochlear spiral. Receive 95% of afferent input from the auditory nerve and are considered the true sensory receptors for hearing. innervation ratio.  Referring to the motor unit, number of muscle fibers innervated by a single LMN. insula.  Considered by some anatomists as the fifth cerebral lobe, the insula is buried deep to the lateral sulcus and can be seen if the temporal lobe and frontal operculum are retracted away from each other. Plays a complex role in

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consciousness, emotion, and maintenance of homeostasis, and is a segment of the default mode network of the nervous system. Also possesses a role in motivational/affective dimensions of speech and language as well as the programming and generation of speech movements. intensity.  The relative magnitude or strength of a stimulus energy source. intentional tremor.  Low-frequency rhythmic oscillations that emerge during skilled and precision voluntary movement. Associated with cerebellar lesions. interaural intensity differences (IID). The acoustic intensity differences between the left and right ears caused by the head shadow effect. Intensity differences between the two ears are used to localized high-frequency acoustic signals. interaural time delay (ITD).  The acoustic timing differences between the left and right ears due to different travel distances of sound from a localized source. Time differences in the arrival of sound between the two ears are used to localize low-frequency acoustic signals. interblobs.  The spaces between color blobs in the visual cortex. intermediate acoustic stria.  Axons of octopus cells in the VPCN that cross midline and project to the contralateral lateral lemniscus. intermediate cerebellum.  Segment of the cerebellum that appears to be involved in sensorimotor integration and speech motor control. intermediate zone.  A region of spinal gray matter comprised of interneurons mediating protective reflexive activity and neural circuits that underlie coordinated sensorimotor behaviors. Intermediate zone neurons project short distances to interlink sensory and motor cells in the dorsal and ventral gray of the spinal cord, respectively. internal arcuate fibers.  Fibers originating in the cuneate and gracile nuclei, passing in a curved manner across the midline of the medulla to form the contralateral medial lemniscus. internal capsule (IC).  Massive white matter system of projection fibers situated between the thalamus, caudate, and globus pallidus, and ventral to the corona radiata. Highly organized pathway of corticofugal and corticopetal projection fibers. Consists of an anterior and posterior limb. internal carotid artery (IC).  One of the major arterial branches bifurcating from the common carotid artery. Supplies blood to the brain via the anterior and middle cerebral arteries. internal granular layer.  Layer IV of the cerebral cortex. internal jugular vein.  Principal vein of the neck that carries deoxygenated blood from the venous sinuses back to the cardiopulmonary system. internal medullary lamina.  A prominent Y-shaped ribbon of axons that divides the thalamus into an anterior, medial, and lateral collection of nuclei. internal pyramidal layer.  Layer V of the cerebral cortex.

internal superior laryngeal nerve (iSLN).  Nerve branch

of the superior laryngeal nerve of the vagus system that transduces somatosensory inputs from the inner lumen and mucosa of the larynx. interneurons.  Neurons that enable communication between sensory and motor neurons in the central nervous system. Are often modulatory in function. interoception. Ability to sense stimuli that arise from within the body. interpositus (interposed) nucleus. Deep cerebellar nucleus comprised of the globose and emboliform nuclei. interstimulus interval.  The time delay between two stimulus events. interthalamic adhesion.  A small bridge of tissue connecting the left and right medial thalamic nuclei across the midline. Also known as the massa intermedia. intracerebral hemorrhage. See hemorrhagic stroke. intracortical microstimulation (ICMS).  A neurophysiological method that uses electrical current to excite cortical neurons while simultaneously monitoring for muscle twitching in the body. Method allows for understanding the relationship between the activity of neurons in motor areas and evoked muscle contractions. intrafusal fibers.  Highly specialized excitable fibers that operate as sensory organs to detect the amount and rate of length change of skeletal muscles during contraction. Found within the fibrous capsule of the muscle spindles. intraparietal sulcus.  Sulcus separating the superior parietal lobule from the inferior parietal lobule. intraventricular foramina.  Canal connecting the lateral ventricles to the 3rd ventricle and allowing for circulation of CSF between the two. Also known as the foramen of Monro. introns.  The segments of DNA sequences lying between two exons that do not play a role in coding amino acids. Introns are removed during mRNA. invariant features.  Characteristics of a motor program that do not change regardless of the different degrees of freedom and synergies used to achieve a movement goal. inverse model.  The use of resultant sensory information to fine-tune future feedforward commands in an open-loop system. ion.  An atom that has lost or gained an electron, thus taking on an electrical charge. Positive ions have lost an electron (number of protons exceeds number of electrons). Negative ions have gained an electron (number of protons is less than the number of electrons). ion channel.  Collections of proteins configured into a tunnel-like structure spanning a cell membrane. Operates to connect intra- and extracellular fluids and allows for ion motion through the cell membrane. Ion channels are selectively permeable and come in passive and gated forms. ionotropic receptors.  Ion channels (receptors) that are chemically gated, resulting in immediate permeability changes to the cell membrane for an ion.

GLOSSARY

ion pumps.  Protein transporters that aid in the mainte-

nance of ion distributions in a neuron by actively transporting ions against their passive concentration gradients. Examples include the Na+-K+ pump and Ca2+ transporters. iris.  Circular structure in the eye that regulates the diameter and pupil size, thus controlling the amount of light to reach the retina. Eye color is established by the pigmented upper layer. ischemic stroke.  A form of stoke resulting from the blockage of blood flow through a vessel, generally due to a blood clot or arteriosclerotic plaque. Also known as an embolic stroke.

J jaw-jerk reflex.  A reflexive response of the trigeminal sys-

tem created through rapid stretching of spindle sensory receptors of the masseter and temporalis muscles. Results in rapid jaw closure. junctional folds.  Invagination of the sarcolemma at the motor end plate. Uwe Jürgens.  German zoologist and communication neuroscientist specializing in mammalian vocalization. Key figure in the development of our understanding of the neural substrate for vocalization in primates and humans. just noticeable difference (JND).  The minimal difference or change in strength between a reference stimulus and a second stimulus whereby a difference can be detected.

K kinetic energy.  Energy possessed by a mass produced from

its motion.

knockout and knock-in animals. Test animals that

are specifically bred and genetically engineered with a gene either removed (knockout) or added or substituted (knock-in). These types of animal models are developed to test for the physiological and genetic foundations of normal behavior and diseases conditions that are found in the human. Patricia Kuhl.  Developmental speech and language neuroscientist from the University of Washington, Seattle. She developed the social gating hypothesis and was one of the first to suggest that babies learn language through a process of statistical learning.

L labeled-line principle.  Foundational concept of sensory

neuroscience stating that information from a specific receptor travels over specific pathways to specific parts of the nervous system for processing and interpretation. As such, the modality (or submodality) of a sensation depends on which cell, pathway, nucleus, or lobe is activated by the stimulus input.

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language.  A set of arbitrary symbols, agreed upon by a

community, which can be combined to communicate an infinite number of concepts between community members for social cooperation and information transfer. large spherical bushy cells.  A subcategory of spherical bushy cells found in the anterior ventral cochlear nucleus that receive low-frequency inputs from the auditory nerve fibers and outputs bilaterally to the medial superior olivary complex. laryngectomy.  The surgical removal of the larynx due to disease or trauma. larynx.  A cartilaginous anatomical structure that separates the upper and lower airway. Contains the vocal folds, which serve as a valve to protect the airway and for generation of sound during speech and vocalization. lateral collection of thalamic nuclei. Constitute most of the thalamic mass. Region is subdivided into a lateral and ventral tier. The ventral tier is divided into the ventral anterior, ventral lateral, ventral posterior, ventral posterolateral, and ventral posteromedial nuclei. The lateral tier nuclei consist of the lateral dorsal, lateral posterior thalamic, and pulvinar nuclei. lateral corticospinal tract.  Key descending fiber pathway that innervates LMNs of distal muscles used for skilled actions. Tract originates from contralateral hemisphere, decussates in the medulla, and runs through the lateral fasciculus of the spinal cord. Comprises 90% of all descending corticospinal tract projections. lateral dorsal thalamic nuclei (LD).  One of the lateral tier nuclei of the thalamus. lateral fasciculus.  Lateral most region of white matter in the spinal cord. lateral geniculate nucleus (LGN).  Nucleus of the thalamus receiving visual information from the optic tracts. The LGN is retinotopically organized and consists of six layers that receive inputs from different classes of retinal ganglion cells. lateral hypothalamic nucleus.  Nucleus extending across the entire rostral-caudal dimension of the hypothalamus. Helps to regulate cardiovascular operation and water/food intake. lateral inhibition.  A contrast enhancement mechanism whereby the activity of one receptive field is heightened through inhibition of adjacent receptive fields. lateral lemniscus.  Tract of axons that transmits auditory inputs from the cochlear nucleus to the inferior colliculus within the central auditory pathway. lateral medullary syndrome.  Often referred to as Wallen­ berg’s syndrome. Arises from vascular damage to the posterior inferior cerebellar artery and/or the vertebral arteries of the brainstem. Hallmark characteristics of the syndrome include loss of temperature and nociceptive (pain) sensation from the contralateral side of the body below the neck and on the ipsilateral face. Patients also present with loss of the gag reflex, vocal hoarseness, and speech and swallowing deficits.

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lateral posterior thalamic nucleus (LP).  One of the lat-

eral tier nuclei of the thalamus. lateral sulcus.  A deep horizontal and oblique running sulcus separating the temporal lobe from the frontal and parietal lobes. lateral superior olivary complex (LSOC).  The lateral portion of the superior olivary complex that receives inputs of high-frequency information from the small spherical bushy cells of the cochlear nucleus. Cells in the LSOC respond preferentially to intensity differences between the ears, allowing for the ability to localize high-frequency inputs. lateral tract of the ALS.  The lateral tract of the anterolateral system is located in the lateral funiculus of the spinal cord. Conveys inputs from lamina I related to nociceptive and thermal peripheral inputs. lateral ventricles.  Large, paired chambers of the ventricular system in the brain, filled with cerebrospinal fluid. Transmitted inputs play a role in perception of sharp pain, burning pain, cool, warmth, itching, and visceral sensations. lateral vestibulospinal tract.  Projects from the lateral vestibular nucleus and descends ipsilaterally through the brainstem and the anterior white matter of the spinal cord. Fibers exit the tract and innervate ipsilateral LMNs that control limb extensor muscles that help maintain balance and upright posture. L-cones.  Cones sensitive to long wavelengths of EM energy in the red end of the spectrum. learned nonuse.  Behavioral conditioning experiences that result in a human learning not to use a damaged system (e.g., weakened limb, impaired speech/language). It is presumed that use of the damaged system is punished by factors such as pain and lack of success, resulting in the suppression of use of the damaged element. lemniscus.  A ribbon-like band of axons in the central nervous system. length-tension relationship. The starting length of a sarcomere influences the active force that can be generated. This relationship is based on the availability of crossbridges that can be generated and is correlated to the degree of overlap between the thin and thick myofilaments. lens.  A biconvex-shaped structure of the anterior eye suspended in place about its perimeter by zonule fibers. Lens operates as the light focusing element of the eye. lens accommodation. Lens adjustment process that depends on focal distance. lenticular fasciculus.  One of two pathways that interconnect the GPi output nucleus to the ventroanterior and ventrolateral nuclei of the thalamus. lesion.  Injury or damage to a body area negatively affecting the area’s health, structure, and function. ligand gated receptor (channel).  Receptor channels that open in response to a specific chemical signal. ligands.  Chemicals that directly bind and gate ion channels.

limbic association areas.  Association areas of the limbic

system that subserve behaviors spanning from memory formation to emotional regulation to hypothalamic function. limbic lobe.  A term originally coined by Paul Broca, but elaborated by James Papez and Paul MacLean. Recognized today as that region of the central and medial cerebrum responsible for emotional regulation, learning, memory, and instinctual regulation. limbic system. The collection of structures working as the emotional regulatory system in the cerebral cortex. Includes the hypothalamus, hippocampal formation, amygdala, cingulate gyrus, septal area, and hypothalamus. lingual gyrus.  Gyrus ventral to the calcarine fissure of the occipital lobe. localization. Function of the superior olivary complex that involves using differences in intensity and timing disparities to identify the location of a sound source in the environment. locked-in syndrome.  A condition typically associated with bilateral damage to the brainstem resulting in complete paralysis of all voluntary muscles except those involved in selected eye movements. locus ceruleus (LC).  Blue-tinted nucleus within the pons that contains neurons that expresses norepinephrine. Active during physiological responses to heightened levels of stress and panic. longitudinal cerebral fissure.  Major fissure that separates the left and right cerebral hemispheres from each other. long-term potentiation (LTP).  Key synaptic strengthening mechanism that generates a long-lasting increase in signal transmission between the pre- and postsynaptic neurons. Created through synchronous inputs to a synapse. Considered one of the major mechanisms underlying learning, memory, and neuroplasticity in the brain. lower motor neuron (LMN).  Also known as the lower motoneuron. Efferent cells found within the ventral gray of the spinal cord and in brainstem motor nuclei. Lower motor neurons innervate muscles and glands directly. Considered the final common pathway for descending efferent signals to skeletal muscle tissue. lumbar region of vertebral column.  Vertebral column segment that lies above the sacral and directly below the thoracic region. Consists of a plate of five to six massive vertebrae. Designed to support the mass of trunk. Alexander Luria.  A pioneering Russian neuropsychologist who described the cognitive region of the frontal lobe as the “organ of civilization” due to its role in processes underlying the ability to reason and contemplate our own existence in the world.

M Paul MacLean.  American neuroscientist who extended the

work of James Papez. He expanded on the Papez circuit to

GLOSSARY

include the amygdala and the orbitofrontal cortex, and was responsible for coining the term “limbic system.” macroglia.  Major category of glial cell that include the oligodendrocytes, Schwann cells, and astrocytes. macrophages.  A category of white blood cell that aids the immune system by consuming foreign bodies and pathogens. macula.  Layer of specialized epithelium found in the otolith organs housing vestibular hair cells. magnetic resonance imaging (MRI).  Neuroimaging method to examine both the structure of the brain and brain activation (via blood flow) using arrays of magnetic fields oriented in different planes. Very good spatial resolution, but poor temporal resolution. magnetoencephalography (MEG).  Neuroimaging method to examine brain activation using superconducting quantum interference devices (SQUIDs) placed around the scalp to generate magnetic fields. MEG has excellent temporal resolution with better spatial resolution than EEG. magnitude estimation. A test that allows participants to use a numerical scale to estimate the magnitude of a stimulus. magnocellular layers of the lateral geniculate nucleus (LGN).  Layers 1 and 2 of the LGN that receive M-type

retinal ganglion cell inputs.

magnocellular (M-type) retinal ganglion cells. Rapidly

adapting retinal ganglion cells that transmit information regarding motion, onset/offset of light conditions, and the detection of edges. Considered the origin of the dorsal visual processing stream. Projects to Layers 1 and 2 of the LGN. mammillary bodies.  Roundish structures in the diencephalon and ventral to the mass of the midbrain. Considered a part of the limbic system. Play a fundamental role in the regulation of memory, emotion, and instinctual animal behavior. mandibular branch of facial nerve. A branch of CN VII innervating lower facial muscles. mandibular branch of trigeminal (V3).  A branch of the trigeminal nerve innervating lateral skin of the lower face, lower lip, chin, part of the superior oral mucosa, lower dental arch, anterior two thirds of the tongue surface (tactile), external auditory canal, and proprioceptive sensory endings detecting mandibular muscle contraction. massa intermedia. See interthalamic adhesion. massed practice.  Completion of many trials of a single activity in rapid succession without interruption. Massed practice is also sometimes referred to as intense or intensive therapy. maxillary branch of trigeminal (V2).  A branch of the trigeminal nerve innervating the middle facial skin area, nasal mucosa, maxillary sinuses, parts of the superior oral mucosa, and the teeth of the upper arch. Also known as the infraorbital branch of the trigeminal nerve.

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M-cones.  Cones sensitive to medium wavelengths of EM

energy representing the green end of the spectrum.

mechanically gated channels.  Ion channels that open

and close in response to physical changes to the membrane in which the channel is embedded. mechanical nociceptive endings.  Nociceptors that selectively transduce tactile inputs that mechanically damage tissue. mechanoreceptors.  Primary receptors responsible for encoding information regarding touch, hearing, balance, proprioception, and pain. Mechanoreceptors respond to physical deformation and displacements. medial collection of thalamic nuclei.  The medial division of the thalamus. Consist mostly of the dorsomedial thalamic nuclei. medial forebrain bundle.  A major afferent pathway within the lateral hypothalamic zone allowing for communication between the forebrain and hypothalamus. Aids in mediation of information related to one’s emotional state and motivation. medial geniculate body (MGB).  Receives inputs from the IC and is the first location where neurons are activated by specific combinations of sound frequencies or are sensitive to specific time delays between the presentation of two frequencies. medial lemniscus (ML). Massive somatosensory tract originating from second-order neurons in the cuneate and gracile nuclei. Tract passes through the entire brainstem and into the diencephalon. Fibers transmit tactile and proprioceptive inputs from the spinal cord to the ventroposterolateral nucleus of the thalamus. medial longitudinal fasciculus (MLF).  White matter tract located centrally in the brainstem. Comprised of a set of crossed fibers with both ascending and descending projections. Considered the location of the vestibulospinal and tectospinal tracts, which innervate muscles of the neck and upper trunk. medial nucleus of the trapezoid body (MNTB).  A subregion through which the ventral pathway of the cochlear nucleus passes to reach the superior olivary complex. medial olivocochlear bundle. Efferent pathway that projects from the superior olivary complex to the cochlear nucleus and then to the cochlea. Medial OCB fibers make direct connections to the outer hair cells and are thought to have primarily inhibitory effects to protect the hair cells against overstimulation. medial prefrontal cortex (MPFC).  Functional subdivision of the prefrontal cortex. Constitutes the frontal lobe tissue on the medial wall of the cerebral hemisphere, and occasionally includes the anterior cingulate cortical area. medial superior olivary complex (MSOC).  The medial portion of the superior olivary complex that receives low-frequency inputs from the large spherical bushy cells of the cochlear nucleus. Plays a role during the detection of interaural timing differences.

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medial temporal lobe.  Medial-most region of the tempo-

ral lobe situated next to the midbrain. Subdivided into the parahippocampal gyrus, uncus, and entorhinal cortex. Not the same structure as the middle temporal gyrus. medial vestibulospinal tract.  Tract that originates from the medial vestibular nucleus and descends bilaterally through the brainstem in the medial longitudinal fasciculus. Innervates LMNs of neck muscles, specifically those of the spinal accessory nerve. Pathway activity leads to rotation and lifting of the head, and reflexive responses of neck muscles to sudden and unexpected changes in position and orientation. medulla oblongata. The component of the brainstem closest to the spinal cord that acts as a passageway for axon tracts for motor and sensory communication to higher areas of the central nervous system. Critical for behaviors including hearing and balance, swallowing and voice, motion of the head, motion of the tongue, and especially cardiovascular and respiratory function. medullary respiratory center.  Respiratory neural centers in the medulla that control respiration rate and the depth of breathing on a cycle-by-cycle basis through feedback from several different classes of sensory endings embedded within the tissues of the respiratory system. Consists of dorsal respiratory group neurons, ventral respiratory group neurons, and the pre-Bötzinger complex. medullary reticulospinal tract.  Projects from the reticular formation of the medulla and innervates proximal extensor muscles of the lower limbs. Tract inhibits voluntary movement and decreases muscle tone. Meissner corpuscle.  Form of cutaneous mechanoreceptor with small receptive fields that respond best to low-frequency vibration, object friction, and skin motion during movement. Classified as an RA Type I fiber. membrane permeability.  The rate and ease with which ions can pass through a neuron’s cell membrane. membrane potential (Vm).  Voltage across a cell membrane resulting from the unequal distribution of ions and the differences in electrical charge between the intracellular and extracellular spaces. Memory-Unification-Control (MUC) model. Language-​ processing model that includes the following: (a) temporal and parietal areas for storing knowledge of phonology, morphology, syntax, and semantics; (b) frontal areas important for the assembly of these different pieces of knowledge into larger structures (e.g., phrases, sentences); and (c) frontal areas involved in the selection and usage of these unified structures so that context of the communication exchange is accounted for, the correct language is selected, turn-taking and other social mores are followed, and salient information is attended to. meninges.  Layers of nonneural connective tissues that completely encapsulate the CNS. Form a resilient, but flexible protective framework around the CNS. Consist of the dura mater, arachnoid layer, and the pia mater.

mental time travel.  The ability in humans and some ani-

mals to imagine things other than in the present moment. Includes remembering things that have happened in the past and imagining things that might happen in the future. Merkel discs.  Form of cutaneous mechanoreceptor with small receptive fields and sensitivity to edges, corners, and point-like surfaces, responding best to vibration frequencies below 5 Hz. Classified as SA Type I fibers mesencephalic nucleus of trigeminal.  Trigeminal sensory nuclei located in the midbrain. Considered the proprioceptive center of the trigeminal system, receiving muscle spindle activity from muscles of the jaw and mechanoreceptive inputs from periodontal ligaments. mesencephalon.  Uppermost segment of the brainstem, bounded rostrally by the diencephalon, caudally by the pons, and dorsally by the cerebellum. Region plays a role in coordination of movement, action initiation, regulation of ocular muscles, and reflexes related to vision and hearing. Also known as the midbrain. mesoderm. The middle cell layer making up the early human embryo. Matures to become the skeletal system and muscle tissue. messenger ribonucleic acid (mRNA).  A form of ribonucleic acid that works as a transporter of genetic coding for proteins from the nucleus to the ribosomes. metabotropic receptors.  Cell membrane–bound receptors that operate to initiate the activation of second messenger pathways in a neuron. A receptor is directly activated by a neurotransmitter, which in turn activates membrane-bound intracellular proteins. metencephalon. Segment of the embryonic brain that matures from the rhombencephalon to become the pons and cerebellum. method of limits.  Psychophysical method to measure a person’s perception of a stimulus by determining at what level the stimulus is perceived. Ascending method of limits requires a person to report on a stimulus that begins at undetectable levels and increases in magnitude until it becomes minimally detectable. Descending method of limits begins with a reliably detectable stimulus intensity that gradually decreases until the person can no longer perceive it. microfilaments. The thinnest fiber of the cytoskeleton matrix. Consists of actin. microglia.  A type of glial support cell in the central nervous system with phagocytic functions that works to remove necrotic cells or other cellular waste products. microtubules.  Hollow, tube-like components of the cytoskeleton, made of tubulin. middle cerebellar peduncle (MCbP).  One of three massive fiber tracts connecting the cerebellum with the brainstem. Transmits inputs to the cerebellum from the basilar pontine nuclei. middle cerebral artery (MCA).  Major branch of the internal carotid artery supplying blood to the lateral aspects of

GLOSSARY

the cerebral hemispheres. Divided into an upper and lower MCA segment. middle frontal gyri (MFG).  The center gyrus of the three horizontal frontal lobe gyri extending from the precentral sulcus to the most rostral tip of the cerebrum. middle temporal gyrus (MTG).  The middle of three distinct gyri making up the lateral temporal lobe. middle temporal sulci (MTS).  Sulci separating the middle and inferior temporal gyri. midsagittal plane.  The anatomical plane that divides the brain, or other structures, into an exact and symmetrical left and right half. mirror neurons.  Class of neuron first identified in the premotor cortex of primates. Activity of mirror neurons increases when a primate is engaged in planning a motor movement, and when the animal is also observing a related movement performed by another primate. Mirror neurons may represent a means for social animals to learn from one another through imitation and subsequent attempts of a perceived action. mitochondria.  Organelle commonly referred to as the powerhouse of a cell and responsible for cellular respiration and the generation of ATP. mitral cells.  One of the two major types of projection neurons of the olfactory bulb that operate as second-order neurons and project to cerebral targets. mixed nerves.  Peripheral nerves that contain axons of both motor and sensory neurons. M-line.  Located in the center of the H-zone. M-line is a seam comprised of accessory proteins that help anchor myosin filaments to one another end-to-end. modality. The general class and form of sensory stimuli available to the nervous system: somatosensation, hearing, balance, vision, smell, and taste. model.  A simplified conceptualization of an object or phenomenon that shares key characteristics with the object or phenomenon found in nature. modiolus.  Cone-shaped central core of the cochlea. molecular biology.  The study and analysis of genes, macro­ molecules, and chemical cell products in living matter. molecular layer.  The most superficial layer of the cerebral cortex (Layer I) containing a web of axon segments and dendrites originating from neurons in the lower layers of the cortex. monochromatic.  Black and white vision. monocular visual field.  The portion of the visual field mediated by each individual retina. monosodium glutamate (MSG).  Sodium salt of glutamic acid and a substance found in foods that are strongly related to the umami tastant class. monosynaptic.  Involving a single synapse. Contrast with polysynaptic. motor control.  The ability to regulate and direct the mechanisms essential for human movement, or the capacity for a motor system to match the intended and actual output of a the motor system.

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motor coordination.  The process by which multiple mus-

cle groups are made to work seamlessly and smoothly together during behavioral performance. motor endplate.  Specialized region of the sarcolemma within the NMJ complex. Contains the junctional folds and possesses ACh receptors. Intracellular spaces about an endplate contain abundant numbers of mitochondria and nuclei, attesting to the high energetic and metabolic requirements of this region. motor endplate potential (MEP).  Local depolarization that results from NMJ activity. motor equivalence.  The ability of the motor control system to accomplish the same movement goal using a variety of different combinations of degrees of freedom (behavioral elements). motor learning.  The way motor and sensory information interacts to acquire a new skill. motor nerves.  Peripheral nerves that contain only axons of motor neurons. motor neuron pool.  Also known as a motoneuron pool. Collection of motor neuron cell bodies associated with a given muscle or muscle group. motor nucleus of trigeminal.  Located in the pons, this trigeminal nucleus contains lower motor neurons that innervate the muscles of mastication, tensor tympani, tensor veli palatini, mylohyoid, and anterior belly of digastricus. motor skill.  The ability to coordinate volitional movements from a variety of muscles into a recognizable pattern for accomplishing a movement goal. motor speech disorder.  Deficits in planning and execution of the speech production processes due to neurological damage. motor unit (MU).  Smallest unit controlled by the motor control system. Defined as the LMN plus all its innervated muscle fibers. Vernon Mountcastle. Pioneering neuroscientist from Johns Hopkins University responsible for critical findings on the basic operations of cortical function and sensory neurophysiology. movements.  The behavioral characteristics of the body’s muscles, bones, joints, and so forth that are involved with carrying out motor skills. multiform layer.  Layer VI of the cerebral cortex. Outputs to thalamus, spinal cord, and brainstem. multimodal integration.  The study of how information from our different sensory modalities is integrated by the nervous system. Also known as multisensory integration. multipolar cells.  Common form of neuron cell type consisting of an axon with profuse branches of dendrites extending from the cell body. muscle spindles.  Proprioceptive receptors in muscle that detect changes to dynamic and static contraction. Innervated by Ia afferents. muscle twitch.  Contraction response of a single muscle fiber to a single stimulus event. Consists of the latent period, contraction, and relaxation phases.

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muscular hydrostat.  Muscular organ system that lacks any

internal skeletal or cartilaginous framework. Tissue can create complex three-dimensional changes in volume and shape of the muscular organ. mutism.  A general term that means the absence of speech. Mutism can arise from lesions to a variety of regions within the central nervous system. myelencephalon.  Segment of the embryonic brain that matures from the rhombencephalon to become the medulla. myelin.  Fatty protective covering around axons that allows for faster conduction of electrical signals. Formed by oligodendrocytes in the central nervous system and Schwann cells in the peripheral nervous system. myoblasts.  Embryonic cells with the potential to become muscle fibers. myofiber.  Another term for muscle fiber or muscle cell. myofibril.  Largest subcellular element of the muscle cell. Comprised of myofilaments and chains of interconnected sarcomeres. myofilaments.  Any of the ultramicroscopic thread-like elements comprising a myofibril. Thick myofilaments consist of myosin, whereas thin myofilaments consist of actin. myogenesis.  The process by which muscle fibers/cells are created. myoglobin.  Oxygen-binding protein found in great quantities in muscle fibers that use oxidation to create ATP. Gives muscle fibers a reddish hue. myosin.  Protein that comprises the thick filament in the myofibril. Myosin is known for its molecular motor operations during muscle contraction. myosin adenosine triphosphatase (ATPase). Enzyme that hydrolyzes ATP when ATP is attached to the myosin head.

N nasal monocular visual hemifield.  The half of the visual

field for one eye, which exists in the visual space on the same side as your nose. nasal retina.  Region of the retina positioned toward the nose. negative neurological signs.  Constellation of motor signs that indicate loss or absence of normal movement operation and function. neologism.  Error in word production where the word produced is not a real word in the language, but follows the phonological rules of the language. Nernst equation.  Mathematical equation used to predict and calculate individual equilibrium potentials for ions acting on a neuron. nerve fascicle.  A bundle-like structure of axons in the peripheral nervous system. nerves. A bundle of axons in the peripheral nervous system that transmit impulses between the body and the brain. Can be different diameters and lengths.

neural crest cells.  Cells that differentiate from the ecto-

derm to become melanocytes, cartilage and bone, smooth muscle, glial cells, and tissues of the peripheral and enteric nervous systems. neural folds.  Ridge-like structure arising during embryonic neurulation and found on the lateral edges of the neural plate. These cells further differentiate into neural crest cells. neural groove.  Expanse of cells arising during embryonic neurulation, located in the midline region of the neural plate. The neural groove undergoes rapid growth that results in a buckling and an invagination of this tissue inward, eventually forming the neural tube in the embryo. neural integration.  The summation of postsynaptic potentials, both excitatory and inhibitory, within a neuron. neural networks.  A group of neurons interconnected to one another that share common inputs and outputs and participate together during a given behavior. May also be referred to as neural ensembles, neural circuits, and neu­ ronal groups. neural plate.  An embryonic developmental structure that is the foundational tissue for the nervous system. Neural plate cells differentiate from the ectoderm through chemical signaling provided by the notochord. neural signaling.  The process of information being generated and transmitted by neurons to target sites and structures. neural tube. The embryonic structure that matures to become the CNS. The neural tube is formed through the invagination of the neural groove inward in the developing embryo. neuraxis.  Longitudinal (long) axis of the central nervous system. neurocognitive disorders.  A wide variety of chronic and progressive brain diseases or differences. Memory and at least one other cognitive function (including language) are the primary behavioral deficits and must arise gradually. neurofilaments.  Protein polymer fibers found within the cytoplasm that contribute to formation of the neuron’s cytoskeletal structure. Provides internal structural support for axons. neuromuscular junction (NMJ).  Chemical synaptic complex created between the LMN axon terminal and the muscle fiber’s sarcolemma. neuron.  Excitable cells of the nervous system capable of signal integration, generation, and transmission. Considered the basic unit of the nervous system. neuropathic pain.  Pain resulting from injury or disease conditions to regions of the somatosensory pathway, either centrally or in the periphery. Examples include trigeminal neuralgia and phantom limb syndrome. neuropeptides.  Protein-like molecules operating as nonclassical neurotransmitters. Behave in an indirect and modulatory manner through metabotropic receptors. neuroplasticity.  Derived from the notion of a structure that is moldable, neuroplasticity is the general ability of

GLOSSARY

the nervous system to structurally change and functionally adapt in a context- and input-dependent manner. Considered a fundamental neurobiological process that allows animals to adapt their sensorimotor performance and behavior throughout their lifetime to conform to different environmental conditions. neuroscience.  The field of study with the central goal of developing and expanding our appreciation of how the nervous system functions and contributes to all aspects of behavior related to animal life. neurotransmitters (NTs).  Chemical substances stored in synaptic vesicles within the presynaptic terminals that are expressed via vesicle exocytosis to gate open postsynaptic ion channels. neurulation. The differentiating and folding process by which ectodermal cells are transformed into the tissues of the neural tube and crest. Begins approximately 3 weeks after conception. nigrostriatal fibers.  Axons that interconnect the substantia nigra to the striatum in the basal ganglia. Nissl stain.  The method of staining used primarily on tissues of the nervous system to observe parts of a neuron, especially the cell body. nitric oxide (NO).  A gas functioning as a nonclassical neurotransmitter. Used during retrograde messaging to influence presynaptic terminal operation. nociception.  The encoding and processing of harmful or injurious stimuli that will later be consciously perceived as pain. nociceptive pain.  Pain that emerges as a result of direct activation of nociceptive sensory endings by nociceptive types of stimulus inputs. Examples include cutting your finger or spraining a joint. nociceptors.  Sensory nerve endings that respond to stimulus events that can cause tissue injury and damage. Nociceptors fall into two major classes: the A-delta and the C-fibers. Those that respond to thermal, mechanical, and chemical events are called polymodal nociceptors. nodes of Ranvier.  Exposed gaps of axolemma (cell membrane surrounding the axon) in a myelinated axon. Nodes contain the needed cellular elements for action potential regeneration. nonglabrous skin.  A form of skin that possess hair follicles. Nonglabrous skins form the vast majority of the skin found in mammals. noninvasive brain stimulation.  Any of several techniques that use magnetic or electrical currents over the scalp to induce changes in the brain. Depending on the technology, these techniques may cause or prevent action potentials. nonregulatory conditions.  Irrelevant features within the environment that are not used by the motor control system for planning, executing, and evaluating goal-oriented actions. norepinephrine (NE).  Organic molecule acting as a neurotransmitter that is produced primarily in the locus ceru-

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leus (alternative spelling, coeruleus) in the CNS and in sympathetic ganglion in the PNS. notochord.  A long rod-like element of the embryo that lies underneath the ectoderm. Chemical signaling from the notochord drives the differentiation of the ectodermal cell layer into the neural plate. nucleus (nuclei). Collections of cell bodies making up a form of gray matter in the central nervous system. nucleotide.  A complex organic molecule comprised of a nitrogen-based molecule (adenine, guanine, thymine, or cytosine) and its paired sugar. Chains of nucleotides form DNA strands. nucleus accumbens.  Small nuclear structure of the ventral striatum. Active in motivation and cognitive processing of aversive events and reward. Known as the pleasure center of the brain. nucleus ambiguus (NA).  Located in the reticular formation of the medulla. Principal motor nucleus controlling muscle tissue innervated by the vagus and glossopharyngeal cranial nerve systems. nucleus of the solitary tract (NTS). See solitary nucleus. nystagmus.  A condition in which the eyes produce repetitive and uncontrolled reflexive movements. Movements often result in reduced visual and depth perception. Also affects balance and coordination.

O obex.  A distinctive V-shaped gap or depression in the dorsal

medulla forming the caudal segment of the 4th ventricle. Contains the trigones consisting of the underlying nuclei for CN X and CN XII. occipital bone.  Curved, plate-like bone of the cranium found in the posterior part of the skull. Occipital bone articulates with the atlas and the axis of the cervical vertebrae. occipital lobe.  The posterior-most region of the cerebrum, chiefly responsible for the processing of visual stimuli. The occipital lobe contains the primary visual cortex. occipitotemporal gyrus. Also known as the fusiform gyrus, the occipitotemporal gyrus is found on the ventral surface of the cerebrum between the lingual gyrus and parahippocampal gyrus. Functionally active during object recognition. octopus cells.  Cells in the dorsal region of the posterior ventral cochlear nuclei with outputs to the contralateral lateral lemniscus and superior olivary complex. Respond to a wide range of frequencies with an onset PSTH pattern and are sensitive to rapid timing differences in sounds with wide frequency bandwidths. ocular dominance columns.  Basic means of organizing visual processing from the right versus the left visual hemifield in the primary visual cortex. oculomotor nerve (CN III).  One of three motor cranial nerves that mediate movement of the eyes and eyelids.

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Innervates the medial rectus, superior and inferior rectus, and inferior oblique muscles of the eye. Also innervates the levator palpebrae superior muscle of the upper eyelid. oculomotor nucleus.  Motor nucleus of the midbrain tegmentum innervating muscles of the eye. Axons of the oculomotor nucleus become the fibers of CN III. odorant.  A chemical substance that elicits a response from the olfactory system. OFF-bipolar cells.  Bipolar cells that depolarize when photoreceptors are in the dark and hyperpolarize when in light. OFF-center receptive field.  A center-surround receptive field for an OFF-bipolar cell. ohm.  The standard unit of measurement for electrical resistance. Pronounced like the Buddhist mantra /Om/, a chant used to bring peace to the mind and soul. Especially useful for stressed-out students learning neuroscience for the first time. Ohm’s law.  Electrical theory describing the relationship between voltage (V), current (I), and resistance (R), whereby V = I*R. olfaction.  The psychological perception of smell. olfactory bulb and tract.  Prominent central olfactory system structures overlying the gyrus rectus on the ventral surface of the frontal lobe. Olfactory bulb receives primary afferent inputs from olfactory receptor neurons. Second-order neurons of the olfactory bulb project to ventral regions of the cerebrum via the olfactory tract. olfactory cilia. Tentacle-like filaments embedded within the olfactory epithelium and mucous layer. Formed by the peripheral end of axons belonging to olfactory receptor bipolar neurons. olfactory epithelium.  Sheet of tissue deep in the superior area of the nasal cavity housing the receptive endings of the olfactory receptor neuron. olfactory nerve (CN I).  Special visceral afferent cranial nerve mediating our special sense of smell. olfactory receptor neuron (ORN).  Bipolar cell that is the primary afferent for the olfactory system. Transduces odorant molecules that bind olfactory epithelium cilia. olfactory system.  Functional and structural system of smell that allows for the detection, transduction, and perception of chemical odorants. olfactory tubercle.  Considered a multimodal area that integrates olfactory information with visual and auditory inputs. Together with inputs from arousal and reward regions of the brain, the olfactory tubercle allows for the localization of an odorant’s source. oligodendrocytes. A macroglial cell that forms myelin about numerous axons in the central nervous system. olivary eminence.  An anterior medullary landmark that consists of the underlying inferior olivary complex nucleus. olivocochlear bundle (OCB). Efferent pathway of the auditory system consisting of a medial and lateral component. Thought to have primarily inhibitory effects on audi-

tory nerve function during soft sounds and may operate to reduce the effects of the cochlear amplifier. ON-bipolar cells. Bipolar cells that are hyperpolarized when the photoreceptor is in the dark and depolarized when in light conditions. ON-center receptive field.  A center-surround receptive field for an ON-bipolar cell. onset PSTH response.  A response pattern characterized by a brief powerful burst of activity at the onset of an acoustic input. open-loop system.  A system that executes motor commands without the need for feedback from the environment. open system.  A system that is capable of exchanging information with the environment to organize and tune itself. ophthalmic branch of trigeminal (V1).  A branch of the trigeminal nerve innervating skin of the upper face and scalp, surfaces of the eye, and meninges encapsulating the brain. opsin.  Protein that combines with retinal to form a functional photopigment. optic chiasm.  An X-shaped structure formed at the point where axon fibers from the optic nerve cross the midline and are segregated into axonal groups that transmit visual inputs from either the left or right visual fields to the contralateral cerebral hemisphere. Located ventral to the mass of the midbrain. optic disc.  Location where axons of retinal ganglion cells converge to form the origin of the optic nerve. Anatomical location of your blind spot. optic nerve (CN II).  Special somatic afferent cranial nerve mediating our sense of vision. optic radiations.  A dense array of axons that direct outputs from the lateral geniculate nucleus of the thalamus to the primary visual cortex. Also known as Meyer’s loop. optics.  The scientific study of the behavior of light and its interactions with objects in the environment. optic tract. Segregated axons beyond the optic chiasm that transmit visual inputs from either the left or right visual fields to the lateral geniculate nucleus (body) of the thalamus. orbitofrontal cortex (OFC).  Functional subdivision of the prefrontal cortex. Located on the ventral surface of the frontal lobe above the eye orbits and regarded as part of the limbic system. orbitofrontal gyri.  A group of gyri making up the ventral aspect of the frontal lobe. Name is derived from its relative location over the orbits of the eye. Orbitofrontal gyri contain the orbitofrontal cortical area, a region regarded as a segment of the limbic system. organismic constraints.  The characteristics that an individual has at the time of executing a movement goal. Also known as individual constraints. organ of Corti (OoC).  Band of specialized epithelium running along the length of the basilar membrane, functioning as the transduction site for acoustic stimuli.

GLOSSARY

orientation column.  The organization of cells in the visual

primary cortex into clusters with similar orientation processing preferences. orthodromic conduction.  The conduction of an action potential in the typical direction, traveling along the axon away from the soma. otoacoustic emissions.  The spontaneous production of faint tones originating from within the inner ear that can be detected by a sensitive microphone. otoconia.  Small crystals of calcium carbonate in the saccule and utricle of the vestibular system. otolithic membrane.  Gelatinous structure containing the stereocilia of the otolith hair cells. otolith organs.  Located at the base of the vestibular labyrinth and comprised of the utricle and saccule. Provide information regarding linear acceleration as well as static position of the head relative to gravity. outer hair cells (OHCs).  Approximately 12,000 cells forming three rows down the length of the OoC. OHCs are positioned distally to the central axis of the cochlear spiral and receive only 5% of afferent input from the auditory nerve. Involved in actively turning and increasing the sensitivity of the basilar membrane. oxidative phosphorylation.  Metabolic process that requires oxygen and operation of the mitochondria to generate ATP. oxytocin.  A hormone expressed by the paraventricular and supraoptic nuclei regulating social interaction and sexual reproduction. Referred to as the “love hormone.”

P Pacinian corpuscle.  Form of cutaneous mechanorecep-

tor with large receptive fields sensitive to high-frequency vibrations. Classified as an RA Type II fiber. pallidosubthalamic fibers.  Axons that interconnect the globus pallidus and the subthalamic nucleus in the basal ganglia. James Papez.  American neuroanatomist who developed a comprehensive neural description of brain regions active in the control of emotions. The “Papez circuit” includes the hippocampus, cingulate gyrus, hypothalamus, anterior thalamic nuclei, and limbic lobe originally identified by Paul Broca. papillae (sing., papilla). A specialized epithelial tissue found on the surfaces of the tongue that houses the primary sensory complex for taste also known as the taste buds. parabelt region.  Zone of tissue adjacent to the belt region of the auditory association area. Receives inputs from visual and somatosensory sensory systems as well as auditory information from the belt zone. parabrachial nucleus.  Brainstem nucleus located at the junction of the midbrain and the pons. Nucleus receives

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second-order neuron projections carrying taste information from the solitary tract nuclei in the medulla. parahippocampal cortex.  Area of the medial temporal lobe that receives odorant inputs from the olfactory bulb. parahippocampal gyrus.  A subdivision of the medial temporal lobe that extends caudally to the isthmus of the cingulate gyrus. Contains the hippocampal formation deep inside. parallel processing.  Processing mechanism that allows for transduction, transmission, and/or processing of a common source of input by two or more systems or pathways simultaneously. paraphasia.  Production of an unintended utterance. Can be characterized as production of an unintended sound within a word or an unintended word in a phrase. Paraphasias come in three different forms: phonemic, verbal, and neologistic. parasympathetic system.  Branch of the autonomic nervous system responsible for restoring the body to equilibrium after sympathetic activation. paraventricular nucleus.  One of the six nuclei of the anterior region of the hypothalamus. Participates in water conservation through signals to the kidneys during states of dehydration. paresis.  Muscle weakness or other form of partial paralysis. parietal association areas (PAAs).  Association cortices of the parietal lobe that participate in the development of spatial awareness, spatial perception, and sensory guidance of action. PAAs output massively to prefrontal cortical areas such as the DLPFC. parietal bone.  Curved, plate-like bone of the skull that comprises the top aspect of the cranium. Articulates anteriorly with the frontal bone, posteriorly with the occipital bone, and laterally with the temporal and sphenoid bone. parietal lobe.  Located posterior to the frontal lobe and dorsal to the temporal lobe. The parietal lobe is critical for (a) detection and discrimination of all forms of somatic inputs; (b) multimodal and integrative processing of auditory, somatosensory, and visual inputs; and (c) providing the frontal lobe with massive inputs to support cognition and motor control behaviors. parieto-occipital sulcus. The sulcus (groove) on the medial surface of the brain, functioning as a landmark that demarcates the upper edge of an imaginary line that separates the occipital and parietal lobes. Parkinson’s disease (PD).  Degenerative neurological condition involving loss or degeneration of dopamine-producing neurons within the substantia nigra pars compacta of the basal ganglia. pars opercularis of the inferior frontal gyrus.  One of three subdivisions of the inferior frontal gyrus forming the dorsal lip of the lateral sulcus up to the central sulcus. Named for the Latin word operculum meaning “lid or cover.” Considered a segment of Broca’s area.

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pars orbitalis of the inferior frontal gyrus.  One of three

subdivisions of the inferior frontal gyrus, named for its proximity to the eye orbits. pars triangularis of the inferior frontal gyrus.  One of three subdivisions of the inferior frontal gyrus, named for its wedge-like shape. Considered a segment of Broca’s area. parvocellular layers of the LGN.  Layers 3 through 6 of the LGN that receive P-type retinal ganglion cell inputs. parvocellular-type (P-type) retinal ganglion cells. One of the two major functional groupings of retinal ganglion cells. Convey color information into the central visual pathway. Considered the origin of the ventral visual processing stream. Projects to Layers 3 through 6 of the LGN. pathway.  One of several terms referring to a large collection of axons in the CNS. pauser response pattern.  PSTH response pattern that consists of a strong burst at the onset of a tone, followed by a rapid cessation of firing, with a gradual increase in firing rate thereafter. peduncle.  A term referring to a “stalk-like” collection of axons in the CNS. penumbra.  Cells surrounding a site of injury in the CNS. Cells in the penumbra are considered metabolically fragile and susceptible to cytotoxic effects and microglia attack. perception. The transformation of sensory information (sensation) into something meaningful for the central nervous system. perception-action coupling. A continuous exchange between sensory information and motor actions in the context of a given environment. perforant pathway.  Major olfactory afferent pathway from the entorhinal cortex to the hippocampal formation. periaqueductal gray (PAG).  Central gray matter region of the rostral pons and midbrain tegmentum surrounding the cerebral aqueduct. Receives input from the anterior cingulate cortex and plays a critical role in emotional responses, pain mediation, respiratory control, and mammalian vocalization. pericallosal artery.  Distal-most end of the anterior cerebral artery that rides over the surface of the corpus callosum’s body. perilesional areas.  Areas of the brain that immediately surround an area of damage. See also penumbra. perilymph.  Fluid that fills the scala vestibuli and tympani of the cochlea. Perilymph has high concentrations of Na+, but low concentrations of K+. perimysium.  Intermediate layer of connective tissue that encapsulates collections of muscle cells into structural unit called fascicles. perineurium.  A connective tissue layer that groups together nerve fascicles to create a nerve bundle. peripheral nerves.  Bundles of axonal fibers from central neurons that communicate information from the periphery to the central nervous system and vice versa.

peripheral nervous system (PNS).  A major division of

the nervous system that consists of all neural structures that are not already classified as CNS. PNS elements include spinal roots, spinal nerves, ganglia, cranial nerves and their associated brainstem ganglia, and the autonomic nervous system. perirhinal cortex.  Area of the medial temporal lobe that receives odorant inputs from the olfactory bulb. perisylvian language areas or zones.  Areas of the brain in the frontal, temporal, and parietal lobe around the Sylvian fissure (lateral sulcus) that are active in language processing and production. phantosmia.  The perception of a smell that is not physically present. May also be referred to as phantom smell or olfactory hallucination. pharyngeal nerve of vagus.  A special visceral efferent nerve innervating muscles of the pharynx and velopharynx. A branch of CN X. phase-locking.  Firing of an action potential at a specific phase of a stimulus. Phase-locking can be used by the nervous system to encode the periodicity and timing of alternating signals. phonation.  The production of sound by vibration of the vocal folds. phonetic features.  Features used to describe phonemes by the way they are produced, such as place, voice, and manner. phonological loop.  The process that maintains phonological features of repeated verbal information until it is no longer needed. Works to preserve verbal information in working memory (e.g., the act of repeating a phone number in your mind to remember it). phonological paraphasia. Error in word production where the word produced has many of the same sounds as the intended word. phospholipid bilayer.  Basic structure of the cell plasmalemma, composed of molecules known as phospholipids arranged in two opposing layers forming a hydrophobic core and hydrophilic outer surfaces. phosphorylation.  Chemical process by which a phosphate group is added to an organic molecule. The conversion of ADP back to ATP requires phosphorylation to reattach a cleaved phosphate group. photopic.  Vision mediated by cone activity. photopigment.  Specialized pigment molecules that undergo changes, thus enabling the capturing of photons of light. photopsin.  Photoreceptor proteins in cones. photoreceptors.  Primary receptors responsible for encoding information regarding visual information. Responsive to photons of light. phrenic nerve.  Spinal nerve branch innervating the diaphragm. physiological resting length (L0).  Muscle length that sets the sarcomere in the optimal configuration to generate maximal force and tension.

GLOSSARY

pia mater.  Innermost meningeal layer that adheres tightly

to the tissues of the CNS. Closely follows the contours of the cortical surface. piezo proteins.  Mechanosensitive proteins that form the building blocks of mechanoreceptor sensory endings. Piezo1 proteins are found on nonsensory tissues to detect blood flow or pressures within our internal organs. Piezo2 proteins are found on typical sensory tissues of the body. pigmented epithelium.  A layer of pigmented and darkened tissue on the outermost retinal surface that absorbs light not transduced by the photoreceptors. Reduces potential light scatter and blurring of the visual image. piriform cortex.  Area of the ventromedial aspect of the temporal lobe receiving odor inputs from the olfactory bulb. pituitary gland.  Ventral brain structure about the size of a large pea that sits within the bony chamber called the sella turcica. Key location for the release of hormones essential for regulating body systems necessary for growth, reproduction, sex organ differentiation, sleep cycles, and water absorption. Pituitary function is controlled through the hypothalamic nuclei. pixel.  Smallest single element of a two-dimensional digital image. planum temporale.  Area of tissue found folded within the lateral sulcus, located directly posterior to the primary auditory cortex on the surface of the superior temporal gyrus. Sometimes referred to as Wernicke’s area, although this designation is not entirely accurate. plasmalemma.  The cell membrane (phospholipid bilayer). pneumotaxic center.  Group of respiratory-related cells working alongside the apneustic center to form the pontine respiratory group (PRG). Limits inspiratory activity by inhibiting medullary respiratory centers. Active during chewing and swallowing. polymodal nociceptive endings.  Nociceptors that are triggered via chemical exposure, or mechanical or thermal means. polysynaptic.  Neural circuits comprised of several synapses. Contrast with monosynaptic. pons.  Central region of the brainstem that operates as a key anatomical bridge between frontal lobe regions of the cerebrum, the spinal cord, and the neural circuitry of the cerebellum. Critical center for cranial nerve system involved in contraction of the facial muscles, motion of the eyes, and sensation of the facial skin and oral mucosa. pontine arteries.  Smaller arterial branches extending from the basilar artery. Supply blood to the tissues of the pons. pontine nuclei.  Pockets of gray matter scattered about the basilar pons, receiving information from primary motor cortical areas via corticopontine fibers. Nuclei project to the cerebellum via the middle cerebellar peduncle. pontine reticulospinal tract.  Tract originating from the reticular formation in the pons. Tract facilitates LMN acti-

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vation of proximal extensor muscles of the lower limbs and increases muscle tone. pontine tegmentum. The region comprising the dorsal pons. pontocerebellar fibers.  Fiber tract that interlinks the pontine nuclei of the basilar pons with the cerebellar cortex. population coding.  Encoding of higher-order performance features of a behavior such as direction and amplitude of movement through the weighted activity of large groups of interlinked neurons. positive neurological signs.  Broad range of deficits related to lesions at various locations in the direct and indirect motor control systems. Deficits result in “addition” of movement or an increase in performance characteristics or intrusion of unwanted elements for a movement. positron emission tomography (PET).  Functional imaging method that uses the identification of coincident pairs of gamma rays produced by decaying radiotracer injected into the body. The tracer is tagged onto biologically active agents to identify specific structures or metabolic processes. Through triangulation, concentration maps of the circulating tracer can be assembled into three-dimensional images of different body regions of interest. postcentral gyrus.  Gyrus directly caudal to the central sulcus and extending from the lateral sulcus to the midline where it continues into the medial cerebral surface and joins the posterior paracentral lobule. Postcentral gyrus is the anatomical location of the primary somatosensory cortex. posterior cerebral arteries (PCA).  Paired arteries arising from the rostral basilar artery. PCAs’ primary distribution area consists of the inferior temporal gyrus, the parahippocampal gyrus and hippocampus, the ventral cortical surface of the temporal lobe, as well as the entire occipital lobe. Also supply blood to the thalamus and portions of the mesencephalon. posterior cingulate gyrus.  Caudal-most segment of the cingulate gyrus. Most active in memory operations and in visuospatial tasks. Considered a component of the default mode network. posterior circulatory system.  Major division of the neurovascular arterial system. Originates from the subclavian artery and supplies blood to the ventral temporal lobe and the entire occipital lobe. posterior commissure.  Commissural fiber tract located near the top segment of the cerebral aqueduct. Functions as a pathway underlying the pupillary light reflex. posterior communicating artery.  A thin arterial bridge interconnecting the posterior cerebral artery with the middle cerebral artery. posterior fasciculus.  Also known as the dorsal column. Dorsal white matter section of the spinal cord divided into the somatotopically organized gracile and cuneate fasciculi. posterior hypothalamic nucleus.  Part of thermoregulatory system. Operates in a complementary manner to the

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anterior hypothalamic nucleus. Detects decreases in body temperature and initiates heat-preserving behaviors. posterior inferior cerebellar arteries (PICA).  A paired artery branching from the lower vertebral artery that supplies blood to the inferior tissues of the cerebellum and regions of the lateral medulla. posterior inferior temporal sulcus.  Cortical region in the temporal lobe associated with the formation of words based on phonological information. posterior lobe of the cerebellum.  Tissue of the cerebellum located below the primary cerebellar fissure. posterior middle temporal gyrus. Cortical region in the temporal lobe associated with the formation of words based on phonological information. posterior spinal artery.  Artery descends along the lateral and posterior surfaces of the spinal cord on each side of midline, supplying blood to the posterior aspects of the spinal cord tissue. posterior thalamic radiation. See optic radiation. posterior ventral cochlear nucleus (PVCN).  The posterior subarea of the ventral cochlear nucleus. postganglionic cells. LMNs that originate with autonomic ganglia and project to a target location. poststimulus time histogram (PSTH).  Firing rate of a neuron recorded for a set period of time in response to an input’s onset. postsynaptic cell.  The neuron that receives the transmitted signal from the presynaptic terminal at the synapse. postsynaptic potentials.  Change in membrane potentials of a postsynaptic cell as a result of neurotransmitter binding to postsynaptic receptors and the influx or efflux on ions. posttraumatic stress disorder (PTSD).  A mental health disorder developed in response to experiencing a traumatic life event such as combat, sexual assault, or life-threatening incident. potassium (K+).  An ion that is distributed unevenly across the cell membrane of a neuron. Plays a significant role in establishing the resting membrane potential. High intracellular concentration and low extracellular concentration. potential energy.  Energy possessed and stored by a mass, based on its relative position to other masses. power stroke.  Rotational force of the myosin head that provides the energy to drag actin toward the center of the sarcomere. pre-Bötzinger complex.  Group of neurons comprising a segment of respiratory group neurons in the medulla. Plays a critical role in mammalian respiratory rhythms by setting the pace for coordinated respiratory motoneuron activity. precentral gyrus.  Vertically oriented gyrus of the frontal lobe, located directly rostral to the central sulcus, extending from the medial aspect of the cerebrum down to the lateral sulcus. Functionally known as the primary motor cortex (M1).

precentral sulcus. Sulcus that separates the precentral

gyrus from the remainder of the rostral frontal lobe.

precuneus.  Subdivision of the medial parietal lobe. The

precuneus is the continuation of the superior parietal lobe into the midline. The precuneus is an association area that has been implicated as being one of the main hubs for the default mode network of the brain. predictive remapping.  Functional feedforward mechanism of the frontal eye fields (FEFs). FEFs attempt to produce an “educated guess” as to where our visual gaze needs to be the next instant in time during a visual scanning task. prefrontal region.  A region of the frontal lobe operating during executive function behaviors. Consists of the dorsolateral, ventrolateral, ventromedial, and medial prefrontal cortices. preganglionic cells.  Autonomic neurons that project from the brainstem or spinal cord to innervate postganglionic cells. premotor area (PMA).  The segment of the premotor cortex that does not include the SMA. PMA is primarily active during limb motion. premotor cortex (PMC).  Known as BA 6 and found rostral to the primary motor cortex. Plays a significant role in the development and planning of movements. Receives heavy inputs from the dorsolateral prefrontal cortex and the posterior parietal cortices. Active during imagined actions. Projects directly to the primary motor cortex. preoccipital notch.  An indentation at the base of the cerebrum rostral to the occipital lobe. Functions as the lower marker for the imaginary boundary line separating the temporal and parietal lobes from the occipital lobe. preoptic nucleus.  One of the anterior region hypothalamic nuclei. Active in the expression of male sexual/mating behaviors in animals. Also active in correcting for water imbalances. pre-SMA. The rostral subdivision of the supplementary motor area (SMA) that is active during complex and abstract forms of planning. Receives heavy inputs from the prefrontal cortex and from cognitive-related areas of the basal ganglia by way of the thalamus. prestin.  Protein found within the outer hair cells that possess motor properties. Prestin is a direct voltage to force converter and appears to mediate changes in length of the outer hair cell in the cochlea. Protein is implicated as a major factor underlying the sound amplification properties of the cochlea. presynaptic cell.  The neuron responsible for transmitting a signal to the postsynaptic cell in a synapse. presynaptic terminal.  The structure at the end of an axon that contains the necessary cellular machinery for transmitting information to target neurons. Acts as the transmitting half of a synapse. pretectal region.  A region of the midbrain making up part of the subcortical system. Located rostral to the superior

GLOSSARY

colliculus and composed of several nuclei including the Edinger-Westphal. primary afferents.  Axons projecting from a peripheral sensory receptor to the spinal cord or brainstem. Also known as first-order sensory afferents or primary afferent neu­ rons. Primary afferents form a synapse onto second-order sensory neurons. primary auditory cortex (A1).  Cortical area on the superior temporal gyrus (BA 41) receiving auditory input from the medial geniculate body. Possesses a tonotopic representation of the basilar membrane. primary cerebellar fissure.  The prominent fissure separating the anterior and posterior lobes of the cerebellum. primary-like PSTH response.  Auditory nerve response characterized by an extremely short burst in firing rate at the onset of a stimulus, with a gradually decreasing firing profile with continued stimulus presentation. primary-like with a notch PSTH response.  Firing pattern similar to the primary-like response with the exception of a brief interruption in firing (1 ms) after the peak burst. Following the interruption, firing returns to its tonic level. primary motor cortex (M1).  Somatotopically and functionally organized region of the frontal lobe (precentral gyrus) that acts as the chief motor execution center. In humans, a large percentage of upper motoneurons stemming from M1 project monosynaptically to lower motoneurons. Operates in association with the premotor area, supplementary motor area, and primary somatosensory cortex. primary progressive aphasia (PPA).  A progressive specific type of dementia in which language complaints are the first and primary area of difficulty, with other cognitive complaints either absent or not as impactful on activities of daily life. primary somatosensory cortex (S1).  Anatomically located on the postcentral gyrus and defined as the central target for third-order somatosensory neurons of the VPL and VPM. S1 is somatotopically organized and segregated into separate regions mediating proprioceptive and tactile sensation. primary visual cortex (V1).  Cortical region of the occipital lobe that receives direct inputs from the lateral geniculate nucleus and is responsible for mediating primary inputs related to color, orientation, and retinal receptive field location. Retinotopically organized. principal nucleus of trigeminal.  Located in the pons and operates as the chief somatosensory nucleus of the trigeminal system, receiving primary afferent inputs from the ophthalmic, maxillary, and mandibular trigeminal nerve branches. Nucleus consists of second-order neurons that mediate cutaneous tactile inputs from the skin of the face and the oral mucosa. Projects to the ventroposteromedial (VPM) nucleus of the thalamus. progenitor cells.  Cells that are very early descendants of stem cells that can differentiate into a limited number of

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cell types. These cells are far more limited into their differentiating capacity compared to a stem cell. projection fibers.  Fiber pathways interconnecting the cerebral cortex with subcortical locations, the brainstem, and the spinal cord. Promoting Aphasics’ Communicative Effectiveness (PACE).  A pragmatic approach to aphasia therapy that

requires individuals to take turns sending and receiving messages in any communication modality (e.g., written, gestural, spoken). If the message is successfully conveyed, the communicative exchange is considered successful. proprioception.  Ability to identify how the body is moving and positioned in space. prosencephalon. One of three early embryonic brain regions that differentiates into the secondary structures of the telencephalon and diencephalon. prosopagnosia.  A condition caused by damage to the fusiform area of the inferior temporal gyrus that affects a person’s ability to recognize faces. protein kinase.  Enzyme responsible for shifting phosphate groups from free-floating intracellular ATP to various proteins within metabolic pathways. pseudounipolar cells.  A cell type resembling the cross between a unipolar and bipolar cell. Cell body has one process that immediately divides into two projections pointing in opposite directions. psychometric function.  A means of defining normative measures of sensory ability for diagnostic purposes. Generated by plotting the detection level of a stimulus versus its intensity or any other feature of a physical stimulus. psychophysics.  The science of relating physical properties of a stimulus to our internal percepts. ptosis.  Drooping condition of the upper eye lid. Caused by damage to CN III. pulvinar.  One of the major components of the lateral tier nuclei of the thalamus. Forms the most caudal aspect of the thalamus. Active in a wide range of operations that links cognition with visual and auditory signals. Specific functions such as visual perception, attention, language processing, reading, and writing have all been associated with pulvinar activity. pupil.  Opening into the eye behind the cornea and at the center of the iris. Diameter changes to the pupil directly influence the amount of light falling on the retina. pupillary light reflex (response). The reflex response that results in pupil contraction during sudden exposure to a bright light source. Mediated through CN III and the Edinger-Westphal nucleus. putamen.  One of the nuclei comprising the basal ganglia. The putamen is located medial to the insula and lateral to the globus pallidus. Together with the caudate nucleus, the putamen comprises the striatum, the input region into the BG system. pyramidal decussation.  Location in the medulla where the corticospinal tract crosses midline and continues

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downward in the contralateral spinal cord. Anatomically, it can be identified as a smooth area between the left and right pyramids on the ventral surface of the medulla. pyramidal tract.  Older nonspecific term used for the corticospinal and corticobulbar tracts. pyramidal tract neurons (pyramidal cells).  Large pyramidal-shaped neurons within Layer V of the primary motor cortex. Pyramidal neurons are the origination point for the principal descending motor pathways that innervate lower motoneurons of the brainstem and contralateral spinal cord — the corticobulbar and corticospinal tracts, respectively. pyramids.  Hill-like landmarks on the ventral surface of the medulla that contain axon fibers of the principal descending motor pathway called the corticospinal tract.

R radial glia.  An early developing glial cell that projects out

from the ventricular zone to form a rudimentary scaffolding that allows newborn cortical cells to adhere and climb to their designated cortical layer. radiations of the corpus callosum.  Callosal fibers (body segment) that interconnect the left and right posterior frontal lobes and the parietal lobes. rapidly adapting (RA).  The response property of a sensory receptor whereby action potentials fire only at points of dynamic change during a stimulus event. rate coding.  The representation of a stimulus feature by how quickly action potentials are generated by a neuron. For example, signal intensity is rate coded by the primary afferent, with higher-intensity signals generating a faster rate of action potential production compared to a weak signal. receptive aphasia (fluent).  Form of aphasia characterized by severe deficit in the ability to comprehend spoken language, but with preserved ability to produce speech. Speech output is jargon and meaningless. Also known as Wernicke’s aphasia. receptive field (RF).  An anatomical zone of the body surface whereby a stimulus will trigger a response (fire) in a single afferent and sensory receptor. receptor adaptation.  Decreasing firing rate in the presence of a chronic and sustained input. Receptor adaptation can be classified as slowly adapting (SA) or rapidly adapting (RA). receptor potential.  Graded change in membrane voltage caused by the presentation of stimulus within a sensory receptor’s transducing region. Electrical potential change can be depolarizing or hyperpolarizing. recurrent laryngeal nerve (RLN).  Secondary special visceral efferent nerve branch of the vagus nerve complex innervating intrinsic muscles of the larynx except for the cricothyroid. Left and right branches of the RLN are not structurally symmetrical.

red nuclei.  Nuclei dominating the rostral tegmentum of

the mesencephalon. Involved in motor coordination and a component of the cerebellar system’s output pathway. reflection.  The way light bounces off a reflective surface. reflex.  Stereotyped and involuntary motor response to a sensory stimulus event. Reflexes are not fixed responses, but can be modulated through learning and changes in intent. reflexive phonations.  Earliest vocal behaviors observed in infants, which include coughing, sneezing, and crying. refraction.  The bending of light when it traverses across two different transparent conditions or regions. regional hierarchy of language recovery.  A hypothesis that there are three levels of language recovery after stroke: level 1, complete recovery of brain and behavior in the case of temporary and/or very minor damage; level 2, restoration of function in perilesional areas; and level 3, recruitment of right hemisphere homologue areas for language production/processing. regulatory conditions.  Contextually relevant features from the environment used to determine appropriate movement characteristics when accomplishing a movement goal. Reissner’s membrane. In the cochlea, this membrane separates the scala vestibuli from the scala media. relative refractory period.  The time following the absolute refractory period in which an action potential can be triggered, but only by a stimulus stronger than typically required. release phenomena. See positive neurological signs. repolarization.  A condition whereby the intracellular voltage of a neuron is restored back to the resting membrane potential after a depolarizing event. resistance (R).  An opposition force or obstacle that affects the flow of current along a conducting pathway. resting membrane potential (RMP).  The baseline electrical state of a neuron when it is not actively involved in generating a neural impulse. Developed through passive currents of Na+ and K+ and activity of the Na+-K+ pump. resting tremor.  Low-frequency oscillation of body parts when not in motion. Characteristic of basal ganglia dysfunction. reticular formation (RetF).  A diffusely organized network of neurons within the core of the brainstem that regulates behaviors such as cardiopulmonary function, digestion, motivation, attention, and vocalization. reticulospinal tract.  Pathway from the reticular formation of the brainstem to spinal lower motor neurons. retina.  The light-sensitive and sensory transduction region of the eye. Trilayer structure that houses rods and cones, bipolar cells, and the retinal ganglion neurons. retinal.  Form of vitamin A bound to opsins in photo­ receptors. retinal bipolar cells.  Second layer of the retina that operates through graded changes in membrane potential. Chiefly responsible for the development of center-surround receptive field patterns.

GLOSSARY

retinal ganglion cells.  The uppermost and superficial layer

of cells of the retina that receive patterned outputs from the bipolar cells. Generates the first action potentials of the retinal system. retinotopy.  The mapping or organization of visual inputs from the retina through all components of the central visual pathway. retrograde messaging.  Reversed synaptic communication whereby a postsynaptic cell signals the presynaptic terminal to alter its activity, most notably using nitric oxide as a retrograde transmitter. retrograde transport.  Movement of substances from the terminal end of an axon back up toward the cell body of the neuron. retronasal olfaction.  Odorant detection by a small population of olfactory sensory receptors found in the oral and pharyngeal cavities. reuptake.  A process or mechanism that allows for a neuron to reabsorb and recycle unused expressed neurotransmitter from its immediate surroundings. reuptake transporters.  Chemical transporters specialized to remove neurotransmitter from the synaptic cleft and return it to the presynaptic terminal for reuse. reward states.  Pleasant or affirming experiences that foster the drive to reengage in a pleasing event. Opposite of aversion states. Rexed laminae.  Laminar organizing system created by Bror Rexed for the spinal gray area. Divided into 10 distinct layers of cells based on cell structure. rhodopsin. Light-sensitive photopigment and photon receptor of the rods within the retina. rhombencephalon. Early embryonic brain vesicle. Matures to become the metencephalon and myelencephalon. In turn, these divisions differentiate further into the pons, cerebellum, and medulla. rhomboid fossa.  A diamond-shaped space situated between the dorsal surfaces of the pons and medulla of the brainstem, and the ventral cerebellum. The rhomboid fossa is filled with cerebrospinal fluid and constitutes the 4th ventricle. ribosome.  An organelle responsible for the translation of mRNA into a polypeptide chain. rigidity.  Disorder of muscle tone whereby a body part is resistant to passively imposed movement. Considered a positive sign and an indication of a hypertonic state. RNA polymerase.  A transcription enzyme that initiates the synthesis of mRNA in the nucleus. rods.  Sensory photoreceptors of the eye, located primarily in the peripheral regions of the retina and responsible for vision under dim lighting conditions. Exquisitely sensitive to photons of light. rostral.  The anatomical directional term meaning anterior or toward the nose of the animal. rostrum.  The inwardly curved segment of the corpus callosum located rostral to the hypothalamus and dorsal to the septal nuclei.

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rubrospinal tract.  Shares many similarities with the corti-

cospinal tract. Influences the activation of LMNs innervating the flexor muscles. Tract is far less influential in humans and may provide humans with primitive residual motor control for gross motion. Ruffini endings.  A spindle-like cutaneous mechanoreceptor with a large receptive field sensitive to stretch and strain on the skin. Classified as an SA Type II fiber.

S saccades.  Rapid eye movements allowing for quick adjust-

ments of visual attention and gaze.

saccule.  Vestibular system otolith organ that transduces

superior-inferior linear motion of the head.

sacral region of vertebral column. Vertebral column

segment that lies above the coccyx and directly below the lumbar region. Consists of a plate of five to six large and fused vertebrae. The sacral plate looks like an inverted triangle in situ. sagittal plane.  The anatomical plane that runs vertically to the earth and is oriented at a 90-degree angle to the coronal plane. Divides brain and body into left and right sections. salivatory nucleus.  A nucleus of the facial nerve located in the caudal pons and responsible for triggering salivary secretion from the parotid glands. saltatory conduction.  The apparent “jumping” motion of an action potential at the nodes of Ranvier as the action potential propagates down a myelinated axon. sarcolemma.  Cell membrane of the muscle fiber. sarcomere.  Smallest unit of contraction. Segment of the myofibril that contains all the needed molecular machinery to produce contraction. sarcoplasm.  Cytoplasm of the muscle cell/fiber. sarcoplasmic reticulum (SR).  An excitable membranous lattice-like system of channels that surrounds individual myofibrils. SR is a storehouse for the Ca2+ ion. Connected to the transverse tubules at the triads. satellite cell. Stem cells that populate muscle fibers. Become activated when growth or regeneration of the muscle fiber is needed. scala media (SM).  With the cochlea in cross section, the scala media is the middle duct. It houses the organ of Corti. This region is filled with endolymph. scala vestibuli (SV).  With the cochlea in cross section, the scala vestibuli is the uppermost duct. This region is filled with perilymph. scala tympani (ST).  With the cochlea in cross section, the scala tympani is the lowermost duct. This section is filled with perilymph. Schwann cells.  A macroglial cell that forms myelin about axon segments in the peripheral nervous system. sclera.  The white tough outer layer of the eye. S-cones.  Cones sensitive to short wavelengths representing the blue end of the EM spectrum.

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scotomas.  Small visual field deficits. scotopic.  Vision mediated by rods. second messenger cascades.  Biochemical reactions within

a neuron driven by protein kinases that were created through second messenger activation. second (2nd) messengers.  Intracellular signaling molecules responsible for executing and driving biochemical signaling reactions. These molecules act as relay signals or “middlemen” intracellularly between postsynaptic membrane receptors and molecular targets that are involved in the generation of additional enzymes or in the activation of chemical reactions that will alter cell metabolism and activity. Examples of second messengers include cAMP and cGMP. second (2nd) pain.  Burning or aching prolonged pain response to an acute in jury. Long-duration perception. secondary auditory cortex (A2).  Also known as the belt zone. Heavily interconnected with the A1 core region. Belt operates during processing of complex auditory inputs that arise from naturalistic environments and behaviors. secondary somatosensory cortex (S2). Located ventral to S1. Activated strongly during touch and manual manipulation of objects for recognition purposes. Sends object-related information to the frontal lobe. self-organization.  The process by which a collection of elements assembles into a functional system based on the unique interaction of internal and external constraints acting on the system. Patterns emerge, not from preexisting or stored instructional sets, but from the interaction of the system’s elements in real time. sella turcica.  Concave depression in the sphenoid bone at the base of the skull that holds and protects the pituitary gland. semantic jargon.  Real words in sentences spoken with regular stress and intonation, but that do not make understandable sense. Often colloquially referred to by practicing clinicians as jargon or “word salad.” semantic paraphasias.  Error in word production where the word produced is related in meaning to the intended word. semicircular canals. Located in inner ear, these three canals (horizontal, superior, and posterior) provide sensory information related to rotational acceleration of the head. sensation.  Process by which peripheral receptors and afferent pathways transduce and transmit information into the central nervous system. sensitive period.  Period in development where cortical brain systems are highly receptive and malleable to incoming inputs. sensorimotor.  Pertaining to the combination and integration of sensory and motor activity. sensorimotor control.  Fundamental nature of behavior based on the interactive and integrative result of both sensory and motor function.

sensorimotor learning studies.  Type of motor control

research experiment that alters sensory information systematically to examine the role of ongoing sensory information in motor control processes. sensory nerves.  Peripheral nerves that contain only axons of sensory neurons. sensory physiology.  Study of the neural activity associated with a stimulus and how stimulus is transduced and processed by specific neural regions or structures. sensory receptors.  The peripheral anatomical component that encodes and transduces external (real-world) stimulus energy into an electrochemical neural impulse. sensory system.  A neural system comprised of sensory receptors, neural pathways, and specific cortical areas dedicated to processing sensory information within a modality. sensory thresholds.  The smallest magnitude input required to consciously detect a stimulus event 50% of the time. septal area.  Located on the medial wall of the cerebrum, just ventral to the rostrum of the corpus callosum. Forms a key component of the central reward system that includes the basal ganglia, limbic system, and central tegmental area. septum pellucidum.  A thin midline membrane that separates the right and left anterior horns of the lateral ventricles from each other. serial processing. See hierarchical processing. serotonin (5-HT). A monoamine neurotransmitter that aids in sleep, mood, appetite, and vasoconstriction. Most commonly known as a mood stabilizer. shearing action.  The way the organ of Corti basilar membrane and the tectorial membrane move together in an offset manner to bend hair cell stereocilia. Shearing of the stereocilia initiates hair cell depolarization or hyperpolarization depending on the direction of shearing. size principle of motor unit recruitment. Observation that motor units are recruited into action in an orderly fashion based on their size and the force requirement of the behavior. skeletal muscle.  Another term for striated muscle tissue. skull.  Bony structure that forms the head region of the skeleton. For the nervous system, the skull houses and protects the brain and brainstem. Sliding-Filament Theory (SFT).  Theory that describes the nature of skeletal muscle contraction and force development via the shortening of the sarcomere and the interaction between myosin and actin myofilaments. slow fatigue-resistant fibers.  Muscle fibers that can sustain contraction for extended periods of time without loss of force. Fibers produce low-force levels. slowly adapting (SA).  The response property of a sensory receptor whereby action potentials are fired at the onset of a stimulus event and continue to fire as long as the stimulus is present in the receptive field. slow-oxidative fibers.  Muscle fibers that use oxygen and aerobic respiration to generate ATP within the mitochondria.

GLOSSARY

slow-twitch fibers (slow fiber).  Muscle fibers that gen-

erate forces slowly.

small spherical bushy cells.  A subtype of the spherical

bushy cells that populate the ventral cochlear nucleus. Cells receive high-frequency inputs from the auditory nerve and project them to the lateral superior olivary complex. SMA proper.  The caudal subdivision of the supplementary motor area active during simple motor planning. Heavily linked to M1 and receives inputs from more motoric areas of the basal ganglia. smooth muscle.  Spindle-shaped class of muscle tissue that lines visceral organs and blood vessels. Snellen eye chart.  A chart used to assess visual acuity by determining the smallest print size a person can read from a set distance while covering one eye at a time. Social Communication and Language Evolution and Development (SCALED) model.  Attempt to explain

how language evolved in humans and how language develops or is learned in children. SCALED suggests five levels of language evolution and development, from primitive to highly advanced skills. Social Gating Hypothesis.  Theory developed by Patricia Kuhl arguing for the need for social interaction to influence language learning. Social interaction is thought to increase attention, improve the quality of information available for learning, allow for a sense of relationship to develop between communication partners, and bring online neural systems that link our perception of language to our production of language. Society for Neuroscience (SfN). The largest international research and educational professional association for researchers and educators working in any aspect of the neurosciences. An excellent resource for students and faculty needing neuroscience-related educational and research materials, information, and activities. See http:// www​.sfn.org. sodium (Na+).  A positive ion that is distributed unevenly across the cell membrane of a neuron. Na+ is high in concentration extracellularly but found in low concentrations intracellularly. Plays a critical role in the depolarization phase of the action potential. sodium-potassium pump (Na+-K+). Active ion transporter responsible for moving sodium and potassium ions against their natural concentration gradients. Needed to establish the resting membrane potential of the neuron. solitary nucleus.  Located in the dorsolateral medulla. Solitary nucleus is a key sensory element mediating the sensation of tactile inputs from the laryngeal region. Uppermost segment of the solitary nucleus is commonly referred to as the gustatory nucleus of the brainstem. soma.  The cell body of a neuron containing the cell’s organelles and nucleus. somatic motoneurons.  Motoneurons that innervate skeletal muscle.

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somatic motor system.  A branch of the peripheral ner-

vous system containing motoneurons innervating skeletal muscle. somatosensation.  Modality of sensation that includes all submodalities related to touch, nociception, thermal, and proprioceptive sensory signals. somatosensory cortex (S1).  Primary cortical zone on the postcentral gyrus responsible for the first stage of cortical processing of somatosensory inputs from the thalamus. somatotopy.  Systematic spatial organization of the body in the somatosensory system. somites.  Embryonic elements formed by differentiated tissues from the mesoderm. Somites give rise to the tissues of the musculoskeletal system. spasmodic dysphonia.  A neurologic disorder of voice production characterized by sudden intermittent spasms of the laryngeal muscles. Classified as a focal dystonia. spastic dysarthria.  Speech dysarthria resulting from upper motoneuron lesion. Characterized by harsh vocal quality, hypernasality, loudness outbursts, and reduced speech rate. spasticity.  Condition resulting from damage to the upper motor neuron system where muscles are in a continuously contracted state, causing increased stiffness and interference with normal movement, speech, and gait. spatial summation.  Integration of several synaptic potentials generated at multiple synaptic sites. special nerves.  A generic classification of nerves that are restricted to specific areas of the body and not distributed freely. special somatic afferents (SSA).  Functional grouping of nerves responsible for transmitting sensory information related to vision, hearing, and vestibular activity. Includes CN II and CN VIII. special visceral efferents (SVE).  Functional grouping of nerves arising from motor nuclei of the brainstem that innervate the muscles of the face, pharynx, larynx, and some neck muscles. Includes motor aspects of CN V, CN VII, CN IX, CN X, and CN XI. specific thalamic nuclei.  Nuclei that are historically categorized as “relay” in nature. Specific nuclei obtain focused inputs from a limited number of sources and output processed information to localized regions of the cortex. Include the VPL, VPM, MGN, LGN, VA, and VL nuclei. speech.  Verbal expression of thoughts and feelings using time-varying sound patterns decodable by listeners who share a common reference language. sphenoid bone.  Unpaired bone of the inferior cranium. Forms the posterior aspect of the orbits and articulates with the temporal and frontal bones. spherical bushy cells.  Found primarily in the anterior ventral cochlear nuclei that have a bush-like appearance. Can be classified as small or large. Cells process and extract different acoustic features related to sound localization and project this information to different regions of the SOC.

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spike trigger zone.  Region of a sensory receptor proximal

to the transducing area that is responsible for generating action potentials in response to changes in the cells receptor potential. spinal accessory nerve (CN XI).  SVE motor cranial nerve that innervates the trapezius and the sternocleidomastoid muscles. spinal canal.  Protective bony vertebral passageway containing the spinal cord. Formed by the stacked alignment of individual vertebral foramen. spinal nerves.  Mixed nerves of the peripheral nervous system that transmit motor, sensory, and autonomic information between the body and the spinal cord. spinal reflex circuit.  A simple neural network consisting of a sensory arm, a motor arm, and often a modulatory interneuron interposed. Reflex circuits allow the body to respond rapidly to changes in environmental conditions without the need for conscious evaluation of the event. spinal segment.  A functional anatomical division or unit of the spinal cord that contains a bilateral pair of dorsal and ventral nerve roots. spinal trigeminal nucleus. One of three key sensory nuclei of the trigeminal cranial nerve system. Located in the caudal pons and running though the medulla. Mediates crude touch, nociceptive, and thermal inputs from the facial skin and oral cavity. spinocerebellum.  Functional zone of the cerebellar cortex. Receives input from sensory systems of the spinal cord and brainstem. spinothalamic tract.  A synonymous term for the anterolateral system. spiral ganglion. Peripheral ganglion found within the modiolus of the cochlea. Houses the cell bodies of the auditory nerve’s bipolar neurons. splenium.  Posterior end of the corpus callosum. stapedial reflex response. See acoustic reflex response. statistical learning. The method by which our brains process information and identify regularities in the environment. An implicit computational process that happens below the level of our awareness. Hypothesized to be the way in which babies learn the phonetic features and rules of their language. stellate cells.  Cells of the cochlear nucleus located in the posterior ventral cochlear nucleus. Subdivided into T-stellate and D-stellate cell types. stereocilia. Stalk-like projections arranged in bundles found on the top surfaces of hair cells. Stereocilia are the location where hydromechanical energy is converted into electrochemical changes. stochastic pattern.  A completely random pattern whose future behavior cannot be predicted from current conditions. strabismus. The inability to produce coordinated eye movement, resulting in the complaint of double vision (diplopia) from a patient.

straight sinus.  Venous sinus located in the midline at the

juncture of the falx cerebri and the tentorium. Connects the inferior and superior sagittal sinuses to form the location where the transverse sinuses arises. striated muscle.  Class of muscle cell that is under voluntary control and that underlies our capacity to generate movements of the body. Also known as skeletal muscle. striatopallidal fibers.  Axons that interconnect the striatum with the globus pallidus external and internal segments. striatum. Part of the basal ganglia that includes the putamen, caudate nucleus, and nucleus accumbens. stria vascularis.  Secretory epithelial cells embedded within a rich capillary bed in the inner ear. Cells possess ATPdependent ion pumps and active electrotonic transport mechanisms that remove Na+ from, but discharge K+ into the endolymph. Helps maintain the endocochlear potential. subarachnoid space.  Sublayer of the arachnoid meninges that allows for the circulation of cerebrospinal fluid. subclavian artery.  Main arterial branch of the aorta that functions as the origin of the posterior arterial circulatory system for the brain. subcortical nuclei.  Any nucleus found in the cerebrum. Generally does not include nuclei of the brainstem, although rostral midbrain nuclei can be classified as subcortical in nature. Examples include the thalamus and the nuclei of the basal ganglia. subdural hematoma.  Closed-head buildup of blood in the space beneath the dura mater. Generates increases in intracranial pressures that can damage cortical tissues. subiculum.  A region associated with the hippocampal formation. The subiculum and the hippocampus together form the parahippocampal gyrus. submodality.  Finer distinctions and specific characteristics of stimulus energies for a given modality. For example, under the modality of tactile sensations there are many submodalities, including pressure, stretch, vibration, and flutter. substantia nigra (SN).  Subcortical nucleus situated dorsal to the fibers of the crus cerebri that express dopamine. Considered an element of the basal ganglia system. Comprised of the pars compacta and par reticulata. substantia nigra pars compacta (SNpc). Mesencephalic nucleus that projects to the striatum. Cells of this nucleus use dopamine as their neurotransmitter. substantial nigra pars reticulata (SNpr). Mesencephalic nucleus that projects to the thalamus and uses GABA as its neurotransmitter. subthalamic nucleus (STN).  One of the nuclei comprising the basal ganglia. Provides excitatory drive to the output nuclei of the BG system. The only nucleus in the BG system that uses the excitatory neurotransmitter glutamate. subthreshold effects.  Fluctuations in a sensory endings receptor potential to a stimulus that doesn’t reach the firing threshold of the spike trigger zone of the neuron.

GLOSSARY

subunits. Membrane-spanning proteins that form the

major component of an ion channel’s superstructure. sulcus.  The grooves or furrows found on the surface of the cerebral and cerebellar cortices. (plural, sulci) summation. The process by which signals are added together. superior cerebellar artery (SCA).  Artery that arises from the basilar artery below the bifurcation of the posterior cerebral arteries. Supplies blood to the anterior lobe of the cerebellum. superior cerebellar peduncle (SCbP).  One of three massive fiber tracts connecting the cerebellum with the brainstem. Forms the output pathway from the cerebellum to the brainstem and cerebrum. superior colliculi (SC).  Key element of the central visual pathway, located in the midbrain tectum. Superior colliculus receives input from the optic tracts and is active during reflexive turning or orienting of the eyes. superior frontal gyri (SFG).  Dorsal-most of the three horizontal frontal gyri extending from the precentral sulcus to the rostral tip of the cerebrum. Overlaps into the medial aspect of the cerebral hemisphere. superior laryngeal nerve (SLN).  A special visceral efferent branch of the vagus that splits into the external SLN that innervates the cricothyroid and a portion of the inferior pharyngeal constrictor, and the internal SLN that operates as a key somatosensory sensory nerve from the laryngeal lumen and mucosa. superior longitudinal fasciculus (SLF).  Association fiber tract in the deep region above the insula. Tract interconnects the occipital, parietal, and frontal lobes. Along with the arcuate fasciculus, the SLF is considered the “speech-​ language-hearing” association tract because of its critical role in interlinking perisylvian language zones of the lateral hemisphere. superior occipital gyri.  The dorsal gyri found on the lateral aspect of the occipital lobe. superior occipitofrontal fasciculus.  White matter tract that interconnects the frontal, parietal, and occipital lobes. Situated between the caudate nucleus and the corpus callosum. superior olivary complex (SOC).  Second key location along the central auditory pathway and the first site for binaural sound processing. Receives tonotopic inputs from the CN, with low-frequency inputs projecting to the medial SOC and high-frequency inputs projecting to the lateral SOC. Best studied for its role in sound localization. superior parietal lobule (SPL).  Anatomical subdivision of the parietal lobe. Located caudal to the postcentral sulcus, encompasses the dorsal-most aspect of the parietal lobe. Receives heavy inputs from the visual cortices and from S1. Inputs are integrated and then output to prefrontal cortex and premotor areas for use in goal-directed action. superior sagittal sinus.  Cavernous drainage space of the venous system situated overriding the longitudinal cerebral

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fissure. The superior sagittal sinus is created when the meningeal dural layer separates from the periosteal dural layer to become the falx cerebri. superior temporal gyrus (STG).  Dorsal-most temporal lobe gyrus. Houses the primary auditory cortex. superior temporal sulci (STS).  Prominent sulci separating the middle and superior temporal gyri. Cortical region in temporal lobe that is considered important for speech representations at the phonological level. superior thalamic radiation.  A corticopetal projection through the posterior limb of the internal capsule. Fibers mediate somatosensation from the thalamus to the primary sensory cortex in the parietal lobe. supplementary motor area (SMA).  Considered the dorsal-most segment of BA 6. Active during the development and planning of actions. Projects directly to M1. Subdivided into the pre-SMA and the SMA proper. suppression deficit.  Inability to adequately inhibit inferences once they are identified as clearly inappropriate during sentence processing. Characteristic of right hemisphere damage. suprachiasmatic hypothalamic nuclei.  One of six nuclei of the anterior region of the hypothalamus. Suprachiasmatic neurons receive visual inputs that verify daily lightdark cycles. Participate in the triggering of rhythmic release of melatonin and corticosterone. supramarginal gyrus (SMG).  Rostral segment of the inferior parietal lobule. Located directly caudal to the postcentral sulcus. Region is associated with language processing and sensorimotor integration. supraoptic hypothalamic nucleus.  One of six nuclei of the anterior region of the hypothalamus. Initiates pituitary release of vasopressin. supratentorial.  Structures or lesions that occur in the cerebrum because of its location above the tentorium of the dura mater. Sylvian parietotemporal junction (Spt).  Region of cortical tissue that is found within the Sylvian fissure posteriorly and near the junction of the parietal and temporal lobe. Region includes segments of the planum temporale. Functionally, this region demonstrates motor as well as auditory responsiveness. Considered a segment of the dorsal pathway for speech. sympathetic nervous system. Part of the autonomic segment of the peripheral nervous system that increases performance and activity of the body in response to stress and emergency situations. Triggers the “fight or flight” response. synapse.  Communication point between a presynaptic cell and a postsynaptic cell. synaptic cleft.  Miniscule gap (20 nanometers or less) that exists between the pre- and postsynaptic components of a synapse. synaptic plasticity.  Biological processes by which specific patterns of activity in the synapse produce changes in

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synaptic strength. Synaptic plasticity is believed to underlie learning and memory. synaptic vesicles.  Self-contained membranous packages that store chemical transmitters generated in the presynaptic terminal. Vesicles fuse to the presynaptic terminal membrane and release transmitter stores into the synaptic cleft via exocytosis. syndactyl.  Congenital defect of the fingers and toes whereby two or more digits are fused to one another and not capable of being used independently. An artificial syndactyl can be created by purposely binding together two fingers so that they are forced to be used as a single appendage. synergy.  A group of muscles and joints functionally linked by the motor control system to act as one unit in goal-​ oriented actions.

T tactile stereognosis. The ability to use tactile information,

such as texture, size, spatial properties, and temperature, to perceive an object without the use of visual and auditory information. task constraints.  The environmental and organismic factors that allow and/or limit the performance of goal-​directed actions. tastant.  A chemical substance that elicits a response from the gustatory system. taste.  The sensory perception of a tastant. taste buds. A sensory receptor found primarily on the tongue and responsible for transducing taste information. Taste buds are also found in the pharynx and on the epiglottis. taste pore.  A small hole-like opening at the top of a taste bud through which microvilli of taste cells protrude. tectorial membrane (TM).  Gelatinous layer that lies over the organ of Corti. Outer hair cell stereocilia are embedded within this layer. tectospinal tract.  Originates in the superior colliculus with axons decussating and descending through the medial brainstem toward the cervical spinal cord region. Tract influences LMNs and interneurons related to control of the neck, head, upper body, and shoulders. tectum.  Dorsal subdivision of the mesencephalon containing the superior and inferior colliculi. tegmentum.  Area within the pontine and midbrain consisting of a mixture of gray matter and smaller axon tracts transmitting sensory and motor information to and from the CNS. telencephalon. An embryonic structure that matures to become the cerebral hemispheres, basal ganglia, and subcortical white matter. temporal association areas (TAAs).  Association cortex of the temporal lobe active during the production of language, the linking of lexical and semantic functions, and

object feature recognition. Output from the TAAs projects to emotional regulation centers of the frontal lobe, including the orbitofrontal cortex and the ventromedial prefrontal cortex. temporal bone.  Irregular-shaped bone of the lateral cranium. Articulates with the parietal, sphenoid, and occipital bones. Houses many of the key elements of the peripheral auditory system. temporal facial nerve branch.  Major branch of the facial nerve innervating muscles of the upper face and scalp, as well as the cornea. Forms the motor segment of the corneal reflex arc with the ophthalmic branch of the trigeminal sensory nerve. temporal lobe.  Lateral lobe of the cerebrum located ventral to the frontal and parietal lobes and separated from them by the lateral sulcus. Temporal lobe is the home for the primary auditory cortex and most of Wernicke’s area. The temporal lobe has diverse functions in object recognition, spectral acoustic processing, semantic processing, memory, and learning. temporal monocular visual hemifield.  The half of the visual field of one eye that exists in the visual space on the same side as your ear. temporal retina.  Portion of the retina closest to the zygomatic bone of the eye orbit. temporal summation. Integration of several synaptic potentials generated in rapid succession at one synaptic location. With regard to the development of force in a muscle, temporal summation is the condition whereby twitches begin stacking on top of each other, resulting in a continuous addition and increase in force output. tentorial membrane. Gelatinous membrane associated with the organ of Corti in the cochlea. Participates in mechanical shearing of the hair cell’s stereocilia during sound transduction. tentorium cerebelli.  Principal dural fold found within the calvarium and located between the ventral surface of the occipital lobe and the dorsal surface of the cerebellar hemispheres. Sits at a right angle to both the falx cerebri and falx cerebelli. testosterone.  The primary sex hormone playing a key role in the reproductive system and sexual characteristics of males. texture discrimination.  The ability to determine differences among a range of mechanical surface features on different substances or objects. thalamocortical projection fibers.  Third-order projection neurons between the thalamus and the cortex of the cerebrum. thalamus.  A collection of subcortical nuclei that operates as a conduit for the transmission of sensory information from the spinal cord and brainstem to perceptual processing regions of the cerebral cortex. Also plays a critical role in sensory gating and modulation of incoming inputs.

GLOSSARY

Esther Thelen.  Indiana University experimental psycholo-

gist who championed the use of dynamical systems theory to understand developmental processes, including skill acquisition, motor control, and cognition. She upended nativist theories of development and opened a new understanding of the interactive effects of the environment, task, and individual factors in the emergence of human cognition. Theory of Mind (ToM).  The ability of humans to understand how another being thinks or feels, and to imagine ourselves as someone else, with that person’s wants and needs. thermal nociceptive endings.  Nociceptors that selectively transduce extreme levels of cold and heat. thermoreceptors.  Primary receptors responsible for encoding information regarding thermal information. thick filament.  Myofilament comprised of myosin. thin filament.  Myofilament comprised of actin. third (3rd) ventricle.  Thin and midline chamber that is positioned directly between the left and right thalami. The lateral ventricles are connected to the 3rd ventricle via the foramen of Monro. The 3rd ventricle is connected to the 4th ventricle via the cerebral aqueduct. thoracic region of the vertebral column.  A region of the vertebral column including vertebrae T1 through T12 and forming the portion of the column below the cervical and above the lumbar region. thrombosis. Refers to the blockage and the restriction of blood flow caused by a thrombus. thrombus.  A blood clot found within and attached to the lumen of a blood vessel. A thrombus that is fractured can create small fragments that are known as thrombo­ embolisms. thymine.  A base molecule that acts as a building block for DNA. Pairs with adenine. tight-junctions.  Term used to denote a condition where the cell membranes of adjacent cells are virtually linked to one another to form an impermeable barrier. tip links.  Tension-sensitive protein filaments connecting stereocilia together. Tip links are connected to mechanically gated K+ ion channels. When tip links are stretched, K+ channels are gated open, initiating hair cell depolarization. tip of tongue (ToT) phenomena.  When a person fails to retrieve a word from memory when needed or desired. ToT is also accompanied by partial recall of word features and the feeling of being on the verge of remembering the word itself. tissue plasminogen activator (tPA).  Powerful clot-reducing agent that can dissolve a blood clot within a cerebral artery if the drug is given very soon after a stroke. Only given under conditions of ischemic stroke. Contraindicated for hemorrhagic stroke. titin.  The largest protein found in striated muscle. Essential for maintaining the thick filaments in the center of

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the sarcomere and for helping stabilize the thick filament’s position when myosin and actin interact. tonotopy.  Systematic organization of acoustic frequency in the auditory system. tracheostomy.  The surgical puncturing of a person’s trachea and replacement with a synthetic tracheostomy tube allowing a person to breathe. Performed if there is obstruction or an impairment involving the trachea. tracts.  A term referring to collections of axons in the CNS. trafficking proteins.  Proteins that play a role in synaptic vesicle positioning and movement in the presynaptic terminal. transcallosal inhibition.  Process whereby white matter connections from the left to the right hemisphere excite interneurons that inhibit the right hemisphere. Particularly apparent during language processing and production. transcranial direct current stimulation (tDCS). Noninvasive brain stimulation technique that applies electrical current directly to the scalp via electrodes. Anodal and cathodal stimulation is used to excite or inhibit the brain, respectively. tDCS is paired with behaviorally relevant tasks to develop long-lasting effects. transcranial magnetic stimulation (TMS). Noninvasive brain stimulation technique that uses a focused magnetic field pulse placed over the scalp to induce electrical currents in the brain directly beneath the magnetic field. transcription. The process of using DNA as a template to create mRNA. Transcription is completed using RNA polymerase to initiate mRNA generation. transcutaneous electrical nerve stimulation.  Use of electrical current to relieve the presence of chronic pain. Electrical current is used to excite large-diameter afferent fibers that carry cutaneous signals to the spinal cord, and initiate the inhibitory effects described by the gate theory. transfer RNA (tRNA).  A form of ribonucleic acid responsible for transporting amino acids to the ribosome for linking to a growing polypeptide chain. transgenic.  An organism that has DNA from another animal inserted into its own DNA. transient ischemic attacks (TIAs).  Small stroke events caused by embolisms lodging themselves into smaller downstream blood vessels. Any acute neurological deficits that arise from a TIA will usually resolve themselves within a few minutes to a few hours. Generally, a precursor to more severe strokes. transient receptor potential (TRP).  Family of proteins responsible for the ability of thermoreceptors to detect shifts in ambient temperature. translation.  The conversion of mRNA nucleotide sequences into a polypeptide chain (protein) by a ribosome. translational science.  The blending of basic and clinical research into a cohesive and comprehensive approach to investigate human health and well-being.

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transporters. Molecules responsible for moving neu-

rotransmitters against their concentration gradient into synaptic vesicles using driving forces and ATP hydrolysis. transverse section.  An anatomical plane running parallel to the earth. Divides the brain into dorsal and ventral sections. Divides the body into upper and lower parts. Other terms include axial and horizontal sections. transverse sinus.  Horizontal and lateral sinus of the venous system that drains into the internal jugular vein. Located parallel to the position of the tentorium. transverse tubules.  Also known as the T-system or Ttubules. Connected to the sarcolemma and responsible for propagating the action potential from the sarcolemma to the inside of the fiber. triad.  Structure formed between a transverse tubule and the adjacent sarcoplasmic reticulum cisternae. trichromatic theory of color vision.  Processing of S-cone, M-cone, and L-cone channels for transducing color information in the retina. The relative and weighted ratio of cone activity informs cognitive appreciation of a specific color. trigeminal ganglion.  Brainstem ganglion containing somas of the trigeminal nerve’s pseudounipolar afferent cells. trigeminal motor nucleus.  Cranial nerve nucleus that contains cell bodies of motor neurons that comprise the motor branch of the trigeminal nerve. trigeminal nerve (CN V).  A mixed cranial nerve (GSA and SVE) consisting of the ophthalmic, maxillary, and mandibular nerve branches. The GSA segment of the trigeminal nerve mediates tactile and proprioceptive inputs from the facial skin and oral mucous. The SVE segment is the motor component of the trigeminal nerve and innervates muscles of the jaw, the tensor veli palatini, and the tensor tympani of the middle ear. trigeminal system.  A mixed cranial nerve system operating as the chief mediator for tactile, proprioceptive, noxious, and thermal inputs from the facial skin and oral mucosa. The motor component of the trigeminal system innervates the muscles of the jaw, the tensor veli palatini, and the tensor tympani. trigeminolemniscal tract.  Second-order afferent pathway of the trigeminal system that transmits tactile and proprioceptive inputs from the head and vocal tract to the ventroposteromedial nucleus of the thalamus. Also known as the trigeminal lemniscus. trigeminothalamic tract.  Grouping of fibers responsible for mediating and carrying sensory information such as deep pressure, pain, proprioception, and temperature from the head, face, and oral cavity to the thalamus (VPM nucleus). trochlear nerve (CN IV).  GSE cranial nerve innervating the superior oblique muscle of the eye. Contraction of the superior oblique causes the eye to rotate downward and medially.

trochlear nucleus.  Nucleus of the trochlear cranial nerve

situated in the mesencephalon ventral to the periaqueductal gray. tropomyosin. Regulatory protein associated with actin. Wraps about the helical structure of the actin strand and is positioned to block the myosin binding sites on actin. Linked to troponin. troponin.  Regulatory protein associated with actin. Contains binding site for Ca2+. Linked to tropomyosin. T-SNARES.  Complex proteins situated on the presynaptic terminal membrane that pair with V-SNARES (located on the vesicle membrane) to fuse synaptic vesicles to the terminal membrane. T-stellate cells.  The more numerous of two major forms of stellate cells found in the posterior ventral cochlear nuclei. Project contralaterally to the inferior colliculus and the ventral nucleus of the lateral lemniscus. Project ipsilaterally to the dorsal cochlear nuclei and the superior olivary complex. Produce the “chopper” PSTH response pattern. tubercles of the cuneate and gracile nuclei. Landmark consisting of two ridges on the dorsal surface of the medulla. The underlying nuclei act as key sensory relays receiving tactile and proprioceptive sensory information from the body below the neck. tufted cells.  One of the two major types of projection neurons of the olfactory bulb that operate as second-order neurons and project to cerebral targets. tuning curve.  A graph that reveals the activation threshold of a sensory receptor when tested by the optimal stimulus for that receptor across different intensity levels. two-point discrimination.  A perceptual assessment method that determines the minimum distance between two probe tips that an individual can detect on the skin 50% of the time. This method can be used to characterize the size, density, and distribution of receptive fields in the skin. Type 1 fibers.  A category of mechanoreceptive afferents that have small receptive fields. Located in the region near the transition between the dermis and epidermis. Type 2 fibers.  A category of mechanoreceptive afferents that have large receptive fields. Found in the deep dermal layers.

U umami. A class of tastant detectable by humans. Term

comes from the Japanese word for “savory.”

uncinate fasciculus.  Association fiber pathway connecting

the anterior temporal lobe with the inferior frontal and orbital frontal gyri. uncus.  Subdivision of the medial temporal lobe. Houses the amygdala and a segment of the olfactory cortex. unfused tetanus.  Period of force development where individual twitches can still be resolved. unipolar cells.  A cell comprised of a cell body with a single process with many branches. This neuron type lacks dendrites.

GLOSSARY

upper esophageal sphincter.  The upper esophageal sphinc-

ter (UES) consists of the cricopharyngeus muscle and forms the upper entry port into to esophagus. The UES relaxes and is mechanically stretched open during the swallow. upper motoneuron (UMN).  Neuron that originates within the cortex and from select brainstem areas that directly affects the LMN or the networks of interneurons surrounding the LMNs. upper motoneuron syndromes.  A broad collection of deficits associated with damage to the primary motor cortex or its descending cortical projections. Commonly include positive sign symptoms such as paresis, hypertonia, spasticity, and the exaggerated presence of reflexive responses. utricle.  Vestibular system otolith organ that transduces anterior to posterior linear motion of the head.

V vagus nerve (CN X).  A mixed cranial nerve system that is

the most highly distributed cranial nerve system among the 12 CNs, with branches that reach throughout the neck, thorax, and abdomen. The vagus nerve consists of SVE, GVE, GVA, SVA, and GSA functional components. vallate papillae.  Circular-like papillae that form an inverted V-shape array along the anterior edge of the sulcus terminalis of the posterior tongue. variable resonator. Acoustic tube that will amplify or attenuate sound frequencies based on its physical dimensions. The vocal tract is considered a variable resonator. vasopressin.  An antidiuretic hormone expressed by the pituitary gland during dehydration conditions through activation of the supraoptic nucleus. Regulates water retention. velopharyngeal port.  A muscular valve comprised of the soft palate and pharyngeal walls that couple the nasal and pharyngeal cavities. venous sinus.  Chambers created by separation of the layers of the dural folds in the cranium. Sinuses collect and transport venous blood to the internal jugular vein. ventral.  Anatomical direction pointing toward the belly or anterior aspect of an animal. ventral acoustic stria.  Ventral pathway projecting from the cochlear nucleus to the medial nucleus of the trapezoid body and the superior olivary complex. Carries timing and intensity inputs. ventral anterior nucleus of the thalamus (VA). A nuclear area of the ventral thalamus associated with motor control circuits with inputs arising from the basal ganglia. Outputs are to the prefrontal cortex and the supplementary motor area. ventral auditory stream.  Functional pathway through the entire auditory system that transmits and preserves timing features of sound.

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ventral cochlear nucleus (VCN).  The smallest division of

the two major cochlear nuclei. Divided into the anterior and posterior cochlear nuclei. ventral horn.  The ventral-most region of gray matter in the spinal cord. Contains lower motoneurons that innervate peripheral muscle tissue. ventral lateral nucleus of the thalamus (VL).  A nucleus in the ventral thalamus associated with motor control circuits and inputs arising from the cerebellum. Outputs to the primary motor cortex. ventral nucleus of the lateral lemniscus (VNLL). A nucleus that is part of the ascending central auditory pathway connecting the superior olivary complex with the inferior colliculus. ventral posterior nucleus of the thalamus (VP). A nucleus found in the ventral thalamus made up of two subdivisions: the ventral posterolateral and the ventral posteromedial nuclei. VP is the chief input location for somatosensory inputs from the contralateral side of the body. Also receives vestibular information from the vestibular nuclei. ventral processing pathways.  Processing pathways of the cerebral cortex that are active during behaviors related to object recognition and feature categorization. In the visual system, the ventral stream originates in the visual cortex and runs through the visual association areas to the middle and inferior temporal gyri. Ventral processing pathways terminate in the orbitofrontal cortex and in other frontal regions associated with emotional regulation of behavior. Ventral processing pathways have been identified for other sensory modalities and language processing. ventral respiratory group neurons.  A medullary region housing neurons that play a role in controlling and coordinating respiratory motor outputs that help drive the rhythm of breathing. ventral roots.  Bilateral pair of fibers exiting the ventral spinal cord consisting of motoneuron axons that transmit efferent information from the CNS to skeletal and smooth muscle tissue and glands. Merge with dorsal roots to become the spinal nerve. ventral stream.  Processing pathway of the visual system that originates with P-type retinal ganglion cells and projects through the primary visual cortex and visual association areas. Pathway terminates in the temporal association area. Dedicated to processing inputs related to object recognition, identification, and high-resolution object form analysis. ventricles.  A system of interconnected chambers in the brain and brainstem filled with cerebrospinal fluid. The ventricular spaces are the vestiges of the neural tube’s lumen. The system consists of the right and left lateral 3rd and 4th ventricles. ventricular zone.  The deepest and inner region of the neural tube. The ventricular zone is a “birthplace” for neurons

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that are destined to comprise the cortical layers of the cerebrum. ventrobasal complex.  The functional combination of the ventroposterolateral and ventroposteromedial nuclei of the thalamus. ventrolateral prefrontal cortex (VLPFC).  Functional zone of the lateral prefrontal cortex. Found ventral to the dorsolateral prefrontal cortex on the lateral surface of the frontal lobe. Associated function includes motor inhibition. ventromedial hypothalamic nuclei. One of the four nuclei of the tuberal region of the hypothalamus. Stimulation results in a characteristic female mating posture. Also active and known to respond to changes in calorie intake. ventromedial prefrontal cortex (VMPFC). Functional subdivision of the prefrontal cortex. Located on the ventral surface of the frontal lobe above the eye orbits, medial to the orbitofrontal cortex. Comprises the area that includes the gyrus rectus of the midline. ventroposterolateral nucleus (VPL).  A nucleus in the thalamus that receives ascending cutaneous and proprioceptive inputs from second-order projections in the DCML. VPL houses third-order neurons that project to the limb (upper and lower) and trunk representations of the primary somatosensory cortex. ventroposteromedial nucleus (VPM).  Ventral tier nucleus of the thalamus that operates as a key mediator and relay point for cutaneous tactile and proprioceptive sensation from the face and vocal tract. VPM houses third-order neurons that project to the facial and vocal tract representation of the primary somatosensory cortex. verbal working memory. Temporary maintenance and manipulation of verbal information in the brain. vermis.  A central and midline region of the cerebellum. Bounded on each side by the cerebellar hemispheres. Functionally active during locomotion and in the control of body posture. Regions immediately lateral to the vermis are called paravermal areas. vertebral arteries.  Pair of arteries arising from the subclavian artery that travel through the transverse foramen of the cervical vertebrae as they course upward toward the brainstem. The vertebral arteries lie on the ventral surface of the medulla and give rise to the posterior inferior cerebellar and the anterior spinal arteries. vertebral column.  Major component of the axial skeleton consisting of 33 vertebrae stacked into a columnar organization. Operates to protect the spinal cord, manage the load of the trunk, and provide points of attachment for skeletal muscle systems of the limbs, thorax, and abdomen. vertebral foramen.  Center region of an individual vertebrae created by the circular connection of surrounding vertebral elements. When vertebrae are stacked, all the vertebral foramen together become the spinal canal, the area of the vertebral column housing and protecting the spinal cord. vestibular nuclei.  Nuclei of the vestibular system and target site for vestibular afferents of CN VII. Located in the

rostral dorsolateral medulla and caudal pons. Consist of four principal elements: the lateral, medial, superior, and inferior vestibular nuclei. vestibulocerebellum.  Functional region of the cerebellum that receives inputs from the vestibular nuclei of the brainstem. Active in balance and postural control. vestibulocochlear nerve (CN VIII). Principal sensory nerve that originates from afferent terminals in the cochlea and the vestibular system. CN VIII projects to both the cochlear and vestibular nuclei in the medulla and transmits auditory and balance-related input to these structures. Also known as the auditory vestibular nerve. vestibulo-ocular response (VOR).  Response that is triggered through head rotation and motion. The VOR uses head/body motion input to maintain visual gaze in the correct orientation and position for a visual target. vestibulospinal tract.  Principal descending pathway from the vestibular nuclei to motor systems of the trunk and lower limbs. Functions to maintain postural control and balance. visceral motoneurons.  Motoneurons that innervate smooth, cardiac, and glandular tissues. visceral motor.  Branch of the peripheral nervous system that innervates glands, smooth muscle tissue, and circulatory muscle tissue. visceromotor processes.  Events related to the movement of visceral components and structures. Important for maintenance of homeostasis. visceromotor system.  Tasked with controlling all internal and involuntary motor operations of the body. Comprised of two complementary elements that regulate homeostasis: the sympathetic and parasympathetic systems. viscerosensory processes.  Processes relating to the sensory aspect of the viscera. Important for maintenance of general homeostasis. visual field.  The portion of the visual space that can be seen by each retina. visual space.  The extent of external space that can be transduced by both retinas. vitreous chamber.  A chamber comprising most of the eye’s volume, filled with a gel-like watery substance. vitreous humor.  The gel-like watery substance within the vitreous chamber that helps maintain the shape of the eyeball and helps keep the retina in place. vocal fold paresis/paralysis.  Weakness or loss of function of muscles controlling one or both true vocal folds. vocalization.  Complex pattern of sound production produced by mammals and avian species. voice onset time (VOT).  The time between when a stop consonant is released and when voicing is begun. voltage (V).  Electrical potential energy created by charge separation across a barrier. voltage-gating.  Mechanism used to open and close ion channels through detection of minute changes in the electrical potential of the cell membrane in which the channel is embedded.

GLOSSARY

voltage sensor.  Segment of a receptor’s subunit that contains

charged amino acids capable of detecting local electrical potential changes in the membrane in which the receptor is embedded. Gating mechanism for voltage-​regulated ion channels. Georg von Békésy.  Legendary auditory neurophysiologist who first discovered the detailed structure, mechanics, and dynamics of basilar membrane motion along with its contribution to the ability of mammals to detect sound frequencies. V-SNARES.  Complex proteins situated on the membrane of synaptic vesicles that pair with the T-SNARES on the presynaptic membrane. V-SNARES and T-SNARES interact to connect synaptic vesicles to the presynaptic terminal membrane and aid in the process of fusion.

W Wallenberg’s syndrome. See lateral medullary syndrome. waters of hydration.  A cloud of water molecules attracted

to an ion, affecting its overall size. Karl (Carl) Wernicke.  German neurologist who first noted the connection between damage to the posterior temporal lobe and a syndrome characterized by a severe deficit in the ability to comprehend spoken language, but with preserved ability to produce speech.

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Wernicke’s aphasia.  Aphasia characterized by fluent verbal

expression often devoid of meaning. Patients have reduced ability to understand language. Wernicke’s area.  The language reception and comprehension (audio-motor integration) region of the brain. Corresponds to BA 22, a region found in the superior temporal gyrus and along the temporoparietal junction. Damage to BA 22 results in fluent aphasia. white matter.  Vast regions of the CNS comprised of myelinated axons.

X xerostomia. Medical diagnosis of dry mouth. Can be

caused by changes in the quantity of saliva production and reduced salivary flow.

Z Z-line.  Point where two actin filaments are anchored to each

other end-to-end at the center of the I-band.

zonule fibers.  Fibers that span between the ciliary muscles

and the lens of the eye. Fibers translate ciliary muscle forces to the lens to alter its shape. zygomatic facial nerve branch.  Nerve branch of CN VII innervating muscles of the upper-middle face region.

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Index

Note:  Page numbers in bold reference non-text material.

A A1. See Primary auditory cortex A2. See Secondary auditory cortex A-band, 481 Aα fibers, 321 Aß fibers, 321 Aδ fibers, 319, 321 A1 region, of temporal lobe, 208 AAC. See Alternative and augmentative communication Abducens nerve, 125, 129, 131, 137, 150, 151, 156, 160, 165 Abducens nucleus, 139 Abductor spasmodic dysphonia, 647 ABR. See Auditory brainstem response Absolute refractory period, 67 Absorption, 395, 395 Abstraction, 212 Acalculia, 223 ACC. See Anterior cingulate cortex Acceleration angular, 383–385 linear, 381 Accessory nerve, 125, 129, 130, 131, 150, 151, 157, 173–174, 174 Accessory nucleus, 130 Accommodation response, 161 Acetylcholine, 86, 486, 570, 648 Acetylcholine receptor, 76 Acetylcholinesterase, 488 Achromatopsia, 426 Acoustic energy, 373 Acoustic gap, for preterm infants, 701 Acoustic reflex, 723, 724 Acoustic signal, 700 Acoustic stria, 703, 706 Acoustic transduction, 362 Acquired apraxia of speech, 647 Acquired hydrocephalus, 264–265 Actin, 481, 483–484, 484–485 Action potential as all-or-none event, 63 definition of, 17, 63 depolarization for, 65

description of, 62–64 elements necessary for, 64 generation of, 65–67, 68 hyperpolarization, 67 initiation of, 63 mechanism of, 63–64, 65–67, 66 myelin effects on, 70, 71 as negative feedback loop, 69 phases of, 65, 66 propagation of, 67–71 purpose of, 67 regeneration of, 69 repolarization, 67 temporal summation, 89 thresholding of, 63–64 voltage-gated ion channels in, 64–65 Active touch, 311 Active zones, 74, 75 Activity-dependent plasticity, 682 Acute vestibular syndrome, 386 Acute vestibulopathy, 386 Adaptive control model, 639 Adductor spasmodic dysphonia, 647 Adenine, 25, 26 Adenosine 3′,5′-cyclic monophosphate, 81 Adenosine diphosphate, 24, 24, 479 Adenosine triphosphatase, 496 Adenosine triphosphate adenosine diphosphate conversion of, 24, 24, 479 description of, 24, 451 hydrolysis of, 55, 496 ion pump utilization of, 53 mitochondria production of, 24, 24, 479 myosin binding of, 484 Adenylyl cyclase, 81 ADP. See Adenosine diphosphate Adrenalin, 86 Aerodigestive tract cranial nerve innervation of, 460–461 description of, 458 Affective aggression, 234 Affective-motivational pathway, 332–333 777

Afferent neurons, 20–21 Affordance, 601 After-potential, 67 Aggression affective, 234 amygdala’s role in, 234 hypothalamus’s role in, 190 Aging chemosensation changes caused by, 455–456 hearing loss associated with, 371 Agnosia auditory, 702 definition of, 206, 225 visual, 225 Agraphia, 674 with alexia, 223 Airborne pollutants, 439 Akinesia, 554 Akinetic mutism, 236, 646 Akinetopsia, 425 Alar plate, 112 Alexia, 674 All-or-none events, 63 Allodynia, 321 Alpha-gamma coactivation, 505, 506 Alpha motoneurons, 120–121, 504 Alpha-synuclein, 30 ALS. See Anterolateral system Alternative and augmentative communication, 641 Alzheimer’s disease amyloid plaques associated with, 439 bilingualism effects on, 237 blood-brain barrier’s role in, 36 chemosensory changes associated with, 456 Amacrine cells, 401 American Academy of Neurology, 455 American Sign Language, 415 Amine neurotransmitters, 84, 85, 86 Amino acids, 84–86, 85 Ampere, 46 Ampulla, 383, 384 Ampullary crista, 384

778

Neuroscience Fundamentals for Communication Sciences and Disorders

Ampullary hair cells, 383 Amygdala in aggression, 234 anatomy of, 229, 233–234 description of, 191, 228 functions of, 231, 233–235 in threat recognition, 234 Amyloid plaques, 439 Anastomotic vein, 274 Anatomical orientations, 102–104, 103 Anatomical planes, 102, 104, 104 Androgen receptors, 190 Aneurysm, 275–276, 277 Angular acceleration, 383–385 Angular artery, 269 Angular gyrus, 205–206 Anomic aphasia, 675 Anopsia, 426 Anosmia, 158, 456 Ansa lenticularis, 550 Anterior, 103 Anterior arterial system, 266–271, 267–271 Anterior cerebral artery, 266, 268–270, 273 Anterior cingulate cortex, 631–632 Anterior cingulate gyrus, 231, 235–236 Anterior commissure, 254 Anterior communicating artery, 267, 268–269, 269, 273 Anterior corticospinal tract, 520 Anterior cranial fossa, 114 Anterior eye, 395–397 Anterior fasciculus, 121, 122, 123 Anterior hypothalamic nucleus, 186, 188 Anterior inferior cerebellar artery, 268, 271, 273 Anterior limb, of internal capsule, 256–257, 256–257 Anterior median fissure, 128, 129, 130 Anterior middle temporal gyrus, 634 Anterior olfactory nucleus, 444 Anterior parietal artery, 269 Anterior perforated substance, 436 Anterior spinal artery, 268, 271, 273 Anterior spinocerebellar tract, 566, 566 Anterior temporal artery, 269 Anterior thalamic nucleus, 182, 229, 231 Anterior tract, 331 Anterior ventral cochlear nucleus, 703, 706, 708 Anterograde transport, 29 Anterolateral system affective-motivational pathway of, 332–333

anatomy of, 331–332 anterior tract of, 331, 332 characteristics of, 325t description of, 310, 324, 328–335 dorsal column-medial lemniscal system versus, 328–330 inputs to, 329–330, 333 lateral tract of, 331, 331 schematic diagram of, 329, 330 sensory-discriminative pathway of, 332 structural features of, 329–335 Anterolateral system tract, 133 Anterolateral tract, 133 AP. See Action potential Aphasia anomic, 675 Broca’s, 202, 209, 644, 645, 674, 675 communicative treatment for, 684 conduction, 675 constraint-induced therapy for, 684–685 decision tree for, 674 definition of, 644, 673 expressive, 202, 645, 675–676 fluent, 675–676 global, 675 mixed transcortical, 675 nonfluent, 202, 675–676 primary progressive, 678 receptive, 209, 645, 675–676 regional hierarchy of recovery, 685–686 after stroke, 673, 685–686 transcortical motor, 675 transcortical sensory, 675 Wernicke’s, 209, 644, 645, 675 Aplysia, 72 Apneustic center, 136, 465 Apoptosis, 34 Apraxia definition of, 201, 546, 645 ideomotor, 223 of speech, 630, 646, 647 Arachnoid layer, 259, 259, 262 Arcuate fasciculus, 252, 253, 664, 670 Arcuate fibers, 251 Arcuate nucleus, 186, 188, 189 Aristotle, 582, 584–587, 607 Arterial system, 249 anterior, 266–271, 267–271 posterior, 268, 271–272 Arteriovenous malformations, 278, 279 Articulator map, 640 Articulatory system, 622–623 Articulatory variability, 642 ASA. See Anterior spinal artery

Association areas anatomy of, 222 frontal, 222, 224, 226, 227 limbic, 224, 228 parietal. See Parietal association areas temporal, 222, 223–225 Association cortices, 221–223, 222 Association fibers, 250–254 Association thalamic nuclei, 184 Astigmatism, 397 Astrocytes in blood-brain barrier, 36 description of, 33, 35 structure of, 35 tight junctions of, 36 Ataxia cerebellar, 568, 568 description of, 646 Ataxic cerebellar dysarthria, 568, 627 Ataxic dysarthria, 644, 645, 646 Athetosis, 555 ATP. See Adenosine triphosphate ATPase. See Adenosine triphosphatase Attention, parietal association areas in, 223 Attentional control, 305 Attraction forces, 43–45 Auditory agnosia, 702 Auditory association areas, 720–722 Auditory brainstem response, 725–726, 726 Auditory cortex neuroimaging of, 722 primary, 717–720, 718 secondary, 720 Auditory cortical areas, 704 Auditory nerve acoustic intensity and frequency encoded by, 377–378 cochlear nucleus input from, 707 fibers of, 375, 376–377, 378 hair cell receptor potential transmission by, 375–376 phase-locking in, 377, 378 Auditory processing disorders, 702 Auditory radiation, 257 Auditory skills, 698, 698–701 Auditory startle reflex, 698 Auditory system. See also Ear anatomy of, 362, 363 assessment of, 168 cochlea. See Cochlea efferent pathways of, 722–725 hair cells. See Hair cells olivocochlear bundle, 724–725 overview of, 361–362 stapedial reflex response, 723, 724

INDEX

“what” pathway of, 721 “where” pathway of, 721 Auditory-vestibular nerve. See Vestibulocochlear nerve Autism spectrum disorders, 643 Autonomic nervous system functions of, 100 homeostasis functions of, 570–574 hypothalamic regulation of, 189–190 parasympathetic division of, 100, 570, 573–574 sympathetic division of, 100, 570–573, 571 AVMs. See Arteriovenous malformations Axial section, 104 Axoaxonic synapses, 31, 31 Axodendritic synapses, 31, 31 Axon(s) action potential propagation down, 67–71 conduction velocity of, 321 corticopontine, 563 corticospinal, 517 description of, 15, 16, 21, 29, 31–33 of first-order neuron, 324 gustatory, 453 myelinated, 70 retinal ganglion cells, 416–417 sensory receptors, 302, 321–322 synapse formation at, 31 unmyelinated, 69, 69–70 in white matter, 107–108 Axon collaterals, 29 Axon hillock, 15, 17, 29, 65 Axoplasmic flow/transport, 29 Axosomatic synapses, 31, 31

B Babbling, canonical, 642 Babinski response, 200 Babinski sign, 544 Bacon, Francis, 608 Baroreceptor reflex, 126, 169 Baroreceptors, 126, 169 Basal cells, 448, 455 Basal ganglia anatomy of, 547 caudate nucleus of, 546, 549–550 connectivity of, 549 cortico-basal ganglia-thalamo-cortical loop of, 546, 626 description of, 191, 546–549 direct pathway of, 551–552 diseases of, 626 dysfunction of, 544 globus pallidus of, 546, 550, 626

779

hyperkinetic disorders of, 554–557 hypokinetic disorders of, 554–555 indirect pathway of, 551–552 interconnections in, 557 in language, 662 lesions of, 553–557 limbic loop of, 548 in motor control, 626 movement loop of, 548 nuclei of, 546, 547, 548, 551 oculomotor loop of, 548 prefrontal loop of, 548 primary motor cortex input from, 537 processing loops of, 546, 548 putamen of, 546, 549–550 schematic diagram of, 549, 551 in speech, 547, 626–627 striatum of, 626 substantia nigra of, 546, 550–551 subthalamic nucleus of, 546, 550 in vocalization, 626–627 Basal plate, 112 Basal vein, 275 Basilar artery, 268, 271, 273 Basilar membrane anatomy of, 362, 363, 364 as frequency analyzer, 365–367 hair cells and, 370 movement of, from hydromechanical energy, 373 place coding in, 370 as sound prism, 366, 367 structure of, 366 tonotopic organization of, 367 traveling wave through, 366 von Békésy’s studies of, 365–366 Basilar pons, 136 Basilar pontine region, 136 Batteries design of, 45 electrical force fields created by, 44 BBB. See Blood-brain barrier BDNF. See Brain-derived neurotrophic factor Behavior description of, 25 exploratory, 606 movement and, 601 Behavioral variant frontotemporal dementia, 199 Bell’s palsy, 646 Belt zone, 720 Benign paroxysmal positional vertigo, 385 Bernstein, Nikolai, 593–597, 606 Bernstein’s problem, 594

Berry aneurysm, 277 BG. See Basal ganglia Bilingualism, 237 Binaural fusion, 713 Binocular zone, 399 Biosensors, 291 Bipolar cells depolarization of, 409 description of, 375, 403–404 OFF-, 409–413 ON-, 409–413, 411 Bipolar neurons, 20, 21 Bitemporal hemianopsia, 428 Bitter tastants, 446, 448, 451–452, 452–453 Blind spot, 158, 397 Blindsight, 422 Blobs, 421, 421 Blood carbon dioxide levels in, 127 oxygen levels in, 127 Blood-brain barrier astrocytes in, 36 functions of, 36 protective functions of, 36 Blue-yellow color blindness, 407 BMIs. See Brain-machine interfaces Botulinum toxin, 648 Bouba-kiki effect, 643 Bowman gland, 438, 438–439 BPPV. See Benign paroxysmal positional vertigo Brachia, 143 Bradykinesia, 554, 646 Brain. See also specific anatomy anatomy of, 125, 259 anterior arterial system of, 266–271, 267–271 arterial system of, 266–271, 267–271 association fibers of, 250–254, 251f commissural fibers of, 254, 255 4rd ventricle of, 263, 264, 265 lateral ventricles of, 263, 264 lesions of, 618 mapping of, 312 noninvasive stimulation of, 687 posterior arterial system of, 268, 271–272 projection fibers of, 255–2597 3rd ventricle of, 263, 264, 265 vascular system of, 266–279 venous sinuses of, 272, 274 ventricular system of, 262–266, 264 vesicles of, 111 Brain, Walter Russell, 224 Brain-derived neurotrophic factor, 87 Brain freeze, 162

780

Neuroscience Fundamentals for Communication Sciences and Disorders

Brain-machine interfaces, 641 Brain maps, 312 Brain soup method, 194–195 Brainstem anatomy of, 129, 131 in auditory processing, 633 corticofugal fibers in, 255, 258 corticopetal fibers in, 255, 258 descending motor pathways from, 524–527 dorsal perspective of, 132 gustatory center of, 167, 463 lateral perspective of, 131 medulla oblongata. See Medulla oblongata mesencephalon. See Mesencephalon music education and, 168 nuclei in, 106 overview of, 123–126 in parasympathetic system, 573 pons. See Pons respiratory centers of, 465 respiratory control by, 126–127 reticular formation, 124 Branchial arches, 155 Breathing, for speech/vocalization, 620, 622 Broca, Paul, 202, 228, 312 Broca-Wernicke-Lichtheim Gechwind language model, 667 Broca’s aphasia, 202, 209, 644, 674, 675 Broca’s area anatomy of, 197, 198, 202 discovery of, 202 functions of, 197 in speech, 629–630 Brodmann, Korbinian, 213 Brodmann’s areas, 213–215, 214–215, 342, 418, 528, 717 Bushy cells, 708

C C fibers, 319, 321 Ca2+ pump. See Calcium pump Calcarine fissure, 209 Calcarine sulcus, 125 Calcium cytosol concentration of, 24 description of, 47 neuron distribution of, 47 Calcium activated ion channels, 50 Calcium channels, voltage-gated, 76, 489 Calcium pump, 53–54, 491 Callosal transection, 238

Callosomarginal artery, 266, 269 Calvarium, 113 cAMP, 81, 82, 440, 441 Canonical babbling, 642 CAP. See Central auditory pathway Capsaicin, 319 Capsular stroke, 257 Carbon dioxide, blood levels of, 127 Cardiac muscle tissue, 476, 477 Carotid body reflex, 170 Carotid sinus, 169 CAS. See Childhood apraxia of speech CAT. See Communicative aphasia treatment; Computed axial tomography Catalysts, 643 Cauda equina, 115, 116 Caudal, 102, 103 Caudate nucleus, 546, 549–550 Cavernous sinus, 275 Cell(s) amacrine, 401 ampullary hair, 383 basal, 448, 455 bipolar. See Bipolar cells bushy, 708 cerebral cortex, 211 cochlear nucleus, 706–709 D-stellate, 708 Deiters’, 363, 368–369 fusiform, 708 glial. See Glial cells hair. See Hair cells Hensen’s, 369 horizontal, 401 mitral, 444 muscle, 18 nerve. See Neuron(s) neural crest, 109, 111–112 neural tube, 109, 111–112 octopus cell, 708 OFF-bipolar, 409–413 ON-bipolar, 409–413, 411 preganglionic, 570 progenitor, 216 pyramidal, 516, 708 retinal ganglion. See Retinal ganglion cells satellite, 479 Schwann, 33–34, 35 stellate, 708 striatal, 552 T-stellate, 708 taste receptor, 448–449 tufted, 444 Cell body, 15, 16, 21 Cell doctrine, 14

Cell membrane anatomy of, 21, 21–23 ion distribution across, 47 Cellular neurobiology, 13 Center-surround, 411 Central artery, 269 Central auditory pathway anatomy of, 699–700, 702–703, 705 auditory brainstem response testing of, 725–726, 726 auditory nerve fibers in, 702 auditory skills, 698, 698–701 cochlear nucleus. See Cochlear nucleus description of, 697 elements of, 699–700 functions of, 701 inferior colliculus, 142–143, 704, 708, 715–716 lateral lemniscus, 144, 704, 714 medial geniculate body, 143, 704, 716–717 in preterm infants, 701 studies of, 701–703 superior olivary complex. See Superior olivary complex Central canal, 264 Central control system, 587 Central gustatory pathway, 452–453, 454 Central nervous system anatomy of, 99, 99–100, 112 brain. See Brain embryological differentiation of, 111, 111 gray matter in, 105, 105–107 meninges of. See Meninges midsagittal view of, 263 nuclei in, 105, 106–107 peripheral nervous system and, 101 sensory information in, 587 spinal cord. See Spinal cord supportive framework of, 259 white matter in, 105, 250–259 Central neuron, 32–33 Central pattern generator, 463, 467–468, 591, 592 Central somatosensory pathways anterolateral system, 324 dorsal column-medial lemniscal system. See Dorsal columnmedial lemniscal pathway/system overview of, 322–324 Central sulci, 193 Central vestibular pathway, 386, 386–387 Central visual pathway anatomy of, 416, 416

INDEX

lesioning of, 426 optic chiasm, 416–417 optic nerve, 416–417 optic tract, 416–417 primary visual cortex, 418–422 retinal ganglion cells, 416–417 Cerebellar ataxia, 568, 568 Cerebellar cortex, 565 Cerebellar folia, 561 Cerebellar mutism, 646 Cerebellar neurons, 33 Cerebellar peduncles, 137, 139, 562–563, 563 Cerebellum anatomy of, 125, 558–559, 561, 627 anterior lobe of, 559, 561 cerebrocerebellar circuit of, 567–568 cerebrocerebellum, 561, 562, 627–628 cortico-cerebellar-cortical loop of, 564 divisions of, 561–564 embryologic development of, 111 functions of, 560–561 input pathways of, 561–564 input sources for, 558 intermediate, 627 in language, 662 lesions of, 568, 569 in motor coordination, 558 motor cortical inputs to, 558 in motor learning, 558 movement coordination and refinement by, 558–561 nuclei of, 559, 561 output pathways of, 561–564 peduncles of, 137, 139, 562–563, 563 pontocerebellar fibers of, 563 posterior lobe of, 559, 561 primary motor cortex input from, 537 processing circuits of, 564–568 sensory inputs to, 558 in speech, 627–628 spinocerebellar circuit of, 565–567 spinocerebellum, 561, 562, 627 thalamocortical projection fibers of, 565 vermis of, 559, 561 vestibulocerebellar circuit of, 565 vestibulocerebellum, 561, 562, 627 in vocalization, 627–628 Cerebral aqueduct, 265 Cerebral cortex anatomy of, 105, 192, 212–213 association cortices/areas of, 221–223, 222

781

association pathways of, 253 block-diagram of, 218 Brodmann’s areas of, 213–215, 214–215 cells of, 211 cognition-specific organization of, 221–224 cortical columns of, 213, 215–218 corticocortical connections of, 223 description of, 211 dorsal processing pathways in, 220, 220 excitatory activity in, 211 external granular layer of, 212, 213 external pyramidal layer of, 212, 213 functions of, 192, 211 gyri of, 192 hierarchical processing in, 218–219 inhibitory activity in, 211 internal granular layer of, 212, 213 internal pyramidal layer of, 212, 213 layers of, 212, 213 molecular layer of, 212, 213 multiform layer of, 212, 213 organization of, 213–218 parallel processing in, 218, 220 primary motor area of, 222 primary sensory area of, 222 serial processing in, 218–221 sulci of, 192 ventral processing pathways in, 220, 220 Cerebral dominance, 237–239 Cerebral hemispheres anatomy of, 190–191, 191, 210, 237–239 association fibers, 251–254 interhemispheric connectivity of, 237–239 Cerebral peduncle, 129, 140, 142, 144 Cerebral perfusion, 686 Cerebrocerebellar circuit, 567–568 Cerebrocerebellum, 561, 562, 627–628 Cerebrospinal fluid circulation of, 262, 263, 265 composition of, 262 hydrocephalus, 264–265 imaging of, 664 intraventricular foramina for drainage of, 263 protective functions of, 262 Cerebrum anatomy of, 125, 180, 190–211, 192, 437 arteries of, 269 descending motor pathways, 515–519 frontal lobe of. See Frontal lobe

functional cortical zones of, 198 hemispheres of. See Cerebral hemispheres lateral, 193, 516 lobes of, 191–211 occipital lobe of. See Occipital lobe parietal lobe of. See Parietal lobe temporal lobe of. See Temporal lobe ventral, 196 white matter of, 250 white matter tracts associated with, 251–257, 252, 665–666 Cervical vertebra, 113, 115 cGMP, 409 Channel gating, 50, 50 Characteristic frequency, 709 Characteristic frequency response, 376 Chemical senses description of, 435 dysfunction in, 454–456 smell. See Olfactory system taste. See Taste Chemical signals, 41 Chemical synapse activation of, 77 excitatory postsynaptic potentials, 78, 79, 83, 92 functions of, 72, 76–78 inhibitory postsynaptic potentials, 78, 80, 83, 92 localization of, 91 presynaptic terminal of, 72, 74 receptive phase of, 74, 78 SNARES, 75, 75–76 structure of, 72–76, 74 synaptic vesicle of, 74–75 transmission phase of, 74, 76–78, 83, 84 voltage-gated calcium channels, 76 Chemoreceptors, 127, 294, 295, 296 Chemosensation age-related changes in, 455–456 alterations in, 455 definition of, 435, 452 disease-related changes in, 456 injury-related changes in, 456 surgery-related changes in, 456 Chest wall muscles, 119, 119 Cheyne-Stokes respiration, 127 Cheyne-Stokes respiratory syndrome, 127 Childhood apraxia of speech, 28, 647 Chloride description of, 47 influx of, 57 neuron distribution of, 47 Cholinesterase, 76

782

Neuroscience Fundamentals for Communication Sciences and Disorders

Cholinesterase inhibitors, for myasthenia gravis, 76 Chomsky, Noam, 659 Chorda tympani, 167, 464 Chorea, 555 Choroid plexus, 263, 263 Chromatic vision, 405 Chromosomes, 25 CI. See Cochlear implant CIAT. See Constraint-induced aphasia therapy Ciliary muscle fibers, 397 CILT. See Constraint-induced language therapy CIMT. See Constraint-induced movement therapy Cingulate gyrus, 235–236 Cingulate motor area, 236, 516, 524, 631–632 Cingulate motor map, 542 Cingulum, 253, 253 Circadian rhythms hypothalamus’s role in, 189 visual information in, 428 Circle of Willis, 271, 273 Cistern, 262 Cisternae, 481 Clinical trials, 687 Closed-loop systems, 588–591, 590, 638 Clostridium botulinum, 648 CMA. See Cingulate motor area CNV. See Copy number variation Coarse coding deficit, 681 Coccyx, 113, 115 Cochlea acoustic signals in, mechanotransduction mechanism for, 372–380 anatomy of, 362, 363–364 electrical potentials in, 365 place coding in, 370 scala media of, 362, 364, 364 scala tympani of, 362, 364, 364 scala vestibuli of, 362, 364, 364 Cochlear implant, 370 Cochlear nucleus anatomy of, 703–710 anterior ventral, 703, 706 auditory nerve input to, 707 cells of, 706–709 description of, 135, 703 divisions of, 705 dorsal, 703, 706, 708–709 frequency preservation in, 709 functions of, 704 intensity preservation in, 710

temporal preservation in, 709–710 ventral, 703, 706, 708 Codons, 27–28 Cognition, cerebral cortex and, 221–224 Cognitive communication disorders, 644, 679 Cognitive-executive control of language, 660, 664 Cognitive reserve, 227, 237 Cold receptors, 318–319 Color blindness, 407 Color blobs, 421 Color vision, 406 Combinatorial encoding, 442, 442 Commissural fibers, 250, 254, 255, 665 Common carotid artery, 266, 267 Communicating hydrocephalus, 264 Communication sciences and disorders, 4 Communicative aphasia treatment, 684 Complete spinal cord injury, 115 Computational models, of speech production, 637–642 Computed axial tomography, 702 Computed tomography, 346 Concentration gradients, 41–42, 42, 59 Conduction aphasia, 675 Cones, 158, 403, 403, 405–407 Confluence of sinuses, 274–275, 275 Conformational state, 482 Congenital hydrocephalus, 264 Conjugate deviation, 201 Connexons, 72 Consensual response, 161 Constraint-induced aphasia therapy, 684–685 Constraint-induced language therapy, 684–685 Constraint-induced movement therapy, 683–684 Constraints, 598–599, 599, 643 Contextual shifts, 293 Contralateral neglect syndrome, 224–225 Convergent transmission, 32, 32–33 Coordinative structures, 606 Copy number variation, 30 Core communication deficit, 681 Corollary discharge, 345, 566, 720 Corona radiata, 255, 258, 258–259 Coronal plane, 104, 104 Corpus callosum anatomy of, 125, 190, 229, 254 body of, 254 genu of, 254 posterior vein of, 274 radiations of, 254, 255

rostrum of, 254 splenium of, 254 Cortex auditory. See Auditory cortex cerebellar, 565 cerebral. See Cerebral cortex definition of, 105 extrastriate, 210, 422, 423 premotor. See Premotor cortex primary motor. See Primary motor cortex somatosensory. See Somatosensory cortex visual, 106, 418–422, 423 Cortical columns, 213, 215–218 Cortical deafness, 702 Cortical swallowing, 465–467 Cortico-basal ganglia-thalamo-cortical circuits, 626 Cortico-basal ganglia-thalamo-cortical loop, 546 Cortico-cerebellar-cortical loop, 564 Cortico-reticular tract, 623 Corticobulbar fibers, 141–142, 144 Corticobulbar pathway, 257 Corticobulbar tract, 200, 515–522, 517, 521, 628 Corticocortical connections, 223 Corticofugal fibers, 255, 258 Corticofugal pathways, 723 Corticomotoneuronal projections, 520 Corticopetal fibers, 255, 258 Corticopontine axons, 563 Corticopontine fibers, 564 Corticospinal pathway, 257 Corticospinal tract, 133, 200, 515–519, 517, 628 Corticostriatal projections, 550 Corticothalamic fibers, 516 Corticothalamic projections, 180 Corticotropin-releasing factor, 87, 189 Cortisol, 140, 189 Coulomb, 46 Coup-contrecoup brain injury, 679, 680 COVID-19 anosmia caused by, 158 neurological signs of, 265 CPG. See Central pattern generator Cranial fossa, 113, 114 Cranial nerves aerodigestive tract innervation by, 460–462 cell bodies of, 151 description of, 124 functional classification of, 154–156 general somatic afferent, 155 general somatic efferent, 155

INDEX

general visceral afferent, 155 general visceral efferent, 155 I, 125, 129, 131, 150, 151, 156, 156, 158 II, 125, 129, 131, 150, 151, 156, 159, 159–160 III, 125, 129, 131, 150, 151, 156, 159–161, 160 IV, 125, 129, 131, 150, 151, 156, 161–162 motor functions of, 136 motor nuclei of, 151 nuclei of, 124, 151–153, 152 organization of, 150–154 overview of, 149 sensory nuclei of, 151 special somatic afferent, 155 special visceral afferent, 155 special visceral efferent, 155 types of, 125, 129, 131, 150, 151 V. See Trigeminal nerve VI, 125, 129, 131, 150, 151, 156 VII. See Facial nerve VIII, 125, 129, 131, 150, 151, 157, 167–168, 169, 386 IX, 125, 129, 131, 150, 151, 157, 170 X, 125, 129, 131, 150, 151, 157, 171, 171–173 XI, 125, 129, 131, 150, 151, 157, 173–174 XII, 125, 129, 131, 150, 151, 157, 174, 175 Cranial vault anatomy of, 261 description of, 113 dural folds in, 260, 260 Craniofacial muscles, 478 Cranium anatomy of, 113, 114 protective functions of, 260–261 Crescent monocular zones, 400 CRF. See Corticotropin-releasing factor Cribriform plate, 436, 438, 443, 455 Critical periods, 656 Cross-bridge, 484, 489–491, 490 Crus cerebri, 140, 141–142, 143–144, 519 CSD. See Communication sciences and disorders CSF. See Cerebrospinal fluid CT. See Computed tomography Cuneate fasciculus, 122, 122, 326, 328 Cuneate nucleus, 130–131, 327 Cuneus, 209 Cupula, 383–385, 384 Current, 46

783

Cutaneous mechanoreceptors, 312–313, 313–314 Cutaneous tactile receptors, 310–316 Cyclic AMP. See cAMP Cyclometry, 598 Cytoarchitectural, 213 Cytokines, 439 Cytology, 13 Cytoplasm, 23, 23 Cytosine, 25, 26 Cytoskeleton, 22–23, 23 Cytosol, 23–24

D D-stellate cells, 708 DAI. See Diffuse axonal injury Dark current, 408, 409 DBS. See Deep brain stimulation DCML pathway/system. See Dorsal column-medial lemniscal pathway/system Deafness cortical, 702 single-sided, 702 Decussation definition of, 130 pyramidal, 128, 129, 130, 132, 520 Deep brain stimulation, 555 Deep cerebellar nuclei, 559, 561 Default-mode network, 207 Degrees of freedom, 594–595, 597 Deiters’ cells, 363, 368–369 Dejerine’s syndrome, 135 Delay lines, 711 Dementia, 678–679 Dendrite–axon–dendrite organization, 17–18 Dendrites anatomy of, 15, 16, 21, 29, 31–32 arborization of, 33 synapse formation at, 31, 33 Dendritic spines, 33 Dentate gyrus, 233 Dentate nuclei, 559, 561 Denticulate ligaments, 262 Deoxyribonucleic acid. See DNA Deoxyribose-phosphate molecules, 25 Depolarization, 56, 57, 61, 65, 70, 77 Dermatomes, 322, 323–324 Descending motor pathways from brainstem, 524–527 from cerebrum, 515–519 Descending tracts, of direct motor control system, 515–527 Deterministic pattern, 603, 603 Diabetes insipidus, 189

Diaphragm innervation of, 119, 622 in speech production, 620, 622 Dichotic listening, 713 Diencephalon anatomy of, 111, 111, 179 hypothalamus. See Hypothalamus thalamus. See Thalamus Diffuse axonal injury, 679, 680 Diffusion, 83 Diffusion tensor imaging, 236, 250, 665, 669 Diffusion tensor imaging tractography, 250, 250 Diplopia, 159, 397 Direct motor control system corticobulbar tract, 515–522 corticospinal tract, 515–519 descending tracts of, 515–527 description of, 514 premotor cortex. See Premotor cortex reticulospinal tract, 525–527, 526 Direct response, 161 Directions Into Velocities of Articulators model, 638–642, 639 Disinhibition, 552, 555 Distributed practice, 683 DIVA model. See Directions Into Velocities of Articulators model Divergent transmission, 32, 33 Dizziness, 385–386 DLPFC. See Dorsolateral prefrontal cortex DMD. See Duchenne muscular dystrophy DMN. See Default-mode network DMth. See Dorsomedial thalamic nucleus DNA in animal behavior, 25 bases of, 25, 26 chromosomes of, 25 double-helix structure of, 25, 26 nucleotides in, 25 structure of, 25–26, 26 DNA microarray, 30 DNLL. See Dorsal nucleus of lateral lemniscus Dopamine glutamate and, 87 as neurotransmitter, 86 Dorsal, 102, 103 Dorsal acoustic stria, 703, 706 Dorsal auditory processing stream, 721 Dorsal auditory projection stream, 703 Dorsal cochlear nucleus, 703, 706, 708–709

784

Neuroscience Fundamentals for Communication Sciences and Disorders

Dorsal column-medial lemniscal pathway/system anatomy of, 327 anterolateral system versus, 328–330 characteristics of, 325t definition of, 324 description of, 310, 323–324 first-order neurons in, 324, 326 schematic diagram of, 326 second-order neurons in, 324–325, 328 structural features of, 324–328, 326 third-order neurons in, 324–325 Dorsal columns description of, 121, 122, 326 nuclei of, 326–327 Dorsal fasciculus, 121, 122 Dorsal horn, 119–120, 120 Dorsal medullary syndrome, 135 Dorsal motor nucleus of vagus, 130, 169 Dorsal nucleus of lateral lemniscus, 714 Dorsal parietal association area, 223 Dorsal processing pathways, 220, 220 Dorsal respiratory group neurons, 127, 465 Dorsal root(s), 117, 117–118 Dorsal root ganglion, 118, 118, 326, 327 Dorsal superior temporal gyrus, 634 Dorsal tegmentum, 165 Dorsal visual stream, 422–425, 424 Dorsolateral prefrontal cortex, 203, 221, 227 Dorsomedial nucleus, 186, 188 Dorsomedial thalamic nucleus, 183, 231 DRG. See Dorsal root ganglion DST. See Dynamic systems theory Dual-path models, of language processing, 669–671, 670 Dual-stream sensory processing models, 633, 633 Duchenne muscular dystrophy, 495 Dura mater, 259, 259–260 Dural folds, 260, 260 Duration, of stimulus, 295, 304–305 Dynamic systems theory, 598–601, 603–604 Dysarthria ataxic, 644, 645, 646 ataxic cerebellar, 627 definition of, 644 flaccid, 644, 645 hyperkinetic, 644, 645, 646 hypokinetic, 644, 645, 646 multiple sclerosis-related, 70 spastic, 644, 645, 646 subtypes of, 644

Dysdiadochokinesia, 568 Dyskinesia, 553–554, 626 Dysmetria, 568 Dysosmia, 456 Dysphagia, 456, 466 Dysphonia abductor spasmodic, 647 adductor spasmodic, 647 definition of, 645, 646–647 mixed spasmodic, 647 multiple sclerosis-related, 70 spasmodic, 647–648, 648 Dystonia, 544, 648

E Ear. See also Auditory system cochlea of. See Cochlea inner. See Inner ear middle, 362, 364 outer, 362 Eccentricity graph, 404, 404 Ectoderm, 109, 110 Edinger-Westphal nucleus, 142, 144, 161, 416, 429, 574 EE auditory neurons, 717 Effector enzymes, 80 Effector organs, 587 Efference copy, 345, 566, 588 Efferent neurons, 20–21 Efferent pathways of auditory system, 722–725 of speech, 620–623 of vocalization, 620–623 EI auditory neurons, 717 EK. See Equilibrium potential Electrical currents, 56 Electrical gradients, 43–44 Electrical potential, 46, 49, 55 Electrical signals, 41 Electrical synapse, 72 Electricity current, 46 definition of, 41, 44 resistance, 46–47 voltage, 44–46, 46 Electroencephalography, 657, 702 Electromagnetic energy, 288, 394, 394 Electromotility, 379 Electron, 44 Electronystagmography, 168 Embolic stroke, 275, 278 Emboliform nuclei, 559, 561 Embolism, 278, 278 Embolus, 278 Embryo cell layers of, 109, 110

development of, 109, 110 Embryologic development of cerebellum, 111 of medulla, 111 of nervous system, 109–112, 110–112 of pons, 111 of spinal cord, 111, 113, 115 Emergent phenomenon, 594 Emotions in language, 660 limbic system and, 228–237 Endocochlear potential, 365 Endocrine processes, 184 Endoderm, 109, 110 Endolymph, 364, 365, 383–384 Endolymphatic sac dysfunction, 385 Endomysium, 477, 478 Endoneurium, 107, 108 Endoplasmic reticulum of neuron, 23, 24–25 rough, 23, 24–25 smooth, 23, 24–25 Energy kinetic, 43 potential, 43 ENG. See Electronystagmography Engram, 597 Enriched experiences, 350 Enteric system, 100 Entorhinal cortex, 208, 233, 436, 444 Environmental constraints, 599, 599 Environmental pollutants, 439–440 Enzymatic degradation, 83 Epimysium, 477, 478 Epinephrine, 86, 573 Epineurium, 107, 108 EPSPs. See Excitatory postsynaptic potentials Equilibrium potential, 60 Esophageal phase, of swallowing, 458–459, 467 Essential tremor, 557 Estrogen, 190 Ethmoid bone, 113, 114 Eustachian tube, 363 Evarts, Edward, 531–533, 533 Event-related potential, 657 EWN. See Edinger-Westphal nucleus Excitation-coupling, 488–489 Excitatory event, 57 Excitatory postsynaptic potentials, 78, 79, 83, 88–89, 89, 91–92, 302–303 Excitotoxicity, 36 Executive function, 202, 226 Exons, 25, 27

INDEX

Experience-dependent cortical reorganization, 346 Experience-dependent neuroplasticity, 353, 682 Expressive aphasia, 202, 645, 675–676 External auditory meatus, 363 External branch of superior laryngeal nerve, 464 External carotid artery, 266, 267 External granular layer, of cerebral cortex, 212, 213 External pyramidal layer, of cerebral cortex, 212, 213 External superior laryngeal nerve, 622 Exteroception, 309 Extracellular fluids, 47, 47 Extrafusal fibers, 316–317, 504 Extraocular muscles description of, 395 eye gazes produced by, 160 studies of, 478 trochlear nerve innervation of, 161 Extrapyramidal system, 524 Extrastriate cortex, 210, 422, 423 Extreme capsule, 664 Eye. See also Visual system anatomy of, 395–398 anterior, 395–397 posterior, 397–398 visual fields, 398–399, 398–400 Eye gazes, 160

F FAAs. See Frontal association areas Face proprioception of, 318 somatosensory innervation of, 322 Facial nerve anatomy of, 125, 129, 131, 137, 150, 151, 166 assessment of, 167 branches of, 167, 446, 464 buccal branch of, 167 cervical branch of, 167 characteristics of, 165–167 in feeding, 462, 463–464 functions of, 157 mandibular branch of, 167 muscle innervation by, 464 in swallowing, 462, 463–464 temporal branch of, 167 zygomatic branch of, 167 Facial nucleus, 139 Facial palsy, 522–524 Falx cerebelli, 260, 260–261 Falx cerebri, 260, 260–261, 273

785

Fascicles, 477 Fasciculus anatomy of, 121, 122 anterior, 121, 122, 123 arcuate, 252, 253, 664, 670 cuneate, 326, 328 dorsal, 121, 122 gracile, 122, 122, 326, 328 inferior longitudinal, 251, 253, 672 inferior occipitofrontal, 251, 251–252 lateral, 121–122, 122 lenticular, 550 median longitudinal, 525, 672 posterior, 121, 122 superior longitudinal, 251–252, 253, 666, 670 superior occipitofrontal, 251, 251–252 uncinate, 251, 252 Fast fatigable fibers, 497 Fast fatigue-resistant fibers, 497 Fast-glycolytic fibers, 497, 499 Fast-oxidative fibers, 497, 499 Fast-twitch fibers, 497 Fastigial nuclei, 559, 561 FAT. See Frontal aslant tract Fear amygdala’s role in, 190 hypothalamus’s role in, 190 Fechner’s equation, 293 Feedback, 589–590 Feedback control, 638, 640 Feedforward control, 587–588, 638, 640 Feedforward processing, 429 Feeding chemosensory systems in, 457 description of, 435 facial nerve in, 462, 463–464 hypothalamus’s function in, 187, 189 neural substrate of, 457–468 process of, 458–465 FEFs. See Frontal eye fields Festination of gait, 554 “Fight or flight” response, 135, 140, 189 Filtering, 289–290 First-order neurons, 324, 326, 329–330 First pain, 319 Fixation assessment, 168 Flaccid dysarthria, 644, 645 Flaccidity, 644 Flavor, 446 Flocculonodular lobe, 561 FLTD. See Frontotemporal lobe degeneration

Fluent aphasias, 675–676 fMRI. See Functional magnetic resonance imaging Focal dystonias, 544 Foliate papillae, 446, 447 Foramen magnum, 113 Foramen of Luschka, 265 Foramen of Magendie, 264, 265 Foramen of Monro, 263 Force fields, 43–44, 44 Forceps major, 254, 255 Forceps minor, 254, 255 Foresight, lack of, 203 Forkhead box P2, 28 Formant frequency, 700 Formant frequency shift, 700 Fornix, 229, 233 Forward model, 588 4th ventricle, 130, 263, 264, 265 Fovea, 158, 398, 405, 406 Foveola, 405 FOXP2 mutation, 28 Fractured somatotopy, 530 Frequency, of auditory signal, 700 Frontal aslant tract, 254, 254, 664, 666, 672 Frontal association areas, 222, 224, 226, 227 Frontal bone, 113, 114 Frontal eye fields, 198, 201–202, 429 Frontal lobe anatomy of, 125, 194, 197 Broca’s area of, 202 cognitive functions of, 195–197 frontal eye fields of, 198, 201–202 functions of, 195–197 gyri of, 197 homunculus of, 199, 200 in language, 661 M1 region of, 197–200 motor functions of, 195–197 orbitofrontal gyri of, 197 Phineas Gage case study, 225–226 precentral gyrus of, 197 prefrontal cortex of, 198, 198, 202–203, 226 premotor area of, 198 premotor region of, 200–201 primary motor cortex of, 198–200, 227 somatotopic mapping of, 198 Frontopontine fibers, 144 Frontotemporal disorders, 199 Frontotemporal lobe degeneration, 199 Functional magnetic resonance imaging, 226, 656, 722 Functional variability, 598, 600, 603

786

Neuroscience Fundamentals for Communication Sciences and Disorders

Fungiform papillae, 446, 447 Fused tetanus, 496 Fusiform cells, 708 Fusiform gyrus, 208

G G-actin, 484 G-coupled gated receptors, 407–408, 451–452 G-coupled receptors, 440–442 G-protein, 79–80, 82 G-protein-coupled receptors, 79 GABA. See Gamma-aminobutyric acid Gadolinium agents, 346 Gage, Phineas, 225–226 Galambos, Robert, 724 Galen of Pergamum, 3, 582, 584–585, 607 Gamma-aminobutyric acid, 84–86, 552 Gamma motoneurons, 121, 317, 504–505 Ganglia basal. See Basal ganglia definition of, 107 Gap junction, 72, 73, 365 Gargalesis, 302 Gases, as neurotransmitters, 84, 85, 86–87 Gate theory of pain, 333–334, 334 Gating, 50, 50, 115, 120, 302, 516 Gaze, 160 GDP. See Guanosine diphosphate Gene(s) definition of, 25 in neurological disease, 30 Gene chip, 30 Gene expression, 26–28, 29 Gene expression profiling, 30 General motor program theory, 597–598, 600 General motor programs, 597–598 General nerves, 154 General somatic afferent, 155 General somatic efferent, 155 General visceral afferent, 155 General visceral efferent, 155 Genetic variation, 30 Genome-wide association, 30 Gentamicin, 385 Georgopoulos, Apostolos, 535–536 Geschwind, Norman, 206 Glabrous skin, 310, 312 Glial cells description of, 14 functions of, 36 groups of, 33–36

in information processing, 36 macroglia. See Macroglia microglia, 33, 34 name origin of, 33 Glioblastomas, 35 Global aphasia, 675 Globose nuclei, 559, 561 Globular bushy cells, 708 Globus pallidus, 550, 626 Globus pallidus external, 550, 626 Globus pallidus internal, 550, 626 Glomeruli, 443, 443–444 Glossopharyngeal nerve anatomy of, 125, 129, 131, 150, 151, 157, 169–170, 170, 386, 447 in swallowing, 462, 464 Glutamate description of, 35–36 dopamine and, 87 excitotoxicity, 36 hair cell release of, 375 as neurotransmitter, 84–85, 211 photoreceptor expression of, 409–410 Glycine, 84, 86 Glycogen, 497 Glycolysis, 497 Goal-oriented functions, 584, 603 Golgi, Camillo, 14 Golgi apparatus, 23, 25 Golgi tendon organ, 316–318, 317, 463 Goosebumps, 189, 571 Gracile fasciculus, 122, 122, 326, 328 Gracile nucleus, 130–131, 327 Gradients concentration, 41–42, 42, 59 electrical, 43–44 in neural signaling, 42–44 Granule neurons, 212 Gravity, 45–46, 58 Gray matter anatomy of, 105, 105–107 imaging of, 664 of mesencephalon, 142 spinal cord, 119–121, 120 stroke-related damage to, 686 Great cerebral vein of Galen, 274 GSA. See General somatic afferent GSE. See General somatic efferent GTP. See Guanosine triphosphate Guanine, 25, 26 Guanosine diphosphate, 81 Guanosine triphosphate, 81 Gustation, 445 Gustatory center, 167, 463 Gustatory pathways, 452–453 Gustatory receptors, 446–447

Gustatory system. See also Taste central pathway of, 452–453, 454 overview of, 445–446 tastant detection by. See Tastants GVA. See General visceral afferent GVE. See General visceral efferent GWA. See Genome-wide association Gyri anatomy of, 105–106, 106, 192 angular, 205–206 anterior cingulate, 235–236 cingulate, 235–236 dentate, 233 dorsal superior temporal, 634 fusiform, 208 Heschl’s, 717 inferior frontal, 197 inferior occipital, 209 inferior temporal, 207 lingual, 209 medial temporal, 232 middle frontal, 197 middle temporal, 207 occipitotemporal, 196, 207–208 orbitofrontal, 197 parahippocampal, 208, 231 postcentral, 204, 628 precentral, 197 superior frontal, 197 superior occipital, 209 superior temporal, 207 supramarginal, 205–206, 632 Gyrus rectus, 196, 197

H H-zone, 482 Hair cells activation of, 370 ampullary, 383 auditory nerve innervation of, 376 basilar membrane and, 370 damaging of, 371 depolarization of, 374, 374 description of, 361 electromotility of, 379 functional features of, 369–371 inner, 363, 368, 368–369, 375 otolith, 382 outer, 363, 368, 368–370, 373, 379–380 preservation of, 371 receptor potentials of auditory nerve transmission of, 375–376 description of, 373 resting potential of, 365

INDEX

shape of, 368 shearing of, 370 speed of, 374 stereocilia of, 371–372, 371–372, 379 structural features of, 369–371 tonotopic organization of, 369, 376 vestibular system, 380–381 Hair follicle endings, 312, 315 Head trauma olfactory system affected by, 158 traumatic brain injury, 679–681, 680 Healthy volunteer, in clinical trial, 687 Hearing central auditory pathway in. See Central auditory pathway cochlear nucleus. See Cochlear nucleus physiology of, 362 Heat receptors, 319 Helicotrema, 362, 366 Hemiballism, 555 Hemichannels, 72 Hemorrhagic stroke, 275–276, 277 Hensen’s cells, 369 Herniation syndromes, 262 Heschl’s gyrus, 717 Heteronomous hemianopsia, 428 Hierarchical processing, 218–219 High-frequency sound localization, 713 Hippocampal formation anatomy of, 232, 233 dentate gyrus, 233 in operant conditioning, 230 in spatial learning, 230–233 subiculum, 233 Hippocampus description of, 191 functions of, 231 injuries to, 230 lesions of, 230 Histology, 21 Holmes, Gordon, 627 Homonymous hemianopsia, 428 with macular sparing, 428 Homonymous quadrantanopsia, 428 Homunculi, 312 Homunculus, 199, 339 Horizontal cells, 401 Horizontal distribution, 212 Horizontal plane, 104, 104 HPA axis. See Hypothalamic-pituitaryadrenal axis Human Connectome, 671 Huntington’s disease, 30, 555, 556, 626 Hydrocephalus, 264–265

787

Hydrocephalus ex-vacuo, 264 Hydrolysis, 24, 24 Hydrophilic, 22 Hydrophilic odorants, 439 Hydrophobic, 22 Hydrophobic odorants, 439 Hyperalgesia, 321 Hypercapnia, 127 Hypercolumn, 421, 421 Hyperkinesia, 646 Hyperkinetic dysarthrias, 555, 644, 645, 646 Hyperkinetic dyskinesias, 554–557 Hypermetropia, 397 Hyperpolarization, 57, 57, 67 Hyperpolarizing event, 57 Hypertonia, 200, 544 Hypoglossal nerve anatomy of, 125, 128, 129, 131, 150, 151, 157, 174, 175 in swallowing, 462, 465 Hypoglossal nucleus, 130 Hypokinesia, 646 Hypokinetic dysarthrias, 554–555, 644, 645, 646 Hypokinetic dyskinesias, 554–555 Hyposmia, 158, 456 Hypothalamic-pituitary-adrenal axis, 140, 186 Hypothalamus in aggression, 190 anatomy of, 180, 187 in autonomic system regulation, 189–190 in circadian rhythms, 189 in cyclic behaviors, 189 description of, 184, 186 in fear responses, 190 in feeding, 187, 189 functions of, 184, 186–187, 189–190, 231 homeostatic functions of, 186–187, 189–190 inputs to, 184, 185, 186 neural inputs to, 184 nuclei of, 186–190, 188 pituitary gland and, 186, 189 in sexual arousal, 190 in temperature regulation, 189 in water consumption, 189

I I-band, 481 Ia afferents, 316, 504 Ib afferents, 317 ICMS. See Intracortical microstimulation

Ideomotor apraxia, 223 IID. See Interaural intensity differences Immediate zone, 121 Incomplete spinal cord injury, 115 Incus, 363 Indirect motor control systems basal ganglia. See Basal ganglia cerebellum. See Cerebellum description of, 514 Individual constraints, 599, 599 Indusium griseum, 229 Infarct, 249 Inference, 289–290 Inferior, 103 Inferior anastomotic vein, 274 Inferior cerebellar peduncle, 137, 562–563, 563 Inferior colliculus, 142–143, 704, 708, 715–716 Inferior frontal gyrus, 197, 629–630 Inferior longitudinal fasciculus, 251, 253, 672 Inferior occipital gyrus, 209 Inferior occipitofrontal fasciculus, 251, 251–252 Inferior olivary complex, 130, 133, 566 Inferior parietal lobule, 204–207 Inferior petrosal sinus, 274–275 Inferior sagittal sinus, 272, 273–274 Inferior salivatory nucleus, 574 Inferior temporal gyrus, 207 Inferior temporal lobe, 209 Inferior temporal sulcus, 196, 634 Inferior thalamic radiation, 257 Information processing, glial cells in, 36 Informed consent, 234 Infratentorial, 260 Infundibulum, 186 Inhibitory event, 57 Inhibitory interneurons, 591 Inhibitory postsynaptic potentials, 78, 80, 83, 88–89, 92 Inner ear cochlea of. See Cochlea cochlear amplifier function of, 724 description of, 361 semicircular canals of. See Semicircular canals Inner hair cells, 361, 363, 368, 368–369, 375 Innervation ratio, 500 Insula, 191, 210–211, 231, 632, 662 Intensity of auditory signal, 700 of stimulus, 295, 302–304, 303 Intensity coding, 710 Intentional tremors, 568, 646

788

Neuroscience Fundamentals for Communication Sciences and Disorders

Interaural intensity differences, 710, 711, 714 Interaural time delays, 710, 711–712 Interblobs, 421, 421 Interhemispheric connectivity, 237–239 Intermediate acoustic stria, 703, 706 Intermediate cerebellum, 627 Intermediate horn, 119, 120 Internal arcuate, 328 Internal branch of superior laryngeal nerve, 464 Internal capsule anterior limb of, 256–257, 256–257 corona radiata of, 258, 258–259 description of, 255, 256–257 lesions of, 257–258 organization of, 256 posterior limb of, 256–257, 257 stroke of, 257 Internal carotid artery, 266, 267 Internal cerebral vein, 274 Internal granular layer, of cerebral cortex, 212, 213 Internal jugular vein, 272, 275 Internal medullary lamina, 182 Internal pyramidal layer, of cerebral cortex, 212, 213 Interneurons description of, 20–21 information flow modulation by, 32 inhibitory, 591 in swallowing central pattern generator, 468 Interoception, 309 Interposed nucleus, 561 Interstimulus interval, 495 Interthalamic adhesion, 183, 265 Intervertebral discs, 113 Intracellular fluids, 47, 47 Intracerebral hemorrhage, 276 Intracortical microstimulation, 529, 542 Intrafusal fibers, 316–317, 504 Intraparietal sulcus, 204–205 Intraventricular foramina, 263, 264 Intrinsic muscles of the larynx, 478, 622 Introns, 25 Invariant features, 597 Inverse model, 588 Involuntary movements, 585 Ion(s) charge of, 56 concentration gradient, 48 definition of, 14, 42 motion of, 49–50 negative, 44 positive, 44 size of, 49

Ion channels calcium activated, 50 creation of, 48–49, 49 definition of, 48 gating by, 50, 50 ion motion affected by, 49–50 ion pumps versus, 53 ionic current gated by, 50–52 ligand gating of, 50–51, 51 mechanical gating of, 51, 51–52 membrane permeability, 55 open, 52–53, 55 patency of, 50 resting, 52–53, 55 structural features of, 49 subunits of, 48, 49 types of, 55 voltage gating of, 51, 51 Ion pumps, 53–54, 56 Ionic current, 50–52 Ionotropic receptors, 78–79 IPSPs. See Inhibitory postsynaptic potentials Ischemic stroke, 275, 277, 278, 279 ISI. See Interstimulus interval Itching, 320 ITDs. See Interaural time delays

J Jaw-jerk reflex, 164, 335 JND. See Just noticeable difference Junctional folds, 486 Jurgens, Uwe, 236 Just noticeable difference, 293

K Kinesophobia, 569 Kinetic energy, 43 Knee-jerk response/reflex, 18, 19, 115, 316 Knismesis, 302 Knock-in animals, 21 Knockout animals, 21 Knockout mice, 22 Kuhl, Patricia, 657–658

L L-cones, 406 LAAs. See Limbic association areas “Lab-on-a-chip” devices, 291 Labeled-line principle, 292, 319 Language acquisition of, 656–658 basal ganglia in, 662

cerebellum in, 662 cognitive-executive control of, 660, 664 critical period for, 656 definition of, 655–656 emotion in, 660 evolution of, 658–659, 672 frontal lobe in, 661 functional magnetic resonance imaging studies of, 656–658 insula in, 662 lateralization of, 662 left hemisphere dominance of, 238 novel utterances in, 659 occipital lobe in, 662 parietal lobe in, 661 perisylvian area of, 659, 660f sensitive period for, 656 statistical learning, 658 temporal lobe in, 661 thalamus in, 662 Wernicke’s area in, 208–209 Language disorders aphasia. See Aphasia dementia, 678–679 right hemisphere damage as cause of, 681–682 traumatic brain injury as cause of, 679–681, 680 Language processing brain areas in, 659–666, 661–663 dual-path models of, 669–671, 670 white matter tracts in, 665–666 Language production Memory, Unification, Control model of, 668, 669 models of, 666–671 Wernicke-Gechwind model of, 667–668, 667–669 Language rehabilitation constraint-induced language therapy, 684–685 neuroplasticity in, 683 noninvasive brain stimulation for, 687 overview of, 682–683 after stroke, 685–687 Laryngectomy, 456 Larynx intrinsic muscles of, 478, 622 in speech, 622 in vocalization, 622 Lateral corticospinal tract, 122, 124, 520 Lateral fasciculus, 121–122, 122 Lateral geniculate nucleus, 143, 183–184, 185, 209, 416–417

INDEX

Lateral hypothalamic nucleus, 186–187, 188 Lateral inhibition, 300, 301, 411 Lateral lemniscus, 144, 704, 714 Lateral medullary syndrome, 135 Lateral spinothalamic tract, 122 Lateral sulci, 193 Lateral superior olivary complex description of, 708, 710 high-frequency sound localization, 713 Lateral tract, 331 Lateral ventricles, 263, 264 Lateral vestibular nucleus, 387 Lateral vestibulospinal tract, 387, 525, 526 Lateralization of language, 662 Laughing/laughter, 631 Learned movements, retention of, 607 Learned nonuse, 683 Learning constraints during, 599 limbic system in, 228–229 sensorimotor, 605 statistical, 658 Left visual hemifield, 418 Length-tension relationship, 492–493, 492–494 Lens accommodation, 397 Lenticular fasciculus, 550 Lesions basal ganglia, 553–557 cerebellum, 568, 569 hippocampus, 230 internal capsule, 257–258 suprachiasmatic nucleus, 189 Ligand(s), 50 Ligand-gated ion channels description of, 50–51 diversity of, 52 Ligand-gated receptors, 73 Ligand gating, 50–51, 51 Light absorption of, 395, 395 in environment, 394–395 reflection of, 395, 395 refraction of, 395, 395 transduction of, 407, 408 Limbic association areas, 224, 228 Limbic system amygdala. See Amygdala anatomy of, 228, 229, 231 anterior cingulate gyrus, 235–236 aversive centers of, 229 discovery of, 228 emotions and, 228–237 functions of, 228

789

in learning, 228–229 reward operations of, 229–230 septal area, 236–237 Lingual gyrus, 196, 209 Lip gestures, 503 LMNs. See Lower motoneurons Location, of stimulus, 295, 297–302 Locked-in syndrome, 641, 646 Locus ceruleus, 86, 136, 140 Logopenic primary progressive aphasia, 678 Long-term potentiation, 233 Longitudinal cerebral fissure, 190, 191, 196 Loudness, 123, 377 Low-frequency sound localization, 710–714 Lower motoneurons damage to, 544–546, 545 description of, 120–121, 486, 495–496, 499–501, 500, 504 facial palsy, 522–524 influences on, 518 injury to, 544–546, 545 input on, 518 negative neurological signs after injury to, 545 pathways, 515 LSOC. See Lateral superior olivary complex LTP. See Long-term potentiation Lumbar vertebra, 113, 115 Luria, Alexander, 195

M M1. See Primary motor cortex M-cones, 406–407 M-line, 482 M-type retinal ganglion cells, 414, 415, 417 MacLean, Paul, 228 Macroglia astrocytes, 33, 35, 35 description of, 33 oligodendrocytes, 33–34, 35 Schwann cells, 33–34, 35 Macula, 398, 405 Macular shearing, 382 Magnetic resonance imaging, 346, 702 Magnetoencephalography, 656, 702 Magnets, 43–44, 44 Magnitude estimation, 293 Magnocellular lateral geniculate nucleus, 425 Magnocellular-type retinal ganglion cells, 414, 415, 417

Malleus, 363 Mammillary bodies, 129, 143, 186, 188, 196, 229 Mandible, 623 Massa intermedia, 183, 265 Massed practice, 682 Mastication, 463 Mayo Clinic classification scheme, 644 MEC2 mutation, 31 Mechanical gating, 51, 51–52 Mechanical nociceptors, 320 Mechanically-gated ion channels, 51–52, 53 Mechanoreceptors anatomic distribution of, 312 cutaneous, 312–313, 313–314 description of, 127, 294–296, 295, 304, 311 hair follicle endings, 312, 315 Meissner corpuscles, 312, 313–314, 314–315 Merkel discs, 312–314, 313–314 Pacinian corpuscles, 312, 313–314, 315 rapidly adapting fibers of, 313 Ruffini endings, 312, 313–314, 315, 318 slowly adapting fibers of, 313 tactile, 318 types of, 312, 313 variations in, 312 Medial forebrain bundle, 237 Medial geniculate body, 143, 704, 716–717 Medial geniculate nucleus, 183–184, 185 Medial lemniscal pathway, 328. See also Dorsal column-medial lemniscal pathway/system Medial lemniscus, 133, 140 Medial medullary syndrome, 135 Medial nucleus of the trapezoid body, 703, 710–713 Medial olivocochlear bundle, 380 Medial prefrontal cortex, 203, 236 Medial superior olivary complex description of, 708, 710 low-frequency sound localization processing in, 710–714 Medial temporal gyrus, 232 Medial vestibulospinal tract, 387, 525, 526 Median longitudinal fasciculus, 525, 672 Mediodorsal thalamus, 256 Medulla oblongata anatomy of, 126–128, 150, 151 anterolateral tract of, 133

790

Neuroscience Fundamentals for Communication Sciences and Disorders

Medulla oblongata  (continued) axial section of, 133–134 caudal, 133 concept map of, 129 corticospinal tract of, 133 description of, 124 embryologic development of, 111 external features of, 128–130 functions of, 126 internal features of, 130–135, 131–135 medial lemniscus of, 133 olivary eminence of, 128, 129, 130 pyramidal decussation of, 128, 129, 130, 132, 520 pyramids of, 128, 129, 130 respiratory neural centers in, 127 reticular formation, 124, 126 rostral, 134 Medullary respiratory center, 127, 128, 465 Medullary reticulospinal tract, 525, 526 Medullary syndromes, 135 MEG. See Magnetoencephalography Meissner corpuscles, 312, 313–314, 314–315 Membrane permeability, 55 Membrane potential characteristics of, 56 depolarization effects on, 56 description of, 54–56 hyperpolarization effects on, 57 ionic gradients and currents effect on, 56–58 negative, 57–58 resting, 58–62, 62–63 Membrane voltage from separation of charges, 56 shifting of, 57 Memory, Unification, Control model, 668, 669 Meniere’s disease, 385 Meninges anatomy of, 259 arachnoid layer of, 259, 259, 262 definition of, 259 dura mater, 259, 259–260 pia mater, 259, 259, 262 Mental time travel, 659 Menthol, 319 Merkel discs, 312–314, 313–314 Mesencephalic nucleus, 140, 164, 335–336, 336, 463 Mesencephalon anatomy of, 140–142, 150, 151 caudal, 141 concept map of, 143

crus cerebri of, 140, 141–142, 143–144 description of, 111, 124 external features of, 143–144 gray matter of, 142 inferior colliculus of, 142–143 internal features of, 144–145 lateral lemniscus of, 144 midpoint of, 141 oculomotor nerve in, 159 red nuclei of, 142, 144 rostral, 142 substantia nigra of, 86, 142, 144 superior colliculus of, 142–143 tectum, 111, 125, 142 tegmentum, 111, 136, 142, 144–145 ventral, 143 Mesoderm, 109, 110 Messenger ribonucleic acid. See mRNA Metabotropic receptors, 78–79, 81–82, 408, 410 Metencephalon, 111, 112 Method of limits, 292 Microelectrode mapping, 339 Microfilaments, 22 Microglia, 33, 34 Microtubules, 22 Midbrain. See Mesencephalon Middle cerebellar peduncle, 137, 562–563, 563 Middle cerebral artery anatomy of, 266–267, 268–270, 271, 273 branches of, 270 Middle cranial fossa, 114 Middle ear, 362, 364 Middle frontal gyrus, 197 Middle temporal artery, 269 Middle temporal gyrus, 207 Middle temporal lobe, 209 Middle temporal sulcus, 207 Midsagittal plane, 104 Mini-strokes, 276 Mirror neurons, 202, 538–539, 540 Mitochondria adenosine triphosphate production by, 24, 24, 479 definition of, 479 of neuron, 24, 24 Mitral cells, 444 Mixed spasmodic dysphonia, 647 Mixed transcortical aphasia, 675 MNTB. See Medial nucleus of the trapezoid body Modality, of stimulus, 294–296, 295 Modiolus, 375 Molecular biology, 21

Molecular layer, of cerebral cortex, 212, 213 Monochromatic vision, 405 Monocular visual field, 398, 398 Mononeuropathies, 108 Monosodium glutamate, 446 Motoneurons alpha, 120–121, 504 gamma, 121, 317, 504–505 lower. See Lower motoneurons somatic, 115 upper. See Upper motoneuron(s) visceral, 115 Motor control basal ganglia in, 626 Bernstein’s studies of, 593–597 closed-loop systems in, 588–591, 590 definition of, 581, 585 description of, 475, 582–585 dynamic systems theory of, 598–601, 603–604 open-loop systems in, 587–588 reflexes in, 591–593 theory of, 586–597, 607–608 Motor control systems direct, 514 flowchart of, 515 indirect, 514 lower motoneuron damage effects on, 544–545 overview of, 513–514 upper motoneuron damage effects on, 544–545 Motor coordination, 515, 558 Motor endplate, 486 Motor endplate potential, 486 Motor equivalence, 593–597 Motor homunculus, 199, 200, 529 Motor learning cerebellum in, 558 description of, 515 Motor nerve neuropathies, 108 Motor neuron pools, 121, 619, 623 Motor neurons, 20, 33, 504. See also Motoneurons Motor nuclei of cranial nerves, 151 of trigeminal system, 140 Motor program theory, 597–598, 600 Motor skill acquisition of, 604–607 definition of, 585 sensorimotor, 605–607 Motor speech disorders, 644–646, 645 Motor unit definition of, 499 innervation ratio of, 500

INDEX

lower, 499–501, 500, 504 size principle of recruitment, 502–504 Mountcastle, Vernon, 215, 293 Movements behavior and, 601 biology–environment interactions as source of, 601–602 coordination of, 594, 596 definition of, 585 involuntary, 585 learned, retention of, 607 voluntary, 585 MPFC. See Medial prefrontal cortex MRI. See Magnetic resonance imaging mRNA, 26, 27 MSG. See Monosodium glutamate MSOC. See Medial superior olivary complex Multiform layer, of cerebral cortex, 212, 213 Multimodal integration, 204, 429–430, 430 Multiple sclerosis blood-brain barrier’s role in, 36 definition of, 70 speech production affected by, 70 Multipolar neurons, 20, 21, 23 Muscle cells, 18 Muscle fibers anatomy of, 479–481, 480 contraction physiology of, 488–489 cross-bridge of, 484, 489–491, 490 excitation-coupling in, 488–489 fatigability of, 498 skeletal, 496–499, 499 Muscle spindle, 316, 316–318, 463 Muscle tissue cardiac, 476, 477 contraction of, 494–499, 504–505 excitability of, 18 length-tension relationship in, 492–493, 492–494 skeletal. See Skeletal muscle smooth, 476, 476 striated, 476, 476 types of, 476–477 Muscle twitch, 494, 494 Muscular hydrostat, 623 Music education, 168 Mutism, 645, 646 Myasthenia gravis, 76 Myelencephalon, 111, 112 Myelin, 33–34, 70, 71 Myelinated axon, 70 Myofiber, 479 Myofibril A-band of, 481

791

anatomy of, 480 definition of, 479 H-zone of, 482 I-band of, 481 M-line of, 482 neuromuscular junction of, 485–488 organization of, 481–494 sarcomere of. See Sarcomere structure of, 481–494 thick filament of, 481–482, 483 Z-lines of, 480, 481–482 Myofilaments, 481 Myogenesis, 479 Myoglobin, 497 Myosin, 481, 482–484, 483 Myosin adenosine triphosphatase, 496

N Na+-K+ pump. See Sodium-potassium pump Nasal monocular retinal hemifield, 399 Nasal retinal hemifield, 399 Negative charge, 45 Negative ions, 44 Negative neurological signs, 545 Neglect syndrome, 224–225 Neologism, 673–674 Nernst equation, 60 Nerve(s). See also Cranial nerves; Peripheral nerves; specific nerve definition of, 107 peripheral, 107 structure of, 107, 108 Nerve cells. See Neuron(s) Nerve fascicle, 108 Nervous system anatomy of, 99–100, 99–102 apoptosis in, 34 autonomic. See Autonomic nervous system central. See Central nervous system divisions of, 99–100, 99–102 embryologic development of, 109–112, 110–112 excitotoxicity caused by trauma to, 36 glial cells of. See Glial cells neurons. See Neuron(s) operation of, 13 peripheral. See Peripheral nervous system Neural circuits, 17 Neural crest anatomy of, 110 cells of, 109, 111–112 Neural ensembles, 17 Neural folds, 109

Neural groove, 109, 110 Neural information, 37 Neural integration analogies for, 92–93 definition of, 88, 89 description of, 88–92 in postsynaptic cell, 92–93 Neural networks description of, 17–18 for knee-jerk reflex, 18, 19 model of, 37–38 reflexes as example of, 18–20, 19 Neural plate, 109, 110 Neural signaling chemical signals, 41 definition of, 41 driving forces of, 41 electrical signals, 41 gradients in, 42–44 Neural tube, 109, 111–112 Neurobiologists, 14 Neurocognitive disorders, 678 Neurofilaments, 22 Neuromodulation, 87 Neuromodulators, 87 Neuromuscular junction definition of, 486 description of, 18 motor endplate of, 486 in myasthenia gravis, 76 myofibril, 485–488 structure of, 487 Neuron(s). See also Motoneurons action potential of, 17 activation of, 93 activities performed by, 17–18 afferent, 20–21 arrangement of, 15–17, 31, 32 axons of, 16, 21, 29, 31–33 bipolar, 20, 21 cell membrane of, 21, 21–23 central, 32–33 cerebellar, 33 chemical agents used by, 87 classification of, 20, 21 communication functions of, 15 concept map of, 37 convergent pattern of, 32, 32–33 cytoplasm of, 23, 23 cytoskeleton of, 22–23, 23 definition of, 14 dendrites of, 21, 29, 31–33 divergent pattern of, 32, 33 dorsal group central pattern generator, 468 efferent, 20–21 electrical signaling by, 14–15

792

Neuroscience Fundamentals for Communication Sciences and Disorders

Neuron(s)  (continued) excitatory input for, 17 extracellular fluids, 47, 47 first-order, 324, 326, 329–330 fluid environment of, 47 functions of, 17–18 glial cells versus, 14 Golgi apparatus of, 23, 25 granule, 212 inhibitory input for, 17 interconnected groupings of, 17 interneurons. See Interneurons intracellular fluids of, 47, 47 ion environment of, 47, 48 “leaky,” 55, 58 mirror, 202, 538–541, 540 mitochondria of, 24, 24 models of, 37–38 motor, 20, 33 multipolar, 20, 21, 23 nucleus of, 25–28 olfactory receptor. See Olfactory receptor neurons optic tract, 417–418 population of, 15–17 population response of, 15, 17 postganglionic, 574 projection, 444–445 pseudounipolar, 20, 21 pyramidal tract, 197, 532, 534 resting state of, 17 rough endoplasmic reticulum of, 23, 24–25 second-order, 324–325, 328, 329–330, 338–339, 452 sensory, 20 separation of charges, 56 serial pattern of, 31, 32 smooth endoplasmic reticulum of, 23, 24–25 soma of, 16, 21 structural features of, 15, 16, 21–33 synapse of. See Synapse third-order, 324–325, 329–330 unipolar, 20, 21 Neuronal groups, 17 Neuropathic pain, 321 Neuropathy motor nerve, 108 peripheral, 108 sensory nerve, 108 Neuropeptides, 84, 85, 86–87 Neuroplasticity in cortical motor maps, 542–544 description of, 13, 83 enriched experiences and, 350 language rehabilitation and, 683

overview of, 346–347 principles of, 353 purpose of, 346 rehabilitation and, 354 sensory inputs, 350–353 Neuroscience definition of, 3–4 early studies in, 3 growth of, 3 Neurotransmitters acetylcholine, 86, 570 amines, 84, 85, 86 amino acids, 84–86, 85 classes of, 84–87, 85 definition of, 74 description of, 50, 84 dopamine, 86 epinephrine, 86, 573 gamma-aminobutyric acid, 84–86 gases, 84, 85, 86–87 glutamate. See Glutamate glycine, 84, 86 identification of, 85 neuropeptides, 84, 85, 86–87 nitric oxide, 85, 87 nonclassical, 86 norepinephrine, 86, 570, 573 postsynaptic receptor binding, 78 serotonin, 86 in synaptic cleft, 75, 83 Neurulation, 109, 110 Night blindness, 397 Nigrostriatal fibers, 550 Nissl stain, 25 Nitric oxide, 85, 87 NMJ. See Neuromuscular junction Nociception description of, 319–321 pain and, 319 pathways of, 310 regulation of, 320–321 Nociceptive pain, 321 Nociceptors description of, 294, 295, 296, 319–320 free nerve endings of, 320 ion channels of, 320 mechanical, 320 polymodal, 320 thermal, 320 Nodes of Ranvier, 34–35, 35, 70 Nonclassical neurotransmitters, 86 Noncommunicating hydrocephalus, 264 Nonfluent/agrammatic primary progressive aphasia, 678 Nonfluent aphasias, 202, 675–676 Nonglabrous skin, 310

Noninvasive brain stimulation, 687 Nonregulatory conditions, 606 Nonspeech oromotor exercises, 602 Norepinephrine, 86, 570, 573 Normal pressure hydrocephalus, 264 Notochord, 109, 110 Novel utterances, 659 Nuclei abducens, 139 arcuate, 186, 188, 189 in brainstem, 106 caudate, 546, 549–550 cerebellar, 559, 561 cochlear. See Cochlear nucleus cranial nerve, 124, 151–153, 152 cuneate, 130–131, 327 definition of, 105–106 dentate, 559, 561 dorsal column, 326–327 Edinger-Westphal, 142, 144, 161, 416, 429, 574 emboliform, 559, 561 facial, 139 fastigial, 559, 561 globose, 559, 561 gracile, 130–131, 327 hypothalamic, 186–190, 188 interposed, 561 lateral geniculate, 143, 183–184, 185, 416–417 medial geniculate, 183–184, 185 mesencephalic, 140 motor. See Motor nuclei oculomotor, 144 pontine, 139 principal trigeminal, 140 red, 142, 144–145 spinal trigeminal, 131 subcortical, 105, 106 subthalamic, 550 thalamic, 81–184, 185, 199 trochlear, 144 ventroposterolateral, 183, 185, 328, 329 ventroposteromedial, 183, 185, 328, 329, 453 vestibular, 133, 386–387 Nucleotides, 25 Nucleus accumbens, 626 Nucleus ambiguus, 131 Nyctalopia, 397 Nystagmus, 168, 385

O Obex, 130 Object recognition areas, 209

INDEX

Objective tinnitus, 379 OCB. See Olivocochlear bundle Occipital bone, 113, 114 Occipital lobe anatomy of, 125, 194, 209 description of, 209 functional areas of, 209–210 in language, 662 Occipitofemoral gyrus, 253 Occipitotemporal gyrus, 196, 207–208 Octopus cells, 708 Ocular dominance columns, 420, 420 Oculomotor nerve anatomy of, 125, 129, 131, 150, 151, 156, 160 characteristics of, 159–161 paralysis of, 159 Oculomotor nucleus, 144 Odorant(s) definition of, 435 hydrophilic, 439 hydrophobic, 439 olfactory receptor neuron detection of, 442 proteins binding to, 439 transduction of, 438, 440–441, 440–442 Odorant receptors, 436 OFC. See Orbitofrontal cortex OFF-bipolar cells, 409–413 OFF-center receptor field, 411–413, 412 Ohm, 46 Ohm, Georg Simon, 47 Ohm’s Law, 47 Olfaction injury-related changes in, 456 retronasal, 442 in taste sense, 463 testing of, 455 thalamus’s role in, 180 Olfactory bulb anatomy of, 196, 197, 229, 436 glomeruli of, 443, 443–444 projection neurons of, 444–445 Olfactory cilia, 438 Olfactory cortex, 444 Olfactory epithelium, 436 Olfactory nerve, 125, 129, 131, 150–151, 156, 156, 158 Olfactory receptor(s), 438–439 Olfactory receptor neurons adaptability of, 441 anatomy of, 438, 438 cilia of, 438–440 description of, 438 environmental pollutants, 439–440

793

life span of, 438 odorant detection by, 442 Olfactory system brain and, 180 functions of, 436 head trauma effects on, 158 odorant detection by, 435 organization of, 437 overview of, 436–438 peripheral, 438 smells detected by, 436 Olfactory tract, 196, 197, 229, 437 Olfactory tubercle, 229, 436, 444 Oligodendrocytes, 33–34, 35 Olivary eminence, 128, 129, 130 Olivocochlear bundle, 724–725 ON-bipolar cells, 409–413, 411 ON-center receptor field, 411–413, 412 Onset PTSH response pattern, 708 Open channels, 52–53 Open-loop systems, 587–588 Open system, 601 Operant conditioning, 230 Opercula, 210 Opsin, 404 Optic chiasm anatomy of, 143, 158–159, 416–417 damage to, 428 Optic disc, 158, 397 Optic nerve anatomy of, 125, 129, 131, 150, 151, 156, 159 characteristics of, 159–160 fibers of, 416 Optic radiations, 209, 257 Optic tract damage to, 428 description of, 143, 159, 416–417 Optic tract neurons, 417–418 Optokinetic assessment, 168 Optometrist, 397 Oral cavity, 503 Oral preparatory phase, of swallowing, 458–459, 467 Oral transport phase, of swallowing, 458–459, 467 Orbitofrontal artery, 269 Orbitofrontal cortex, 203, 221, 226, 227, 445 Orbitofrontal gyri, 196, 197 Organ of Corti anatomy of, 363, 364 auditory transduction inputs, 367–369 hair cells of. See Hair cells support cells of, 368–369

Organelles, 23 Organismic constraints, 599 Orientation columns, 420, 420–421 ORN. See Olfactory receptor neurons Orofacial skin, 318 Orthodromic conduction, 69 Ossicular chain, 362, 363 Otoacoustic emissions, 380, 725 Otoconia, 382, 382 Otolith organs description of, 380–381 saccule, 381–382 utricle, 381–382 Otolithic membrane, 382 Outer ear, 362 Outer hair cells, 363, 368, 368–370, 373, 379–380 Oval window, 363 Oxidative fibers, 497 Oxidative phosphorylation, 497 Oxygen, blood levels of, 127 Oxytocin, 186

P P-type retinal ganglion cells, 414, 415, 417 PAAs. See Parietal association areas PACE. See Promoting aphasics’ communication effectiveness Pacinian corpuscles, 312, 313–314, 315 PAG. See Periaqueductal gray Pain congenital insensitivity to, 319 first, 319 gate theory of, 333–334, 334 neuropathic, 321 nociception and, 319 nociceptive, 321 perceptual response of, 319–321 second, 319 transcutaneous electrical nerve stimulation for, 334 Palatoglossus, 465 Pallidosubthalamic fibers, 550 Papez, James, 228 Papillae, 446, 447 Parabelt region, 720 Parabrachial nucleus, 453 Parahippocampal cortex, 436 Parahippocampal gyrus anatomy of, 196, 208, 231, 233 hippocampal formation in, 233 Parahippocampus, 229 Parallel processing, 423 Paraphasias, 673, 720 Paraplegia, 115

794

Neuroscience Fundamentals for Communication Sciences and Disorders

Parasympathetic nervous system, 100, 570, 573–574 Paraventricular nucleus, 186, 188 Paresis, 200 Parietal association areas anatomy of, 222, 223 in attention, 223 dorsal, 223 function of, 223 ventral, 223 Parietal bone, 113, 114 Parietal lobe anatomy of, 125, 193, 194, 196, 204–205 description of, 203–204 inferior parietal lobule of, 204–205 intraparietal sulcus of, 204–205 in language, 661 in multimodal integration, 204 postcentral gyrus of, 204 posterior parietal cortex, 204–205 precuneus of, 204, 207 primary somatosensory cortex of, 205 S1 region of, 205 somatosensory inputs, 203 superior parietal lobule of, 204–205 supramarginal sulcus of, 205 ventral segment of, 204 zones of, 203–204 Parieto-occipital sulcus, 125, 204 Parkinson’s disease deep brain stimulation for, 555 description of, 30, 456, 626 essential tremor of, 557 speech deficits in, 554 Pars compacta, 144 Pars opercularis, 197 Pars orbitalis, 197 Pars reticulata, 144 Pars triangularis, 197 Parvocellular-type retinal ganglion cells, 414, 415, 417 Passive potassium channels, 58, 59 Pathological laughing, 631 Patient volunteer, in clinical trial, 687 Patterned behavior, 600 Pause duration, in speech, 123 Pause response pattern, 708 PCG. See Posterior cingulate gyrus Penfield, Wilder, 312 Penumbra, 36 Perception to action, 586 attributes related to, 294–305, 295 cortical structures in, 630 definition of, 288, 586 filtering for, 289–290

inference for, 289–290 measurement of, 292–294 overview of, 287–288 of pain, 319–321 prediction for, 289–290 quantification of, 292–294 regulation of, 305 selection for, 289–290 sensation versus, 288–305 of speech, 632–634 visual, 425 Perception-action coupling, 601, 601, 606–607 Perceptual categories, 290 Perforant pathway, 233 Periaqueductal gray, 140, 144–145, 231, 235–236, 625, 632 Pericallosal artery, 266, 269 Perilesional areas, 685 Perilymph, 364, 365 Perimysium, 477, 478 Perineurium, 107, 108 Peripheral nerves description of, 99 in speech, 619–624 structure of, 107 in vocalization, 619–624 Peripheral nervous system central nervous system and, 101 description of, 100 gray matter in, 105, 105–107 sensory segment of, 102 somatic motor segment of, 102 visceral motor, 100 white matter in, 105, 105 Peripheral neuropathy, 108 Peripheral visual system, 396 Perirhinal cortex, 436 Perisylvian language area/zone, 253, 659, 660f, 674 Perturbation studies, 635 Phantosmia, 456 Pharyngeal nerve, 172, 464, 622 Pharyngeal phase, of swallowing, 458–459, 467 Phase-lock, 709 Phase-locking, 377, 378 Phasic neuron activity, in primary motor cortex, 534 Pheromones, 444 Phonetic features, 701 Phonological loop, 206 Phonological paraphasia, 673 Phospholipid bilayer, 21, 21, 55, 56 Phosphorylation, 24, 24 Photopic, 405 Photopigments, 403, 409

Photopsin, 406 Photoreceptors activation of, 410 description of, 158, 294, 295, 296, 402, 405 glutamate expression by, 409–410 hyperpolarization of, 407 light transduction by, 407, 408 membrane potential of, 407 OFF-bipolar cells, 409–413 ON-bipolar cells, 409–413, 411 Phototransduction, 407–409 Physiological resting length, 493 Pia mater, 259, 259, 262 PICA. See Posterior inferior cerebellar artery Piezo proteins, 315 Pigmented epithelium, retinal, 401 Piloerection, 189 Piriform cortex, 436, 444–445 Pituitary gland description of, 143–144, 186 functions of, 189 hormones of, 189 hypothalamus and, 186, 189 infundibulum of, 186 regulation of, 189 Planum temporale, 720 Plasmalemma, 21–22, 47 Plato, 582, 584–585, 607 PMA. See Premotor area Pneumotaxic center, 136, 465 Polar temporal artery, 269 Polymodal nociceptors, 320 Polyneuropathy, 108 Polysynaptic, 623 Pons anatomy of, 135–136, 150, 151 apneustic center of, 136 basilar, 136 caudal, 138, 139 concept map of, 137 definition of, 135 embryologic development of, 111 external features of, 136–137 functions of, 136 internal features of, 137–140 locus ceruleus of, 140 midpoint of, 138, 140 periaqueductal gray, 140, 144 pneumotaxic center of, 136 respiratory centers in, 128 respiratory functions of, 136 rostral, 139, 140 Pontine arteries, 271 Pontine nuclei, 139 Pontine reticulospinal tract, 525, 526

INDEX

Pontine tegmentum, 136 Pontocerebellar fibers, 563 Population coding, 535–536 Positive charge, 45 Positive ions, 44 Positive neurological signs, 544 Positron emission tomography, 226, 702 Post-central artery, 269 Postcentral gyrus, 204, 628 Posterior, 103 Posterior arterial system, 268, 271–272 Posterior cerebral artery, 268, 270, 271, 273 Posterior cingulate gyrus, 231, 235 Posterior commissure, 254 Posterior communicating artery, 268, 269, 271, 273 Posterior cranial fossa, 114 Posterior eye, 397–398 Posterior fasciculus, 121, 122 Posterior hypothalamic nucleus, 186, 188, 189 Posterior inferior cerebellar artery, 268, 271, 273 Posterior inferior temporal gyrus, 634 Posterior limb, of internal capsule, 256–257, 257 Posterior middle temporal gyrus, 634 Posterior parietal artery, 269 Posterior parietal cortex, 204–205, 344–346 Posterior spinal artery, 271–272 Posterior spinocerebellar tract, 566, 567 Posterior temporal artery, 269 Posterior thalamic radiation, 257 Posterior ventral cochlear nucleus, 703, 706, 708 Postganglionic neurons, 574 Poststimulus time histograms, 707 Postsynaptic cell definition of, 29 description of, 72 neural integration in, 92–93 synapse formation on, 31 Postsynaptic potentials description of, 78 excitatory, 78, 79, 83, 88–89, 89, 92 inhibitory, 78, 80, 83, 88–89, 92 Postsynaptic receptors classification of, 78 description of, 78 ionotropic receptors, 78–79 metabotropic receptors, 78–79, 81–82 Posttraumatic stress disorder, 234

795

Potassium cellular motion of, 59 description of, 47 neuron distribution of, 47 Potassium channels passive, 58, 59 resting, 60 voltage-gated, 65 Potential energy, 43 Power-stroke phase, 489 PPA. See Primary progressive aphasia PPC. See Posterior parietal cortex Pre-Bötzinger complex, 128 Pre-central artery, 269 Pre-supplementary motor area, 201 Precentral gyrus, 197 Precuneus, 204, 207 Prediction, 289–290 Predictive behavior, 588 Predictive remapping, 429 Prefrontal artery, 269 Prefrontal cortex, 198, 198, 202–203, 226, 256 Preganglionic cells, 570 Preganglionic fibers, 574 Premotor area damage to, 545 description of, 200–201, 227, 515, 527 Premotor cortex description of, 514–516, 537–538 functional zones of, 537 hand action and, 538–541 input to, 537–538 mirror neurons in, 538, 538–541 in motor control, 538 neuroplasticity in, 542–544 premotor area of. See Premotor area supplementary motor area of, 201, 236, 238, 516, 527, 537–538, 541–542, 631 upper limb action and, 538–541 Preoccipital notch, 204 Preoptic nucleus, 186, 188 Presbycusis, 371, 380 Pressure gating, 51 Prestin, 379 Presynaptic cell, 29 Presynaptic inhibition, 31 Presynaptic terminal of chemical synapse, 72, 74 depolarization of, 77 description of, 15–17, 16, 29 organelles in, 24 synapse formation by, 31 synaptic cleft, 72–73 Pretectal region, 161

Primary afferent neuron, 102 Primary afferents axon of, 321 definition of, 302, 322 proprioceptive inputs transmitted by, 322 Primary auditory cortex, 208, 717–720, 718 Primary cerebellar fissure, 561 Primary-like PTSH response pattern, 708 Primary motor cortex anatomy of, 628 basal ganglia inputs to, 537 cerebellar inputs to, 537 description of, 198–200, 227 fractured somatotopy of, 530 functional mapping of, 527–531 higher-order performance features, 535–537 inner workings of, 531–533 neuron firing patterns in, 534–535 organization of, 527–531 population coding used by, 535–536 sensory inputs to, 536–537 somatosensory cortex and, similarities between, 629 in speech, 628–629 ventroposterolateral inputs to, 536–537 ventroposteromedial inputs to, 536–537 Primary progressive aphasia, 199, 678 Primary somatosensory cortex, 205, 516 Primary spinal cord injury, 115 Primary visual cortex, 159, 209, 418–422 Principal trigeminal nucleus, 140, 164, 335–336, 337, 463 Progenitor cells, 216 Projection fibers, 250, 665 Projection neurons, 444–445 Promoting aphasics’ communication effectiveness, 684 Proprioception definition of, 309, 316 of face, 318 Golgi tendon organ, 316–318, 317 muscle spindle, 316, 316–318 sensory endings for, 316–318 Proprioceptors, 309 Prosencephalon, 111 Prosopagnosia, 225, 426 Protein conformational state of, 482 synthesis of, 28 Protein kinases, 81–83

796

Neuroscience Fundamentals for Communication Sciences and Disorders

Protons, 44 Pruriceptors, 320 PSA. See Posterior spinal artery Pseudounipolar neurons, 20, 21 PSPs. See Postsynaptic potentials PSTHs. See Poststimulus time histograms Psychometric functions, 292, 292 Psychophysics, 292 Ptosis, 159 Pulvinar, 184, 185, 235 Pupil dilation, 190 Pupillary light reflex, 144, 155, 161 Putamen, 546, 549–550 Pyramidal cells, 516, 708 Pyramidal decussation, 128, 129, 130, 132, 520 Pyramidal tract, 522 Pyramidal tract neurons, 197, 532, 534 Pyramids, 128, 129, 130

Q Quadriplegia, 115 Quantitative electroencephalography, 657

R Radial distribution, 212 Radial glia, 216 Radiations of corpus callosum, 254, 255 Ramón y Cajal, Santiago, 14, 20 Rapidly adapting receptors, 305, 305 Rate coding, 304 Rate of force recruitment, 495 Receptive aphasia, 209, 645, 675–676 Receptive fields description of, 294, 297, 299–300 lateral inhibition, 300, 301 physical dimensions of, 300 size of, 297, 297 tactile, 300, 301 threshold differences, 299 for two-point discrimination test, 298 Receptor adaptation, 304 Receptor potentials, 302–304 Reciprocal processing, 423 Recurrent laryngeal nerve, 172, 464, 622 Red-green color blindness, 407 Red nucleus, 142, 144–145 Referred pain, 162 Reflexes baroreceptor, 126, 169 central pattern generators in, 591, 592

description of, 18–20 jaw-jerk, 164, 335 knee-jerk, 18, 19, 115, 316 in motor control, 591–593 pupillary light, 144, 155, 161 Sherrington’s theory of, 591, 593 vestibulo-ocular, 388, 388 Reflexive phonations, 642 Refraction, 395, 395 Regional hierarchy of aphasia recovery, 685–686 Regulatory conditions, 606 Rehabilitation definition of, 682 language, 682–688 neuroplasticity and, 354 Reissner’s membrane, 362, 363 Relative refractory period, 67 Release phenomena, 544 Repolarization, 67 Repulsion forces, 43–45 Resistance, 46–47 Resistors, 46 Resting channels, 52–53, 55 Resting membrane potential action potential. See Action potential description of, 58–62 elements needed for, 62 mechanism of, 63 Resting state, of neuron, 17 Resting tremor, 555, 646 Reticular formation description of, 124, 126 functions of, 231 respiratory neural centers in, 127, 128 reticulospinal fibers in, 170 in speech, 625 in vocalization, 625 Reticulospinal fibers, 170 Reticulospinal tract, 525–527, 526 Retina amacrine cells of, 401 cones of, 158, 403, 403, 405–407 convergence, 413–414 definition of, 397 description of, 400–401 eccentricity graph of, 404, 404 fovea of, 405 horizontal cells of, 401 layers of, 401, 413–414, 414 macula of, 405 noncortical visual system projections from, 428–430 outputs from, 429 photoreceptors of, 402, 405 pigmented epithelium of, 401

rods of, 158, 402–405, 403 signal transduction, 413–414 surface of, 400 visual fields of, 427, 427 visual information processing in, 401 Retinal, 404 Retinal ganglion cells axons of, 416–417 description of, 407, 411 M-type, 414, 415 P-type, 414, 415 Retinitis pigmentosa, 415 Retinotopy, 184, 209, 417 Retrograde messaging, 87 Retrograde transport, 29 Retronasal olfaction, 442 Rett syndrome, 31 Reuptake, 83 Reuptake transporters, 83 Reversible cold block, 343 Rexed laminae, 119, 120 RFs. See Receptive fields Rhodopsin, 404 Rhombencephalon, 111 Rhomboid fossa, 135, 137 Ribosomes, 24, 27–28 Right hemisphere damage, 681–682 Rigidity, 554 Rizzolatti, Giancomo, 202 RMP. See Resting membrane potential RNA polymerase, 26–27 Rods, 158, 402–405, 403 Rolandic artery, 269 Rostral, 102, 103 Rotational chair test, 168 Rough endoplasmic reticulum, 23, 24–25 Round window, 363 Rubrospinal tract, 122, 124, 524–525, 525 Ruffini endings, 312, 313–314, 315, 318

S S1, 205, 529, 629. See also Somatosensory cortex S-cones, 406 Saccades, 201, 429 Saccule, 381–382 Sacral region, 113, 115 Sagittal plane, 104, 104 Saliva, 445, 449 Salivatory nucleus, 167, 463–464 Saltatory conduction, 70 Salty tastants, 446, 448, 449–451 Sarcolemma, 481, 488

INDEX

Sarcomere actin in, 483–484, 484–485 anatomy of, 480 in contracted condition, 491 definition of, 481 molecular components of, 482–485 myosin in, 482–484, 483 in resting condition, 491 titin in, 483, 485 tropomyosin in, 483–485, 484 troponin in, 483, 484–485 Sarcoplasm, 481 Sarcoplasmic reticulum, 481, 491 SARS-CoV-2. See COVID-19 Satellite cells, 479 Scala media, 362, 364, 364 Scala tympani, 362, 364, 364 Scala vestibuli, 362, 364, 364 SCALED model. See Social Communication and Language Evolution and Development model Schwann cells, 33–34, 35 Schwannoma, vestibular, 387 SCI. See Spinal cord injury Scotomas, 426 Scotopic, 404 Second messenger(s), 80–81, 441 Second messenger cascades, 81 Second-order neurons, 324–325, 328, 329–330, 338–339, 452 Second pain, 319 Secondary auditory cortex, 720 Secondary somatosensory cortex, 344 Secondary spinal cord injury, 115 Selective serotonin reuptake inhibitors, 86 Self-organization, 598 Sella turcica, 114, 144 Semantic jargon, 674 Semantic paraphasia, 673 Semantic primary progressive aphasia, 678 Semicircular canals anatomy of, 363, 380, 381, 384 angular acceleration measurements by, 383–385 endolymph in, 383–384, 384 Sensation. See also Chemosensation definition of, 288, 586 measurement of, 292–294 overview of, 287–288 perception versus, 288–305 quantification of, 292–294 regulation of, 305 Senses description of, 287

797

electromagnetic energy for, 288 smell. See Olfactory system taste. See Taste Sensitive periods, 656 Sensorimotor integration, 115 Sensorimotor learning studies, 635 Sensorimotor skills, 605–607 Sensory-discriminative pathway, 332 Sensory end organs, 311 Sensory gating, 302, 516 Sensory homunculus, 199, 200, 339, 340–341 Sensory information, 291 Sensory nerve neuropathies, 108 Sensory neurons, 20, 619 Sensory nuclei, 151 Sensory physiology, 292 Sensory receptors axons of, 302, 321–322 chemoreceptors, 294, 295, 296 mechanoreceptors. See Mechanoreceptors nociceptors, 294, 295, 296 photoreceptors, 294, 295, 296 rapidly adapting, 305, 305 slowly adapting, 304, 305 spike trigger zone of, 302 thermoreceptors, 294, 295, 296, 318–319 transducing area of, 302 Sensory systems, 291–294 Sensory threshold, 292–293 Sensory thresholding, 292–293 Sensory transduction, 294 Septal area, 236–237 Septal nuclei, 231 Septum pellucidum, 229, 263 Serial transmission, 31, 32 Serotonin, 86 Sexual arousal, hypothalamus’s role in, 190 Shearing definition of, 369 of hair cells, 370 macular, 382 of stereocilia, 373–375, 375 Sherrington, Charles, 14, 309, 591, 593 Sigmoid sinus, 274–275 Single gene mutation, 30 Single nucleotide polymorphisms, 30 Single-sided deafness, 702 Size principle of motor unit recruitment, 502–504 Skeletal muscle anatomy of, 477–479, 478 contraction of, 504–505 fibers of, 496–499, 499

Skin anatomy of, 311 glabrous, 310, 312, 348 mechanoreceptor distribution in, 312 nonglabrous, 310 orofacial, 318 Skull, 113, 114 Sliding filament theory, 489 Slow fatigue-resistant fibers, 497 Slow-oxidative fibers, 497, 499 Slow-twitch fibers, 497 Slowly adapting receptors, 304, 305 SMA. See Supplementary motor area Smell sense, 435. See also Olfactory system SMG. See Supramarginal gyrus Smooth endoplasmic reticulum, 23, 24–25 Smooth muscle tissue, 476, 476 SNARES, 75, 75–76 Snellen eye chart, 159 SNPs. See Single nucleotide polymorphisms Social Communication and Language Evolution and Development model, 672, 672–673 Social Gating Hypothesis, 658 Sodium description of, 47 neuron distribution of, 47 passive flow of, 58 Sodium channels, voltage-gated, 65 Sodium-potassium pump description of, 53–54, 54 resting membrane potential affected by, 58 Solitary nucleus, 131, 133, 133 Soma description of, 15, 16, 21–22 synapse formation at, 31 Somatic motoneurons, 115 Somatosensation description of, 257, 309, 322 inputs for, 322 submodalities of, 323 Somatosensory cortex columnar organization of, 341, 341 cortical body representations, 342–343 description of, 338 functional features of, 338–342 homunculus of, 339 mapping of, 338–339 outputs from, 344 primary, 344, 516, 628 primary motor cortex and, similarities between, 629

798

Neuroscience Fundamentals for Communication Sciences and Disorders

Somatosensory cortex  (continued) primate hand representations, 348, 351–352 secondary, 344 sensory homunculus, 339, 340–341 somatotopic organization of, 340 in speech, 628–629 speech-related activity of, 343–344 structural features of, 338–342 thalamic projections to, 347–350 Somatosensory feedback, 635, 636 Somatosensory system cutaneous tactile receptors of, 310–316 description of, 219, 309–310 exteroception function of, 309 interoception function of, 309 proprioception function of, 309 sensory end organs, 311 submodalities of, 309 Somatotopy, 107, 339, 340, 516, 530 Somites, 110, 111 Sour tastant, 446, 448, 450, 450–451 Spasmodic dysphonia, 544, 647–648, 648 Spastic dysarthria, 644, 645, 646 Spasticity, 200, 646 Spatial learning, 230–233 Spatial summation, 89, 90 Special nerves, 154 Special somatic afferent, 155 Special visceral afferent, 155–156 Special visceral efferent, 155 Specific thalamic nuclei, 184 Speech afferent pathways of, 624 anterior cingulate cortex in, 631–632 anterior cingulate gyrus’s role in, 236 apraxia of, 630, 646, 647 articulatory subsystem of, 622–623 auditory processing of, 632–634 basal ganglia in, 626–627 breathing for, 620, 622 Broca’s area in, 629–630 cerebellum in, 627–628 as complex behaviors, 616–618, 617 definition of, 615 efferent pathways of, 620–623 insula in, 632 left hemisphere dominance of, 238 medial prefrontal cortex’s role in, 236 motor abilities for, development and refinement of, 642–644 motor neuron pools of, 619, 623 multiple sclerosis effects on, 70 neural substrates of, 618 perception of, 632–634

periaqueductal gray matter in, 625 peripheral nerves in, 619–624 phonatory subsystem of, 622 primary auditory cortex in, 719–720 primary motor cortex in, 628–629 respiratory subsystem of, 620, 622 reticular formation in, 625 as sensorimotor behavior, 615 somatosensory cortex in, 343–344, 628–629 subcortical structures in, 624–628 supplementary motor area in, 631 supramarginal gyrus in, 632 thalamus in, 625–626 upper motoneuron damage effects on, 545 velopharyngeal subsystem of, 622 ventilator-supported, 123 as vocalization, 615 Speech breathing, after spinal cord injury, 123 Speech disorders aphasia. See Aphasia dysarthrias, 644–646, 645 Speech formants, 623, 635 Speech processing dorsal stream of, 634 dual stream model of, 633 ventral stream of, 634 Speech production articulators in, 623 basal ganglia in, 547 computational models of, 637–642 cortical structures in, 630 cortical zones in, 629 deficits in, from absence of somatosensory inputs, 343 diaphragm in, 620, 622 Directions Into Velocities of Articulators model of, 638–642, 639 forward model for, 589 mandible in, 623 muscles in, 620–621 sensorimotor adaptation during, 634–637 spinal cord damage effects on, 622 spinal nerves in, 118 tongue in, 623 SPG. See Sphenopalatine ganglion Sphenoid bone, 113, 114 Sphenopalatine ganglion, 162 Spherical bushy cells, 708 Spike trigger zone, of sensory receptors, 302 Spinal accessory nerve. See Accessory nerve

Spinal canal, 115 Spinal cord ascending fibers of, 115 corticofugal fibers in, 255 corticopetal fibers in, 255 descending fibers of, 116, 124 dorsal columns of, 326 dorsal roots of, 117, 117–118 embryologic development of, 111, 113, 115 external structures of, 116–119 functions of, 115–116 gating, 115, 120 gray matter of, 119–121, 120 segments/segmentation of, 116–117, 117–118 somatic motoneurons of, 115 speech production affected by damage to, 622 ventral roots of, 117, 118 visceral motoneurons of, 115 white matter of, 121–123, 124 Spinal cord injury cervical, 119 description of, 115 speech breathing assessment after, 123 Spinal dermatomes, 323 Spinal nerves arrangement of, 322 chest wall muscles innervated by, 119, 119 definition of, 117–118 in swallowing, 465 Spinal reflex circuit, 115 Spinal shock, 544 Spinal trigeminal nucleus, 131, 164, 335–336, 338, 463 Spinocerebellar area, 627 Spinocerebellar circuit, 565–567 Spinocerebellar tract, 122, 566, 566–567 Spinocerebellum, 561, 562, 627 Spinothalamic tract, 329 Spiral ganglion, 363, 375 Splenium, 254 Spontaneity, 604 SR. See Sarcoplasmic reticulum SSA. See Special somatic afferent SSD. See Single-sided deafness Staining methods, 14 Stapedial reflex response, 723, 724 Stapes, 363 Statistical learning, 658 Stellate cells, 708 Stereocilia, 383 description of, 371–372, 371–372 of inner hair cells, 373

INDEX

of outer hair cells, 379 shearing of, 373–375, 375 Stevens’s equation, 293 Stimulus attributes of, 293–294, 295 duration of, 295, 304–305 intensity of, 295, 302–304, 303 location of, 295, 297–302 modality of, 294–296, 295 spatial features of, 300 Stimulus energy, 288 Stochastic pattern, 603, 603 Straight sinus, 272, 274–275 Stretch gating, 51 Stretch receptors, 335 Stretch-sensitive mechanoreceptors, 127 Stria terminalis, 229 Stria vascularis, 363, 364–365 Striatal cells, 552 Striated muscle tissue, 476, 476 Striatopallidal fibers, 550 Striatum, 550, 626 Stroke agraphia with alexia after, 223 aphasia after, 673 blood perfusion changes after, 686 brainstem, 386 capsular, 257 cerebellar-level, 386 conjugate deviation after, 201 embolic, 275, 278 gray matter damage after, 686 hemorrhagic, 275–276 ischemic, 275, 277, 278, 279 language recovery after, 685–687 proinflammatory microglial activity after, 33 upper motoneuron damage caused by, 522 warning signs of, 276 white matter damage after, 686 Study strategies and tips, 9–10 Stylopharyngeus muscle, 169 Subclavian artery, 271 Subcortical nuclei, 105, 106 Subcortical swallowing, 465–467 Subdural hematoma, 261–262 Subiculum, 233 Subjective tinnitus, 379 Sublingual gland, 464 Submandibular gland, 464 Submodality, 296 Substantia nigra, 86, 142, 144, 550–551 Substantia nigra pars compacta, 550, 552–554 Substantia nigra pars reticulata, 550–551 Subthalamic nucleus, 550

799

Subthreshold effect, 304 Sulci anatomy of, 105–106, 106, 192 calcarine, 125 central, 193 inferior temporal, 196, 634 intraparietal, 204–205 lateral, 193 middle temporal, 207 parieto-occipital, 204 superior temporal, 207, 634 Summation definition of, 89 spatial, 89, 90 temporal, 89, 91 Superficial middle cerebral vein, 274–275 Superior, 103 Superior anastomotic vein, 274 Superior cerebellar artery, 268, 271, 273 Superior cerebellar peduncle, 137, 141, 144, 562–563, 563 Superior colliculus, 142–143, 429 Superior frontal gyrus, 197 Superior laryngeal nerve, 172, 464, 622 Superior longitudinal fasciculus, 251–252, 253, 666, 670 Superior occipital gyrus, 209 Superior occipitofrontal fasciculus, 251, 251–252 Superior olivary complex anatomy of, 710 binaural fusion, 713 description of, 136, 139, 380, 633, 702, 703, 704 interaural time delays, 710, 711–7121 lateral, 710 low-frequency sound localization processing in, 710–714 medial, 710–714 physiology of, 710 Superior parietal lobule, 204–205, 345 Superior petrosal sinus, 274–275 Superior sagittal sinus, 272, 273–274 Superior salivatory nucleus, 463–464 Superior temporal gyrus, 207, 718 Superior temporal sulcus, 207, 634 Superior thalamic radiation, 257 Supplementary motor area, 201, 236, 238, 516, 537–538, 631 Supplementary motor area proper, 201, 541 Suppression deficit, 681 Suprachiasmatic neurons, 189 Suprachiasmatic nucleus anatomy of, 186, 188

circadian rhythms and, 428 lesions of, 189 Supramarginal gyrus, 205–206, 632 Supraoptic nucleus, 186, 188 Supratentorial, 260 SVA. See Special visceral afferent SVE. See Special visceral efferent Swallowing brainstem respiratory centers in, 465 central pattern generator in, 467–468 chemosensory systems in, 457 cortical control of, 465–467, 466 description of, 435 esophageal phase of, 458–459, 467 facial nerve in, 462, 463–464 glossopharyngeal nerve in, 462, 464 hypoglossal nerve in, 462, 465 motor innervation for, 461 neural substrate of, 459–468 oral preparatory phase of, 458–459, 467 oral transport phase of, 458–459, 467 peripheral neural control of, 459 pharyngeal phase of, 458–459, 467 phases of, 458–459 process of, 458–465 sensory innervation for, 460 subcortical control of, 465–467 trigeminal nerve in, 462, 463 upper esophageal sphincter in, 459 vagus nerve in, 462, 464 Sweet tastants, 446, 448, 451–452, 452–453 Sylvian parietotemporal junction, 634 Sympathetic nervous system, 100, 570–573, 571 Synapse axoaxonic, 31, 31 axodendritic, 31, 31 axosomatic, 31, 31 chemical. See Chemical synapse definition of, 29, 72 description of, 14, 71–72 electrical, 72 gap junction of, 72, 73 Synaptic cleft description of, 72, 75 neurotransmitter removal from, 83 Synaptic plasticity, 83 Synaptic vesicles, 74–75

T T-SNARES, 75, 75–76 T-stellate cells, 708 T-tubules, 481 TAAs. See Temporal association areas

800

Neuroscience Fundamentals for Communication Sciences and Disorders

Tactile mechanoreceptors, 318 Tactile receptive fields, 300, 301 Tactile receptors, cutaneous, 310–316 Tactile sensation, 435 Tactile stereognosis, 165 Task constraints, 599, 599 Tastants bitter, 446, 448, 451–452, 452–453 classes of, 446, 448 definition of, 435, 446 salty, 446, 448, 449–451 solubility of, 445 sour, 446, 448, 450, 450–451 sweet, 446, 448, 451–452, 452–453 transduction of, 449–452 umami, 446, 448, 451–452, 452–453 Taste. See also Gustatory system age-related changes in, 455 central representation of, 453–454 description of, 435 facial nerve in, 167 Taste buds, 446, 447, 447–449, 449 Taste pore, 449 Taste receptor cells, 448–449 Taste sensitivity, 447–448 TBI. See Traumatic brain injury Tectorial membrane, 363, 368–369 Tectospinal tract, 527, 527 Tectum, 111, 125, 142 Tegmentum, 111, 136, 142, 144–145 Telencephalon, 111, 111 Temperature regulation, 189, 318–319 Temporal association areas, 222, 223–225 Temporal bone, 113, 114 Temporal lobe A1 region of, 208 anatomy of, 125, 182, 194, 207–208 description of, 207 functional areas of, 208–209 inferior, 209 in language, 661 middle, 209 object recognition areas of, 209 primary auditory cortex of, 208 regions of, 207 Wernicke’s area of, 208–209 Temporal monocular retinal hemifield, 399 Temporal retinal hemifield, 399 Temporal summation, 89, 91, 496, 496 TENS. See Transcutaneous electrical nerve stimulation Tentorium cerebelli, 260, 260–261 Testosterone, 190 Tetanus, 496

Tetraplegia, 115 Texture discrimination, 165 Thalamocortical fibers, 180 Thalamocortical projection fibers, 565 Thalamus anterior nucleus of, 182 in auditory processing, 633 corticothalamic fibers of, 516 definition of, 625–626 description of, 159, 179–184 functions of, 179–180 in language, 662 lateral geniculate nucleus of, 143, 183–184, 185, 209 motor-related circuits, 180 nuclei of, 181–184, 185, 199 in olfaction, 180 somatosensory cortex input from, 347–350 in speech, 625–626 ventroposterolateral nucleus of, 328, 329 ventroposteromedial nucleus of, 328, 329 in vocalization, 625–626 Theory. See also specific theory definition of, 586 dynamic systems, 598–601, 603–604 general motor program, 597–598, 600 motor control, 586–597, 607–608 Theory of Mind, 658–659 Thermal nociceptors, 320 Thermoreceptors, 294, 295, 296, 318–319 Thick filament, 481–482, 483 Thin filament, 481–482 Third-order neurons, 324–325, 329–330 3rd ventricle, 263, 264, 265 Thoracic vertebra, 113, 115 Thromboembolism, 278 Thrombus, 278, 278 Thymine, 25, 26 TIAs. See Transient ischemic attacks Tickle, 302 Tics, 555 Tight junctions, 36 Timing, of auditory signal, 700 Tinnitus, 379 Tip links, 372 Tip of your tongue phenomenon, 666–667 Tissue plasminogen activator, 278 Titin, 483, 485 ToM. See Theory of Mind Tongue

gestures produced by, 503 innervation of, 623 muscles of, 623 papillae of, 446, 447 taste sensitivity across, 447–448, 448 Tonotopic mapping, 208 Tonotopy, 107, 184 Top-down processing, 423 Touch active, 311 description of, 288 tactile receptors for, 310–316 tPA. See Tissue plasminogen activator Tracheostomy, 456 Trafficking proteins, 75 Transcallosal inhibition, 686 Transcortical motor aphasia, 675 Transcortical sensory aphasia, 675 Transcription, 26–28, 27, 29 Transcutaneous electrical nerve stimulation, 334 Transducing area, of sensory receptors, 302 Transduction acoustic, 362 gustatory receptors, 446–447 light, 407, 408 odorant, 438, 440–441, 440–442 phototransduction, 407–409 sensory, 288, 294 tastant, 449–452 Transfer RNA. See tRNA Transgenic animals, 21 Transient ischemic attacks, 276, 278 Transient receptor potential channels, 319–320 Transient receptor potential ion channels, 320 Transient receptor potential proteins, 296 Translation, 26–28, 27, 29 Transporters, 75, 83 Transverse section, 104 Transverse sinus, 272, 273–274 Transverse tubules, 481 Trapezoid body anatomy of, 704 medial nucleus of, 710–713 Traumatic brain injury, 679–681, 680 Tremor essential, 557 intentional, 568, 646 resting, 555, 646 Triad, 481 Trigeminal cell, 162 Trigeminal ganglion, 162 Trigeminal motor nucleus, 164

INDEX

Trigeminal nerve anatomy of, 125, 129, 131, 137, 150, 151, 156, 163 branches of, 162, 322, 335, 442 central axons of, 163–164 innervation zones of, 322, 324 mandibular branch of, 162–163, 322 maxillary branch of, 162, 322 mesencephalic nucleus of, 164 motor branch of, 163 ophthalmic branch of, 162, 322 principal nucleus of, 164 sensory branch of, 163, 164 spinal nucleus of, 164 in swallowing, 462, 463 Trigeminal sensory system principal nucleus of, 164, 335–336, 337 schematic diagram of, 337 spinal nucleus of, 131, 335–336, 338 Trigeminal system characteristics of, 325 description of, 136–137, 140 functions of, 335 mesencephalic nucleus of, 335–336, 336 in swallowing, 462, 463 Trigeminolemniscal pathway, 310 Trigeminothalamic pathway, 310 Trigones, 130 tRNA, 28 Trochlear nerve, 125, 129, 131, 150, 151, 156, 160, 161–162 Trochlear nucleus, 144 Tropomyosin, 483–485, 484, 491 Troponin, 483, 484–485 TRP channels. See Transient receptor potential channels TRP proteins. See Transient receptor potential proteins Tufted cells, 444 Tuning curves, 296, 296, 709 Tunnel of Corti, 363 Two-point discrimination, 165, 297–298, 298 Two-point discrimination threshold, 294, 299 Tympanic membrane, 362, 363 Type I auditory afferents, 375 Type II auditory afferents, 375

U Umami, 446, 448, 451–452, 452–453 Uncinate fasciculus, 251, 252 Uncus, 208 Unfused tetanus, 496

801

Unipolar neurons, 20, 21 Unmyelinated axon, 69, 69–70 Upper esophageal sphincter, 459 Upper motoneuron(s) damage to, 544–546, 545 description of, 514 facial palsy, 522–524 injury to, 544–546, 545 pathways of, 515 Upper motoneuron syndromes, 200, 544 Use-dependent neuroplasticity, 682 Usher syndrome, 415 Utricle, 381–382 Utterances, 123

V V-SNARES, 75, 75–76 Vagus nerve anatomy of, 125, 129, 130, 131, 150, 151, 171, 171–173 damage to, 622 in swallowing, 462, 464 Vallate papillae, 446, 447 Vascular disorders aneurysms, 275–276, 277 arteriovenous malformations, 278, 279 embolic stroke, 275, 278 hemorrhagic stroke, 275–276, 277 ischemic stroke, 275, 278 Vascular system, 249 Vasopressin, 189 Velopharyngeal port, 622 Venous sinuses, 272, 273–275 Ventilator-supported speech, 123 Ventral, 102, 103 Ventral acoustic stria, 703, 706 Ventral anterior nucleus, 183 Ventral auditory processing stream, 721 Ventral auditory projection stream, 703 Ventral cochlear nucleus, 703, 706, 708 Ventral horn, 119–121, 120 Ventral lateral nucleus, 183 Ventral nucleus of lateral lemniscus, 714 Ventral nucleus of the lateral lemniscus, 708 Ventral parietal association area, 223 Ventral posterior nucleus, 183 Ventral posterolateral nucleus, 183, 185 Ventral posteromedial nucleus, 183, 185 Ventral processing pathways, 220, 220 Ventral respiratory group neurons, 127–128, 465 Ventral roots, 117, 118 Ventral visual stream, 422–426, 424 Ventricles anatomy of, 262–263, 264

4th, 263, 264, 265 hydrocephalus of, 264–265 lateral, 263, 264 3rd, 263, 264, 265 Ventricular zone, 216 Ventrobasal complex, 183 Ventrolateral prefrontal cortex, 203 Ventromedial neurons, 189 Ventromedial nucleus, 186–187, 188 Ventromedial prefrontal cortex, 203, 221, 226 Ventroposterolateral thalamic nucleus, 328, 329, 349 Ventroposteromedial thalamic nucleus, 328, 329, 338, 453 Verbal working memory, 206 Vermis of cerebellum, 559, 561 Vertebra anatomy of, 113, 115 cervical, 113, 115 lumbar, 113, 115 thoracic, 113, 115 Vertebral artery, 268, 271, 273 Vertebral column, 113–115, 115 Vertebral foramen, 115 Vertigo, 385 Vestibular labyrinth, 380 Vestibular nuclei, 133, 386–387 Vestibular schwannoma, 387 Vestibular system assessment of, 168 central vestibular pathway, 386, 386–387 hair cells of, 380–381 overview of, 361–362 semicircular canals. See Semicircular canals Vestibulo-ocular reflex, 388, 388 Vestibulo-ocular response, 387–388 Vestibulocerebellar circuit, 565 Vestibulocerebellum, 561, 562, 627 Vestibulocochlear nerve, 125, 129, 131, 150, 151, 157, 167–168, 169 Vestibulospinal tract, 387, 525, 526 Visceral motoneurons, 115 Visceromotor processes, 184 Visceromotor system, 570, 571 Viscerosensory processes, 184 Visual acuity, 159 Visual agnosia, 225 Visual cortex, 106, 418–422, 423 Visual fields deficits of assessment of, 159 description of, 426–428 optic nerve damage as cause of, 159 description of, 398–399, 398–400

802

Neuroscience Fundamentals for Communication Sciences and Disorders

Visual hemifields, 428 Visual perception awareness, 425 Visual space, 398 Visual streams dorsal, 422–425, 424 ventral, 422–426, 424 Visual system. See also Eye central visual pathway. See Central visual pathway dorsal visual stream, 422–425, 424 overview of, 393–394 phototransduction, 407–409 retina. See Retina ventral visual stream, 422–426, 424 Vitreous chamber, 396 Vitreous humor, 397 VLPFC. See Ventrolateral prefrontal cortex Vm. See Membrane potential VMPFC. See Ventromedial prefrontal cortex VNLL. See Ventral nucleus of lateral lemniscus Vocal fold paresis/paralysis, 622, 647 Vocalization afferent pathways of, 624 by animals, 619 anterior cingulate gyrus’s role in, 235–236 articulatory subsystem of, 622–623 basal ganglia in, 626–627 breathing for, 620, 622 cerebellum in, 627–628 as complex behaviors, 616–618, 617 definition of, 615 efferent pathways of, 620–623

expansion phase of, 642 neural substrates of, 618 periaqueductal gray matter in, 625 peripheral nerves in, 619–624 phonatory subsystem of, 622 primary auditory cortex in, 719–720 respiratory subsystem of, 620, 622 reticular formation in, 625 speech as. See Speech subcortical structures in, 624–628 thalamus in, 625–626 velopharyngeal subsystem of, 622 Voice onset times, 708 Voice quality, 123 Voltage, 44–46, 46 Voltage-gated calcium channels, 76, 489 Voltage-gated ion channels in action potential, 64–65 description of, 50–51 diversity of, 52 Voltage-gated potassium channels, 65, 66 Voltage-gated sodium channels, 65, 66 Voltage gating, 51, 51 Voltage-regulated sodium channels, 450 Voltage sensor, 51 Voluntary movements, 585 Volunteer, in clinical trial, 687 von Békésy, Georg, 365–366 VOR. See Vestibulo-ocular response VPL. See Ventroposterolateral thalamic nucleus

Warm receptors, 318–319 Water consumption, hypothalamus’s role in, 189 Waters of hydration, 49, 49–50 Weber, Ernst, 293 Weber’s law, 293 Wernicke, Carl, 208–209, 312 Wernicke-Gechwind model, of language production, 667–668, 667–669 Wernicke’s aphasia, 209, 644, 645, 675 Wernicke’s area, 208–209, 270, 634, 718, 720 WG model. See Wernicke-Gechwind model, of language production White matter axons in, 107–108 of cerebrum, 250 connectivity of, 664 description of, 105, 105 imaging of, 664 spinal cord, 121–123, 124 stroke-related damage to, 686 Word salad, 674 Working memory, 226

W

Z-lines, 480, 481–482, 490 Zonule fibers, 396

Walking, 601–602 Wallenberg’s syndrome, 135

X Xerostomia, 456

Z