Neurophysiological Basis of Motor Control [3 ed.] 1718209525, 9781718209527

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Neurophysiological Basis of Motor Control Third Edition

Mark L. Latash, PhD The Pennsylvania State University

Tarkeshwar Singh, PhD The Pennsylvania State University

Library of Congress Cataloging-in-Publication Data Names: Latash, Mark L., 1953- author. | Singh, Tarkeshwar, 1981- author. Title: Neurophysiological basis of motor control / Mark L. Latash, PhD, The Pennsylvania State University, Tarkeshwar Singh, PhD, The Pennsylvania State University. Description: Third edition. | Champaign : Human Kinetics, [2024] | Neurophysiological basis of movement / Mark L. Latash. 2nd ed. c2008. | Includes bibliographical references and index. Identifiers: LCCN 2022022940 (print) | LCCN 2022022941 (ebook) | ISBN 9781718209527 (paperback) | ISBN 9781718209534 (epub) | ISBN 9781718209541 (pdf) Subjects: LCSH: Locomotion. | Neurophysiology. | Motor ability. | Movement disorders. Classification: LCC QP301 .L364 2023 (print) | LCC QP301 (ebook) | DDC 612.7/6--dc23/eng/20220720 LC record available at https://lccn.loc.gov/2022022940 LC ebook record available at https://lccn.loc.gov/2022022941 ISBN: 978-1-7182-0952-7 (print) Copyright © 2024 by Mark L. Latash and Tarkeshwar Singh Copyright © 2008, 1998 by Mark L. Latash Human Kinetics supports copyright. Copyright fuels scientific and artistic endeavor, encourages authors to create new works, and promotes free speech. Thank you for buying an authorized edition of this work and for complying with copyright laws by not reproducing, scanning, or distributing any part of it in any form without written permission from the publisher. You are supporting authors and allowing Human Kinetics to continue to publish works that increase the knowledge, enhance the performance, and improve the lives of people all over the world. To report suspected copyright infringement of content published by Human Kinetics, contact us at [email protected]. To request permission to legally reuse content published by Human Kinetics, please refer to the information at https://US.HumanKinetics.com/pages/permissions-information. The web addresses cited in this text were current as of June 2022, unless otherwise noted. Acquisitions Editor: Diana Vincer; Managing Editor: Melissa J. Zavala; Copyeditor: Kevin Campbell; Proofreader: Pamela Johnson; Permissions Manager: Laurel Mitchell; Graphic Designer: Dawn Sills; Cover Designer: Keri Evans; Cover Design Specialist: Susan Rothermel Allen; Photograph (cover):

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Contents Preface

Introduction Chapter 1    History, Evolution, and Motor Control 1.1 Brief History of Movement Studies 1.2 Evolution of Movements and Nikolai Bernstein’s Theory 1.3 Motor Control and Laws of Nature

Part I    Excitable Cells and Their Communication Chapter 2    Membranes, Particles, and Equilibrium Potentials 2.1 The Biological Membrane 2.2 Movement in a Solution 2.3 Concentration of Water: Osmosis 2.4 Movement of Ions: The Nernst Equation

Chapter 3    Action Potential 3.1 Creation of a Membrane Potential 3.2 Basic Features of the Action Potential 3.3 Mechanisms of Generating an Action Potential Chapter 4    Information Conduction and Transmission 4.1 Conduction of an Action Potential 4.2 Myelinated Fibers 4.3 Structure of a Neuron 4.4 Information Coding in the Nervous System 4.5 Synaptic Transmission 4.6 Neurotransmitters 4.7 Temporal and Spatial Summation Chapter 5    Skeletal Muscle 5.1 Skeletal Muscle Structure

5.2 Myofilaments 5.3 Neuromuscular Synapse 5.4 Mechanisms of Contraction 5.5 Types of Muscle Contractions 5.6 Elements of Mechanics 5.7 Force–Length and Force–Velocity Relations 5.8 External Regimes of Muscle Contraction Chapter 6    Peripheral Receptors 6.1 General Classification and Properties of Receptors 6.2 Muscle Spindles 6.3 The Gamma-System 6.4 Golgi Tendon Organs 6.5 Other Muscle Receptors 6.6 Articular Receptors 6.7 Cutaneous Receptors

6.8 Signals From Peripheral Receptors Chapter 7    Motor Units and Electromyography 7.1 The Motor Unit 7.2 Fast and Slow Motor Units 7.3 The Henneman Principle 7.4 Functional Roles of Different Motor Units 7.5 Electromyography 7.6 Processing Electromyographic Signals Problems for Part I

Part II    Neuroanatomical Foundations of Motor Control Chapter 8    Cerebral Cortex 8.1 Structure of the Cerebral Cortex 8.2 Cells in the Cerebral Cortex 8.3 Premotor Cortex and Supplementary Motor

Areas 8.4 Primary Motor Cortex 8.5 Efferent Output From the Cortical Motor Areas 8.6 Afferent Input Into the Cortical Motor Areas 8.7 Hemispheric Lateralization in the Cortical Motor Areas 8.8 Preparation for a Voluntary Movement 8.9 Neuronal Population Vectors 8.10 Encoding Movement Parameters in the M1 8.11 Brain–Machine Interfaces Chapter 9    Basal Ganglia 9.1 Anatomy of the Basal Ganglia 9.2 Inputs and Outputs of the Basal Ganglia

9.3 Direct and Indirect Pathways Within the Basal Ganglia 9.4 Dopamine Modulation of Basal Ganglia Circuits 9.5 Motor Circuits Involving the Basal Ganglia 9.6 Activity of the Basal Ganglia During Movements 9.7 Movement Disorders Associated With the Basal Ganglia 9.8 Other Functions of the Basal Ganglia Chapter 10    Cerebellum 10.1 Overall Structure of the Cerebellum 10.2 Inputs and Outputs of the Cerebellum 10.3 Pathways Within the Cerebellum 10.4 Distinct Cerebellar Regions Control

Discrete Motor Functions 10.5 Cerebellar Control of Movement 10.6 Consequences of Cerebellar Lesions on Movements 10.7 Cerebellar Contribution to Motor Learning 10.8 Cerebellar Interactions With the Basal Ganglia and Cortex Chapter 11    Brainstem and Extrapyramidal Tracts 11.1 Brainstem Anatomy 11.2 Reticular Formation 11.3 Superior Colliculus 11.4 Red Nucleus 11.5 Vestibular Nuclei 11.6 Cranial Nerves 11.7 Descending Tracts Problems for Part II

Part III    Sensory Basis of Motor Control Chapter 12    Central Processing of Somatosensory Information 12.1 First-Order Neurons 12.2 Second-Order Neurons 12.3 Third-Order Neurons 12.4 Proprioceptive System 12.5 Primary and Secondary Somatosensory Cortex 12.6 Integration of Somatosensory Input With Other Sensory Modalities 12.7 Injuries to Somatosensory Pathways Chapter 13    Vestibular and Auditory Systems 13.1 Transduction in the Vestibular System

13.2 Vestibular Afferents Respond to Head Motion 13.3 Central Projections From the Otolith Organs and Semicircular Canals 13.4 Central Pathways That Stabilize Gaze, Posture, and Head Movements 13.5 Peripheral Auditory System 13.6 Central Auditory Projections From the Cochlea 13.7 Auditory Integration 13.8 Auditory Thalamus and Cortex 13.9 Auditory Cortex and Limb Motor Control Chapter 14    Visual System 14.1 Structure of the Eye

14.2 Structure of the Retina 14.3 Rods and Cones 14.4 Optic Nerve, Tracts, and Radiations 14.5 Striate Cortex 14.6 Retinotopic Organization of V1 14.7 Extrastriate Cortex 14.8 Neurons of the Two Visual Streams 14.9 Visual Deficits Due to Area-Specific Visual System Damage 14.10 Ocular Movements Problems for Part III

Part IV    Reflexes and Reflex-Like Movements Chapter 15    Reflexes 15.1 Definition of a Reflex

15.2 Reflex Arc, Gain, and Latency 15.3 Reflex Classifications 15.4 Conditioned Reflexes Chapter 16    Excitation and Inhibition Within the Spinal Cord 16.1 The Spinal Cord 16.2 Excitation Within the Central Nervous System 16.3 Postsynaptic Inhibition 16.4 Recurrent Inhibition and Renshaw Cells 16.5 Reciprocal Inhibition 16.6 Presynaptic Inhibition 16.7 Persistent Inward Currents Chapter 17    Monosynaptic Reflexes

17.1 H-Reflex and MResponse 17.2 Tendon Tap Reflex (T-Reflex) 17.3 Effects of Voluntary Muscle Activation on Monosynaptic Reflexes 17.4 F-Wave Chapter 18    Oligosynaptic and Polysynaptic Reflexes 18.1 Oligosynaptic Reflexes 18.2 Polysynaptic Reflexes 18.3 Flexor Reflex 18.4 Tonic Stretch Reflex 18.5 Tonic Vibration Reflex 18.6 Interaction Among Reflex Pathways 18.7 Interjoint and Interlimb Reflexes

Chapter 19    Long-Loop Reflexes and Reflex-Like Reactions 19.1 Preprogrammed Reactions 19.2 Preprogrammed Reactions Versus Stretch Reflexes 19.3 Afferent Sources of Preprogrammed Reactions 19.4 Preprogrammed Reactions During Movement Perturbations 19.5 Basic Features of Preprogrammed Reactions 19.6 Preprogrammed Corrections of Vertical Posture 19.7 Corrective Stumbling Reactions Problems for Part IV

Part V    Control and Coordination of Goal-Oriented Movements

Chapter 20    Voluntary Control of a Single Muscle 20.1 What Is Voluntary Movement? 20.2 Feedforward and Feedback Control 20.3 Servo Control 20.4 Servo Hypothesis 20.5

α-γ Coactivation

20.6 Voluntary Activation of Muscles 20.7 Equilibrium-Point Hypothesis Chapter 21    General Issues of Motor Control 21.1 Force Control 21.2 Engrams and the Generalized Motor Program 21.3 Internal Models 21.4 Equilibrium-Point Hypothesis: Main Ideas 21.5 Equilibrium-Point Hypothesis: Subtle Details

21.6 Dynamic Systems Approach Chapter 22    Motor Synergies 22.1 The Problem of Motor Redundancy 22.2 Optimization Approaches 22.3 Bernstein’s Level of Synergies 22.4 Uniting Muscles Into Groups 22.5 Principle of Abundance 22.6 Ensuring Stability of Movements 22.7 Uncontrolled Manifold Hypothesis Chapter 23    Patterns of Single-Joint Movements 23.1 Isotonic Movements and Isometric Contractions 23.2 Task Parameters and Performance Variables

23.3 Kinematic Patterns During Single-Joint Isotonic Movements 23.4 EMG Patterns During Single-Joint Isotonic Movements 23.5 EMG Patterns During Single-Joint Isometric Contractions 23.6 Dual-Strategy Hypothesis 23.7 Single-Joint Movements Within the EquilibriumPoint Hypothesis Chapter 24    Multijoint Movement 24.1 Two Issues With Controlling Natural Reaching Movements 24.2 Interjoint Reflexes 24.3 Multijoint Coordination by the Spinal Cord 24.4 Supraspinal Mechanisms

24.5 Neural Control Variables for Multijoint Movements 24.6 EquilibriumTrajectory Hypothesis 24.7 Hierarchical Control With Spatial Referent Coordinates 24.8 Multijoint Synergies Chapter 25    Postural Control 25.1 Vertical Posture 25.2 Postural Sway 25.3 Role of the Vestibular System 25.4 Role of Vision 25.5 Role of Proprioception 25.6 Anticipatory Postural Adjustments 25.7 Corrective Postural Reactions

25.8 Postural Synergies Chapter 26    Locomotion 26.1 Two Approaches to Locomotion 26.2 Central Pattern Generator 26.3 Locomotor Centers 26.4 Spinal Locomotion 26.5 Spinal Control of Locomotion in Humans 26.6 Gait Patterns 26.7 Dynamic Pattern Generation 26.8 Step Initiation 26.9 Corrective Stumbling Reaction Chapter 27    Prehension 27.1 Hand Joints and Muscles 27.2 Cortical Representations of the Hand 27.3 Indices of Finger Interaction

27.4 Multifinger Synergies in Pressing Tasks 27.5 Grasping 27.6 Prehension Synergies and Principle of Superposition Problems for Part V

Part VI    Sensorimotor Integration for Perception and Action Chapter 28    Kinesthetic Perception 28.1 Sensation and Perception 28.2 Weber-Fechner Law 28.3 Ambiguity of Sensory Information 28.4 Afferent and Efferent Components of Perception 28.5 Vibration-Induced Kinesthetic Illusions 28.6 Distorted Efferent Copy and

Preconceptions 28.7 Sense of Effort 28.8 Stability of Percepts 28.9 Perception–Action Coupling Chapter 29    Multisensory Integration 29.1 Spatial Multisensory Integration for Limb Motor Control 29.2 Temporal Multisensory Integration for Limb Motor Control 29.3 Coordinate Frames for Limb Motor Control 29.4 Postural Balance and Motion Perception 29.5 Neural Correlates of Multisensory Integration Chapter 30    Visual Perception and Action 30.1 Two Visual Streams

30.2 Magnocellular and Parvocellular Ganglion Cells and Streams 30.3 Motion Processing in the Cortex 30.4 Color, Object, and Face Recognition in the Ventral Stream 30.5 Feedforward and Feedback Control for Reach-to-Grasp Movements 30.6 Neural Structures Involved in Oculomotor Control 30.7 Roles of Two Visual Streams in Eye–Hand Coordination 30.8 Eye and Hand Coordination for Movements Starting From Rest 30.9 Eye and Hand Coordination During Movement

30.10 Eye and Hand Coordination While Intercepting Moving Targets Problems for Part VI

Part VII    Emerging, Evolving, and Adapting Movements Chapter 31    Fatigue 31.1 Fatigue and Its Contributors 31.2 Muscular Mechanisms of Fatigue 31.3 Spinal Mechanisms of Fatigue 31.4 Supraspinal Mechanisms of Fatigue 31.5 Adaptive Changes During Fatigue 31.6 Abnormal Fatigue Chapter 32    Effects of Aging 32.1 General Features of Movements in Elderly Persons

32.2 Changes in Muscles and Motor Units 32.3 Muscle Reflexes in Elderly Persons 32.4 Changes in Sensory Function 32.5 Muscle Activation Patterns During Fast Movements 32.6 Changes in Posture and Gait 32.7 Hand Function in Elderly Persons 32.8 Changes in Motor Synergies 32.9 Adaptive Changes in Motor Patterns 32.10 Effects of Training Chapter 33    Typical and Atypical Development 33.1 Humans at Birth 33.2 Motor Milestones During Typical Development 33.3 Exploration and Emergent Motor

Patterns 33.4 Development of Motor Synergies 33.5 Down Syndrome 33.6 Effects of Practice in Persons with Down Syndrome 33.7 Autism 33.8 Developmental Coordination Disorder Chapter 34    Motor Learning 34.1 Adaptation, Learning, and Memory 34.2 Muscle Memory 34.3 Habituation of Reflexes 34.4 Conditioned Reflexes 34.5 Operant Conditioning and Learning Spinal Reflexes 34.6 Short-Term and Long-Term Memory

34.7 Adaptation to Unusual Force Fields 34.8 Motor Skills 34.9 Learning Motor Synergies 34.10 Stages in Motor Learning 34.11 Effects of Practice on Cortical Representations Problems for Part VII

Part VIII    Motor Disorders Chapter 35    Peripheral Muscular and Neurological Disorders 35.1 Myopathies and Neuropathies 35.2 Muscular Dystrophies 35.3 Continuous Muscle Fiber Activity Syndromes 35.4 Myasthenia Gravis 35.5 Mononeuropathies

35.6 Multiple Mononeuropathies 35.7 Polyneuropathies 35.8 Radiculopathies Chapter 36    Spinal Cord Injury and Spasticity 36.1 Consequences of Spinal Cord Injury 36.2 Signs and Symptoms of Spasticity 36.3 Possible Mechanisms of Spasticity 36.4 Defining Muscle Tone 36.5 Treatment of Spasticity Chapter 37    Disorders Involving the Basal Ganglia 37.1 Clinical Features of Parkinson’s Disease 37.2 Voluntary Movements in Parkinson’s Disease 37.3 Vertical Posture and Locomotion in Parkinson’s Disease

37.4 Motor Synergies in Parkinson’s Disease 37.5 Treatment of Parkinson’s Disease 37.6 Huntington’s Chorea 37.7 Hemiballismus 37.8 Dystonia 37.9 Tardive Dyskinesia Chapter 38    Cerebellar Disorders 38.1 Consequences of Cerebellar Injuries in Animals 38.2 Consequences of Cerebellar Disorders in Humans 38.3 Abnormalities of Stance and Gait 38.4 Voluntary Movements in Cerebellar Disorders 38.5 Cerebellar Tremor 38.6 Ataxias 38.7 Changes in Motor Synergies 38.8 Cerebellar Cognitive Affective

Syndrome Chapter 39    Cortical Disorders 39.1 Consequences of Lesions of Different Cortical Lobes 39.2 Stroke 39.3 Myoclonus 39.4 Tics 39.5 Tourette Syndrome 39.6 Williams Syndrome Chapter 40    Systemic Disorders 40.1 Amyotrophic Lateral Sclerosis 40.2 Multiple Sclerosis 40.3 Multisystem Atrophy 40.4 Essential Tremor 40.5 Cerebral Palsy 40.6 Wilson’s Disease Chapter 41    Motor Rehabilitation 41.1 Do “Normal Movements” Exist? 41.2 Changes in CNS Priorities 41.3 Neural Plasticity

41.4 Adaptive Changes in Motor Patterns 41.5 Consequences of Amputation 41.6 Functional Electrical Stimulation 41.7 Constraint-Induced and DiscomfortInduced Therapies 41.8 Brain–Computer Interface 41.9 Practical Considerations Problems for Part VIII Glossary References Index About the Authors

Preface Since the original publication of the first edition of Neurophysiological Basis of Movement in 1998, major changes have happened in the field of the neural control of movements or, briefly, motor control. Over the past 25 years, the International Society of Motor Control (ISMC) has been formed, which now has its official journal Motor Control, runs a series of biennial conferences Progress in Motor Control, awards every two years the Bernstein Prize for outstanding contributions to motor control, and helps organize the annual Motor Control Summer School. There have been major developments in the theoretical foundations of motor control accompanied by an increase in the number of experimental studies, including studies of animals and humans over the life span, from neonates to the elderly, as well as various patient populations, aiming to discover the neurophysiological mechanisms involved in the production of functional movement patterns. There are courses in motor control at both undergraduate and graduate levels, textbooks, reference books, and national and international conferences on motor control. At this time, motor control is striving to become a field of natural science comparable in its rigor and exactness to established fields such as classical physics. This requires bringing more exactness into the terminology and rigor into the logics of the textbook. In particular, we strive to offer clear definitions to such frequently used but rarely defined concepts as synergy, motor program, motor command, and muscle tone. Neurophysiology forms the foundation of motor control, and therefore we consider an understanding of the basic neurophysiological structures and processes to be vital for progress in the field. The two previous editions of this book have been used to teach both upper-level undergraduate and entry-level graduate classes. In particular, at Penn State, the textbook has been used to teach a 400level undergraduate course, Movement Disorders, and a 500-level graduate course, Neurophysiological Basis of Movement. The former

course targeted those students in the department of kinesiology who planned to continue their education in areas related to motor disorders and rehabilitation. Most students who have taken this course so far planned to continue their education in a medical school, a physical therapy or occupational therapy school, a chiropractor’s school, a physician’s assistant program, or other related program. For that class, the course was tailored by selecting only the basic information on neurophysiology and focusing more on chapters related to changes in movements and neurophysiological mechanisms associated with fatigue, development, aging, and various movement disorders. In contrast, the graduate class was targeting students who joined the graduate program in kinesiology after completing undergraduate studies without taking any classes related to the central nervous system. These students commonly came from areas such as engineering, physics, mathematics, philosophy, and sociology. Those more mature students were exposed to material on basic neurophysiology, neurophysiological mechanisms of various behaviors, and more theoretical issues such as the ideas of parametric control and the control of action stability. This third edition has been expanded to allow more flexibility in tailoring the material to courses targeting different audiences and course contents. In particular, we added chapters on motor learning and sensorimotor integration, and we expanded significantly the sections on the role of different sensory modalities in motor control, on kinesthetic perception, and on action–perception interactions. We also took this opportunity to add more one-minute questions and self-test problems, which have proven to be highly useful (based on the student feedback). We are addressing rather explicitly many of the controversial issues in the area of motor control and coordination. Originally, the textbook was somewhat sugarcoated, presenting only wellestablished facts in the most noncontroversial manner. A number of chapters in the third edition deal directly with current theories of motor control and coordination and present different opinions on the very basic issues.

The preparation of this edition was helped a lot by the very useful (and frequently harsh) feedback from the students who took the two aforementioned courses at Penn State and from colleagues who took their time to tell us how the textbook could be improved. We are particularly grateful to Vladimir Zatsiorsky for the innumerable helpful comments over the past 30 years, to Robert Sainburg for the many fruitful discussions of how to teach motor control and neurophysiology, and to Karl Newell for the encouragement to develop the two courses at Penn State. Mark Latash and Tarkeshwar Singh

Introduction

Chapter 1 History, Evolution, and Motor Control KEY TERMS AND TOPICS history of movement studies Nikolai Bernstein evolution of movements motor control laws of nature physical approach What is the origin of purposeful movements by animals, including humans? Why is it easy for an observer to distinguish movement by an animal from that of an inanimate object, for example a stone? These questions have been in the center of attention of researchers, philosophers, and clinicians for literally thousands of years (for reviews on the history of movement science, see Latash and Zatsiorsky 2001; Meijer 2002). Classical Greek philosophers formulated the first of these questions somewhat differently: How does the soul control the body? And what is the origin of soul action?

1.1 Brief History of Movement Studies One of the founders of geometry, Pythagoras (571?-497? B.C.), viewed soul as an entity (a number) that can move by itself following the motion of heavenly spheres. Further, motion of the soul was somehow transmitted to body parts. Somewhat later, Democritus (460-370? B.C.) introduced a theory that all objects in the world consisted of very small basic objects, atoms, and concluded that movement of the soul was transmitted to the body by the movement of atoms. This was a brilliant insight preceding the current understanding of the role of moving ions in the communication between the central nervous system and muscles. Animals, according to Plato (428-347 B.C.), possessed a unique ability to show self-motion (i.e., they can move without being pushed by other objects). He viewed this ability as a reflection of the immortal soul, which was present in animals but not in inanimate objects. The soul was assumed to move body parts similarly to how fingers of the puppeteer pull on strings and move the marionette. The development of this view over the past 2,000 years is reflected in the idea that the brain prescribes spatial trajectories of body parts during voluntary movements. Aristotle (384-322 B.C.) was arguably the first to emphasize the importance of coordination during voluntary movements, an undefined feature prescribed by the Creator that makes biological movements look harmonious. PROBLEM 1.1 What makes the soul command the body according to classics of Greek philosophy? And what could be the origin of commands to the soul?

Until the second century A.D., philosophers discussed only very general features of biological movements without paying much attention to organs within the body that were crucial for movements to occur. The great Roman physician Galen (129-201) was arguably the first to emphasize two important features of animal movements. The first is the involvement of muscle pairs with opposing actions (agonists and antagonists, for example flexors-extensors) in voluntary movements of body segments. And the second was the role of nerves that delivered animal spirits to muscles that led to their force production. The formulation of the main question of movement as that of soulbody interaction persisted until relatively recently. A great philosopher of the Renaissance, René Descartes (1596-1650), is credited for introducing the basics of dualism, a branch of philosophy that views two independent entities forming every human being, the soul and the body (not very different from the ancient Greeks). Following Galen, Descartes thought that the soul used animal spirits to move the body, although some movements, for example the beating of the heart, were viewed as independent of the soul. Descartes also emphasized the importance of senses and the central nervous system for some movements. Descartes and a British anatomist Thomas Willis (1628-1678) viewed quick motor reactions to sensory stimuli as building blocks for voluntary movements—a view developed in the 20th century by Sherrington. Later, Jean Astruc (1684-1766) introduced the term reflex for such actions. At about the same time, the science of biomechanics was born with particularly impressive contributions by Giovanni Alfonso Borelli (1608-1679), a disciple of Galileo. Borelli viewed muscles as elastic structures controlled by the soul with droplets of nerve juice delivered by nerves—a great insight into the role of chemical processes and neuromuscular mediator (acetylcholine) in the production of biological movements. PROBLEM 1.2

Present examples of biological movements dependent and independent of the soul according to Descartes. The importance of electricity for biological movements was discovered just over 200 yrs ago by Luigi Galvani (1737-1798). This field of research developed rapidly in the 19th century, leading to the discoveries of the role of electricity within muscles by Carlo Matteucci (1811-1868) and Etienne DuBois-Reymond (1818-1896). In the middle of the century, studies of muscle reflexes by a German scientist Eduard Friedrich Wilhelm Pflüger (1829-1910) demonstrated the role of the spinal cord in reflex movements and its ability to produce activations of different muscles to the same stimulus depending on the initial state of the body. At about the same time, studies of biomechanics were moved forward by the invention of photography, and two great researchers, Etienne-Jules Marey (1830-1904) and Eadweard J. Muybridge (1830-1904), developed photographic methods specifically for the analysis of natural movements. Mechanical movement analysis was also refined by the Weber brothers (Ernst Heinrich, 1795-1878; Wilhelm Eduard, 1804-1891; and Eduard Friedrich Wilhelm, 18061871), who contributed significantly to the understanding of the mechanics of locomotion and other movements involving multijoint effectors. Neurophysiological studies of movements got very important contributions from studies of neuroanatomy by the great Italian neuroanatomist Camillo Golgi (1843-1926), who developed the method of silver-staining of neurons, and the Spanish neuroanatomist Santiago Ramon y Cajal (1852-1934), who used this method to visualize a variety of cells. His amazing drawings of neurons in different parts of the brain remained unsurpassed in quality for many years. One of the greatest neurophysiologists of the 20th century, Sir Charles Sherrington (1852-1952), and his colleague Sir Michael Foster (1826-1907) coined the term synapsis (later transformed into synapse) for sites of interaction between neurons. The contributions of Sherrington were many and varied, and his

name will be featured in several chapters, particularly those dedicated to description of muscle reflexes and the neural control of locomotion. In particular, Sherrington introduced the notion of active inhibition within the central nervous system and emphasized the importance of reflex connections from peripheral receptors to motoneurons in the spinal cord. He viewed muscle reflexes not as hardwired stereotypical responses to stimuli but rather as flexible mechanisms that formed the basis of motor behavior. A student of Sherrington, Thomas Graham Brown (1882-1965), performed studies of animals without sensory input into segments of the spinal cord from peripheral receptors. He documented locomotion-like movements in these animal preparations and introduced the notion of networks within the spinal cord (and, possibly, other parts of the central nervous system) able to generate rhythmic patterns of neural activity. Such neural networks were later termed central pattern generators. Further important steps in movement studies were helped by the development of new methods of analysis of electrical processes in the muscles (electromyography, EMG) and in the brain (electroencephalography, EEG). One of the pioneers of electromyography, Kurt Wachholder (1893-1961), and his student Hans Altenburger published a series of studies of EMG patterns during voluntary movements and described important regularities in muscle activation, including the triphasic pattern of muscle activation. The name of Nikolai Bernstein (1896-1966) will be featured in many chapters of this textbook. Bernstein is viewed by contemporary researchers as the father of motor control and physiology of activity. His research method was based on Darwin’s ideas of evolution: He viewed anatomical, physiological, and behavioral phenomena as reflections of the evolutionary process and fight for survival. Based on these views, he developed a hierarchical scheme for the control of biological movements (Bernstein 1947/2020), which remains one of the best developed schemes deeply rooted in neurophysiology.

1.2 Evolution of Movements and Nikolai Bernstein’s Theory Bernstein assumed that the process of evolution led to gradual development of the central nervous system based on new tasks faced by animals. He used the expression “new tasks formed the brain” in a very direct meaning. Furthermore, he viewed each qualitatively new evolutionary step as associated with the construction of a new level of control on the foundation of preexistent levels. In other words, in higher animals up to humans, one can see reflections of the whole process of evolution. Based on these views, Bernstein classified electrical phenomena in the body into paleokinetic and neokinetic. The first term was used to address evolutionarily older, relatively slow processes, which are going to be discussed further in this textbook under the label of postsynaptic potentials and local currents, and the second term described evolutionarily more recent, fast processes such as action potential generation and conduction. In his most detailed book, Bernstein (1947/2020) introduced several levels within the central nervous system participating in the construction of movements. His classification of levels was based on two principles. The first associated certain classes of motor tasks and task components with specific levels. The second linked the levels to different neurophysiological structures and pathways. The main levels identified by Bernstein are illustrated in table 1.1. The lowest level, Level A, also known as the paleokinetic level, or the rubro-spinal level, was viewed as the level where muscle tone (sometimes addressed as muscle tonus) was defined. We will return to this notion later in the textbook, in particular in chapters dedicated to movement disorders in neurological patients. This level was supposed to play auxiliary roles, for example, providing necessary postural backgrounds for actions led by higher levels. Bernstein emphasized the importance of spinal reflexes, in particular reciprocal inhibition, in the functioning of this level. According to

Bernstein, descending control of this level from the brain was associated with the output of the red nucleus, a nucleus in the brain, the origin of the rubrospinal tract, which mediates, in particular, effects of processes in the cerebellum on limb and body movements. Table 1.1    Hierarchical Scheme of the Neural Control of Movements Level Alias

Physiology

Functions

A

Paleokinetic level

Rubrospinal

Muscle tone, posture

B

Level of synergies

Thalamic-pallidar

Synergies, stability

C

Level of spatial field

Pyramidal-striatal

Targets, affordances

C1

Striatal

Trajectory

C2

Pyramidal

Target

D

Level of actions

Parietal-premotor

Topology, skills

E

Level of symbolic actions

Higher cortical

Language, music

Adapted from Bernstein (1947/2020).

The next level, Level B, which had two names, the level of synergies and patterns and the thalamic-pallidar level, was responsible for uniting numerous muscles that take part in most functional actions, for example locomotion, into groups. Muscles within each such group were expected to show parallel changes in their activation levels, which is currently viewed as one of the distinguishing features of multi-muscle synergies. Bernstein realized the importance of movement stability in the continuously changing, unpredictable world, and associated this function with Level B. It is rather amazing that Bernstein linked this level to the thalamus and globus pallidus—two structures within the brain involved in neural loops that define movement-related output of cortical areas. As we will see later, this insight maps well on the current understanding of the role of the thalamus and basal ganglia (globus pallidus is part of this system of subcortical structures) in the control and coordination of movements.

Bernstein associated the next level, Level C, the level of the spatial field, or the pyramidal-striatal level, with the concept of spatial field, a portion of the external space accessible for specific actions, with its geometry and metrics. This notion included not only motor elements but also sensory signals relevant to that portion of the surrounding space and its perception with the help of various sensory modalities, including proprioception, touch, vision, and vestibular system. The notion of spatial field is a close relative to the notion of affordances introduced later by the great American psychologist James Gibson (1904-1979) to describe possibilities for action existing in the environment given the properties of the body, location of targets, obstacles, and external forces (Gibson 1979). The level of spatial field was viewed as responsible for actions toward targets in the external space. Two sublevels were responsible for identification of a target and ultimately reaching it (C2, pyramidal sublevel) and for ensuring specific trajectories from the initial state to the target (C1, striatal sublevel). Note that proper functioning of this level always has to take into consideration actual and expected forces acting from the environment. Since such expectations are never 100% perfect, behaviors controlled by Level C are always associated with motor variability and can be characterized with accuracy—consider, for example, catching a ball. Bernstein introduced one of his famous expressions with respect to actions controlled at Level C: “Repetition without repetition.” He implied that, when a person tried to perform the same task multiple times, the process of solving this motor problem was repeated but actual trajectories were not—a great insight considered in detail later. PROBLEM 1.3 Can spatial field be described with nonspatial variables? Present examples. Actions at the next level are seen nearly exclusively in humans. This level, Level D, the level of actions, or the parietal-premotor

level, is responsible for object-oriented meaningful actions. Actions performed at this level not only reach for an object or transport it but do so for a reason; the main characteristic of these movements is their topology (i.e., higher-level spatial characteristic). One of the examples discussed by Bernstein is handwriting: One can write any given letter, for example the letter r, in many different ways, using different implements and holding them differently, even with different body parts, but they will all be recognized as r and will carry respective meaning. This is the level where motor skills are developed. As the name of this level suggests, Bernstein associated it with processes in parietal and premotor areas of the cortex. The highest level, Level E, the level of symbolic, highly coordinated actions such as speech and writing, was not associated by Bernstein with any specific brain structures. He described this level as based on “highest cortical control.” Using the example of handwriting, this level took responsibility not only for writing the letter r in a legible way but writing it in a proper position within a word. Using a different example, a musician has to produce not only an action that leads to a specific note when playing a musical instrument, but playing it at a proper time and level of sound within the piece. We will return to Bernstein’s multilevel scheme for the construction of movements later when we discuss specific neurophysiological structures, circuits, reflexes, and behaviors.

1.3 Motor Control and Laws of Nature Although this textbook is not explicitly about motor control, we will always view specific neurophysiological structures and circuits as contributors to the control and coordination of functional movements. There is no agreed upon definition of the commonly used expression “motor control,” and this situation is a major source of misunderstanding in the field studying the neural control of

movements. Two attitudes to motor control dominate the field. One of them is based on the impressive success of control theory and engineering during the 20th century in the design of control systems for artificial objects, from ballistic missiles to artificial satellites, to self-driving cars, and to robots. According to this approach, the central nervous system of a moving animal performs computational operations similar to those performed by the control systems in human-built objects with the purpose of predicting future states of the animal, changes in the environment, and interactions between the two, and generating neural signals needed to produce requisite force profiles. The goal of motor control, within this theoretical framework, is to understand the software underlying those computations and the neurophysiological systems involved in delivering relevant signals to and from structures performing the computations. According to principles of engineering, animal bodies are built rather poorly. As we will see further in the textbook, our bodies have sluggish and not very predictable motors (muscles) that produce forces dependent on muscle length and velocity; they are equipped with rather ambiguous and fuzzy sensors (receptors) and have very long delays in the conduction of information along neural fibers from the receptors to the central nervous system, within the central nervous system, and back to the muscles. In contrast, artificial systems, such as robots, are equipped with powerful actuators that can produce patterns of force and torque independently of the kinematics; their sensors are accurate and dedicated to specific salient variables, and conduction delays in the electrical circuits are very short. Overall, if we were designed by a 21st century engineer, this person would have not been praised by his or her employers. That is why we need an omnipotent computer (the brain) to handle all the difficulties introduced by this apparently faulty design. The alternative view is: Evolution makes no mistakes or, at the very least, it makes fewer mistakes when compared to contemporary engineers. (Indeed, look at the best robots trying to play soccer! They are amazingly clumsy and inept.) If our bodies have specific features, these are the best to handle everyday motor problems and

be successful at solving them. This approach views animals and their body parts, including the brain, as natural objects that behave according to laws of nature and perform no computational operations. Indeed, very coordinated and agile animals cannot be taught to add two numbers. Within this approach, motor control is defined as an area of natural science exploring laws of nature that define how body parts interact with each other and with the environment during natural movements. This view of biological movements is going to be addressed further as the physical approach. To introduce the physical approach, one has to start with a few very basic definitions. Laws of nature are concise descriptions of regularities in the behavior of different classes of objects observed by researchers, commonly in the form of equations. Consider, for example, two of the best-known laws of nature from the field of classical mechanics, Newton’s second law and Hooke’s law. Newton’s second law describes how forces change the motion of material objects: where F is force, a is acceleration, and m is mass (figure 1.1a). Note that, here and later, italics will be used to denote variables and parameters characterized by magnitude only, and bold-italic fonts will be used for vectors (variables characterized by both magnitude and direction). Hooke’s law described how forces lead to the deformation of certain classes of objects, which we will address as springs (figure 1.1b): where ΔF stands for a change in external force, Δx for a change in the object’s dimension, and k for stiffness.

Figure 1.1    An

illustration of two basic laws of nature from classical physics, (a) Newton’s second law and (b) Hooke’s law. Both laws involve variables: F, a, ΔF, and ΔX and parameters: m and k. F = force; a = acceleration; m = mass; ΔF = change in force; X = coordinate; X0 = coordinate corresponding to zero length of the spring; ΔX = change in coordinate; k = stiffness.

Note that each of the two presented equations involves two types of symbols, variables (F, a, ΔF, and Δx) and parameters (m and k). Variables are constrained by each law, while parameters are not. Indeed, mathematically it does not matter whether you write F = ma or F = am. However, if you apply force to an object, it would lead to proportional acceleration, not a change in mass. The same is true for Hooke’s law: Changing force acting on a spring will lead to its deformation, not a change in its stiffness. This is true even for objects that are characterized by quickly changing parameters. For example, m remains a parameter in Newton’s second law even if it changes quickly as, for example, in a rocket burning lots of its fuel. Classical laws of nature described in physics textbooks are applicable to all objects, biological and inanimate. However, there is a qualitative difference. Inanimate objects behave in a wellpredictable way if we know all the variables and parameters of the relevant laws of nature. Biological objects do not violate those laws, but their behavior is not prescribed, only constrained, by them.

Indeed, animals frequently show behaviors that are not expected from inanimate objects. Examples include running uphill and swimming against the current. These behaviors suggest that some of the relevant laws of nature have not been discovered yet, which makes the field of motor control very exciting. Further, we will try to link specific features of neurophysiological systems and circuits in the body to possible biology-specific laws of nature. Figure 1.2 uses the well-known law of gravity to illustrate the difference between the two main approaches, based on the control theory (left panel) and on laws of nature (right panel). The law of gravity was introduced by Isaac Newton in the following form:

where FG stands for the gravity force acting between two bodies, M1 and M2 for the masses of the two bodies, R for the distance between the bodies, and γ is a constant. Imagine now that there is a computational device on the Sun that receives signals from sensors on the planets informing it of their masses and distances from the Sun. This computational device also has information on the mass of the Sun itself. Based on those data, it computes the requisite force using equation 1.3 and sends signals to actuators that produce the precomputed force on the planets.

Figure 1.2    An

illustration of two approaches to the origin of gravity force acting between the Sun and a planet. (a) The Sun gets information from sensors on the mass (m) of and distance (R) to the planet, computes planned force (F) based also on its own mass (M), and sends a signal to hypothetical actuators that put this force into action. (b) The Sun creates gravity field G. Any object in this field experiences force proportional to the field and the mass of the object. γ = constant.

The alternative is to introduce the notion of a gravitational field created by any object with mass and formalizing the force it creates on other objects with mass in the form of equation 1.3. No sensors, computational devices, or actuators need to be assumed: Celestial bodies move as dictated by the law of gravity, which is one of the basic laws of nature. The fact that human bodies are equipped with apparent anatomical “actuators” (muscles) and “sensors” (receptors) does not by itself prove that the brain performs computations similar to those that are used to control robots and satellites. Note that the functioning of other organs such as the liver, the heart, and the stomach is not based on assumed computations but on physiological

mechanisms that are based on laws of nature. In this book, we will try not to invoke computations performed by our objects of study, including the brain, but to understand how they participate in the production of natural movements based on the known physiological mechanisms and laws of nature. According to one of the influential theories of motor control (reviewed in Feldman 2015), which we will describe in more detail later, the neural control of biological actions is based on prescribing parameters within the relevant laws of nature. This type of control— addressed as parametric control—is qualitatively different from movements in inanimate nature. Indeed, there is only one method to induce movement (or to change movement) of an inanimate material object: to apply force—a variable—to that object, which will induce acceleration according to Newton’s second law. Biological objects, however, change parameters to initiate or modify movements.

Figure 1.3    A

simple physical system: an ideal pendulum (a point mass on a massless, rigid cord). Its motion can be controlled by changing parameters of the pendulum: L (length) and {x0, y0, z0}—coordinates of its suspension point. Forces acting on the pendulum emerge with its motion: FG = force of gravity, FC = force from the cord, and FRES = resultant force.

These two methods of control can be illustrated with the example of a simple pendulum consisting of a ball attached by a massless rigid cord to the point of suspension (figure 1.3). Natural movement of the pendulum is defined by its parameters. In particular, the natural frequency of its oscillations is defined by the length of the cord (L), and the portion of the external space where it oscillates is

defined by the coordinates of the point of its suspension in space (x0, y0, z0; we assume that the direction of gravity, g, is not changing). Its motion is accompanied by changes in the resultant force acting on the ball (FRES in figure 1.3), but this force is not prescribed by a controller. It emerges during the motion of the pendulum given the external field of gravity and parameters of the pendulum. How can one change the movement of this simple pendulum? There are two methods. First, one can push the ball during its motion (i.e., apply an external force). Second, one can change some of the parameters that define its motion; for example, one can shorten the cord (and it will start to oscillate faster) or move the point of suspension (and it will oscillate in a different area of space). The second method is an example of parametric control. So, the idea that biological movements are produced by parametric control implies that living objects can change their relevant parameters. Imagine that a pendulum has learned (as a result of “pendulum evolution”) how to change—at will!—its length and coordinates of suspension. This would lead to any desired movement of the ball without any computation of forces.

CHAPTER 1 IN A NUTSHELL Philosophers and researchers have been thinking about problems of interaction between

the

intention)

human

and

mind

body

(soul,

literally

for

millennia. Development of new methods of

observation,

analysis leading about

played the

the

measurement, a

major

evolution

interactions

of

role

and in

thinking

between

the

central nervous system and the rest of

the body. Nikolai Bernstein introduced a

multilevel

scheme

of

the

construction of movements based on the evolutionary

approach;

many

of

his

guesses have been confirmed in later studies. There are two approaches to motor control. One of them is based on concepts

from

engineering;

control

the

theory

other

is

based

and on

ideas from natural science. According to the latter approach, motor control is a field of study trying to discover laws

of

interactions

nature among

that body

define

structures,

including the central nervous system, and

between

the

body

and

the

environment during natural movements.

Part I Excitable Cells and Their Communication

Chapter 2 Membranes, Particles, and Equilibrium Potentials KEY TERMS AND TOPICS biological membranes movement of particles in solutions osmosis movement of ions Nernst equation equilibrium potential Nikolai Bernstein singled out two events in biological evolution that he viewed as crucial for the development of life on Earth (Bernstein 1947, 1996; Latash 2020). One of them is easy to guess: This is the emergence of a stable molecule that can replicate itself. Otherwise, it would be impossible to pass information to future generations. The second event is less obvious. It is the emergence of the biological membrane, which separates the contents of the simplest organism, the cell, from the environment. We are not going to discuss viruses here. They may be viewed as even simpler organisms able to survive and succeed in the evolutionary process without the membrane.

Further, Bernstein described a feasible chain of events leading to more and more complex organisms up to humans. He emphasized the following steps, which are going to be discussed in more detail in future chapters: 1. Cells form groups. Within such groups, cells on the surface become sensitive to salient external stimuli, and cells inside the groups develop an ability to change shape (i.e., to produce movements). This leads to the emergence and specialization of receptors and muscles. 2. One of the ends of such a group of cells, its “mouth end,” becomes its active end, searching for food, defending from predators, and providing information on objects that are not in direct contact with the body with the help of specialized sensors—telereceptors. 3. Specialization of groups of cells for fast information transmission. Emergence of groups of cells (neural ganglia, the spinal cord, the medulla, and the brain) dedicated to the control of certain tasks. 4. Searching for more food and avoiding predators leads to new motor tasks, which require more and more sophisticated problem-solving abilities. Bernstein emphasized, in particular, the role of locomotion and postural tasks for the development of the central nervous system. 5. The process of encephalization, when larger and larger groups of tasks and associated problems are delegated to the brain. We will begin with one of the two earliest “inventions” of evolution, the cellular membrane. Other steps will be clarified later in the book.

2.1 The Biological Membrane The cellular membrane (figure 2.1) isolates information within the cell from the external world and thus allows for its storage, it protects the contents of the cell, and it defines its boundary, thus making it a unit

separate from the environment. If the membrane were absolutely impermeable to any substances, the cell would not be able to interact with the world, to extract the necessary information and substances (e.g., sources of energy), and to get rid of products of metabolism. This would make it an alien structure rather than a part of the environment. If the membrane were permeable to everything, its function would be completely lost. So, one of the most important functions of the cellular membrane is its partial permeability that allows exchange of information with the environment while protecting the contents of the cell.

Figure 2.1    Cellular

membrane is a sophisticated structure that is permeable to some substances but not to others. Its selective permeability makes the membrane a unique structure that allows the cell both to interact with the environment and to be separate from it.

The movement of substances across the membrane is a central theme of an area of biology called “membrane physiology.” Membranes are commonly very thin (about 40 Ångstrom or about 4 nm = 4 · 10−9 m), but they control the movement of substances much more effectively than the cells themselves, despite their relatively

large volume. There are three major groups of substances that can travel across the membrane and whose properties we are going to consider: 1. Solvents. The most common solvent is water; however, some substances are soluble in lipids, which allows them to pass through cellular membranes more easily because the membranes are built mostly with lipid molecules. 2. Electrolytes. These are ions (fragments of molecules) that have a nonzero electric charge. 3. Nonelectrolytes. These are molecules or fragments of molecules without a net electric charge. Many products of cellular metabolism are nonelectrolytes. Movements of electrolytes will play a particularly important role in this course, because they create electric current through the membrane. Most of the urgent information is transmitted within the nervous system (as well as within other systems of our body) with the help of electricity. So, electric currents created by movements of electrolytes are vital for information transmission that, in turn, underlies all the processes of the generation of commands to muscles and the execution of these commands by the muscles.

2.2 Movement in a Solution Water is a very good solvent because of the polar nature of its molecule, H2O, because this molecule has local positive and negative charges that sum up to zero. As a result, an electrolyte (e.g., molecules of salt, NaCl) dissociates in water, creating ions. Nonelectrolytes that, like water, are polar also dissolve rather well but without breaking down to ions. Movement of water commonly occurs because of a difference in hydrostatic pressure; this bulk flow or convection is proportional to pressure difference (figure 2.2). Bulk flow carries water with all the dissolved particles.

Figure 2.2    Convection

is movement of a solvent (for example, water) and solutes from an area of high pressure to an area of low pressure.

The concentration of particles of a certain kind in water defines another type of movement, which is called diffusion. If the concentrations in two areas of a solution are different, random motion of particles (molecules or ions) in different directions, the Brownian motion, leads to a net movement in a direction from the site with a higher concentration to the site with a lower concentration (figure 2.3).

Figure 2.3    Diffusion

is movement of particles dissolved in a solvent from an area of their high concentration to an area of their low concentration.

As a result, diffusion changes the concentration of particles leading to a decrease in the difference in concentrations at different sites. Note that relative change in concentration depends on several factors, including actual difference in the number of particles and total volume of each site (compartment). The bigger the compartment, the smaller the change. When discussing diffusion of particles across cellular membrane, the extracellular space is typically considered to be much larger than the intracellular space, so diffusion processes lead to a change in the concentration inside the cell but not outside it. Note also that diffusion takes time, particularly when it occurs across large distances. So, our body uses other means of transporting solutes over large distances, in particular, convection with the help of the circulatory system. The rate of diffusion from or into a cell depends on the surface/volume (S/V) ratio for the cell. Small cells have large S/V ratios, and diffusion occurs quickly, while large cells have low S/V ratios and diffusion is slow. For a spherical cell:

where r is radius. Electrolytes and nonelectrolytes both move with convection and diffusion. Electrolytes, however, can also move under the action of an electric field. In this case, the movement of electrolytes obeys Ohm’s law: where I is current or change in electric charge (I = dQ/dt), V is voltage or difference of electric potentials, and R is a coefficient termed resistance (figure 2.4).

Figure 2.4    An

electric field creates a difference of potentials (U), which induces a flow of charged particles (current, I). The current is proportional to the difference of potentials. The inverse of the coefficient of proportionality is termed resistance, R.

Convection, diffusion, and movement under the action of an electric field occur in a solution irrespectively of the presence or absence of membranes. Let us now turn to movements of these substances across biological membranes. Membranes typically are built of lipid layers that are very permeable to water, quite impermeable to virtually any particles, but particularly hate to let ions through. So, almost all movement of substances across membranes occurs at special sites called membrane channels. At these sites, specialized macromolecules let certain substances across the membrane. For example, sodium channels use a polypeptide with an enormous molecular weight of about 260,000 daltons. The rate of movement of a substance through the membrane depends on the concentration gradient (like in diffusion) and on voltage gradient (if

we are dealing with ions). There are substances that can cross membranes in substantial quantities without the help of channels; these are solutes that can dissolve in lipids, examples being anesthetics and some other drugs.

2.3 Concentration of Water: Osmosis To measure concentration of all the particles in a volume of a solvent, one needs to know the total number of different particles in that volume. For this purpose, it is useful to borrow a special unit from electrochemistry, namely a mole. A mole is the amount of a substance for which the weight in grams is equal to the substance’s molecular weight. For example, molecular hydrogen has a molecular weight of 2 (1 for each hydrogen atom); thus, one mole of hydrogen weighs 2 g; similarly, one mole of oxygen weighs 32 g (16 for each atom). Note that one mole of any chemical substance, for example, atom, molecule, or ion, always contains 6.02 times 10 to the power of 23 particles (Avogadro’s number). The concentration of water is measured as the total concentration of all particles. Thus, the osmolarity of a solution with a nondissociating substance (e.g., sucrose), will correspond to the number of molecules of this substance. So, a 1 millimolar (mM, remember that “milli” means divided by 10 to the power of 3) solution has an osmolarity of 1 mOs (milliosmole). If the substance is one that can dissociate, for example, salt, each molecule of this substance (NaCl) will produce two particles, Na+ and Cl−, so that a 1 mM solution of NaCl has an osmolarity of 2 mOs. Note that the concentration of a substance can change without changing its amount (i.e., if the total volume of the cell changes). This can happen, for example, if you put a red blood cell (erythrocyte) into a solution with a smaller or higher concentration of salt than in blood plasma.

PROBLEM 2.1 What will happen with a red blood cell in these solutions? Note that the membrane surface cannot change much. A solution is called isoosmotic if it has the same concentration of solute as the reference solution (plasma), hypoosmotic if it has a lower concentration, and hyperosmotic if it has a higher concentration of solute. These are nearly synonyms to the commonly used terms isotonic, hypotonic, and hypertonic. Osmosis is a process of movement of the solvent (for example, water), rather than the solute, across the membrane, in order to obtain osmotic equilibrium. Remember that motion of ions and other particles through the membrane is typically restricted, while water can travel freely. It is important to understand that osmotic equilibrium (when water does not move from one side of the membrane to the other) is achieved only if the osmolarity of the solution on either side of the membrane is equal. So, the concentration of particles inside the cell (Si) should be equal to the concentration outside the cell (So). Note that concentration equals the number of particles (A) divided by volume of the site (V), So, if you take a cell from a solution with the concentration of particles S1 and place it into a new solution with the concentration of particles S2, cell volume will change so that osmotic equilibrium is reached (figure 2.5). Initially, Si1 = So1. From equation 2.3, A1/V1 = So1 In the new solution, similarly we get A2/V2 = So2 A simple transformation gives:

Figure 2.5    If

you take a cell from a solution with a concentration of particles S1 and place it into a new solution with a concentration of particles S2 (S2 > S1), cell volume will change (decrease) until a new osmotic equilibrium is achieved.

So, in order to know how cell volume will change in a new solution, we need to know the concentration of the solute outside and the amount of the solute inside the cell. PROBLEM 2.2 What will happen with the cell if it is placed in a solution containing only permeable substances?

2.4 Movement of Ions: The Nernst Equation Ions move by both diffusion and voltage gradient (figure 2.6). As mentioned earlier, diffusion is driven by a concentration difference. The chemical force driving diffusion is termed chemical potential (Fc):

Figure 2.6    Ions

move under the influence of two forces. The first is related to the concentration gradient (Fc), while the second is related to the difference of potentials (Fe). C = concentration, V = voltage, T = temperature (Kelvin scale), z = valence, R and Φ = coefficients (Avogadro’s number and Faraday number).

where R is the gas constant, T is absolute temperature (Kelvin scale), and C is concentration. If there is an external electrical field, the electrical force (Fe) acting on a charged particle can be defined from: where z is the valence (don’t forget that valence can be positive or negative!), Φ is the Faraday constant, and V is voltage. So, the total electrochemical force acting on an ion is If an ion is in equilibrium, forces acting on particles of the ion on the two sides of the membrane must be equal. These forces are sometimes addressed as electrochemical potentials: From this equation, one can calculate the equilibrium potential (Veq) inside the membrane with respect to the potential outside (Veq

= Vin − Vout)—that is, the potential at which there is no net movement of the ions through the membrane:

This is the Nernst equation. So equilibrium potential, by definition, is an electric potential that induces the movement of an ion across the membrane equal and in the opposite direction to movement of the ion due to the difference in concentrations (note that in figure 2.6, Fc, force due to the difference in concentrations, and Fe, force due to the difference in the electric potentials, are acting in opposite directions). Electric force acting on an ion is directly proportional to its charge (i.e., it is twice as high in the case of Ca++ as in the case of Na+ or K+). It is equal in magnitude and acts in the opposite direction in the case of Cl− as compared to Na+. At body temperature, RT/Φ is a constant (62 mV), and so:

Note the following properties of the equilibrium potential: 1. It is a measure of the concentration ratio for an ion that has the meaning of energy available for diffusion; 2. it is a potential when there is no net passive movement of an ion across the membrane; and 3. it is actual voltage on the membrane, but only if just one ion species can move through it (e.g., if there is just one kind of channel, as in squid axon membrane, which is permeable at rest only to K+). PROBLEM 2.3 In which direction will electric current flow across a membrane if the potential inside the membrane is higher than Veq? Solve it for Na+ and for Cl−.

The direction of the current is defined by the potential on the membrane, while its magnitude is defined by Ohm’s law (see equation 2.2). So, for example, electric current due to the movement of K+ ions will be: where I is current, gk is the conductance for K+, V is voltage, and Vk is equilibrium voltage for K+. Note that gk is not a constant and may change quickly. Note also that the concentration gradients do not change much during brief events such as an action potential. So, virtually all ion movements through the membrane will be defined by equation 2.11.

CHAPTER 2 IN A NUTSHELL Biological

membranes

structures

that

are

allow

unique

cells

to

interact with the environment and be separate

from

it.

Particles

in

solutions can move among compartments under the influence of differences in pressure,

differences

concentration,

and

in

electrical

field.

Osmosis is a process of movement of the

solvent,

across

the

equilibrate

rather membrane,

than in

concentrations

solute, order

to

of

all

particles. Equilibrium potential is a potential on a membrane that creates an electrical force acting on charged

particles, which is equal and opposing the

force

due

to

the

difference

in

particle concentrations. It is defined by the Nernst equation.

Chapter 3 Action Potential KEY TERMS AND TOPICS membrane potential ion conductance sodium–potassium pump generation of action potential The action potential is the most important unit of information transmission in the bodies of higher animals. Its importance is immense. In lower animals, information within the body is transmitted mostly by diffusion and by convection—that is, by bulk flow of liquids containing important chemical substances. This mechanism of information transmission is called humoral, and its speed is limited by the rate of liquid flow under the difference in pressure. In the process of evolution, the emergence of the ion mechanism leading to the generation and transmission of action potentials signified a many-fold increase in the speed of information processing and conduction, giving species who possessed this “novelty” a significant advantage in the everlasting competition of life. The humoral mechanism of information transmission is still present in the higher animals, but all the processes that require quick decision-making and quick action take advantage of the much faster electrochemical mechanism. Some of the properties, limitations, and disorders of

movements are rather directly linked to the mechanism of generation and transmission of action potentials.

membrane is separating two areas, with and without ions of Na+ and Cl−. Diffusion of these ions may occur at different speeds. As a result, a new equilibrium will be reached with different ion concentrations to the right and to the left, when the electric force will exactly compensate for the concentration gradient force. Figure 3.1    A

3.1 Creation of a Membrane Potential Consider a membrane separating a volume into two halves (figure 3.1). Initially, there is no NaCl to the right of the membrane, and there is some to the left. Note that there is no voltage across the membrane because the number of ions of Na+ to the left of the membrane is exactly the same as the number of ions of Cl−. Diffusion will begin because of the concentration gradient. However, different ions may move at different velocities. Imagine that in our

case, Cl− moves faster. Then, when the concentration of ions on both sides is equal, there will be a little bit more of Cl− to the right and a little bit more of Na+ to the left. Thus, an electric potential will emerge across the membrane, or, more precisely, a difference of potentials known as the membrane potential. Note that the potential is being created not by all the ions but only by a tiny fraction that is not balanced. For example, the extra amount of ions needed to create a potential of 100 mV (a typical value for membrane potentials) is only 10-12 M (one picomole) for the area of membrane of 1 cm2. All biological potentials are created by tiny amounts of unbalanced ions. So, to a good approximation, you can always consider the total concentration of positive ions in a solution to be equal to the total concentration of negative ions. PROBLEM 3.1 Find an error (an imprecise statement) in the previous paragraph. Note that the membrane also behaves like an electric capacitor, a physical structure able to store electrical charge in the presence of an external electric field. In particular, like in regular electric capacitors, its ability to store electric charge depends on its surface but not on the volume of the solution. The net (unbalanced) charge (Q) on a membrane equals its capacitance (C) multiplied by voltage (V) across the membrane: This is a version of Coulomb’s law, which is also the definition for capacitance as a coefficient of proportionality between the difference of potentials and stored charge. When the voltage changes, the charge changes as well. By definition, capacitative current is the change of charge (Ic = dQ/dt). So,

Note that capacitative current is different from the current created by the movement of ions through a membrane. Capacitative current is created by changing an electric field, and it does not require any carriers or channels. It may play a significant role in some cases of small changes in membrane potential. There are several important ions that play special roles in the electric phenomena in neurons of mammals. We are now going to consider sodium (Na+), potassium (K+), and chlorine (Cl−). Their concentrations inside and outside a membrane are rather different (figure 3.2). Using the Nernst equation, we can calculate equilibrium potentials for these ions. Later, we will turn our attention to one more important ion, Ca++, which has very low concentration inside the typical membrane.

Figure 3.2    A

membrane may be considered a capacitor. Its charge (Q) is proportional to the difference of potentials (V) across the membrane with a coefficient termed capacitance (C).

PROBLEM 3.2 Calculate (approximately) equilibrium potentials for Na+, K+, and Cl−.

Figure 3.3 shows typical concentrations of the three ions K+, Na+, and Cl− inside and outside the membrane and the corresponding equilibrium potentials. The difference in ion concentrations inside and outside the membrane is maintained actively and requires energy. This mechanism is commonly called the sodium– potassium pump. Ion pumps involve the action of proteins that carry ions against their concentration gradient. The sodium– potassium pump involves proteins that carry Na+ outside the membrane and carry K+ inside the membrane. The number of carried ions is not balanced: The protein carries two K+ ions inside for every three Na+ ions carried outside. As a result, the pump generates a net negative potential inside the membrane or, in other words, contributes to its hyperpolarization. Figure 3.4 shows schematically how the pump works, receiving energy from adenosine triphosphate (ATP) stored in mitochondria.

Figure 3.3    The

differences in the concentration of the three most important ions across the membrane. Equilibrium potentials for each ion are shown in parentheses.

Figure 3.4    Maintaining

the ion concentration gradients across the membrane requires energy, which is provided by a chemical process that transforms ATP (stored in mitochondria) into ADP. This mechanism is called the sodium–potassium pump.

Let us imagine that a number of ions, for example K+, Na+, and Cl−, can cross a membrane through the same channels and thus are in a competition. Membrane potential will be defined according to equation 3.3:

where P is permeability of the membrane to an ion and C is concentration of an ion (note the subscripts K, Na, and Cl) in and out of the cell. This is the Goldman-Hodgkin-Katz equation. If the channels are perfectly selective, the equation will look like this:

where g is conductance and E is equilibrium potential for a given ion. You may consider g as a reflection of the number of open channels for a particular ion. Then, the more channels that are open, the bigger is the contribution of the equilibrium potential of this ion to the actual resting potential on the membrane. In particular, if only one ion can cross the membrane, its resting membrane potential will be

equal to the equilibrium potential for that particular ion. Equation 3.4 is a decent approximation since membrane channels are rather ionspecific. However, note that it is not applicable during fast changes in membrane potential, as for example, during the action potential. PROBLEM 3.3 Why is equation 3.4 inadequate during fast changes in membrane potential? What has not been taken into account? Why, in equation 3.3, are members for Cl− represented differently than those for K+ and for Na+? Actual resting (or equilibrium) potential on the membrane depends on the values of conductance (g) for different ions and on their equilibrium potentials. The resting membrane potential can be quite different in different neurons; for example, it is about −40 mV in rods and cones in the retina at rest and about −75 mV in the pyramidal neurons in the cortex. The resting membrane potential can also show changes within the sleep-wakefulness cycle (Hirsch et al. 1983). For simplicity, we are now going to assume that the resting potential equals −70 mV and is mostly defined by the higher g for ions of Cl− as compared to the conductance values for K+ and Na+ ions. This value is not far from the membrane potential on the squid giant axon, which has a diameter of about 0.5 mm and, as a result, can be pierced by relatively large microelectrodes. Studies on the squid giant axon by Alan Hodgkin and Andrew Huxley in the 1930s documented a potential inside its membrane of about 60 mV.

3.2 Basic Features of the Action Potential The word “potential” has quite a few meanings. We are going to speak now about a process, a time function of the transmembrane voltage that we are going to call action potential. Don’t confuse it

with membrane potential, which describes a membrane’s state at a particular instant of time.

Figure 3.5    If

you stimulate a membrane with relatively small electrical stimuli, its resting potential will change somewhat in response to each stimulus, and then will return to its resting level.

One of the most interesting features of an action potential is its threshold nature. Imagine that you start to stimulate a membrane by applying short pulses of electric current through the membrane with an external stimulator (figure 3.5). At low values of the stimulating current, the membrane will respond with a small change in its potential that will rather quickly return to its equilibrium (or resting) value. Your stimulus will certainly spread because an electric field spreads, but it will not spread far because the electric field drops quickly with distance from the source of stimulation. So, the maximal deviation of the membrane potential from its resting value will be seen close to the site of stimulation only. If you start to increase the current, the deviation of the membrane potential will also increase (figure 3.6), and at a certain value of the stimulus something amazing will happen: The membrane will respond with a disproportionally huge change in its potential. The

value of membrane potential at which this qualitative change occurs is termed the membrane threshold or stimulation threshold. If you continue to increase the strength of the stimulus, surprisingly, no further change will occur. The membrane will react with exactly the same action potential. This feature of the action potential to either be of a standard height or not to be at all without any intermediate behavior is termed the all-or-none law.

Figure 3.6    An

increase in the stimulation current will lead, at low values, to a gradual increase in the deviation of the membrane potential from its resting level. At some value of the stimulus, when it reaches a certain threshold magnitude, an action potential will be generated. Further increase in the strength of the stimulation will not lead to a change in the membrane response.

PROBLEM 3.4 Suggest examples of the all-or-none law from everyday life. Please note that we are addressing now transmembrane potentials (i.e., the difference between the potential inside the membrane and the potential outside the membrane). If you put a couple of measuring electrodes outside the membrane, you can record a difference of potentials between the electrodes but not across the membrane. Extracellular potentials are typically much

smaller than the amplitude of the action potential (by a factor of one thousand!). Similarly, if you try to stimulate a membrane without penetrating it, you will need rather high currents because the extracellular solution and the membrane effectively shield the inside of the cell from the effects of externally applied currents. Let us perform a mental experiment and insert a very thin stimulating electrode through the membrane into a cell so that the integrity of the membrane is not violated (figure 3.7). If we now apply current that makes the voltage in the cell more negative, the change in the membrane potential will be called hyperpolarization. A current in the opposite direction will induce a change in the transmembrane potential called depolarization. Both hyperpolarization and depolarization spread electrotonically (i.e., they affect neighboring areas of the membrane due to the membrane’s electrical properties), and typically they quickly become smaller and disappear with distance.

3.7    A thin electrode is inserted into the cell without breaking the membrane. Now we can apply electrical current to change the membrane resting potential either toward lower (depolarization) or higher (hyperpolarization) magnitudes of membrane polarization. Figure

3.3 Mechanisms of Generating an Action Potential First, it is important to realize that an action potential emerges because of the dependence of membrane permeability for certain ions upon the membrane potential. Let us consider an example (figure 3.8). There is only one ion that can move through special channels in a membrane. Each channel is being guarded by a demon who sometimes falls asleep. The probability of the demon falling asleep depends on membrane potential so that, at rest, all the demons are awake and do not let the ions cross the membrane. We can apply short-lasting pulses of stimulation to change the membrane potential. A depolarizing pulse puts some of the demons to sleep so that some ions can cross the membrane. The more demons that are asleep, the bigger is the current created by the ions. Note, however, that the current itself will change the membrane potential.

nonscientific illustration. A demon is guarding each channel for Na+ in the membrane. Membrane depolarization makes some of the demons fall asleep, so that their channels become open. Ions will cross the membrane and will increase the depolarization, putting more demons to sleep. Figure 3.8    A

Now, we have two major possibilities: 1. The current hyperpolarizes the membrane and, therefore, wakes up some of the demons, who quickly start closing the gates and restoring the resting potential. 2. The current further depolarizes the membrane (i.e., works in the same direction as the stimulus). Then, the current puts to sleep more demons, thus opening more channels, thus increasing the current, thus putting to sleep more demons, thus … and so on. The process described in the second example is called positive feedback (figure 3.9), while the first possibility corresponds to negative feedback. Apparently, systems with positive feedback are capable of generating large signals very quickly, while systems with negative feedback generally tend to bring any “perturbing” signal down to zero.

A very similar mechanism gives rise to the “all or none” signal that emerges on the membrane when it is excited to the threshold: depolarization increases membrane permeability to a certain ion, while increased permeability induces membrane current that increases depolarization.

Figure 3.9    A

positive feedback process where (a) leads to a rapid amplification of the effect, while a negative feedback process (b) quickly restores the original state.

One can study the mechanisms involved in the process of generating an action potential with the voltage clamp technique. This technique is used to keep membrane potential at a certain level with the help of external electronics, which add electrical charges to or remove them from the membrane, thus keeping the potential constant (like a thermostat keeping room temperature constant by adding or removing heat). These conditions do not allow the positive feedback mechanism to generate an action potential, but they allow the experimenter to study the dependence of conductance in specialized ion channels upon membrane potential.

constant depolarization is applied to the membrane. Note that Na+ conductance (gNa) turns on and off while K+ conductance (gK) changes slowly and stays at a new level. Note also that higher stimuli lead to higher values of gNa achieved over shorter times. Figure 3.10    A

Figure 3.10 shows the dependence of the sodium conductance (gNa) upon voltage after a depolarizing voltage step is applied to the membrane. Note that gNa turns off spontaneously—that is, it goes down to its original, very low value without an obvious additional external stimulus, even when the membrane voltage is kept constant artificially (shown by the “Stim” line in figure 3.10). At higher stimulation voltages, peak values of gNa are much higher, they are reached more quickly, and gNa drops faster. Note also that the time it takes gNa to reach peak value is shorter for larger stimuli while for gK it is almost unchanged. When the conductance for both major ions, Na+ and K+, is increased, one can say that all the channels are open, the sodium–potassium pump becomes functionally disabled, and

membrane potential changes are primarily defined by ion movement through the open channels. If you turn the voltage off and let the membrane potential return to its resting value, gNa gets down close to zero if it is not zero already. There is an important phenomenon of channel inactivation, which means that after a spontaneous turn-off, gNa cannot be increased immediately even if you apply a very strong voltage (figure 3.11). It needs some time to recover. When the conductance cannot be increased by any external voltage, the membrane is said to be in an absolute refractory period. When you need higher than usual voltage to increase the conductance, but you can do it, the nerve is said to be in a relative refractory period.

Figure 3.11    After

a stimulus (St1) leading to an increase in gNa, another stimulus is less able to turn it on for some time. For a short period of time this inactivation is absolute—that is, gNa will not respond even to a very strong stimulus (St2, absolute refractory period). Then, a stronger-than-usual stimulus can turn gNa on (St3, relative refractory period).

So, the channels can close in response to a change of membrane potential and also spontaneously, when they require some time to recover. In the first case, you can open the channels with an external depolarizing stimulus; in the second case, the only available method is to wait. Figure 3.10 also shows the dependence of potassium conductance (gK) on membrane potential. Note that gK starts to increase with depolarization but does not turn off spontaneously. It goes down to its original value only when the membrane potential returns to its resting level. This means that there is no channel inactivation, and no refractory period for potassium channels. Note also that gK increases more slowly than gNa, which means that early in the process of membrane depolarization, the open sodium channels will play a bigger role. As can be seen from the figures already shown, both gNa and gK behave “smoothly” with membrane voltage (i.e., they do not show any threshold effects). In order to understand the mechanisms giving rise to the all-or-none action potential, we need to remove the voltage clamp and allow the potential to change. Note that opening channels for sodium and for potassium leads to different consequences for the membrane potential because of the difference in the concentrations of Na+ and K+ ions inside and outside the cell. An increase in gK, for example, induced by a short depolarizing pulse, leads to a flow of K+ out of the cell. The loss of positive ions leads to a drop in the membrane potential (remember, membrane potential is measured inside the cell with respect to the outside!)—that is, to a decrease in depolarization or to hyperpolarization. This, in turn, will lead to a drop in gK. So we have a system with a negative feedback that will quickly restore the original resting potential. An increase in gNa, however, will lead to an inflow of Na+ inside the cell (i.e., to further depolarization). Here we deal with a system with a positive feedback which, as is well known, loves to go berserk. Different dependencies of gNa and gK on membrane potential, together with the property of sodium channels to inactivate, lead to the generation of the action potential.

Remember that the direction of flow of an ion depends on its equilibrium potential such that the difference between actual membrane potential and the equilibrium potential of an ion defines the direction in which the ion will flow. On the other hand, an ion with a higher permeability plays a bigger role in defining the overall membrane potential than ions with smaller permeabilities. This means that changes in gNa and gK can lead to changes in the resting membrane potential. Figure 3.12 shows an action potential and the changes in gNa and gK in different phases of the potential. The sequence of the events is as follows: 1. The initial depolarization (created by an external stimulus) increases gNa so that the membrane potential tries to reach sodium equilibrium potential. 2. The sodium channels are quickly inactivated, leading to a drop in gNa; as a result, the membrane potential has no time to reach the sodium equilibrium potential. 3. After a brief delay, gK increases and draws membrane potential to its equilibrium potential (i.e., repolarizes the membrane). 4. There is a rather long period of hyperpolarization (the afterpotential) after which membrane potential returns to its resting value.

in Na+ and K+ conductance during an action potential. Note that the peak of the action potential is positive, and after the action potential the membrane remains hyperpolarized for some time. Figure 3.12    Changes

PROBLEM 3.5 Why does the membrane potential drop below the resting level? Can you imagine a situation in which the afterpotential would be higher than the resting potential? Neurons within the central nervous system can exhibit a variety of electrophysiological properties reflected in different shapes and features of their action potentials (figure 3.12). For example, the large Purkinje cells in the cerebellum can generate very high frequency trains of action potentials (over 200 Hz) interrupted by effects from Ca++ channels. These cells can also generate unusual, long-lasting action potentials (complex spikes) discussed later in the chapter on the cerebellum. Broad action potentials at lower frequencies can be seen in other neurons in the brain due to an interaction among conductance changes for Ca++, Na+, and K+. Many neurons in the central nervous system can generate rhythmic bursts

—clusters of action potentials at a very high frequency within each cluster. Until now, we have only discussed transient, relatively shortlasting ion currents through the membrane. There are also longerlasting, persistent ion currents. In particular, persistent Na+ currents can be seen in response to relatively low levels of membrane depolarization, below the level needed for the generation of an action potential. These currents can help the membrane to generate an action potential in response to relatively small depolarizing stimuli. They can also contribute to the plateau potentials—relatively long-lasting (up to a few seconds) membrane depolarization. Persistent Ca++-dependent currents can be seen in relatively thin neural fibers—dendrites. These will be discussed later in more detail.

CHAPTER 3 IN A NUTSHELL The action potential is the unit of information bodies

of

transmission higher

within

animals.

the

Membrane

potential is created by a small number of unbalanced ions. Movement of ions through the membrane occurs at special sites called ion channels. An active molecular

mechanism,

potassium

pump,

difference

in

the

a

sodium–

maintains concentrations

the of

sodium and potassium ions across the membrane. The dependence of the sodium ions’

conductance

on

the

membrane

potential leads to the generation of an

action

potential

when

membrane

depolarization reaches its threshold. After

an

membrane state

of

action stays

in

potential, a

insensitivity

the

short-lasting due

to

inactivation of sodium channels.

the

Chapter 4 Information Conduction and Transmission KEY TERMS AND TOPICS conduction of action potentials neuron myelinated and nonmyelinated axons information transmission in the central nervous system synapse synaptic transmission neurotransmitters persistent inward currents temporal and spatial summation As mentioned earlier, the action potential is probably the most important process or event in our body because it is used for information transmission over considerable distances within the neuromuscular system. An important feature of the action potential is its propagation—that is, an action potential never stays at one place; it travels along nerve or muscular fibers. One of the main

characteristics of action potential propagation is its velocity. Since an action potential is a process, a time function measuring its velocity requires identification of a well-defined point on the action potential curve (e.g., the time of its peak) and a measure of the time interval from the moment when this point occurs at one location to the moment when it occurs at another location: ΔT = T2 − T1. If a researcher stimulates a neural fiber with an electrical stimulator at a certain point, an action potential may occur at this point. The membrane potential recorded further down the nerve fiber will show a similar time function—that is, a similar action potential that will occur, however, at a time delay after the first one (figure 4.1). If one knows the distance between the two points (ΔS), the average velocity of transmission (V) can be computed as:

Figure 4.1    Action

potential travels along a neural fiber. For calculation of the velocity of its propagation (V), the action potential has to be recorded at different times (t1 and t2) at different coordinates (s1 and s2).

PROBLEM 4.1 If a neural fiber is stimulated strongly at some point in the middle, in what direction will the action potential propagate?

4.1 Conduction of an Action Potential When an action potential occurs in a certain segment of a cellular membrane, it sets up local current circuits that flow to the neighboring segments largely according to Ohm’s law (i.e., without any help from pumps, channels, and other sophisticated mechanisms). The charge leaks through the membrane capacitance according to equation 3.1 in chapter 3. Figure 4.2 shows schematically a simplified electrical system of a membrane and the currents that flow within this system. The local currents depolarize the membrane and, if the depolarization is strong enough, another action potential(s) can occur. So, strictly speaking, the action potential does not travel along a membrane of a neural fiber but rather emerges at different spots and disappears, giving rise to new potentials. However, since all the potentials look alike (because of the all-or-none law), the process looks as if one potential were traveling along the fiber.

Figure 4.2    A

simple electrical scheme of a membrane and the direction of local currents (shown by arrows).

Two factors are very important for the process of propagation of the action potential: 1. inactivation of sodium channels leading to the absolute refractory period within an area of the membrane just after an action potential, and 2. different densities of sodium channels at different sections of the membrane. The first factor does not allow an action potential to “backfire” during its natural propagation along a fiber. That is, if an action potential appears at point 1 in figure 4.3 at time t1 and then disappears, giving rise to an action potential at a neighboring point 2 at t2, the membrane at point 1 stays refractory for some time and cannot be excited by local currents created by the second action potential. So, the second action potential at point 2 can excite the membrane at point 3 but not back at point 1.

Figure 4.3    The

phenomenon of inactivation of sodium channels does not allow an action potential to “backfire.” If an action potential comes to point 2 from point 1, it cannot go back; it travels only forward to point 3.

PROBLEM 4.2 What would happen in response to a single strong stimulus applied to the membrane of a long neural fiber if there were no sodium inactivation mechanism? The second factor makes some areas of the membrane more readily excitable and, therefore, favors the generation of an action potential in those particular areas. The process of generation of a single action potential is brief, but nevertheless it takes time on the order of 1 ms, while local currents spread almost instantaneously. Let us consider two neural fibers. An action potential has just emerged in both at point A in figure 4.4. The local currents generated by the action potential spread in the surrounding tissue and decrease very quickly with distance from point A. However, the current spreads more easily, and decreases at larger distances, in thick fibers as compared to thin fibers. So the next most distant action potential will be generated in fiber 1 at point B and in fiber 2 at point C. Note that it will take the same time for the potential to jump over distance (B–A) in fiber 1 and (C–A) in fiber B. We have come to the conclusion that thick fibers conduct action potentials at higher velocities. Although action potentials typically have the same shape, their width can change under certain special circumstances. Wider action potentials induce larger local currents and can bring more distant

areas of the membrane to its threshold. Figure 4.5 illustrates the dependence between the pulse’s duration and the strength it needs to just reach the threshold at a certain point on a membrane and between pulse duration and maximal distance at which membrane potential can reach the threshold for a constant amplitude of the pulse. Note that there is a value in the strength of a stimulus (rheobase) below which an increase in the duration is unable to induce an action potential.

Figure 4.4    Action

potentials emerge simultaneously at point A in fibers 1 and 2. Local currents decrease with distance more slowly in the thicker fiber 2. Thus, they will bring the membrane to the threshold at a more distant point. So the next action potential will emerge at the same time at point B in fiber 1 and at point C in fiber 2. Hence, the speed of conduction is higher in the thicker fiber.

dependence between stimulus duration and the amplitude needed to just reach the threshold of a membrane. Figure

4.5    The

4.2 Myelinated Fibers Some neural fibers, particularly the thicker ones, are covered with a sheath made of myelin that is built of specialized, nonneuronal Schwann cells. Schwann cells wrap around such neural fibers in several layers, forming the myelin sheath. The sheath has breaks that are called Ranvier nodes (figure 4.6). This design allows the action potential to travel at much higher speeds. There are two important features of myelinated fibers. First, myelin sheath increases the distance at which local currents from an action potential are able to reach the threshold of membrane depolarization for the generation of another action potential. Second, the sodium channels are concentrated in Ranvier nodes so that their density there is much higher than average, and their density under the myelin sheath is much lower than average. As a result, if an action potential occurs at a Ranvier node, it gives rise to local currents that bring the membrane to the threshold at the neighboring node, and the action potential kind of jumps from one node to another. This phenomenon is addressed as saltatory conduction, which is characterized by a considerable increase in conduction velocity. Thicker fibers have larger intervals between neighboring Ranvier

nodes, and therefore, they conduct action potentials at higher velocities. Actually, there is a very simple equation relating the diameter of a myelinated fiber and the conduction velocity of action potential: where V is velocity in m/s and d is fiber diameter in microns. Note that this equation is not applicable to nonmyelinated fibers.

Figure 4.6    A

myelinated fiber is enclosed in a sheath made of nonneural cells (glial cells). The myelin sheath has breaks (Ranvier nodes) where action potentials are generated.

PROBLEM 4.3 What will happen if a myelinated fiber suddenly loses its sheath? What can you expect from such a fiber in a hot bath and in a cold bath? Note that ion diffusion proceeds much more quickly at high temperatures.

Table 4.1 compares the velocities of different processes. Note that speeds of conduction in our body are rather high, but not extremely high. Certainly, they are not comparable to the speed of light, which is equal to the speed of propagation of an electromagnetic field. Table 4.1    Characteristic Velocities of Different Processes Process

Velocity (m/s)

Slow nerve conduction

0.5

Sprinting (humans)

10

Driving at 90 km/h (65 mph)

25

Fast nerve conduction

120

Sound traveling in air

330

Light (electromagnetic field)

300,000,000

PROBLEM 4.4 The nature of an action potential is electric. Why is the speed of its propagation so much lower that the speed of electric events like electric current?

PROBLEM 4.5 The speed of neural conduction is comparable to the highest movement velocities observed in athletes. Does this mean that there is an upper limit for movement velocity set by action potential conduction speed? Knowing the speeds of conduction is very important for understanding the characteristics of many neurophysiological processes that include conduction of information from one place to another within our bodies. In some situations, these conduction delays dominate in the total time delay between a stimulus and a response—for example, in the case of spinal reflexes described in a later chapter. In other situations—for example, when a person is

asked to perform a simple action (e.g., press a button) as quickly as possible following a signal—conduction delays contribute significantly to the reaction time, although they may not dominate it. We are going to encounter a few classifications in this textbook. One of the most helpful and commonly used is the classification of neural fibers according to their diameter and function, sensory versus motor, or, using a different pair of terms accepted in neurophysiology, afferent versus efferent. It was suggested by a great physiologist, David Lloyd, and is illustrated in table 4.2.

4.3 Structure of a Neuron Before moving further, we need to introduce certain basic notions related to the structure of a single neural cell (a neuron). Figure 4.7 shows an illustration of a “typical neuron”; the quotation marks reflect the fact that many neurons within the human body look significantly different from this cartoon. The neuron consists of three major parts: soma, axon, and dendrites. The soma, or body of the neuron, contains the nucleus (or several nuclei) and other important small structures (organelles). Mitochondria are major storage places and sources for the release of molecules whose chemical transformations generate energy for the processes inside the cell, in particular for the sodium–potassium pump. Table 4.2    Types of Neural Fibers (Axons) and Conduction Speeds of Action Potentials Type

Innervated

Fiber diameter

Conduction

structure

(microns)

velocity (m/s)

Afferent or sensory muscle nerves* Ia

Muscle spindle,

(Aα)

primary endings

Ib

Golgi tendon organ

(Aα)

13-20

80-120

13-20

80-120

Innervated

Fiber diameter

Conduction

Type

structure

(microns)

velocity (m/s)

II

Muscle spindle,

6-12

40-80

(Aβ)

secondary endings

III

Muscle deep pressure

1-5

5-30

(Aδ)

endings

IV (C)

Nociceptors (pain)

0.2-1.5

0.5-2

Efferent or motor nerves Aα

Skeletal muscles

18

100

Aβ

Muscles and spindles

8

50

Aγ

Muscle spindle

5

20

*Classifications for cutaneous nerves are shown in parentheses.

Figure 4.7    A

neuron schematic.

The axon is typically a long, rather thick branch that carries the output signals generated by the cell. At its end, the axon splits into a whole bunch of smaller, thin branches (terminal branches) that make contacts with other cells and transduce information to these cells. These branches are commonly much shorter than the main part of

the axon. Axons can be very long, up to 1 meter, as in the case of the axon of a motoneuron with its soma located in the spinal cord that sends signals to a muscle in a foot. There are long axons of neurons within the central nervous system as well, including axons of neurons in the cortex of the large hemispheres that send their signals to neurons in the lower parts of the spinal cord. The place where the axon exits the soma is called the axon hillock. At this place, the density of sodium channels is very high, and so this is the place where action potentials are typically being generated. The axons of groups of neural cells, typically united by a functional or anatomical feature, commonly run together over relatively large distances. In such cases, the groups of axons are addressed as neural tracts (if they travel from one place to another within the central nervous system) or as nerves (if they connect the central nervous system with peripheral structures such as muscles and sensory organs). Dendrites form a tree around the soma and serve as sites of inputs into the cell. Terminal branches of the axons of other cells make connections (synapses) on the dendrites as well as on the soma itself. To summarize, dendrites and soma serve as sites where information comes to the neuron from other neurons and is integrated (assessed, compared, and put together); the axon hillock is the place where action potentials are generated in response to the incoming information, and the axon serves to conduct action potentials to distant places and to transmit information to other cells. Dendrites’ properties have attracted much attention in relation to the ability of the dendrite membranes to show steady depolarization. In other words, dendrites have been shown both theoretically (Gutman 1991) and experimentally (Schwindt and Crill 1977, 1981; Heckman et al. 2003, 2005) to have long-lasting changes in the membrane potential induced by persistent inward currents. A persistent inward current is a depolarizing current produced by voltage-sensitive channels that do not show the phenomenon of inactivation (this is why they can be long-lasting or persistent). These channels on dendrites are specialized for Ca++ ions. Effectively,

persistent inward currents may be seen as the means of reducing the threshold for action potential generation and, hence, reducing the distance from the membrane resting potential to this threshold. So these currents seem to facilitate the process of generating action potentials. On the other hand, persistent inward currents tend to sharply limit the efficacy of additional synaptic inputs into the neuron, so their overall effects on the excitability of the neuron may not be easily predictable. Figure 4.8 illustrates the dependence between the voltage and current over a membrane in the absence of persistent inward currents (thin dashed curve) and when these currents are present (thick solid curve). Note that when the current is zero, the membrane, by definition, is at its resting potential. The thin line shows only one value of the membrane potential when the current is zero (i.e., only one value of the resting potential). The thick line shows three crossings of the abscissa axis. The first and third crossings are stable, while the intermediate one is not. An amazing feature of the second resting potential (point 3 in figure 4.8) is that it can be above the threshold for the generation of an action potential. If the resting potential of a dendrite membrane is at that second state, the dendrite starts generating action potentials and would continue doing so without any external stimuli as long as the membrane potential stays above the threshold value and the neuron does not run out of energy. We will discuss the implications of this phenomenon for voluntary movements in later chapters.

characteristics of a dendrite membrane in the absence (thin lines) and in the presence (thick lines) of persistent inward currents (PIC). In the second case, potentially there may be two stable values of the membrane potential (points 1 and 3). Point 3 may be over the membrane threshold for the generation of action potentials. Figure

4.8    Current–voltage

4.4 Information Coding in the Nervous System Because of the all-or-none law, individual neurons can only generate single action potentials of a relatively constant duration and amplitude. Thus, an action potential by itself transmits only limited amounts of information: It either occurs or it does not occur at any point in time. The only way a neuron can encode significant amounts of information is by generating sequences of action potentials. In other words, information is encoded by changing the frequency of firing. Note that here we talk about instantaneous frequency of neuronal firing—that is, an inverse of the time interval between two successive action potentials:

where T2 and T1 are times of occurrence of two successive action potentials. Intervals between successive action potentials fluctuate all the time, even if the apparent input to the neuron stays constant. So, neurons never fire at a constant frequency, and they should be characterized either by instantaneous frequency or by average frequency of firing over some time period. As mentioned earlier, some neurons can demonstrate bursts of action potentials at a relatively high frequency separated by intervals of silence; in such cases, one number is apparently not enough to describe the behavior. This type of information transmission is called frequency coding or frequency modulation. However, if one considers groups of neurons, frequency coding loses its exclusive right as the only method of information transmission in the central nervous system because of possible changes in the number of neurons within the group that is generating action potentials within any time interval. Hence, frequency modulation is supplemented with amplitude (or magnitude) modulation. The ability of neurons to integrate incoming information (see the discussion of spatial and temporal summation in section 4.7) allows them to take into account both the timing of incoming action potentials and their number. So, the firing rate (instantaneous frequency of firing) of a neuron depends on both the frequency and the magnitude of its input.

4.5 Synaptic Transmission A very important feature of neurons is the ability both to conduct information from one place to another and to transmit it to other cells. In this textbook, we focus primarily on synaptic transmission that does not involve electrical contact between the membranes of two cells. Electrical transmission via a mechanism addressed as ephaptic was demonstrated in the brains of vertebrates (Bennett et al. 1959), including mammals (Baker and Llinas 1971; Korn et al. 1973). In contrast to the more typical synaptic transmission involving neuromediators, such electrotonic synapses (sometimes called

ephapses) are primarily excitatory, can transmit signals in both directions (from cell A to cell B and from cell B to cell A), and are less able to show plastic changes. More typically, transmission of information from one cell to another occurs at specialized sites of the membranes of the two cells and do not involve direct contact. At these sites, the membranes come very close to each other and form synapses. A synapse consists of three major components: presynaptic membrane, postsynaptic membrane, and synaptic cleft (figure 4.9). The presynaptic membrane belongs to the cell that transmits information (coded as a sequence of action potentials), while the postsynaptic membrane belongs to the cell that receives the information.

Figure 4.9    A

synapse consists of a presynaptic membrane, a synaptic cleft, and a postsynaptic membrane. An action potential in the presynaptic fiber makes synaptic vesicles move to the membrane, fuse with it, and release molecules of a neurotransmitter into the cleft. The neurotransmitter acts at the postsynaptic membrane and changes its potential.

There are two major groups of synapses, obligatory and nonobligatory. If an action potential on the presynaptic membrane always gives rise to an action potential on the postsynaptic membrane, such a synapse is called obligatory. Typical examples of obligatory synapses are those between neural cells and muscle cells. Non-obligatory synapses are much more common within the central nervous system: A single action potential on the presynaptic membrane is typically unable to induce an action potential on the postsynaptic membrane. Neuron-to-neuron synaptic transmission uses various chemical substances called neurotransmitters or synaptic mediators. Neurotransmitters are normally synthesized by the presynaptic neuron and stored in special reservoirs (vesicles) close to the presynaptic membrane. The typical scheme of synaptic transmission is as follows (figure 4.9): 1. An action potential arrives to the presynaptic membrane. 2. It induces chemical changes in the membrane properties (with an important role played by Ca++ ions), which lead to movement of vesicles with a neurotransmitter to the presynaptic membrane, their fusion with the membrane, and release of the neurotransmitter molecules into the synaptic cleft. This process is called exocytosis. 3. The molecules of the neurotransmitter travel across the synaptic cleft (its typical width is on the order of 100 nm) by passive diffusion. 4. These molecules act at special sites (receptors) on the postsynaptic membrane and change its potential. 5. These molecules are quickly removed from the synaptic cleft by a special chemical substance (an enzyme) or are taken back into the presynaptic membrane and recycled. Molecules of neurotransmitter bind to receptor sites on the postsynaptic membrane and induce one of two basic effects: They can depolarize the membrane or they can hyperpolarize it (figure 4.10). In the first case, a depolarizing potential will appear that is

called an excitatory postsynaptic potential (EPSP). In the second case, a hyperpolarizing potential will emerge that is called an inhibitory postsynaptic potential (IPSP). The peak magnitude of EPSPs and IPSPs is relatively small in neuro-neural synapses and can be very large (up to several tens of millivolts) in neuromuscular synapses. In response to a single presynaptic action potential, postsynaptic potentials last for about 15 ms and then disappear. When a number of action potentials come to presynaptic membranes that make synapses with the same postsynaptic membrane, the balance of EPSPs and IPSPs on the postsynaptic membrane will define whether the potential reaches the threshold and whether an action potential is generated.

Figure 4.10    A

presynaptic action potential can induce either a depolarization or a hyperpolarization of the postsynaptic membrane. These effects are called EPSP and IPSP, respectively.

Note that typical synapses transmit signals in one direction only, in particular because there are no vesicles with neurotransmitters in the postsynaptic membrane and no receptors sensitive to neurotransmitters on the presynaptic membrane. The efficacy of neuro-neural synapses can be modified by previous activity of the presynaptic neuron, which leads to plasticity and activity-dependent changes in neural transmission—a very important mechanism for memory and learning.

4.6 Neurotransmitters Neurotransmitter release is quantal in nature. It can happen spontaneously, leading to small, stereotypical potentials on the postsynaptic membrane called miniature excitatory or inhibitory postsynaptic potentials (MPSPs). There are three major groups of neurotransmitters: amino acids, biogenic amines, and neuropeptides. Amino acids are building blocks for all proteins and are very common in our bodies, in the nervous system in particular. Not all amino acids act as neurotransmitters. One of the most frequently encountered neurotransmitters is gamma-aminobutyric acid (GABA). It can be found in a significant proportion of all the synapses (about 25% to 40%). Among dominant excitatory neurotransmitters let us mention glutamic acid and leucine. They depolarize the postsynaptic membrane and thus bring it closer to the threshold for the generation of an action potential. Glycine is an inhibitory mediator found, in particular, in the spinal cord. Biogenic amines are found in smaller quantities than amino acids. There are several biogenic amines whose role as neurotransmitters is particularly important. These are acetylcholine, serotonin, dopamine, and norepinephrine. Their action on the postsynaptic membrane is not as unambiguous as that of GABA and glutamic acid. In particular, acetylcholine commonly exerts inhibitory effects on postsynaptic neurons within the central nervous system, but it is also the most important excitatory mediator in the transmission of signals from neurons to muscle fibers. The phenomenon of persistent inward currents mentioned in an earlier section involves complex intracellular mechanisms. It can be put into action by several neurotransmitters, including serotonin and norepinephrine. Neuropeptides were viewed as occurring only in small quantities within the central nervous system and therefore were overlooked for many years. They generally modulate the synaptic efficacy of other neurotransmitters. Typical examples are endorphins and enkephalins that act at specific receptor sites that can also be taken by certain

drugs, such as opiates. One of the widely encountered neuropeptides is neurotensin, which has been linked to burst-like activity in neurons using other neurotransmitters, such as dopamine.

4.7 Temporal and Spatial Summation It has already been mentioned that neuron-neuronal synapses are mostly non-obligatory. This means that one presynaptic action potential cannot force the postsynaptic membrane to generate an action potential. Such stimuli are called subthreshold. So, in order to generate an action potential, the postsynaptic membrane must somehow sum up the effects of a number of presynaptic signals. There are two basic ways of doing this. The first way is based on the fact that postsynaptic excitatory potentials (EPSPs) are of a relatively long duration (about 15 ms). So, if another action potential comes to the same synapse at a delay smaller than the typical duration of the EPSP, its postsynaptic effects will superimpose on the effects on the previous signal and lead to a larger EPSP (figure 4.11). This mechanism is called temporal summation. A sequence of presynaptic action potentials may be able to bring the postsynaptic potential to the membrane threshold when a single potential is unable to do this.

Figure 4.11    Temporal

summation occurs when several action potentials arrive at a presynaptic membrane at intervals that do not allow individual EPSPs to disappear. Their effects can sum up and induce an action potential.

PROBLEM 4.6 What is the minimum frequency of presynaptic action potentials that can theoretically lead to temporal summation and to a postsynaptic action potential? Another mechanism is based on the fact that a postsynaptic membrane can receive many presynaptic inputs located close to each other and on the existence of local currents through the membrane and in the surrounding media. When a presynaptic action potential induces a subthreshold EPSP (figure 4.12), membrane depolarizes in an area that is in direct contact with the neurotransmitters released by the presynaptic membrane. Local currents spread this depolarization to neighboring areas of the postsynaptic membrane, certainly with a quick decrement in its amplitude. So, if other synapses are located nearby (synapses 2 and 3 in figure 4.12), the postsynaptic membrane may “feel” the effects of the local currents from all three synapses. If three action potentials

come simultaneously to the three synapses, the depolarization of the postsynaptic membrane in all three synapses will be bigger than that which occurs in response to only its own action potential. This effect is called spatial summation.

Figure 4.12    Spatial

summation occurs when several action potentials AP1, AP2, and AP3 arrive simultaneously at different synapses on the same presynaptic membrane so that their individual EPSPs sum up and can induce an action potential. The insert drawing shows possible locations of the three synapses on the target neuron.

PROBLEM 4.7 What will happen if action potentials to synapses 1, 2, and 3 come not simultaneously but at a delay? The mechanisms of temporal and spatial summation are examples of how postsynaptic membrane can integrate information coming from presynaptic cells. They make it possible to transfer signals through non-obligatory synapses.

PROBLEM 4.8 Imagine that two groups of neurons (A and B) send their signals to another group of neurons (C). Action potentials generated simultaneously by all the neurons of group A lead to a response C1 (the number of activated neurons in group C); action potentials generated simultaneously by all the neurons of group B lead to a response C2. What can be the magnitude of the response to action potentials in all the neurons in both groups A and B? Can it be bigger than, smaller than, or equal to (C1 + C2)? Why?

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Chapter 5 Skeletal Muscle KEY TERMS AND TOPICS skeletal muscle myofibril neuromuscular synapse excitation–contraction coupling twitch and tetanic contractions elements of mechanics length and velocity dependence of muscle force external regimes of muscle contraction Skeletal muscle is a machine (a “motor”) that converts chemical energy to mechanical work and heat. It is probably the most amazing motor known to humans. Its ability to quickly generate power is superior to virtually any human-designed motor of approximately the same size. It has numerous features that may seem weird to an external observer. These include relative slowness of force generation, its dependence on muscle length and velocity, and a few others reviewed later. Some of them look rather suboptimal or even bizarre. There are two ways to look at these unique features. The first is to ask oneself: How does the central nervous system cope

with (or compensate for) all the “weirdness” of muscle design, its nonlinearities (you will learn what these are), time delays, and other features that seem terrible when they are viewed through the eyes of a 21st century engineer? The alternative is to ask oneself: How are the unusual features of skeletal muscle used by the central nervous system to produce the unique properties of human movements that make them far superior to any robot? These properties include, in particular, flexibility, dynamic stability, and the ability to handle fragile objects. As suggested in chapter 1, we will look at skeletal muscle optimistically—as a unique design developed by evolution, and not as a blunder of nature. When people talk about muscles, they sometimes mean different things. For example, when a person flexes the knee, it is commonly said that the quadriceps muscle is being stretched. In this case, the word “muscle” is used to imply the whole complex of structures that includes muscle fibers, tendons, and ligaments. However, depending on a number of factors, the muscle–tendon complex may be stretching while the muscle fibers are shortening. This can happen, in particular, when the muscle generates active force while being elongated by an external force (eccentric contraction; see later discussion)—for example, by the force of gravity while landing after a jump. In the example of the quadriceps, it is also implied that the four anatomically distinct muscles behave in a qualitatively similar way. Some muscles have less obvious separation into portions (called compartments) that have different actions and show a degree of mechanical and physiological independence (Jeneson et al. 1990; Danion et al. 2003a). Typical examples are the extrinsic finger flexors: flexor digitorum profundus and flexor digitorum superficialis. These muscles have single proximal tendons and four distal tendons directed at their points of attachment at the four fingers. Their mechanical behavior is rather complex due to the transmission of forces across the compartments. In this chapter, we will first discuss the “naked muscle”—that is, the properties of muscle fibers irrespective of the way in which the force generated by the processes in muscle fibers is being

transferred by tendons to create torques in joints. The role of tendons will be considered at the end of the chapter.

5.1 Skeletal Muscle Structure Whole muscle is composed of parallel fibers (muscle cells or myofibrils). Each fiber is a rather large cell; the fibers may be several centimeters long and from 10 to 100 μm in diameter. Muscle fiber, like any cell, has a membrane (sarcolemma), inside which there is sarcoplasma containing myofilaments and sarcoplasmic reticulum. The structure of a muscle fiber is shown in figure 5.1. The sarcolemma has many invaginations that are called T-tubules. They plunge deeply into the interior of the fiber, thus increasing the surface area by a factor of 3 to 10. T-tubules come very close to cisternae in the sarcoplasmic reticulum. The gap there is very narrow, about 300 Å (i.e., even smaller than the typical synaptic cleft).

Figure 5.1    (a)

The structure of a muscle fiber. (b) A schematic representation of a cross-section of a fiber.

A major role in the mechanism of muscle contraction is played by Ca++ ions. We have already mentioned major physiological roles for Ca++ in the persistent inward currents through dendritic membranes and in synaptic transmission; the same ion is vital for proper muscle functioning. At rest, ion pumps pump Ca++ ions from sarcoplasma into the sarcoplasmic reticulum (similar to the sodium–potassium pump). This process, similar to other ion pumps, involves specialized macromolecules and requires energy. Sarcoplasmic reticulum contains a special protein that binds Ca++ and does not let it escape. As a result, the concentration of Ca++ in sarcoplasma is very low

(less than 10-7 M). We will examine the role of calcium in muscle contraction in the next section.

5.2 Myofilaments Myofilaments are major force-producing elements of muscle cells, consisting of two major molecules, myosin and actin (figure 5.2). Thick filaments contain mostly myosin, while thin filaments contain mostly actin. Actually, thin fibers contain two actin molecules that form a structure that looks like a double helix (resembling the famous DNA structure). In order to develop force, the two sets of filaments, actin and myosin, must make connections to each other. These connections are called cross-bridges. Actin and myosin filaments are organized so that regularly arrayed myosin filaments are surrounded by six actin filaments (like a kitchen floor mosaic), while each actin molecule is in contact with three molecules of myosin. At one end, actin filaments are attached to a structure called a Z-line. Two sets of actin filaments and one set of myosin filaments between two Z-lines constitute a sarcomere. Sarcomeres are the most important functional units of myofibrils in the production of muscle force. In order to characterize the state of a myofibril, two more terms are used: The length of the myosin filaments within a sarcomere is called the A-band, while the length of actin filaments that do not overlap with myosin filaments is called the I-band. These bands are clearly seen under a strong microscope as alternating dark (A-band) and light (I-band) zones (figure 5.2).

Figure 5.2    The

structure of a myofibril. The lower figure shows the sequence of dark and light bands (A-bands and I-bands). The upper drawing shows the typical configuration of actin and myosin molecules within a myofibril.

There are several more important protein molecules that play major roles in the mechanism of muscle contraction. The first is tropomyosin. Its long molecules lie along the actin molecules in thin filaments (figure 5.3). Another important molecule is troponin. Troponin molecules are attached at regular intervals to tropomyosin molecules, forming a complex that can change its configuration under the action of calcium ions. These changes play an important role in the formation of cross-bridges, which are the units of active muscle contraction (see later discussion). There is a third filament system inside the myofibrils that acts in parallel to the actin–myosin complex. This system has elastic properties. A major macromolecule forming this system is titin. Studies of titin have suggested its major role not only in defining the elastic properties of muscle fibers at rest but also during active muscle contractions (Granzier and Labeit 2004, 2005).

Figure 5.3    The

structure of the thin filament (actin). Note long tropomyosin molecules in parallel with the actin strands. Troponin attaches to tropomyosin at regular intervals.

synapse. A presynaptic nerve action potential induces the movement of vesicles with acetylcholine (ACh) to the presynaptic membrane, their fusion, and the release of ACh into the cleft. ACh diffuses to the postsynaptic muscle membrane, depolarizes it, and induces an action potential. Remaining ACh molecules are either re-uptaken into the presynaptic membrane or removed by an enzyme, acetylcholinesterase. Figure

5.4    Neuromuscular

5.3 Neuromuscular Synapse The neuromuscular synapse (or neuromuscular junction) is a region of contact between a single presynaptic nerve fiber (recollect that an axon branches, giving rise to many presynaptic fibers) and a muscle fiber. These two fibers come very close to each other so that the synaptic cleft is only about 500 Å wide, but they do not make direct contact (figure 5.4). The presynaptic axonal membrane has active zones that contain many synaptic vesicles with a neurotransmitter (acetylcholine) and also a high concentration of mitochondria that store and supply molecules that are metabolized to get energy. When a decision is made by the central nervous system to induce a muscular contraction, signals eventually go to neurons—known as α-motoneurons—in the spinal cord (or in the brainstem, for head and neck muscles) that send their long axons to appropriate muscles or, in other words, innervate muscles. Action potentials travel at a high speed along these thick efferent fibers and arrive at the point of branching. There, the action potential excites each of the branches, so that each of them delivers an action potential to the presynaptic membrane at about the same time. Neuromuscular synapses are obligatory—that is, a presynaptic action potential always induces a postsynaptic action potential and initiates the process of muscle contraction. This is achieved by an amplification of the incoming signal with chemical mechanisms. Let us consider the most important steps involved in this process: Step 1: An action potential arrives at the presynaptic membrane and opens voltage-dependent Ca++ channels. Normally, the intracellular concentration of Ca++ is very low. However, after an action potential arrives, the concentration of Ca++ increases dramatically (by a factor of 20). Intracellular Ca++ activates processes leading to movement of synaptic vesicles to the presynaptic membrane. The vesicles fuse with the membrane and let their contents out, into the synaptic cleft (exocytosis).

Step 2: The neurotransmitter (acetylcholine, ACh) released into the cleft diffuses across the short distance to the postsynaptic membrane and binds to specific molecular receptors on the postsynaptic membrane. There is very high density of ACh-sensitive receptors on the postsynaptic membrane (up to 10,000/μm2). ACh in the synaptic cleft is quickly broken down by a special enzyme, acetylcholinesterase, into two substances, acetate and choline. The presence of this enzyme makes the duration of the postsynaptic effects very brief. Relatively large amounts of ACh are taken back by the presynaptic membrane and recycled. PROBLEM 5.1 Imagine that you have a muscle without acetylcholinesterase. What can you expect in response to a single presynaptic action potential? Step 3: ACh acts on the postsynaptic membrane and induces changes in its ion permeability, leading to a depolarizing potential (excitatory postsynaptic potential, EPSP). In healthy muscles, EPSPs induced by presynaptic signals are always suprathreshold, leading to the generation of an action potential on the postsynaptic membrane. Note that subthreshold depolarizing potentials may emerge spontaneously (i.e., without an apparent stimulus) at the postsynaptic muscle membrane (endplate region of muscle fiber). These potentials are about 1 mV in peak amplitude, and their functional meaning is unclear. They are called miniature endplate potentials or MEPPs (see figure 5.5).

excitatory postsynaptic potentials (endplate potentials, MEPPs) spontaneously occur on the muscle postsynaptic membrane. A presynaptic nerve action potential always makes the postsynaptic membrane reach the depolarization threshold and induces a muscle action potential. Figure

5.5    Miniature

PROBLEM 5.2 A presynaptic action potential induces contraction of 20 myofibrils. Can a sequence of action potentials induce the contraction of more than 20, less than 20, or exactly 20 myofibrils? The next steps involve events already happening in the muscle fibers, and we will address them as the mechanisms of muscle contraction.

5.4 Mechanisms of Contraction Step 4: Postsynaptic action potential travels along the muscle cell membrane (sarcolemma) entering the T-tubules (figure 5.6). There it opens Ca++ channels. At rest, virtually all Ca++ ions are stored in sarcoplasmic reticulum where they are “captured” by a special protein. Opening calcium channels leads to a massive influx of Ca++ ions into the sarcoplasma, increasing the concentration of these ions

by a factor of 100. This increase is transient, and Ca++ is quickly pumped back into the sarcoplasmic reticulum.

Figure 5.6    Muscle

action potential travels along the sarcolemma, enters Ttubules, and leads to a release of Ca++ ions from the sarcoplasmic reticulum.

Step 5: The sliding filament theory (figure 5.7). Calcium ions in sarcoplasma act on the troponin–tropomyosin complex. At rest, tropomyosin blocks the myosin-binding site on actin—that is, a special place on an actin molecule that would eagerly attach to a special place on a myosin molecule. Calcium ions make the binding site available. If there is energy available (normally, ATP molecules), the myosin head binds to a site on actin and uses the energy to ratchet the filaments with respect to each other. As mentioned earlier, these attachments between actin and myosin molecules are called cross-bridges. Then myosin releases itself from the actin site and springs back, getting ready to attach to the next available site and to repeat the cycle (certainly, if Ca++ ions and energy sources are still available). Note that the interaction between myosin and actin filaments occurs in the three-dimensional space so that each myosin molecule simultaneously makes and breaks cross-bridges with six actin molecules. This means, in particular, that when some of the cross-bridges break, others maintain force of contraction. Force developed by a muscle fiber may be considered approximately

proportional to the average number of simultaneously engaged cross-bridges.

sliding filament theory. Ca++ ions remove troponin and free a site for myosin to bind to actin (this process uses the energy from ATP). A ratchet motion occurs, moving the filaments with respect to each other. Figure 5.7    The

PROBLEM 5.3 What would happen if the troponin–tropomyosin complex were permanently inactivated? Steps 4 and 5 are commonly known as excitation–contraction coupling. Step 6: After excitation stops (action potentials do not arrive anymore), Ca++ is actively pumped from sarcoplasm into the sarcoplasmic reticulum, the troponin–tropomyosin complex takes over all the sites of myosin binding, and the filaments slide back along each other (relaxation). Note that muscle relaxation is a passive process: One cannot command a muscle to relax, only to stop sending excitatory action potentials. The sliding filament mechanism provides an explanation for some of the features of the dependence of muscle force upon muscle length that are going to be considered in the next section.

PROBLEM 5.4 Imagine that a muscle is developing force under a constant level of stimulation. Draw a cartoon depicting the dependence of muscle force upon muscle length based on what you already know.

5.5 Types of Muscle Contractions Muscular contraction leads to the generation of force that is always directed to shortening the muscle fibers. Muscles cannot actively elongate. Later in this chapter, we will see that a muscle can develop active force while its length is increasing (eccentric contraction). However, in such cases, muscle length is always changing under the action of another force, produced either by other muscles or by the environment, or because of the inertia of the muscle and body parts to which it is attached. When a single action potential comes to a muscle fiber, it responds with a unitary contraction called a twitch contraction or simply a twitch (figure 5.8). Depending on the properties of the fiber, twitch contractions last from a few tens of milliseconds to a couple of hundred milliseconds. Note for comparison that a muscle action potential has a duration of about 10 ms. This means, in particular, that the mechanical consequences of an action potential last much longer than the action potential itself.

Figure 5.8    A

typical twitch contraction of a muscle in response to a single

stimulus.

PROBLEM 5.5 Why does the twitch contraction outlast the action potential? If several fibers are stimulated simultaneously, their twitch contractions superimpose. This superposition can lead both to an increase in the peak amplitude of the twitch contraction and to its prolongation if a muscle fiber with a longer-lasting twitch is added to a group of fibers with short-lasting twitches. If two action potentials come to the same fiber at a short interval, their mechanical effects may superimpose, as shown in figure 5.9, so the peak force of the contraction induced by the second action potential will increase. If many action potentials come at a frequency that allows superposition of their mechanical effects, a sustained level of contraction is observed, called tetanus or tetanic contraction (figure 5.10). Tetanus may display local peaks of contraction at relatively low frequencies of action potentials (sawtooth tetanus) or may lead to total fusion of individual twitches, in which case it is called smooth tetanus.

Figure 5.9    Two

action potentials come at a short interval and induce two twitch contractions. Their mechanical effects superimpose, leading to a higher level of muscle force.

Figure 5.10    A

sequence of action potentials may lead to a tetanus (a sustained contraction). At a high frequency of action potentials, individual contractions may fuse, leading to a smooth tetanus.

PROBLEM 5.6 Smooth tetanus is rarely observed in individual fibers in real life. Why are our muscle contractions normally smooth?

simple mechanical model of a muscle. It contains a force generator (F), a damping element (B), and two elastic elements, a parallel spring (K1) and a series spring (K2). Figure

5.11    A

5.6 Elements of Mechanics Let us now turn to real life and remind the reader that muscles do not exist by themselves, but their action at joints is affected by the mechanical properties of tendons and ligaments, as well as by the geometry of the tendon attachment to the bones. Typical models of muscles involve at least four components (figure 5.11): a contractile element (force generator) about which we have been speaking until now, a damping element (dashpot), and two elastic elements, one parallel and one serial. Unfortunately for investigators, most of these elements are essentially nonlinear, which means that their mechanical behavior differs from that of ideal springs and dampers and may be characterized by abrupt changes in their characteristics. It seems to be the proper time to introduce a little bit of mechanics. Elastic elements or springs are physical objects that resist external attempts at changing their length by developing force acting against the imposed deformation. During deformation, springs

accumulate potential energy that can be released. In the simplest case of a linear spring, the force developed by the spring is described with Hooke’s law: where Fe is elastic force, x is spring length, x0 is zero length (i.e., the length at which elastic forces are zero), and k is a coefficient termed stiffness. Note that the minus sign implies that force acts against the change in length with respect to x0. The notion of stiffness can only be applied to springs. One cannot measure a change in force and a change in length (or displacement) of an arbitrary object and claim that the ratio of the two is stiffness (Latash and Zatsiorsky 1993). In particular, “joint stiffness” (also “limb stiffness,” or “body stiffness,”) is not a very meaningful expression because joints do not deform, they move. Tissues crossing joints, such as muscles and tendons, do deform, but characterizing their overall time-varying behavior by a single parameter, stiffness, is very questionable. Damping is the ability of a system to generate force against the vector of velocity:

where Fv is damping force, V is velocity of length change, and b is a coefficient. Note again that the minus sign implies that force acts against the velocity vector; as a result, damping always acts to reduce the kinetic energy of a moving object. Sometimes damping is imprecisely referred to as viscosity, which is a property of liquids, whereas equation 5.2 can be applied to various objects. All material objects also have inertia, which is a coefficient between applied force and acceleration:

where Fi is inertial force, a is acceleration, and m is a coefficient termed mass.

Equations 5.1 through 5.3 describe what are called linear elements. Such elements produce outputs in proportion to input signals. For example, if a force F1 acts on a spring and induces a displacement x1, and force F2 produces a displacement x2, the combined action of two forces (F1 + F2) will produce displacement (x1 + x2). The same rule of simple summation can be applied to damping and inertial forces. Such systems are relatively easy to analyze, and equations describing their behavior can often be solved analytically. Linear systems are commonly studied in textbooks of elementary physics; however, in real life they are rare. It does not take much to make a system nonlinear. For example, if stiffness depends on spring length, this element is already nonlinear, and consequently, a system with such an element is very likely to be nonlinear. The situation becomes even more complicated if a characteristic of an element changes in a step-like fashion, which is typical for intact muscles as described later in the book.

5.7 Force–Length and Force– Velocity Relations A typical example of the nonlinear behavior of a whole muscle is its force–length relationship. Such a relationship can be obtained in an experiment in which muscle length is fixed at a certain value (isometric conditions), a standard stimulation is applied to the muscle nerve with the help of an external electrical stimulator, and peak muscle force is measured. Then, muscle length is fixed at a different value, the same stimulation is applied, and the force is measured again. And so forth. As a result, a force–length curve is observed similar to those shown in figure 5.12. It is important to remember that the measurements are performed when muscle length is not changing, which means that inertial and viscous properties do not play a major role.

Figure 5.12    Force–length

curves measured in a muscle for different levels of external stimulation (S1, S2, and S3). Note that the muscle behaves like a nonlinear spring. Changing the strength of the stimulation modifies the zero length of the spring and the shape of the characteristic. Force drop with stretch does not happen during natural movements because the anatomical range of muscle length changes is limited.

PROBLEM 5.7 The last statement is not 100% correct. Why? If you change the parameters of the stimulation (its amplitude or frequency) and perform the same experiment, the curve will shift to the right or to the left nearly parallel to the length axis. So the muscle behaves like a nonlinear spring (note that its stiffness, the slope of the curve, changes with length as well as with the level of excitation) whose zero length changes in response to a change in an incoming activation signal (stimulation). PROBLEM 5.8 In which direction will the curve shift if you increase either the frequency or the amplitude of the stimulation?

One can measure the force–length relationship in a single sarcomere (i.e., inside the contractile element shown as F in figure 5.11). The active force developed by the sarcomere will show a dependence on the sarcomere length that is somewhat similar to the one for the whole muscle: At low values of sarcomere length, crossbridges cannot develop force because of the lack of space for new attachments; at intermediate values of length, the force is maximal; while at high values of sarcomere length, there are only a few crossbridges that can generate force, and it drops again. Another important relation for a whole muscle is the force–velocity curve. Such curves are usually studied in experiments when a muscle performs a twitch contraction under different loads and the peak velocity of muscle shortening is measured. The curve typically looks hyperbolic (figure 5.13) and can be well approximated with the famous Hill equation:

5.13    A typical force–velocity curve for a whole muscle. The x-axis represents velocity of muscle stretch (frequently, this curve is drawn using velocity of muscle shortening). Note that the muscle develops higher forces when it is lengthening (positive velocity) than when it is shortening (negative velocity). Compare this figure with the Hill equation. Figure

where F is force, F0 is force at zero velocity (in isometric conditions), V is peak velocity of shortening (i.e., it is negative for a stretched muscle), and a and b are constants specific for a given muscle.

5.8 External Regimes of Muscle Contraction Muscle contraction in conditions that prevent changes in muscle length is termed isometric, and a load leading to such conditions is termed “isometric load.” When muscle contracts acting against a constant external force, such contraction and load are termed isotonic. If a muscle is acting against a springlike load, the load is termed elastic. Examples of different loading conditions are shown in figure 5.14.

Figure 5.14    A

muscle always works against a load. Three types of loads are illustrated. Isometric load prevents changes in the length of the “muscle plus tendon” complex; an isotonic load does not change; an elastic load acts like a spring. A typical muscle characteristic is shown for comparison (the thin curve).

The problem with these terms is that they are misleading. Consider, for example, what will happen if movement in a joint is prevented (isometric conditions). If a muscle acting at this joint is activated, it develops contractile force that acts on all the elements, including the parallel and serial elastic elements. Depending on the

relative properties of these elements, the muscle will induce a change in their relative length even if the length of the whole complex “muscle plus tendon” is kept constant. Note that a relaxed muscle is usually less stiff than its tendon, while activated muscle is typically more stiff than the tendon. Thus, muscle fiber length is going to change in isometric conditions as well. PROBLEM 5.9 What will happen with the relative length of muscle fibers and with the tendon under activation in isometric conditions? Isotonic conditions are also not associated with a constant external load if we try to look at it from the point of view of the muscle, not of an external observer. Joint movement is associated with changes in joint geometry, including changes in the distance from the center of joint rotation to the line of muscle action. As a result, to produce a certain value of the moment of force required to balance the action of the external load, muscle force will have to change with joint angle.

CHAPTER 5 IN A NUTSHELL Muscle contractions are produced by an interaction of two types of molecules, actin and myosin, inside muscle cells. Muscle

cells

neuromuscular of

a

are

synapses

mediator,

potentials

excited with

through the

acetylcholine.

lead

to

the

help

Action

release

of

calcium ions, which make cross-bridge formation

between

actin

and

myosin

molecules possible. In response to a single

stimulus,

muscle

fibers

generate a single twitch contraction. A number of stimuli coming at a high frequency

lead

to

the

summation

of

individual twitches and the generation of a tetanic contraction. Muscle force increases

with

muscle

length

and

decreases with the velocity of muscle shortening. Muscles always act against external loads, typical examples being isometric, loads.

isotonic,

and

elastic

Chapter 6 Peripheral Receptors KEY TERMS AND TOPICS Classification of receptors Weber-Fechner law muscle spindles fusimotor innervation Golgi tendon organs articular receptors skin and subcutaneous receptors Receptors are specialized cells or subcellular structures that change their properties in response to stimuli (sources of energy) of a special type or modality. Thus, different receptor systems enable humans and animals to differentiate among different sources of energy (for example, light, sound, and mechanical energy) that are being absorbed by the body. Receptors of a certain type are typically rather specific (i.e., they ignore alien stimuli), although many of them can be forced to fire with an electrical stimulation or even with a strong mechanical stimulus. For example, a hard hit to an eye can lead to a whole bunch of sparks, that is, to visual images induced by the activity of visual receptors in the eye responding to mechanical deformation. Interestingly, although many of our receptors react to electrical stimulation and transduce information using electrical

phenomena, we do not have a developed system for sensing an electromagnetic field outside the visible light range.

6.1 General Classification and Properties of Receptors The obvious function of receptors is to make information about particular types of stimuli available to other neurons within the central nervous system. Some of this information is related to the environment, while other information is related to the state of the body itself. There are four major groups of receptors: 1. Interoceptors transduce information from within the body; 2. Exteroceptors transduce information from the environment; 3. Proprioceptors transduce information about the relative configuration of body segments; and 4. Haptic receptors transduce information about the direct mechanical contacts with the environment. Sometimes, receptors associated with pain are classified as a special group of nociceptors. These receptors will be discussed in more detail later in the chapter on kinesthetic perception. Receptors within each group can be sensitive to stimuli of different modalities; on the other hand, receptors belonging to different groups may react to energy of the same kind. For example, there are mechanoreceptors (i.e., receptors that react to mechanical stimuli) in each of the four groups. Receptors sensitive to certain chemicals (chemoreceptors) are rather widespread. Some of them are located on membranes and are sensitive to certain neurotransmitters. As already discussed, these receptors play a major role in synaptic transmission of information. On the other hand, the activity of chemoreceptors in the mouth and nose plays an extremely important role in one’s life, creating the senses of taste and smell. Before moving to the mechanisms and function of specific groups of receptors, let us mention a law that is applicable to the conscious

perception of signals from many of the receptor systems. This law states that perceived sensation is related to stimulus magnitude by a logarithmic function. It can be studied by changing the magnitude of a stimulus of a certain modality and asking the subject to report how strong the stimulus feels on a scale from 0 to 10. It is called the Weber-Fechner law:

where P is the magnitude of perception, M is the magnitude of the stimulus, M0 is the magnitude of the stimulus when the subject just feels it (the threshold stimulus), and k is a constant. This law is an example of psychophysical functions that relate dimensions measured directly by an experimenter to perceived dimensions reported by the subject. PROBLEM 6.1 Give an example of a receptor system that does not obey the Weber-Fechner law. In this chapter, we will consider proprioceptors and some of the haptic receptors whose activity is closely tied to the motor function. A typical proprioceptor is a specialized neural cell with the body located in a special place, a ganglion, close to the spinal cord (figure 6.1). These neurons are rather unusual in their structure; in particular, they do not receive inputs from other neurons and do not have a typical dendritic tree. Their axons serve both for inputs into the neuron and for its output. The axon of such a neuron is termed an afferent axon or afferent fiber; it has a characteristic T-shape. An afferent axon splits into two branches close to the neuron body. One of the branches goes to a peripheral site in the body, where it ends with a specialized ending (sensory ending); the membrane of the ending can be depolarized to the threshold by a stimulus of a certain strength and modality. The other branch goes through the back

(dorsal) portion of the spinal canal (through the dorsal roots) into the spinal cord, where it can make connections with many different neurons, leading to various motor and sensory effects.

Figure 6.1    The

body of a sensory neuron is located in a ganglion near the spinal cord. One branch of its T-shaped axon goes to the peripheral sensory ending, while the other branch goes through the dorsal roots into the spinal cord.

Proprioceptor neurons differ from most of the neurons within the central nervous system in the way they generate and transmit action potentials. While most neurons generate action potentials on their body membrane (in particular, at the axonal hillock) in response to excitatory synaptic effects, proprioceptors generate action potentials in the periphery, in the sensory ending excited by an external stimulus. Most neurons integrate information from many other neurons to generate an action potential. Proprioceptor neurons have only one source of excitation, at the peripheral sensory ending. Most neurons transmit action potentials from the body down the axon; this type of transmission is called orthodromic. Action potentials generated by a sensory ending travel in the opposite direction,

toward the body; this type of transmission is called antidromic. Further, the action potential is conducted orthodromically along the central branch of the T-shaped axon.

6.2 Muscle Spindles The muscle spindle is one of the most amazing inventions of nature (figure 6.2). These structures with a very sophisticated design supply other neurons within the central nervous system with information related to the length and velocity of muscle fibers. Muscle spindles have an elongated shape (they are commonly up to 1 cm long) with a thicker area in the middle that makes them look like regular spindles. They are scattered among muscle fibers in large quantities. Each spindle contains specialized muscle fibers, intrafusal fibers, that are oriented parallel to the regular power-producing extrafusal fibers. The middle part of a spindle is covered with a capsule made of connective tissue. At both ends, intrafusal muscle fibers are connected either to extrafusal fibers or to tendinous ligaments. So, when extrafusal fibers change their length, intrafusal fibers are stretched or shortened correspondingly.

Figure 6.2    (a)

A muscle spindle is oriented parallel to extrafusal muscle fibers. It is covered with a capsule connected to the extrafusal fibers by strings of connective tissue (b). Spindles contain two types of intrafusal muscle fibers, the bag fibers (BF) and the chain fibers (CF). Two types of sensory endings can be found in muscle spindles, primary (Ia) and secondary (II). Primary endings are typically seen in virtually all intrafusal fibers, while secondary endings are seen in CF and static BF, but not dynamic BF.

Spindles contain two major types of intrafusal fibers, called bag fibers and chain fibers. These names reflect the distribution of nuclei within a fiber, clustered as in a bag, or spread along the fiber in a chain-like fashion. In turn, bag fibers are of two subtypes, static and dynamic, reflecting their role in the responses to muscle length and velocity of its changes. Two types of sensory endings can be found in muscle spindles. They are located mostly in the middle (equator) portion of the spindle. Endings of the first type, called primary spindle endings, are seen on virtually all intrafusal fibers, including both bag and chain fibers, while endings of the second type, called secondary spindle endings, are rarely seen on dynamic bag fibers, but are common in static bag and in chain fibers. A spindle ending, like any sensory ending of a proprioceptive neuron, is located at the end of the axon of a neuron whose body is in a spinal ganglion. Axons of primary endings belong to group Ia afferent fibers, while axons of secondary endings belong to afferent fibers of group II. Primary sensory endings are sensitive to both muscle length and velocity. Figure 6.3 shows a typical response of a primary ending to an externally imposed muscle stretch at different velocities. Note that the frequency of firing of the ending is higher after the stretch than before, which means that the ending is sensitive to muscle length. In addition, during stretching, the frequency of firing of the ending is higher for faster stretches, meaning that the ending is sensitive to velocity as well. Note that velocity sensitivity of primary spindle endings leads to an increase in the frequency of their firing during muscle elongation and also to a decrease in the frequency of firing during muscle shortening. Primary afferent axons are among the fastest neural fibers. They are myelinated, with the diameter ranging from 12 to 20 μm, which corresponds to action potential velocity of up to 120 m/s.

Figure 6.3    Typical

responses of a primary spindle ending to an externally imposed muscle stretch at different velocities. Note that the response increases with muscle length and with the velocity of stretch. The top drawing shows the length changes and individual action potentials. The bottom drawing shows the changes in firing frequency (ƒ) starting from some nonzero level (ƒ0).

PROBLEM 6.2 What can you say about the state of the muscle (its length and velocity) if you know the frequency of firing of a primary ending in this muscle? Secondary endings are sensitive only to muscle length but not to velocity. Figure 6.4 shows the response of a typical secondary

ending to muscle stretch and shortening. The proprioceptor neurons innervating secondary endings have smaller axons, and the speed of conduction is also lower, ranging from 20 to 60 m/s.

Figure 6.4    A

typical response of a secondary spindle ending to an externally imposed muscle stretch and shortening. Note that the response increases with muscle length and does not depend on velocity. The figure is organized similarly to figure 6.3.

PROBLEM 6.3 Draw a graph of time changes in the firing frequency for a primary ending and for a secondary ending if muscle length changes as a sine function.

PROBLEM 6.4 Draw a graph of length changes for a muscle whose typical primary spindle ending shows a smooth, ramp-like increase in the firing frequency with time from a certain steady level to another, higher steady level followed by a ramp-like decline in the firing frequency to a level somewhat higher than the original one.

Endings in muscle spindles have very high sensitivity to lowamplitude changes in muscle length, particularly if these changes occur at a high frequency. This is particularly true for primary spindle endings, which can be forced to generate an action potential or even several action potentials in response to every cycle of highfrequency vibration (on the order of 100 Hz) when the amplitude of the vibration is 1 mm and the vibration is applied to the skin over the muscle belly or over the tendon. If a vibrator is attached directly to muscle fibers, a few μm of vibration amplitude are enough to drive primary spindle endings at the frequency of the vibration.

6.3 The Gamma-System Primary and secondary spindle endings are unique among proprioceptors in their ability to change their sensitivity to the respective physical variables, muscle length and velocity, in response to signals from special groups of neurons that form the gamma-system (γ-system). Intrafusal muscle fibers receive signals from the efferent axons of neurons of a particular type with the bodies located in the spinal cord. These neurons belong to the class of motoneurons together with spinal neurons that send their signals to power-generating, extrafusal fibers. Motoneurons innervating muscle fibers inside muscle spindles belong to the gamma system and are called γmotoneurons. They are much smaller than the other group of motoneurons, α-motoneurons; their axons are of approximately the same length since their target is located in the same muscles, but they are much thinner and, correspondingly, conduct action potentials at much lower velocities (about 20 m/s). There are two types of γ-motoneurons (figure 6.5), dynamic and static. Dynamic γ-axons innervate dynamic bag muscle fibers and, thus, affect the sensitivity of primary spindle endings that are located in these fibers to muscle velocity. Static γ-motoneurons send their axons to static bag and chain fibers. They can change the sensitivity of both primary and secondary endings to muscle length.

are two types of small motoneurons (γ-motoneurons) innervating intrafusal fibers of muscle spindles. Dynamic γ-motoneurons innervate dynamic bag fibers and change the sensitivity of primary endings. Static γmotoneurons innervate static bag and chain fibers. They change the sensitivity of both primary and secondary endings. Figure

6.5    There

Figure 6.6 shows how electrical stimulation of dynamic γ-axons can change the response of a primary ending to muscle stretch and shortening. Note the increase in the effects of stretch on the spindle response. Static γ-axons innervate intrafusal fibers containing both primary and secondary sensory endings. So, the effect of their stimulation can be seen in the response of both groups of sensory endings to muscle length as an increase in the frequency of firing.

Figure 6.6    The

effects of activation of dynamic γ-motoneurons on the response of a primary spindle ending to muscle stretch and shortening. Thin line shows frequency changes (ƒ) without gamma stimulation. Thick dashed line shows the effects of γ-dynamic stimulation.

PROBLEM 6.5 How will a secondary ending react to an increase in the activity of dynamic γ-motoneurons innervating the spindle?

PROBLEM 6.6 When we voluntarily contract a muscle, its length decreases. However, the frequency of firing of the spindle endings in the muscle may remain constant. How can this happen?

6.4 Golgi Tendon Organs Another group of proprioceptors are located close to the junction between tendons and muscle fibers (figure 6.7). These receptors are sensitive to mechanical deformation and are called Golgi tendon organs. Note that tendons may be viewed as nearly perfect elastic

structures (springs). This means that mechanical deformation of a tendon increases with muscle force, and so Golgi tendon organs appear to be nearly perfect force sensors. Golgi tendon organs do not receive any additional innervation (that would be similar to the gamma-system for muscle spindles); they are also not responsive to the rate of force change. Thus, their response to muscle force is relatively independent of other factors. The fact that tendons are nonlinear springs makes Golgi tendon organs nonlinear sensors; however, this is unlikely to be a major problem as long as their properties do not change.

Figure 6.7    Golgi

tendon organs are located in series with extrafusal muscle fibers at their junction with the tendon. They are innervated with fast-conducting Ibgroup axons of sensory neurons in spinal ganglia.

Figure 6.8 illustrates a typical response of a Golgi tendon organ to force generated by muscle fibers that are in series with the tendon organ. Note, however, that Golgi tendon organs are rather selective —that is, they respond to force generated by “their” muscle fibers. If muscle force is generated by fibers that do not act at the area where a Golgi organ is located, it will not increase its firing frequency, and it may even show a drop in activity. This may result from an unloading of a particular “braid” of the tendinous structures where the Golgi organ is located.

Figure 6.8    A

response of a Golgi tendon organ to muscle force. Note that it is similar to the response of secondary spindle endings to muscle length.

PROBLEM 6.7 Imagine that you prevent movement of your right elbow joint and then quickly activate the biceps to a rather large force (isometric conditions). Draw a graph of the change in the firing frequency for a primary and secondary muscle spindle ending and for a Golgi tendon organ. Assume that all endings showed a steady-state firing level before the force increase.

PROBLEM 6.8 Now, do the same for a very fast elbow flexion movement against a constant external force. Axons originating from Golgi tendon organs are nearly as large as axons of primary spindle endings, and their speed of conduction is of the same order of magnitude; it may reach about 80 m/s.

6.5 Other Muscle Receptors

A few other types of sensory endings can be found in a muscle. The first is paciniform corpuscles that are similar in their structure to Pacinian corpuscles found in the skin (see section 6.7), although smaller. Paciniform corpuscles are commonly located at the area of musculotendinous junction, and they are quite sensitive to highfrequency vibration. Not much is known about their functional significance and central connections. There are also free sensory endings scattered all around the muscle. They are sensitive to strong mechanical stimuli (like those occurring during pinching) as well as to certain chemicals. These receptors are likely to play an important role in the sense of pain and in certain reflex responses that are described later. They are innervated with small, nonmyelinated axons with a relatively slow conduction speed (under 10 m/s).

6.6 Articular Receptors Another group of proprioceptors reside in the joints; these are called articular receptors. There are actually several different types of articular receptors, including sensory endings similar to Golgi tendon organs, as well as free nerve endings. They are innervated by axons of variable size, from rather thin ones lacking myelin sheath to large ones with a diameter of over 10 μm that belong to group I fibers and are characterized by fast speeds of conduction (up to 80 m/s). These receptors were thought for a long time to be perfect angle transducers that inform the central nervous system about the position of the joints. However, a closer inspection of their behavior has revealed that individual articular receptors fire within a rather small range of joint angles (figure 6.9). Moreover, many active receptors are found when joint position is close to one of its anatomical extremes, while only a few of them are active in the middle range of joint motion. Thus, articular receptors are unlikely to provide reliable information about joint position during natural movements.

Figure 6.9    Most

articular receptors fire in rather narrow ranges of joint angles, mostly close to the anatomical limits. An increase in muscle force leads to an increase in joint capsule tension, and articular receptors increase their response (bold lines).

Articular receptors are also sensitive to changes in joint capsule tension. Typically, a receptor increases the frequency of its firing over the whole range of its activity in response to an increase in joint capsule tension (figure 6.9). Note that joint capsule tension increases with muscle force. All this makes signals from articular receptors even less attractive as a major source of information about joint position because a receptor may demonstrate similar firing frequencies at different positions if joint capsule tension magnitudes are different—for example, as a result of coactivation of agonist and antagonist muscles acting at the joint. These receptors appear to be better suited for detecting and signaling potentially damaging states of the joints, such as those associated with high joint capsule tension, joint angles close to one of the anatomical limits, and joint inflammation.

6.7 Cutaneous Receptors Human skin houses cutaneous receptors sensitive to different sensory modalities. Among them are thermoreceptors sensitive to

temperature, nociceptors sensitive to potentially damaging stimuli and giving rise to the sense of pain, and mechanoreceptors sensitive to pressure. The last group of receptors plays a particularly important role in the control of human movements, especially those involving tactile discrimination (haptic perception) and manipulation of objects. Figure 6.10 shows the major types of cutaneous mechanoreceptors in the glabrous skin of the hand. Meissner corpuscles and Merkel disks are located closest to the skin surface, on the border of epidermis and dermis. Deeper down, in dermis, there are Ruffini endings, and even deeper, in subcutaneous tissue, there are Pacinian corpuscles.

Figure 6.10    Major

types of cutaneous and subcutaneous mechanoreceptors in the glabrous skin of the hand.

Merkel disks and Meissner’s corpuscles are closer to the surface of the skin, in the epidermal sweat ridges and dermal papillae respectively, and have much smaller receptive fields than the Ruffini endings and Pacinian corpuscles that reside in the dermis and deeper tissue. Merkel disks respond to vertical pressure on the skin surface but not to lateral displacements. A group of Merkel disks is commonly innervated by one afferent axon, which effectively

integrates information from a skin area. Meissner corpuscles are sensitive to quickly changing pressure on a small area of skin. They quickly adapt and stop responding if the pressure does not change. Each Meissner corpuscle is innervated by two or more axons. Ruffini endings can be activated from much larger skin areas, from as far as 5 cm away from the location of an ending. They are slowly adapting and continue firing in response to stable deformation of the skin. Pacinian corpuscles are the biggest of them all; their size ranges from 1 to 5 mm. Pacinian corpuscles react to very quickly changing mechanical deformation (for example, to vibration). Sensory afferents are further distinguished by the temporal dynamics of their responses to mechanical stimulation. A particular subset of afferents fires rapidly when the rate of the application of mechanical stimulation changes but falls silent during sustained constant stimulation. These afferents are called rapidly adapting afferents, and they are very effective in communicating to the nervous system about dynamic changes in the stimulation. Meissner corpuscles and Pacinian corpuscles are rapidly adapting fibers. In contrast, other afferents produce a constant rate of discharge in the presence of sustained stimulus. These afferents are called slowly adapting afferents, and they relay to the nervous system properties of the stimulus such as shape, size, and dimensions. Merkel disks and Ruffini endings are slowly adapting fibers. Each of these mechanoreceptors adapts differently to mechanical pressure and serves different purposes for stereognosis. Stereognosis is the ability to perceive and recognize the shape and form of objects with tactile manipulation in the absence of visual or auditory stimuli. Stereognosis relies on a symphonic interplay between responses of the four sensory afferents to mechanical stimulation. A detailed list of their properties and functions appears in table 6.1. Table 6.1    Afferent System and Properties Receptor

Merkel

Meissner Pacinian

Ruffini

Receptive field

Small

Small

Large

Large

Receptor

Merkel

Meissner Pacinian

Ruffini

Receptive field

9 mm2

22 mm2

60 mm2

area

Entire hand or finger

Axon diameter

7-11 mm

6-12 mm

6-12 mm

6-12 mm

Conduction velocity

40-65

35-70 m/s

35-70 m/s

35-70 m/s

m/s Innervation density

100/cm2

150/cm2

20/cm2

10/cm2

Spatial acuity

0.5 mm

3 mm

10+ mm

7+ mm

6.8 Signals From Peripheral Receptors Where does the information go after activating the receptors? Three major effects of proprioceptor activity are of considerable importance for us at this point. First, proprioceptors induce changes in muscle activity, bypassing our consciousness. Some of these effects are called reflexes, while others are termed triggered reactions or preprogrammed reactions. For now, let us avoid linguistic debates on the appropriateness of the term reflex. There is considerable disagreement on whether this term is informative or ambiguous and misleading (e.g., Prochazka et al. 2000). It will be considered in more detail in a later chapter. This term has been used for “more or less automatic” and “more or less stereotypical” reactions to external stimuli that do not involve conscious participation by the subject. As described in other chapters, reflexes may be not so automatic and not so standard; they may even occur in different muscles in response to the same stimulus. However, they do reflect the stimulus, albeit in a more complex way than was thought in the first half of the 20th century. Second, proprioceptors inform the central nervous system about the body’s configuration, its orientation, and its interaction with external objects. In particular, they let us know where our arms and

legs are, and how heavy or light, how rough or soft, the objects we handle are. Third, proprioceptors play a major role in creating an internal system of coordinates that is used by the brain to plan and execute movements. Problems with the functions of the proprioceptive system result in major disruption of the neural control of movements, making some habitual actions impossible—for example, standing with one’s eyes closed or pointing to a memorized target without the help of vision. This can be seen, for example, in “deafferented persons”—an imprecise term that reflects severe cases of peripheral large-fiber neuropathy, which prevents signals generated by the sensory endings from reaching the central nervous system, and resulting in major problems with joint coordination (Sainburg et al. 1993, 1995). Signals from proprioceptors travel along afferent axons into the spinal cord (figure 6.11). There, they make connections with different kinds of neurons. Primary spindle afferents are the only known ones to make direct projection on spinal α-motoneurons. The majority of afferent axons make synapses on interneurons that are typically smaller cells processing incoming information and making projections onto other neurons, including motoneurons. Careful tracing of spinal projections from different proprioceptors revealed a rather complex picture (Jankowska 1979; Jankowska and McCrea 1983): Different afferents project onto the same interneurons, so the original information about length, velocity, pressure, force, and joint angles gets totally and seemingly irrecoverably mixed. Some afferent fibers go as far as the brain without making intermediate connections, which makes them probably the longest neural fibers in the body—up to 2 m long from the sensory ending to the projection in the brain. After they get into the brain, they apparently participate in such processes as perception of the body and limb position and movement planning.

Figure 6.11    Afferent

nerves from peripheral receptors enter the spinal cord through the dorsal roots. There they make synapses on interneurons and motoneurons and send signals to the brain. Note that the same interneurons may receive signals from afferents of different modalities.

The axons of mechanosensory afferents (both tactile and proprioceptive) enter the spinal cord through the dorsal roots and divide into ascending and descending branches. For the tactile system, both branches project onto the gray matter of the spinal cord and extend across several segments. The ascending branches of the first-order neurons, called the dorsal column, ascend ipsilaterally to the level of the caudal medulla, where they synapse on the neurons of the dorsal column nuclei. Thus, the axons of these neurons are quite long and extend all the way from the receptors, through the spinal cord, to the brainstem. The proprioceptive afferent axons also enter the dorsal roots and divide into ascending and descending systems. But more

importantly, some neurons entering the dorsal roots synapse on motor neurons in the ventral horn. This circuit forms the basis of the stretch reflex. The stretch reflex or the myotatic reflex refers to a muscle contraction in response to passive stretching of muscle fibers. The proprioceptive afferent axons in the ascending branches travel along with axons of tactile afferents in the dorsal column. From there they follow the same route to the primary somatosensory cortex as the tactile afferents. More information about the reflex effects of proprioceptive afferent axons can be found in Chapters 17 through 19. Perceptual effects are described in Chapters 12 and 28.

CHAPTER 6 IN A NUTSHELL Receptors parts

of

external Signals

are

specialized

cells

that

stimuli from

can

of

cells

or

respond

to

certain

receptors

types.

lead

to

a

perception of stimuli that is related to the strength of the stimuli by a nonlinear law. Proprioceptors produce information

about

the

relative

configuration of body segments. Muscle spindles

contain

sensory

endings

of

two types, sensitive to muscle length and and

sensitive

to

velocity.

spindle

endings

special

system

fusimotor

or

both

The is of

muscle

length

sensitivity modulated neurons,

gamma-system.

by

of a the

Golgi

tendon organs are sensitive to muscle

force.

Articular

sensitive

to

(typically,

close

limits

of

receptors

both

joint

to

joint the

are angle

anatomical

rotation)

and

joint

capsule tension. Skin and subcutaneous receptors skin.

measure

Sensory

pressure

endings

send

on

the

signals

along the peripheral branch of the Tshaped axon to spinal ganglia, where the

bodies

located. the

of

Then,

central

sensory signals

branch

of

neurons travel the

are along

T-shaped

axon into the central nervous system.

Chapter 7 Motor Units and Electromyography KEY TERMS AND TOPICS motor units Henneman principle recruitment patterns electromyography It is time to make a step from considering the properties of single cells to the next functionally important level of complexity. It would certainly be unwise to expect the central nervous system to control the level of activity of each and every neural and muscular cell separately. Such an approach would impose a computational load beyond human imagination. It is comparable to calculating the trajectory of each individual elementary particle within a baseball in order to ensure a desired trajectory of the ball. The central nervous system simplifies the task and decreases the computational load by uniting small elements of the neuromuscular system into functional units that are controlled with just one or two parameters. The smallest functional unit of the neuromotor system is termed a motor unit.

Figure 7.1    Alpha-motoneurons

in the spinal cord send their axons through the ventral roots. Each axon branches in the target muscle and innervates several muscle fibers. A motoneuron and the muscle fibers it innervates are called a motor unit.

7.1 The Motor Unit Figure 7.1 shows a couple of neural cells in the spinal cord innervating a muscle (i.e., α-motoneurons). Their axons branch at the end and innervate several muscle fibers each. Since each neuron obeys the law of all-or-none, such an arrangement leads to synchronized contraction of all the muscle fibers innervated by one α-motoneuron in response to each action potential delivered by the axon of the motoneuron. So, all these muscle fibers also behave according to the law of all-or-none. The motoneuron and the muscle fibers it innervates are called a motor unit. Typically, each muscle

fiber is innervated by only one axon branch, although during development and during recuperation following nerve injury, muscle fibers may receive inputs from a number of axons. With time, however, such “redundant” inputs disappear, and each muscle fiber ends up being innervated by one axon. Motor units differ in size, which relates to the size of the motoneuron body, the diameter of its axon, and the number of muscle fibers innervated by the motoneuron. These parameters are closely correlated, so large motoneurons (with a large body cell and large axon) innervate more muscle fibers than smaller motoneurons. The number of muscle fibers innervated by a single motoneuron (the innervation ratio) varies in a wide range, from under 10 in muscles controlling eye movements to over 1,000 in large muscles participating in postural control during standing. With age, the number of motoneurons decreases, and a process of reinnervation of orphan muscle fibers takes place that leads to an increase in the size of individual motor units and a corresponding increase in the innervation ratio. These issues will be considered in more detail in chapter 32 on the effects of aging. PROBLEM 7.1 Can one motor unit produce different levels of muscle force? Why?

PROBLEM 7.2 You want a large motor unit and a small motor unit to contract simultaneously. How would you time neural commands to the two motoneurons? Up to now, we have been discussing the most common muscle fibers that generate action potentials in response to local membrane depolarization at the neuromuscular synapse, conduct these potentials, and generate twitch contractions in response to each

action potential. Another type of muscle fiber is relatively rare and has been seen in muscles involved in eye, throat, and ear movements. These are sometimes called tonic fibers. Each tonic fiber is typically innervated at a number of places. It does not generate action potentials on its membrane in response to presynaptic inputs but rather spreads postsynaptic depolarization with local currents. As a result, the response of a tonic fiber to presynaptic stimuli does not obey the all-or-none law and can be graded. However, we are not going to consider these unusual fibers further, but instead we return to the more common twitch fibers that are involved in movements of the human body and limbs.

7.2 Fast and Slow Motor Units Each muscle consists of a number of motor units. This number ranges from less than a hundred for small muscles (e.g., those controlling eye movements), to thousands for large muscles controlling the movements of large body segments. Within a muscle, one can see motor units that differ not only by their relative size but also by their contractile properties.

Figure 7.2    (a)

Twitch contractions and (b) tetanic contractions of three motor units. Note that the fastest and strongest motor unit (motor unit 1) shows the largest drop in force with time (fatigue), while the smallest and slowest motor unit (motor unit 3) does not show fatigue at all.

There are two basic tests that are used to describe the functional properties of motor units. One is twitch contraction, while the other is fatigue. Figure 7.2a shows twitch contractions of three motor units. Note that these motor units generate different levels of peak force and take different times to reach the peak force level. In particular, motor unit 3 takes the longest time for its twitch contraction and generates the lowest peak force, while motor unit 1 is the first to reach the peak force level and has the highest peak force. If the same motor units are stimulated at a rather high frequency, they produce tetanic contractions. This can be achieved by stimulating the axons of the motor units with an external electrical stimulator. If the frequency of the stimulation is the same for all three

motor units, the peak force will once again be the highest for motor unit 1 and the lowest for motor unit 3 (figure 7.2b). If the stimulation continues for a rather long time, changes in the level of the contraction force will be observed (figure 7.2b), induced by fatigue. The mechanisms of fatigue will be discussed in chapter 30. Here, it is important to note that the changes in the force levels of motor unit 2 and motor unit 3 are small, while the force level of motor unit 1 drops significantly. Thus, there seem to be three types of motor units. Motor units of the motor unit 1 type are typically called fast-twitch fatigable, motor units of the motor unit 2 type are called fast-twitch fatigue resistant, and motor units of the motor unit 3 type are called slow-twitch fatigue resistant. These groups are sometimes referred to as FF, FR, and S motor units. Slow motor units (S) typically have fewer muscle fibers, smaller motoneurons, and thinner axons. Correspondingly, the speed of conduction of action potentials along the axons of slow motor units is the lowest (although it is rather high since, as you remember, the axons of α-motoneurons are thick, myelinated, group I neural fibers). FF motor units are characterized by the highest conduction velocity. The difference in conduction velocity may be more than twofold (from 40 m/s in some S motor units to 100 m/s in some FF motor units). The differences in the physical properties of motor units correlate with their different biochemical and morphological characteristics. Consider three major sources of energy used for muscle contraction. The first is ATP contained in myofibrils; the importance of this source may be assessed by the level of activity of the enzyme ATPase that participates in metabolizing ATP. The second source is oxidative metabolism occurring in mitochondria. Its rate may be assessed by the activity of a couple of enzymes, succinic dehydrogenase and NADH dehydrogenase. The third source is glycogen, whose metabolism is anaerobic. Table 7.1 shows the three major types of motor units and the relative representation of different physiological and biochemical characteristics of their muscle fibers. The table shows that S motor units contain mostly slow, oxidative fibers characterized by a high level of mitochondrial oxidative processes

and a well-developed blood supply network. Fast motor units use more energy from ATP and glycogen metabolism. FR motor units have a rich capillary supply comparable to that of S motor units, while FF motor units have a sparse capillary supply reflected in the color of muscles with a high percentage of FF motor units: these are pale muscles. Table 7.1    Properties of Motor Units Type

FF

FR

S

Fiber diameter

Large

Medium

Small

ATPase

High

High

Low

Glycogen

High

High

Low

Succinic dehydrogenase

Low

Medium

High

NADH dehydrogenase

Low

Medium

High

FF = fast fatigable; FR = fast fatigue resistant; S = slow.

Most muscles contain a mixture of motor units of different types, although the percentage of slow and fast motor units may differ. Slow muscles (i.e., those with a high percentage of S motor units) are typically red (an example is the soleus), while fast muscles (i.e., those with a high percentage of FR and FF motor units) are typically pale (an example is the lateral head of the gastrocnemius). Within a muscle, the central nervous system has come up with a rule that coordinates the order in which different motor units are recruited during natural muscle contractions. This rule is extremely important by itself but also as a unique example of a coordinative rule.

Figure 7.3    The

Henneman principle (size principle). Small motor units recruit first at low muscle forces. An increase in muscle force leads to recruitment of larger motor units. Derecruitment (with relaxation) follows the opposite order.

7.3 The Henneman Principle The Henneman principle (also know as the size principle) states that the recruitment of motor units within a muscle goes from small motor units to large ones. That is, if a person contracts a muscle at a low force, nearly all the force is produced by the slowest motor units (figure 7.3). If the contraction force is increased, larger motoneurons start to generate action potentials, recruiting larger motor units. At the highest level of muscle contraction (maximal voluntary contraction force), the largest motor units are recruited. Note that derecruitment of motor units during a decline of muscle force follows the inverse order: The largest motor units are the first to be turned off, while the smallest ones are the last to stop firing. The contribution of a motor unit to total muscle force depends upon two factors, the size of the motor unit and the frequency of action potentials generated by its α-motoneuron. Larger motor units have larger forces generated in response to single action potentials, while all motor units generate more force (up to a limit, of course, defined by the force during smooth tetanus) when action potentials arrive at a higher frequency. The importance of the frequency of firing for the force contribution of a motor unit gives the central nervous system options for developing the same level of muscle force with different combinations of motor units. Figure 7.4 illustrates that the same level of muscle force may result from the recruitment

of fewer motor units at higher frequencies or from the recruitment of a larger number of motor units at lower frequencies. Recruitment and changes in firing frequency are the two major mechanisms of regulating muscle force. During sustained contractions, one can commonly see derecruitment (turning off) of some motor units accompanied by recruitment of new motor units or changes in the firing frequency of already recruited motor units. Thus, the Henneman principle does not by itself define which motor units are going to be recruited and at what frequencies for a given level of muscle force. However, it limits the area where the solutions can be searched for to particular combinations of motor unit recruitment patterns. As such, it can be compared to rules of grammar, which do not define exact word combinations that have to be used to express particular meanings but limit the freedom of choosing such combinations to grammatically acceptable ones. The Henneman principle is a coordinative rule rather than a prescribing rule.

Figure 7.4    Muscle

force is kept constant. A change in the number of recruited motor units correlates (negatively!) with their mean frequency of firing.

PROBLEM 7.3

Formulate the size principle for the order of motor unit involvement when the contraction is induced by progressively increasing the strength of electrical stimulation of the muscle nerve. There are situations when the Henneman principle does not work perfectly, although these are relatively rare. In particular, if a muscle participates in a task where it is not the primary mover (for example, it participates in a postural task component), the order of motor unit recruitment within this muscle may change, leading to a violation of the size principle for certain pairs of motor units: A larger motor unit may be recruited before a smaller one. A reversal of the size principle can also be seen in certain reflex responses, in particular in responses to cutaneous stimulation.

7.4 Functional Roles of Different Motor Units The functional role of motor units is largely defined by their properties. That is, tasks that require prolonged exertion of muscle force are mostly carried out by slow, fatigue-resistant motor units, while tasks that require a quick but short-lasting increase in muscle force are mostly performed by fast motor units. In particular, many of the postural muscles have a large proportion of S motor units. On the other hand, muscles that participate in quick limb movements, such as kicking, hitting, or catching, typically have a large proportion of FR and FF motor units. Most muscles, however, have a relatively wide range of motor units of different types reflecting their participation in a variety of motor tasks. Some muscles, such as the triceps surae, are composed on several heads with substantially different compositions of motor units reflecting the roles of the different heads in various motor tasks. In particular, the soleus has a large proportion of slow muscle fibers and is best suited for postural

tasks such as prolonged standing. In contrast, the lateral gastrocnemius has a large proportion of fast-twitch, fatigable fibers and is used for quick actions, such as jumping. PROBLEM 7.4 Which motor units would you expect to find in abundance in a marathon runner, in a weightlifter, and in a swimmer? The rates of sustained firing of motoneurons are commonly rather high (from about 6 Hz to about 35 Hz) so twitch contractions of individual motor units overlap, leading to a tetanus, although fully fused (smooth) tetanus is observed rarely. During natural voluntary movements, the central nervous system uses both methods of force modulation: recruiting more motor units, and increasing the firing frequency of already recruited motor units (figure 7.5). The relative role of recruitment versus an increase in the firing frequency differs across muscles and tasks. For example, hand muscles are known to show full motor unit recruitment at relatively moderate force levels (about 40% to 50% of the maximal voluntary contraction force) such that further increase in the force can only be accomplished by an increase in the average firing frequency. In contrast, large leg and trunk muscles show recruitment of new motor units up to very high forces.

Figure 7.5    To

increase muscle force, the central nervous system may recruit new motor units or increase the frequency of firing of already recruited motor units. Here, F is force, f is a monotonically increasing function, and ƒ is frequency of firing.

During most voluntary movements, individual motoneurons do not demonstrate any substantial level of synchronization. At very high levels of muscle force, however, during fatigue, and in some neurological disorders (those accompanied by loss of voluntary muscle force, such as following a spinal cord injury), synchronization of motor unit firing becomes a way of achieving higher forces or maintaining a required level of force for a considerable time. Motor unit synchronization has both positive and negative features. The gain is obvious: Synchronized discharges sum up to higher total muscle force compared to asynchronous motor unit firing. However, the smoothness of the contraction will suffer. There is also a possibility of quicker fatigue. PROBLEM 7.5 You have invented a way to induce abrupt synchronization of motor units in human muscles. What groups of athletes would you

recommend this method to, and what groups of athletes would you suggest not even try it? Synchronization of motor units can be measured directly, with the method of cross-correlation of action potentials, or indirectly, by performing spectral analysis of the “summed” (interferential) electromyogram (see section 7.5). If one records the activity of a couple of motor units for a long time, the cross-correlation function shows a peak at about zero delay, if the motor units are well synchronized. So far, muscles have been discussed as separate units that are controlled by the central nervous system to produce movements. This is a major simplification. In particular, the notion of muscle compartments has gained prominence (English 1984; Fleckenstein et al. 1992; Serlin and Schieber 1993). Muscle compartments are groups of muscle fibers that show similarities in their behavior in physiological tests and motor tasks. In a way, muscle compartments are muscles within a muscle. Compartments have been described in both animal and human muscles. For example, human extrinsic finger flexors have their muscle bellies in the forearm, while their distal tendons, four tendons per muscle, attach to phalanges of different fingers of the hand (see chapter 27 on prehension). Several studies have suggested that motor units of these muscles form groups that act preferentially (or even nearly exclusively) to produce force in only one of the tendons. This allows us to achieve individual control of finger motion such as that seen in professional musicians.

7.5 Electromyography There are two basic methods of recording muscle activity: Intramuscular or needle electromyography and surface or interferential electromyography. In the first method, a thin needle (with a diameter of less than 1 mm) is inserted into a muscle (figure 7.6). Inside the needle, there is a very thin wire that is electrically isolated from the needle. The tip of

the wire is not isolated. An amplifier picks up the difference of potentials between the tip of the wire and the needle. Since the dimensions of each electrode and the distance between the two electrodes are very small, the electrodes selectively pick up signals (action potentials) in the closest proximity to the tip of the wire. Such electrodes are designed to record the patterns of activity of individual motor units. Note that each motor unit contains many muscle fibers, but they all generate action potentials synchronously, so that the electrode picks up the compound action potential of the whole motor unit. Typically, a needle electrode can record the electrical activity of a few motor units whose muscle fibers happen to be in close proximity to the electrode. However, because each motor unit has a somewhat different number of muscle fibers and also because the location and orientation of these fibers with respect to the electrode are different, each motor unit has a different, unique pattern of voltage changes, a unique signature (figure 7.7). These differences make it possible to record several motor units with one electrode and identify their compound action potentials with a high degree of certainty. Needle electromyography is frequently used in clinical tests.

Figure 7.6    Intramuscular

electromyography uses thin needle electrodes. Inside the needle, there is a very thin wire that is electrically isolated from the needle. The difference of potentials (Δφ) between the tip of the wire and the tip of the needle is amplified and recorded.

Figure 7.7    A

schematic of a typical recording with an intramuscular needle electrode reveals a few motor units with different shapes of the compound potentials MU1, MU2, and MU3.

The other method is interferential electromyography, which is more frequently used in studies of voluntary movements of healthy persons. The main goal of interferential electromyography is to

represent the activity of as many motor units as possible across a muscle and to obtain a reflection in its overall involvement in the task. Typically, two electrodes are taped on the skin over the muscle belly, and the difference of potentials between the electrodes is amplified (figure 7.8). On the one hand, the desire to sum up the activity may suggest using very large electrodes and placing them as far from each other as possible. On the other hand, in most studies, a researcher would probably like to focus on just one muscle and to avoid recording the activity of its neighbors. So there is a trade-off, which is resolved differently by each experimenter and in each particular case. For example, if one wants to record the activity of a relatively small forearm or facial muscle, one cannot use very large electrodes because they will pick up the activity of many other muscles in the neighborhood. Alternatively, if one wants to record the activity of a large postural muscle such as the latissimus dorsi or biceps femoris, using large electrodes would probably be appropriate. Typically, the size of electrodes used for surface electromyography varies from 1 mm to 20 mm in diameter, while the distance between the centers of the electrodes varies from 5 mm to 50 mm or even more. The choice of particular electrodes and their placement is part of the art of electromyography.

Figure 7.8    Surface

electromyography uses a pair of electrodes that are placed on a muscle belly. A third electrode (ground) is used to reduce noise.

Absolute values of electromyographic signals recorded with surface electrodes are typically on the order of tens to hundreds of microvolts. There are numerous sources of electrical noise that can obscure the biological potentials and make them indistinguishable from the noise. The most frequently encountered sources of noise are the 60 Hz voltage used as the power supply in every laboratory and radio waves that are picked up by the subject’s body acting like an antenna. Other possible sources include electric motors and strong electrical magnets, even when these are located in an adjacent room. In order to minimize the noise and ensure selective recording of biopotentials, the body surface is usually grounded with a large indifferent or reference electrode. Developments in data acquisition and analysis during surface electromyography have led to methods that combine the benefits of surface and intramuscular electromyography (reviewed in Farina et al. 2010, 2014; De Luca et al. 2015). The idea of these methods is to record the same signals travelling within the muscle from different

locations on the skin over the muscle belly and then to extract from them components (signatures) reflecting compound action potentials of individual motor units. This is done by using arrays or clusters of electrodes placed over the muscle belly. Such methods allow for the exploration of recruitment patterns of individual motor units while avoiding the unpleasant sensations associated with inserting needles into one’s muscle. Data processing of such signals is usually much more complex than typical data processing of surface electromyographic signals. Figure 7.9 illustrates the results of using this method to record a set of motor units (the data for four motor units are illustrated) using surface electromyography from an extrinsic finger flexor, the flexor digitorum superficialis. The subjects performed cyclical force production by the ring finger (shown in the middle panel). The shapes of the motor unit action potentials are shown in the left panel, the timing of their action potentials (raster plots) is shown in the middle panel, and the changes in firing frequency with time are shown in the right panel.

Figure 7.9    Arrays

of surface electrodes can be used to identify individual motor unit action potentials. (a) Examples of identified motor units. (b) Their firing patterns during two cycles of force production. (c) The frequency profiles of the motor units. Reprinted by permission from S. Madarshahian, J. Letizi, and M. Latash, “Synergic Control of a Single Muscle: The Example of Flexor Digitorum Superficialis,” The Journal of Physiology 599 (2020).

7.6 Processing Electromyographic Signals It is impossible to recommend a universal method to record and process electromyograms. There are several standard types of procedures; however, each researcher selects his or her own methods of data processing based on the actual goals of the study and the researcher’s own imagination. Three operations are frequently used in processing a surface electromyogram. The first is filtering. Note that action potentials are very fast events with typical times of potential changes of about a few milliseconds. So a high-pass filter is frequently used, which cuts off all the frequencies equal to or below 60 Hz. As a result, the 60 Hz noise is reduced as well as possible reactions of the electrodes to purely

mechanical factors that are usually much slower than changes in biological potentials. On the other hand, the upper limit of filtering frequency is chosen based on the characteristic times of events that are of interest for the experimenter. If the experimenter is not interested in the microstructure of the electromyographic signals such as the shapes of individual action potentials, a low-pass cut-off frequency is commonly chosen on the order of a few hundred hertz. The second operation is rectification. The purpose of this procedure is to be able to get a quantitative estimate of an electromyographic signal. If an action potential runs along a muscle fiber under a pair of recording electrodes (figure 7.10), the difference of potentials at the electrodes will change gradually, leading to a reversal in its sign. Actually, many biopotentials show a nearly symmetrical picture with respect to zero level. Integrating an unrectified signal over a reasonably long time will yield a very small number (close to zero) because the signal is composed of an approximately equal number of positive and negative values. Integrating a rectified electromyogram will result in a value reflecting the average magnitude of the activity over the time of integration.

Figure 7.10    An

action potential runs under a pair of electrodes. The difference of potentials recorded by the electrodes will change its sign (the upper record). Rectification means making all the values of the difference of potentials positive (the lower record).

There are two types of rectification. Full-wave rectification consists of turning all the negative values of the difference of potentials into positive values of equal magnitude (figure 7.10). Half-wave rectification cuts off all the negative values and substitutes them with zeros. Full-wave rectification is used more frequently. However, recent analyses have shown that using this method may lead to misleading outcomes, in particular in the identification of the timing of bursts of muscle activation (Farina et al. 2004). PROBLEM 7.6 Imagine that you have an EMG record. You can filter it and then rectify it or, alternatively, you can rectify it and then filter. Which method is better? Why? The third procedure is integration. Actually, there are two types of integration used for different purposes. If a researcher is interested in the overall shape of the electromyogram rather than in its microstructure, an EMG envelope is calculated. The EMG envelope represents a time function each point of which is the result of integration over small time periods, such as several tens of milliseconds. The other integration procedure is used when an overall measure of the amount of muscle activity over a certain period of time is needed. Integration of a rectified EMG gives a value reflecting total current between the electrodes as well as total resistance. Skin resistance is very hard to control; it can vary in a wide range, and it may even change during an experiment—for example, if the subject sweats. So, in order to compare integral electromyographic measures across subjects, one needs to normalize these indices. Normalization commonly means dividing a measured value by a number that is likely to reflect the differences in the conditions of recording (for example, skin resistance) but not the differences in the signal of interest:

where EN is normalized EMG, ∫EMG is a calculated integral of a signal that one is interested in, and ∫EMGst is a calculated integral over the same time interval during a standard task. This procedure is another component of the art of EMG processing: It is very subjective, and different experimenters use different methods of normalization. Typically, integrated EMGs are normalized with respect to the value recorded when the subject exerts maximal voluntary contraction of the muscle or, alternatively, when the subject exerts a standard level of force. Normalizing the EMG with the signal recorded when the subject is asked to relax is typically not a good idea; it is very sensitive to noise and borders on dividing the signal by zero. Figure 7.11 illustrates the effects of different filtering and rectification procedures on an EMG signal recorded from the left biceps brachii muscle of one of the authors. The upper trace is the raw (unprocessed) EMG signal amplified and sampled at a high frequency (1,000 Hz) by a computer. The next panel shows a fullwave rectified signal without any additional filtering. The next two panels show the effects of low-pass filtering (with a commonly used second-order Butterworth filter; if you are interested, look into a textbook on signal processing) at the cutoff frequencies of 100 Hz and 20 Hz. The lowest panel shows the same signal rectified and processed with a moving-average window of 100 ms to create an EMG envelope signal. Note that filtering can affect characteristics of the signal rather dramatically. It is always up to the experimenter to select appropriate signal processing techniques based on the purposes of the recording.

Figure 7.11    The

effects of different filtering and rectification procedures on an EMG signal recorded with surface electrodes from a human biceps muscle during a series of brief voluntary contractions. The upper signal is the “raw” (unprocessed) EMG signal sampled at a high frequency (1,000 Hz) by the computer. Note the similarities (e.g., burst timing) and differences in the signal under different filtering.

PROBLEM 7.7 Suggest methods to normalize EMG signals during very fast movements and during very small changes in the level of muscle activity.

CHAPTER 7 IN A NUTSHELL A motor unit is a motoneuron and all the

muscle

fibers

innervated

by

its

axon. There are three major types of motor units: slow, fatigue resistant; fast,

fatigue

fatigable.

resistant;

Slow

motor

and

units

fast, contain

neurons with a smaller body, thinner axon,

slower

action

potentials,

innervated natural

conduction muscle

muscle

velocity

of

and

fewer

fibers.

During

contractions,

motor

units are recruited in a fixed order, from the smallest to the largest (the size

or

Derecruitment

Henneman follows

principle). the

opposite

order,

from

the

largest

to

the

smallest. Electromyography is a method of

studying

and many

muscle

patterns nuances

results.

activation

levels

that

requires

learning

to

achieve

accurate

Problems for Part I

Self-Test Problems 1. You have an atypical neural cell in which the concentration of K+ ions inside the cell is not 150 mmol/L, but only 50 mmol/L. Everything else is exactly as in “regular” cells. Calculate the equilibrium potential for K+. How will the equilibrium potential on the membrane and the action potential in this cell differ from those in “regular” neurons? 2. You observe two fibers under changes in temperature. A stimulator is placed at one end of each fiber, and you record the response at the other end. One fiber decreased the speed of transmission of action potentials with a decrease in temperature and eventually stopped transmitting them. The other fiber did not transmit action potentials at higher temperatures, started to transmit them at lower temperatures, and stopped transmitting them at very low temperatures. What can you conclude about these two fibers? Explain the differences in their behavior. 3. You have a neural cell with one excitatory and one inhibitory synapse. At a certain frequency of stimulation of both presynaptic fibers, the neuron does not generate an action potential. You increase the frequency of stimulation of the inhibitory input without changing the frequency of stimulation of the excitatory input. After some time, the neuron starts to generate action potentials. Why? In another experiment, you increase the frequency of stimulation of the excitatory input. The neuron generates several action potentials and then becomes silent. Why? 4. You study the response of a neural cell to a single excitatory input. The cell generates action potentials at a certain frequency. You add an excitatory neurotransmitter to the extracellular space and the cell stops firing. What happened? 5. You induce a twitch contraction of a muscle by a direct electrical stimulus. The external load is zero. Draw time changes in the frequency of firing of a primary spindle ending,

of a secondary spindle ending, and of a Golgi tendon organ. Prior to the contraction, each receptor showed steady firing at a constant frequency. Solve the same problem for isometric conditions, that is, when the “muscle + tendon” complex cannot change its length. 6. A person generates 5% of the maximal voluntary contraction force of a muscle. Then muscle force increases slightly so that only one new motor unit is recruited. What can you say about the properties of this motor unit? The same person generates 95% of the maximal voluntary contraction force. Again, muscle force increases slightly so that only one new motor unit is recruited. What can you say about the properties of this motor unit?

For Those Addicted to Multiple-Choice Tests You have 20 minutes. Circle only one answer (statement) for each question. Write a short phrase explaining why you chose this answer. 1. A quick shortening of a muscle a. leads to an increase in the activity of secondary spindle endings b. leads to a decrease in the activity of Golgi tendon organs c. leads to a burst of activity of primary muscle spindle endings d. all of the above e. none of the above Why? 2. A person generates a force of 5% of the maximal voluntary contraction. Then a new motor unit is recruited. What can be said about this motor unit? a. It is large and will fatigue quickly. b. It is small and will not fatigue. c. It is small and will fatigue quickly.

d. It is large and will not fatigue. e. It consists of one γ-motoneuron and several muscle fibers. Why? 3. During an isometric muscle contraction a. the length of the muscle fibers does not change b. Golgi tendon organs show a drop in their activity c. tendon stiffness is higher than the muscle stiffness d. secondary spindle endings show a steady increase in their activity level e. none of the above Why? 4. An activated muscle is quickly stretched by an external force to a new length. What will happen? a. The activity of Golgi tendon organs will drop quickly and then increase back to the original level. b. Muscle force will drop. c. The activity of Golgi tendon organs will increase quickly, and then drop somewhat. d. The activity of Golgi tendon organs will induce a monosynaptic reflex in the muscle. e. The muscle will show a period of silence in its electrical activity (EMG). Why? 5. In a neuromuscular synapse, the mediator (ACh) is quickly destroyed by ACh-esterase. What will happen if ACh-esterase is removed from the muscle? a. Actively generated muscle force will depend on muscle length. b. The time profile of force during a single twitch contraction will change. c. The muscle will demonstrate a prolonged contraction in response to a short sequence of action potentials in the motor nerve.

d. All of the above e. None of the above Why?

Part II Neuroanatomical Foundations of Motor Control

Chapter 8 Cerebral Cortex KEY TERMS AND TOPICS primary motor cortex premotor cortex supplementary motor area corticospinal tracts brain–machine interfaces The vast majority of visually guided voluntary movements that we make on a daily basis involve many areas of the cerebral cortex. The cortex receives visual information in the occipital cortex, and then integrates this information with signals from other sensory modalities, such as the vestibular and somatosensory systems in the parietal cortex. It then relays this information to the frontal lobe for movement planning and execution. The roles of these different cortical areas have been understood through numerous studies that have defined the motor challenges faced by individuals with different neurological disorders affecting distinct regions in the cerebral cortex. For example, a stroke in the frontal lobe causes motor and cognitive impairments, whereas a stroke in the parietal cortex primarily causes visuospatial neglect. In this chapter, we focus primarily on the most extensively studied motor areas in the frontal lobe of the brain. These areas include the primary motor cortex (M1), the premotor cortex (PM), and the

supplementary motor area (SMA). M1 has been implicated in direct activation of α-motoneuronal pools (Evarts 1968, Asanuma et al. 1979) and also specifying higher-order movement parameters, such as direction of movement (Georgopoulos et al. 1986). The PM is primarily involved in coupling sensory cues to motor actions (e.g., stopping when traffic light is red and driving when it is green), whereas the SMA appears to participate more in guidance and planning of internally generated movements that do not rely on external sensory cues.

8.1 Structure of the Cerebral Cortex The cerebral cortex consists of two hemispheres, four lobes in each hemisphere, separated by the corpus callosum and anterior commissure. These are the occipital, parietal, frontal, and temporal lobes. The insular cortex is also part of the cerebral cortex. The insula is an integration hub and shares strong connectivity to many cortical and subcortical brain regions that serve sensory, emotional, motivational, and cognitive functions. It also makes reciprocal connections with the limbic system. Recent studies have also implicated the insula in motor control and decision-making, but its exact role is not clear (Gogolla 2017). The corpus callosum consists of approximately 200 million heavily myelinated white matter tracts that connect the left and right cerebral hemispheres, and these tracts integrate and transfer information from both the hemispheres to process sensory, motor, and cognitive information. A view of the left cerebral hemisphere from the side is shown in figure 8.1. The illustration shows the main gyri and sulci that are used as landmarks to define the location of different cortical motor areas.

Figure 8.1    A

left sagittal view of the human brain showing the four lobes, the central sulcus, the precentral gyrus, and the postcentral gyrus. The primary motor cortex is in the precentral gyrus, and the primary somatosensory cortex is in the postcentral gyrus.

To understand how the cortical motor areas control movement, let’s take a simple example of a person reaching for a glass of water that rests on a table along with other items, such as computers and books. To make this simple movement, the nervous system performs a series of operations. First, the visual system discerns the location of the glass with respect to the body and other items on the table. Then the visuospatial location of the glass is used to create a motor plan to perform the movement of a hand. The proximal limb muscles are activated first to initiate the transport of the arm toward the glass. Once the movement is underway, the distal arm and digit muscles are activated to open the hand so that the grip aperture is gradually scaled to the diameter of the glass. Finally, as the hand approaches the glass, the fingers are gradually closed to make contact with the glass, lift it, and bring it to the lips.

When the visual system detects an object (e.g., the glass), it sends the sensory information along two parallel neural streams (figure 8.2) to process the information related to the various properties of the object. First, the dorsal visual stream that extends from the occipital to the parietal cortex processes the spatial location of the glass with respect to the body and other objects on the table. Specifically, the dorsal visual stream can process different objects at different locations on the table but may not be able to judge what they are (e.g., differentiate a glass from a book). The ventral visual stream will serve that function by identifying objects, but this stream does not specialize in spatial localization.

Figure 8.2    The

dorsal visual stream facilitates visuomotor function. This stream is further divided into the dorsomedial and dorsolateral streams. The dorsomedial stream facilitates reaching movements, and the dorsolateral stream facilitates grasping movements. Both of these streams project to different parts of the premotor cortex. The ventral visual stream subserves visual perceptual functions.

The dorsal stream is further divided into the dorsomedial and dorsolateral streams, where the former facilitates reaching movements and the latter grasping movements. The dorsomedial and dorsolateral streams project to the dorsal premotor (PMd) and the ventral premotor (PMv) cortices, respectively. These premotor areas then project to different areas in the primary motor cortex (M1). Some motor neurons in M1 project directly to the spinal cord, and others project indirectly through the brainstem to activate the interneurons and α-motoneurons in the spinal cord that activate the limb muscles to move the arm and fingers. As stated earlier, we will focus only on the structure and functions of M1, PMd, PMv, and SMA in this chapter. We will discuss the dorsal and ventral visual streams in more detail in chapter 14. PROBLEM 8.1 During a reach-to-grasp movement, the grip aperture gradually scales as a function of the remaining distance between the hand and the object. What does that tell us about how visual sensory information is integrated during a limb movement? We will refer to the different cortical regions using the mapping of the cortex suggested by the German anatomist Korbinian Brodmann (figure 8.3). Brodmann’s areas (BA) of the cortex refer to 52 regions of the cerebral cortex identified based on cytoarchitectonic (cell size, packing density, etc.) differences. The cortical motor areas in the frontal lobe consist of the primary motor cortex (BA 4), premotor cortex (BA 6), and supplementary motor area (BA 6c). BA 4 is part of the precentral gyrus and lies anterior to the central sulcus and posterior to the precentral gyrus. It borders the somatosensory cortex (BA 3, 1, and 2) posteriorly. BA 6 lies anterior to the precentral sulcus and its medial part is BA 6c. Both BA 6 and BA 6c are involved in motor planning, movement initiation, and movement inhibition, and are parts of two major loops involving subcortical structures such as the basal ganglia and the cerebellum. It is

important to underscore that these abbreviations are often used in scientific publications but are not used as frequently in the clinical world. You will learn a little bit more about Brodmann areas 1, 2, and 3 in chapter 12.

numbers shown in the map indicate Brodmann’s areas. Brodmann assigned these numbers to the brain regions based on their cytoarchitectonic structure. Figure

8.3    The

8.2 Cells in the Cerebral Cortex There are two major types of neural cells in the cerebral cortex (figure 8.4). These are pyramidal cells and stellate (or granule) cells. The cortex has a characteristic layer structure that can be seen in vertical sections. The uppermost layer is called the molecular layer. It is composed mostly of axons and apical dendrites and contains only a few cell bodies. The next is the external granular layer containing a large number of small pyramidal and stellate cells. It is followed by the external pyramidal layer containing mostly

pyramidal cells. The first three layers are the primary origin and termination of intracortical connections. The next, internal granular layer is composed of stellate and pyramidal cells and receives projections from the thalamus. The fifth, internal pyramidal layer contains large pyramidal cells. And the last, sixth layer, the multiform layer, consists of different neurons. The last two layers connect the cerebral cortex with other subcortical regions. The stellate cells play the role of interneurons within the cerebral cortex (i.e., their axons do not leave the cortex). In contrast, the axons of pyramidal cells leave the cortex and form its most conspicuous output. Some of the dendrites of pyramidal cells are oriented toward the surface of the cortex and may reach the molecular level. Other dendrites are oriented horizontally in layers 2, 3, and 4, and may be a few millimeters long. Input signals (afferents) to cortical neurons come mainly from thalamic nuclei and from other cortical neurons. Thalamic nuclei play the role of a relay processing and transmitting information from peripheral afferents, the cerebellum, and the basal ganglia. As stated earlier, thalamic inputs make synaptic connections mostly in layer 4, which contains many stellate cells with vertically oriented dendrites that make synapses on pyramidal cells. As a result, the pyramidal cells receive information that has been processed in both the thalamus and the cortex. The vertical (column) input–output organization is typical for the cortical structures. It is combined with intercolumn connections with the help of horizontally oriented dendrites.

Figure 8.4    Cortical

layer 4 is rich in stellate neurons with local axons primarily restricted to the primary sensory cortices (neuron on the left). These neurons receive input from the thalamus. Layer 5 contains pyramidal neurons whose axons leave the cortex (neuron on the right).

8.3 Premotor Cortex and Supplementary Motor Areas Before we look at the detailed structure and function of the primary motor cortex (BA 4), we will discuss how premotor areas transform sensory signals to facilitate the generation of descending signals by the primary motor cortex. The premotor cortex (PM) serves the important role of transforming visual sensory signals that it receives from the dorsal visual stream in the parietal cortex to generate descending motor signals for arm transport and hand grasping. Compared to the motor cortex (see section 8.4), the premotor areas of the brain have been identified more recently and are only isolated from the motor cortex based on the cytoarchitectonic distinctions made by Brodmann in his cortical atlas. The premotor cortex is divided into the dorsal premotor cortex (PMd) and the ventral premotor cortex (PMv) (figure 8.2). PMd

receives input from a parietal area called the medial intraparietal area (also known as the parietal reach region), which is a node in the dorsomedial pathway that encodes the direction of the reaching movements and integrates visual information with proprioceptive information from the somatosensory cortex to facilitate reaching movements. PMv has reciprocal connections with cells in the anterior intraparietal area in the parietal cortex. The anterior intraparietal area is a part of the dorsolateral “grasping” circuit that encodes an object’s shape. PMv then transforms the visual sensory signals into neural signals to adapt the hand (wrist and fingers) to the object’s shape. It is hypothesized that a special class of neurons called canonical neurons in PMv that encode shapes of objects and discharge during motor preparation are responsible for performing these transformations. These neurons discharge selectively during observation of graspable objects and when those objects are grasped. Canonical neurons were first observed in monkeys by Rizzolatti and colleagues in Italy (Rizzolatti and Gentilucci 1988), but since then they have also been shown to exist in humans. PMv contains another special class of cells called mirror neurons. Mirror neurons modulate their activity both when an individual executes a specific motor action and when they observe the same or similar act performed by another person (reviewed in Rizzolatti and Craighero 2004). When mirror neurons were first discovered, researchers assumed that they had to play a critical role in action understanding and observation-based motor learning. Mirror neurons have now been reported to exist in both ventral and dorsal premotor cortices as well as in the parietal cortex across species. These neurons fire when one tries to repeat actions performed by others and also during imitation learning. Note that performing “the same” movement by different animals or by different individuals necessarily involves different muscle activation patterns and different joint rotations. Hence, mirror neurons likely participate in encoding more general, topological properties of movements. Recently, it has also been suggested that these neurons may facilitate learning of reachto-grasp movements in infants (Oztop et al. 2004). However, some researchers believe that the function of mirror neurons in motor

learning is limited—that they play a major role in social cognition but not in the learning of movements. Both PMd and PMv are densely interconnected with the primary motor cortex (M1). To facilitate visually guided reaching movements, PMv encodes higher-level planning of goals, such as which target to reach (a glass with water or a plate with snacks). PMv also plays a major role in processing object properties relevant for grasping and specification of hand shape and grip force. In contrast, PMd encodes the relative positions of the target (the glass versus the plate), hand, and gaze. PMd neurons are active both during the preparatory phase of the movement and when the movement is underway, correcting any deviations from the intended movement trajectory. For example, while making a movement toward the glass, you realize that there is an obstacle (e.g., a book); PMd will facilitate the correction of the movement trajectory. Thus, the main roles of PMd are integration of sensory information into motor commands and specification of movement amplitude, direction, and speed. The supplementary (SMA) and presupplementary motor areas (pre-SMA) are located in the dorsomedial frontal cortex (figure 8.5). The SMA is located on the medial surface of the cortex anterior to the precentral sulcus, and the pre-SMA lies just anterior to the SMA. Studies in primates suggest that pre-SMA and SMA are involved in the sequencing and initiation of movements, with the pre-SMA playing a more abstract, higher-level cognitive role and the SMA playing a more motor-specific role. Indeed, the pre-SMA is strongly connected with the prefrontal cortex, whereas the SMA is more heavily connected with the motor cortex, suggesting a functional division with the pre-SMA involved in higher-level motor planning and the SMA with motor execution. More recently, the SMA has been shown to facilitate response inhibition in reaction to sudden changes in a task, such as those encountered when a traffic light suddenly changes from green to yellow, prompting a swift change of moving the foot from the accelerator to the brake (Nachev et al. 2008). A few final points to note about the premotor cortex and supplementary motor areas is that electrical stimulation of these

areas induces muscle activity, but the magnitude of stimulation current required in premotor cortex areas to elicit muscle activity tends to be much higher than the motor cortex. Such stimulation induces more complex movements that frequently involve a number of joints. Both the premotor and supplementary motor areas also contain somatotopic maps of the body.

Figure 8.5    The

frontal cortex areas involved in motor planning. The premotor cortex (dorsal and ventral) and SMA receive extensive projections from the parietal cortex and other brain areas. The pre-SMA receives strong projections from the prefrontal cortex and is considered to be involved in cognitive motor control. The motor planning areas are connected to the primary motor cortex (M1).

PROBLEM 8.2 While driving a car in the countryside, you decide to increase the speed of the car by 5 mph. Which frontal premotor area will be primarily responsible for facilitating the change in the car’s speed? At another time during the drive, you see that cars ahead are moving slowly, and many of them have their emergency flashers

on. You then gradually slow down the car. Which premotor area will be primarily responsible for this action?

PROBLEM 8.3 How can you interpret the fact that stimulation of the premotor areas requires higher currents to induce visible muscle contractions than does stimulation of the primary motor cortex?

8.4 Primary Motor Cortex Brodmann area 4 (BA 4) or the precentral gyrus is also known as the primary motor cortex (M1). Together with the premotor cortex (PMd and PMv) and supplementary motor areas (SMA and pre-SMA), the M1 makes up the cortical motor pathway. An important distinction between the premotor and supplementary motor areas and the motor cortex is that the motor cortex contains giant pyramidal cell bodies known as Betz cells. The Betz cells are rarely present in the premotor areas. Another important distinction between the premotor areas and M1 is that the threshold of electrical stimulation for initiating movements is much lower in M1. This suggests the presence of relatively large and direct pathways from M1 to the spinal cord and brainstem. In the 19th century, the British neurologist John Hughlings Jackson became interested in the cortex as a critical area for motor control based on his observations of epileptic seizures. He saw that seizures would often begin in the hand and then spread systematically up the body toward the face. This led Jackson to hypothesize that a motor map in the cortex might be responsible for movement in different parts of the body. At around the same time, the German physiologists G. Theodor Fritsch and Eduard Hitzig used electrical stimulation on the canine cortex to show that the motor cortex elicits contraction of muscles in the contralateral limbs.

A little later in the 20th century, Sir Charles Sherrington mapped the motor cortex using minimum currents to elicit the smallest discernable limb movements in the great apes. One of Sherrington’s students, Wilder Penfield, extended this work to humans and showed that the motor cortex contains a somatotopic map of the contralateral body. He showed that stimulation of small regions in the motor cortex elicited activity in specific muscles, suggesting that vertical columns of cells in the motor cortex may encode individual muscles in specific body parts. Penfield and his collaborators called this representation the motor homunculus (figure 8.6). A similar map also exists in the somatosensory cortex, and it is called the sensory homunculus (chapter 12). However, according to many contemporary motor physiologists, the idea that the motor cortex encodes a simple somatotopic map of the body is not tenable anymore. Though in the motor cortex, the head and the limbs have largely separate representations, the distal and smaller body parts have widely distributed mosaic representations within these major regions. More recent studies have shown that even small currents capable of eliciting a limb motor response initiate activity in multiple muscles, suggesting that the motor map in the cortex might encode movements instead of individual muscles (Kakei et al. 1999). Even within the separate representations (e.g., face or upper limb) in M1, specific movements can be elicited by stimulation of widely separated neural areas, suggesting that intracortical connections interlink the cortex throughout major body parts, and the convergent output of many M1 motor neurons reaches the same spinal motor neuron pools to organize those movements. In addition, divergent output from many M1 motor neurons reaches multiple spinal motor neuron pools. Experiments on monkeys by Graziano and his colleagues have shown that application of longer episodes of electrical stimulation to the same cortical areas produces smooth, complex multijoint actions that seem to resemble components of the everyday motor repertoire of the animal (Graziano et al. 2002). These studies further suggest that the motor cortex might encode movements rather than control the individual contractions of muscles.

Figure 8.6    The

motor homunculus is a topographic representation of the body in the motor cortex. Note that the hands and face have a much larger representation than the legs.

8.5 Efferent Output From the Cortical Motor Areas Efferent projections of the cortical motor areas have been extensively studied with the help of direct electrical stimulation of the cortex in animal studies. The major output from the cortical areas extends to the basal ganglia, the cerebellum, the red nucleus, the reticular formation, and the spinal cord. With the exception of the projections to the basal ganglia and cerebellum, all other cortical output projections contribute directly or via spinal interneurons to muscle activation. The pyramidal tracts consist of pyramidal cells in

layer 5 of the cortex and are part of the upper motor neuron system —a system of efferent nerve fibers that carry motor signals from the cerebral cortex to either the brainstem (corticobulbar tract) or the spinal cord (corticospinal tract). The output neurons of the cerebral cortex reside in M1, the premotor cortex (both PMd and PMv), and the SMA. In contrast, the pre-SMA has a sparse projection in the corticospinal system. M1 also shares strong reciprocal connections with PMd, PMv, and SMA, but not with the pre-SMA. The dense interconnections between these areas mediate the planning and initiation of complex temporal sequences of voluntary movements. The pyramidal cells in layer 5 of M1 consist of Betz cells (~5% of all the cells) and non-Betz pyramidal cells (~95% of all the cells). Though there are relatively few Betz cells in M1, they do play a critical role in activating αmotoneurons in the spinal cord that control muscles. The non-Betz cells are also found in the premotor and supplementary motor areas. The myelinated axons of the output cortical neurons descend in the corticospinal tract and terminate in the spinal cord. The cell bodies of these upper motor neurons lie in M1 (~40%), premotor areas (30%), supplementary motor areas (15%), and the somatosensory cortex. The corticospinal tract contains more than 1 million axons. There are two corticospinal tracts coming from the left and right hemispheres. Approximately at the level of the medulla, 80% to 90% of the axons switch sides (decussate), forming the lateral corticospinal tract (figure 8.7). Decussation is when nerve fibers cross from one side of the body to another. Most of the axons that form the lateral corticospinal tract from the right hemisphere travel on the left side of the spinal cord and innervate muscles of the left limbs, and vice versa. The lateral corticospinal tract forms a direct pathway from the cortex to the spinal cord, and it projects to the lateral portions of the central horn in the spinal cord. About 20% of the axons from this tract directly project to α-motoneurons in the spinal cord that innervate distal muscles in the forearm and hand. These axons are critical for dexterous control of finger muscles and allow us to make fine precision movements, such as lifting a glass grasped with the fingertips, writing with a pen, and tying shoelaces.

The remaining 80% or so of the axons in the lateral corticospinal tract terminate on spinal interneurons that coordinate activation of the α-motoneurons that innervate different muscles. The axons that do not decussate at the level of the medulla make up the ventral corticospinal tract and terminate bilaterally. The ventral tract primarily affects activation of postural muscles in the trunk and proximal limb muscles.

Figure 8.7    About

90% of the axons of the corticospinal tract decussate and form the lateral corticospinal tract. They innervate α-motoneurons of the distal muscles. The remaining 10% of the axons form the ventral corticospinal tract and innervate trunk and proximal limb muscles.

The activity of corticospinal tract neurons has been examined during relatively simple movements, such as flexion or extension in a joint, mostly in experiments on monkeys. If a monkey is trained to make a simple movement in response to a sensory stimulus, the first changes in the muscle activity (EMG) occur at a delay (latency) of about 150 ms. Changes in the activity of pyramidal neurons can be seen up to 100 ms prior to the EMG changes. These changes are more tightly coupled with the EMG changes than with the sensory

stimulus, suggesting that they are related to movement production, not to the perception of sensory stimuli. The magnitude of the changes in the firing rate of pyramidal neurons has been reported to be more closely related to the magnitude of force produced by the animal (Evarts 1968). PROBLEM 8.4 Does the last finding prove that pyramidal neurons control muscle force? Why? More careful, later studies by D. Humphrey (1982) have suggested that there may be two subpopulations of cortical neurons. One subpopulation shows reciprocal changes in the activity during movements in the opposite directions (e.g., flexion and extension). The other subpopulation changes its activity with a change in cocontraction of agonist and antagonist muscles, which modifies apparent joint stiffness without causing a major change in the net joint torque or joint movement. There is, however, considerable overlap between these groups, as there is among virtually all other groups of neurons identified in brain structures. The equilibrium point hypothesis (Feldman 1966) is based on two variables: one related to joint equilibrium position and the other to joint apparent stiffness. The presence of two subpopulations of cortical cells provides indirect support for this view.

8.6 Afferent Input Into the Cortical Motor Areas The cerebellum and the basal ganglia are the primary sources of noncortical input to the motor areas. The cerebellum and basal ganglia project to the ventrolateral nuclei of the thalamus. These projections in turn make synapses onto the primary motor cortex, supplementary motor area, and premotor cortex (figure 8.8). Figure

8.8 oversimplifies the actual picture of thalamo-cortical projections, which is characterized by considerable overlaps.

Figure 8.8    The

projections from the cerebellum and the basal ganglia to the frontal motor areas, premotor cortex (PM), and primary motor cortex (M1) go through the thalamus.

The parietal cortex and cortical inputs are a major source of input into the cortical motor areas. The parietal cortex integrates multisensory information from the somatosensory system (proprioception and tactile) and the visual and vestibular systems and provides this information to the cortical motor areas for motor planning and execution. The premotor and supplementary areas also receive input from the prefrontal cortex. The prefrontal cortex is involved in higher-order executive functions, such as representation of abstract and complex rules, short-term working memory, and decision-making. The connections between the prefrontal and premotor areas indicate that the output of the prefrontal cortex targets specific areas of the premotor cortex involved in motor control (Lu et al. 1994). The prefrontal cortex also shares strong connections with the pre-SMA,

which suggests that the pre-SMA plays an important role in cognitive motor control.

8.7 Hemispheric Lateralization in the Cortical Motor Areas Most neural fibers within the corticospinal tract cross the midline of the body, so the primary motor cortex in the right hemisphere predominantly sends signals to the left limbs, and vice versa. Besides the anatomical lateralization seen in many vertebrates, the two cerebral hemispheres also specialize in distinct behavioral functions. For example, speech and language comprehension is controlled by Broca’s and Wernicke’s areas, respectively, and both these areas are located in the left hemisphere in about 95% of righthanders and about 70% of left-handers. In contrast, the right hemisphere, particularly the parietal cortex, primarily guides visual attention to both the left and right halves of the body. This separation of neural circuitry to divide labor between the two sides of the brain is considered an organizational attribute of vertebrate nervous systems that may permit efficient behavior. This form of organizational lateralization has also been proposed for the cortical motor areas (Sainburg 2005). Though the primary motor cortex contralateral to the arm has the greatest influence on arm motor behavior, it has been proposed that both hemispheres contribute to the control of unique aspects of behavior (Sainburg 2005). In right-handed people, the left hemisphere is specialized in controlling movement dynamics and the right hemisphere contributes to controlling the postural aspects of the movement. As an example, when you reach out to lift a glass of water, the left hemisphere specifies the spatiotemporal sequence of signals that lead to muscle activations to control the trajectory of the arm movement, whereas the right hemisphere specifies how the muscles are activated to respond to any unexpected perturbations that the arm might encounter (such as the arm bumping against a book).

The premotor cortex is also considered to be functionally lateralized. The left dorsal premotor cortex is activated during unimanual movements of the left or the right hand and is particularly involved in the selection of movements in response to visual stimuli. In contrast, the right dorsal premotor cortex is active during control of bimanual movements. However, it is unclear if functional lateralization also exists in the ventral premotor cortex; the mirror neuron system in the ventral premotor cortex does not seem to exhibit functional lateralization.

8.8 Preparation for a Voluntary Movement Voluntary movements are typically initiated in one of two ways. The first way is through spontaneous internally guided intentions that do not originate in the sensory system. For example, you may feel thirsty or you may remember that you should rehydrate regularly before you reach out to grab a glass of water. This is typically described in the literature as top-down motor control, or control that originates in the prefrontal areas of the brain. Here “top” refers to prefrontal regions that are critical for controlling behaviors in accordance with intentions or rules. However, this is a gross simplification, and intentions for many actions that humans perform may originate not in the prefrontal areas but in the limbic system. The second way actions might originate is in the sensory systems. For example, you may just be glancing around from your computer when your gaze lands on the glass of water, which may cause a desire to take a sip. This is labeled as bottom-up, sensory feedback– initiated motor control, where sensory signals in the peripheral nervous system trigger the chain of sensorimotor events that eventually lead to the initiation of movement. In a series of experiments with monkeys, Miller and colleagues (Buschman et al. 2007; Siegel et al. 2015) implanted electrodes and recorded neural spikes (action potentials) and local field potentials

from multiple areas in the visual, parietal, frontal, and temporal cortices to elucidate how neural signals associated with sensory processing (bottom-up) and action selection (top-down) flowed in the brain. Local field potential is the electric potential in the extracellular space around neurons that can be recorded by electrode arrays. In one experiment, monkeys were led to make saccades (rapid eye movements between fixation of gaze on objects) to a visual target. In a “bottom-up” kind of condition, the target was located among three identical distractors that differed from the target in two properties (color and orientation), making it incredibly easy to spot the salient target. In another “top-down” condition, the distractors matched the target on either color or orientation, forcing the monkeys to search for the target while using their short-term working memory (an executive function associated with the prefrontal cortex) to memorize the target appearance. They showed that top-down and bottom-up signals arise in the frontal and sensory cortices, respectively, and contribute to the initiation of the saccades. The supplementary motor areas mediate action selection based on top-down, internally guided actions. For example, if action sequences are initiated based on memory (e.g., without external instructions or visual cues), the prefrontal and supplementary motor areas are activated. The supplementary areas have also been associated with the control of motor readiness during voluntary initiation of movements. Electroencephalographic recordings from humans have revealed a slowly increasing negative potential, known as the Bereitschaftspotential, or the readiness potential (Deecke et al. 1969), that is centered over the SMA and pre-SMA before movement initiation (see figure 8.9). This would suggest that for these movements, neural activity would start in the prefrontal cortex, followed by the supplementary motor areas, and then the upper motor neurons of the primary motor cortex. Changes in the resting electroencephalogram (EEG) pattern can be seen as early as 1.5 s prior to the first signs of changes in the background muscle activity. The relatively long duration of the readiness potential is surprising. Humans can make a decision to move and to start a movement in

much less time than 1.5 s. Actually, the shortest reaction time to a visual or auditory stimulus is just over 100 ms. PROBLEM 8.5 Suggest an explanation for the difference between the typically short reaction times (commonly under 200 ms) and the rather long readiness potential.

8.9    The electroencephalographic (EEG) signals before self-initiated voluntary finger movements (right index finger flexion) show a negative potential shift that begins approximately 1.5 s before the finger movement–related surface electromyographic (EMG) muscle activity is detected. The EEG signal was termed Bereitschaftspotential by Kornhuber and Deecke and provided the first insights into the neural origins of self-initiated movements. Figure

Distributed under the terms of the Creative Commons Atrtibution 4.0 International License (http://creativecommons.org/licenses/by/4.0/).

For many other real-world activities that originate in the sensory system, the nervous system forms arbitrary associative maps between bottom-up sensory signals and motor responses (e.g., go when light is green, slow down when it’s yellow, and stop when it’s red). Neurons in the dorsal premotor cortex (PMd) fire during observation of the visual cues (e.g., go for green and stop for red) and facilitate the selection of an appropriate action based on the cues. Thus, the PMd plays an important role in action selection when movements are guided by sensory signals.

Movement preparation and action stopping, where a planned movement is abruptly aborted, have been studied using transcranial magnetic stimulation (TMS) over M1 (reviewed in Duque et al. 2017). TMS is a noninvasive technique that can induce rapid and transient (~250 μs) electrical currents in the human cortex. When the stimulating coil is placed over M1, TMS elicits descending volleys in the corticospinal tracts. TMS over M1 activates corticospinal neurons not only directly but also indirectly via the stimulation of intracortical circuits that project to corticospinal neurons. These tracts synapse on spinal α-motoneurons that innervate peripheral muscles contralateral to the hemisphere being stimulated. The evoked response, called the motor evoked potential (MEP), is measured using surface electromyography (EMG). Over the course of three decades, TMS protocols have been developed to probe M1 connectivity with other neural areas. In paired-pulse protocols, a low-intensity subthreshold conditioning pulse is applied first, and then a suprathreshold test pulse is generated in the same coil. The two TMS pulses are applied over M1 at specific intensities and different time intervals. When the interstimulus interval between the conditioning pulse and the test pulse is 2 to 5 ms, it causes test MEP responses to be inhibited (intracortical inhibition), and when they are between 8 to 15 ms, test MEP responses are facilitated (intracortical facilitation). The conditioning pulse is assumed to probe GABAergic inhibitory neurotransmission in the cortical areas. As a reminder, the GABAergic system is the main inhibitory neurotransmitter in the central nervous system (see also chapter 4).

8.9 Neuronal Population Vectors In the late 1960s, Ed Evarts used recordings in M1 of monkeys and showed that single M1 neurons were active during movement of one joint but less active or not active at all for other joints. In addition, neurons fired when the preferred joint moved in one direction and were less active when the joint moved a different direction. This

activity was observed 50 to 150 ms before the onset of agonist muscle activity of the preferred joint. This work was extended in an exciting series of studies performed in the 1980s by Georgopoulos and his colleagues in investigations of the behavior of large populations of neurons in the primary motor cortex (and later, in other areas). In these experiments, monkeys were trained to perform hand movements to visual targets that might appear in different parts of the screen, which means they performed movements in different directions. A large number of neurons were recorded with implanted electrodes. The changes in the firing level of each neuron demonstrated a peak during movements in a certain preferred direction (figure 8.10). Movements in directions close to the preferred one were accompanied by slightly lower increases in the resting activity. Movement in the opposite direction could lead to suppression of the resting activity. Each neuron was associated with a unitary vector in the direction for which the neuron demonstrated the largest increase in its resting activity. Then the animal performed movements in different directions, and the activity of all the neurons was recorded during movements in all the directions. If a neuron demonstrated an action potential in a time interval just prior to the movement, a unitary vector in its preferred direction was drawn. If the neuron demonstrated two or three action potentials, two or three vectors were summed up, and so forth. Then all vectors were summed up across all the neurons. Note that the population vector points in a direction that is very close to the direction of the movement. A change in movement direction in response to a change in the position of the visual stimulus is accompanied by a rotation of the population vector from the first to the second target. The procedure itself is at least partly responsible for the result, which can be obtained for any array of units (neurons or nonneurons) that satisfy two conditions: (1) their activity is related to movement direction by a cosine function, and (2) they cover the whole range of movement directions. In particular, if one records EMGs of all the limb muscles during the same task, the result will be very similar. The same thing may happen if an experimenter records

and processes in a similar fashion the activity of muscle spindle endings or Golgi tendon organs. So these results, by themselves, do not prove that the population of neurons in the cortex controls movement direction. This is an example of a very important distinction between correlation and causation.

Figure 8.10    (a)

The figure shows a raster plot of a single neuron during arm movements in eight directions. Here 0 on the x-axis indicates movement onset. Each vertical line on the raster plot indicates an action potential. The activity of this particular neuron increased when a movement was made between 90º and 225º and decreased below baseline levels when the movement was made between 45º and 315º. (b) The firing frequency of a cortical neuron demonstrates a cosine-like dependence on the direction of voluntary movement. For this particular neuron, the preferred direction is 135º. Adapted from Georgopoulous (1982).

Later, this experiment was performed with a modification when the monkeys were trained to move not in the direction of the target but in

another direction shifted by a constant angular value from the target. This procedure apparently requires a mental calculation (or a mental rotation) in order to move in the required direction. In this task, the monkeys demonstrated a considerably larger delay between the stimulus and the initiation of a response; apparently this was related to the task’s complexity. Recording the activity of a population of cortical neurons revealed that the population vector rotated from the direction of the stimulus to the movement direction during the prolonged preparatory period. These very elegant experiments strongly suggest that cortical neurons participate in processes that encode the direction of voluntary movements.

8.10 Encoding Movement Parameters in the M1 Since the pioneering work of Georgopoulos and colleagues, where they showed that the activity of a population of cells in M1 encodes higher-order movement parameters such as hand direction, many researchers have questioned the tenability of this hypothesis. Using physiological models of the musculoskeletal system, they have shown that given the complex properties of the limb and musculature, the relationship between neural activity and limb movement can be shown to encode a variety of movement parameters, such as target location in peripersonal space, hand or joint motion, joint torques, and even muscle activation patterns. Furthermore, there is now growing evidence that M1 cells discharge both during action and during action observation, much like mirror neurons in the ventral premotor cortex. Furthermore, somatosensory responses in M1 neurons have been reported using tactile stimulation, mechanical perturbation, and passive movements of the limbs. These studies from the 1970s and 1980s showed that M1 cells integrated sensory information from muscles about the particular joint that was perturbed and then activated synergistic muscles to generate corrective motor responses.

More recently, Pruszynski and colleagues have provided compelling evidence to show that the motor cortex integrates sensory feedback from not one but multiple muscles spanning different joints (Pruszynski et al. 2011). The authors perturbed either the shoulder or the elbow joint and observed different neural responses in a population of shoulder-tuned M1 neurons approximately 50 ms after the perturbations. The interesting aspect of these perturbations was that both the shoulder and the elbow perturbation produced the same shoulder motion. Despite the unclear signals from the shoulder muscles, M1 cells integrated peripheral sensory information from the muscles spanning the two joints to generate an appropriate motor response. This suggests that M1 cells may also serve intelligent sensory functions. Though there is no doubt that the cortical motor areas serve important functions for voluntary movements, the sensory responses observed in the premotor and motor cortices suggest that we should think of the cortical motor areas as nodes or layers in sensorimotor neural networks. Almost 90 y ago, Bernstein (1935) wrote, “No area of the cortex can currently be viewed as the origin or the final destination of a neural process … Every area and every layer of the cortex represent only transit points of the neural process (p. 326).” Researchers who try to model the neural functions with the method of artificial neural networks would express this idea somewhat differently: The cortex is neither the input layer nor the output layer of any meaningful neural process; it is always a hidden layer (figure 8.11). Note that at the hidden layer level, the information is typically mixed up to such a degree that no clear reflections of the input or output variables can be found.

Figure 8.11    Schematic

of a neural network with three layers. The input layer could process sensory information, and the output layer could output the motor response processed by the hidden layer.

8.11 Brain–Machine Interfaces In the last two decades, neuroscientists have collaborated with engineers and clinicians to create devices based on interfacing neural activity in the brain with control machines that can then be used to restore functions lost to neurological insults and diseases. The design of brain–machine interface (BMI) devices involves four components: a neural recorder for the acquisition of brain signals from a population of neurons that encode motor goals, a decoder to process and decode neural signals using artificial neural networks and convert them into control signals for the machine, a device that takes the control signals from the decoder to operate an end-effector (a robot, mechanical system, or virtual control program), and implementation of sensory feedback to facilitate adaptive plasticity and control of the BMI device.

A schematic representation of a BMI device is shown in figure 8.12. There are three important things to note here. First, even though most intracortical microelectrode arrays are planted in M1 to obtain neural recordings, signals have also been obtained from the posterior parietal and premotor cortices to improve function. Second, though there is no agreement among neuroscientists on what aspects of movements are encoded in M1, a decoder does not need to know that. It simply uses machine learning algorithms to extract important features of movement to implement control signals for a robot or end-effector. Finally, BMIs have been developed using different forms of recordings, such as single- or multiunit recordings of action potentials, electrocortography, electroencephalography, and functional magnetic resonance imaging. This shows the versatility of time scales over which neural information can be integrated to drive brain–machine interfaces.

Figure 8.12    A

brain-machine for upper limb motor function. The patient is asked to imagine making movements of the paralyzed arm. The neural activity is recorded with electrodes (often implanted in the brain). Then those signals are processed and decoded. The decoded information is then used to generate control signals to drive the motors of the prosthetic device. Reprinted by permission from E. López-Larraz, A. Sarasola-Sanz, N. Irastorza-Landa, N. Birbaumer, and A. Ramos-Murguialday, “Brain-Machine Interfaces for Rehabilitation in Stroke: A Review,” NeuroRehabilitation 43, no. 1 (2018), with permission from IOS Press. The publication is available at IOS Press through 10.3233/NRE-172394.

CHAPTER 8 IN A NUTSHELL The

motor

involved

areas in

execution motor

of

both

of

the

the

actions.

cortex

(M1)

brain

are

planning

and

The

primary

provides

the

most

input to the corticospinal tract that is

involved

in

the

control

of

fine

upper-limb arm and hand functions. M1 receives input from the premotor areas of the brain. The premotor areas are strongly

interconnected

with

the

parietal and prefrontal cortices. The premotor

areas

transformation parameters These

are of

of

areas

corticospinal

involved sensory

limb also

input

motor project

tract.

in

The

the to

control. to

the

premotor

cortex is divided into the dorsal and ventral areas, which are both involved in

movements

initiated

by

sensory

signals. The main role of the dorsal premotor

cortex

is

sensory

information

integration into

of

motor

commands and specification of reaching movement speed.

amplitude, In

contrast,

direction, the

and

ventral

premotor

cortex

is

involved

preshaping

of

fingers

movements.

It

also

neurons

that

observation.

The

for

grasping

contains

respond

in

to

supplementary

mirror action motor

area is also an important region that abuts the premotor cortex. It receives extensive

input

from

the

prefrontal

regions and is involved in intentional movements.

Chapter 9 Basal Ganglia KEY TERMS AND TOPICS caudate nucleus putamen globus pallidus substantia nigra subthalamic nucleus dopamine habit formation reinforcement learning Parkinson’s disease Huntington’s disease For many years, the basal ganglia have been viewed as a very important set of brain nuclei for motor function. In particular, the multilevel hierarchical scheme for the neural control of movement introduced by Nikolai Bernstein (1947) involved two levels with crucially important contributions from structures within the basal ganglia. These were the level of synergies and the level of spatial field. Bernstein postulated an important role for the basal ganglia in forming task-specific groups of motor elements and ensuring the dynamic stability of natural movement (done at the level of

synergies) and in the production of movements to spatial targets (controlled at the level of spatial field). The basal ganglia consist of several large subcortical nuclei: the putamen and caudate nucleus—which are addressed together as the striatum—the globus pallidus, the substantia nigra, and the subthalamic nucleus. These nuclei neither receive direct inputs from nor send direct outputs to the α-motoneurons in the spinal cord. The importance of the basal ganglia for control of voluntary movements has been assumed based mostly on clinical observations. Basal ganglia disorders bring about quite different clinical pictures ranging from excessive involuntary movements to slowness and a lack of movement. Because of these clinical observations, it was supposed that the basal ganglia were major components of an extrapyramidal system that was thought to participate in the control of movements in parallel with and largely independent of the pyramidal (corticospinal) system. However, we now know that the pyramidal and extrapyramidal systems are not independent but dynamically cooperate for movement control. Basal ganglia also play an important role in motor learning and habit formation. The function of the basal ganglia is not limited to controlling movements; these structures have a role in cognitive and emotional functions as well.

9.1 Anatomy of the Basal Ganglia Three of the nuclei of the basal ganglia lie deep in the cerebrum, laterally to the thalamus (figure 9.1). Two nuclei, the caudate nucleus and the putamen, form the striatum. The striatum is the major input structure of the basal ganglia, and it receives input from the cerebral cortex, thalamus, and brainstem. The two nuclei in the striatum are separated from each other by the internal capsule. The striatum is organized into modules called striosomes and matrix. Striosomes are islands of relatively densely packed cells that are parts of a larger, less densely packed compartment called matrix.

These areas of the striatum differ in projections they receive from the cortex. The matrix receives inputs from many areas of the cortex, while striosomes receive inputs mostly from the prefrontal cortical areas.

Figure 9.1    A

sagittal and frontal view of the brain showing the basal ganglia and the two input nuclei of the basal ganglia, the caudate nucleus and the putamen. These two structures constitute the striatum. The striatum is the major input structure of the basal ganglia. One of the major output structures of the basal ganglia is the globus pallidus.

The phylogenetically oldest nucleus in the basal ganglia is the globus pallidus, which is also known as the paleostriatum. The globus pallidus consists of two discrete nuclei, internal (GPi) and external (GPe) segments. The internal segment is a major output structure, and the external segment is part of the intrinsic basal ganglia circuitry. The other two nuclei of the basal ganglia, the substantia nigra and the subthalamic nucleus, are located in the midbrain. The substantia nigra is the largest nucleus of the human midbrain. It is divided anatomically into two parts; its dorsal region is called the pars compacta and its ventral region is called the pars reticulata. It contains dopaminergic cells that project to the striatum and other basal ganglia nuclei. The subthalamic nucleus is situated between the thalamus and the substantia nigra; it receives projections from

the GPe, cerebral cortex, thalamus, and brainstem, and it sends outputs to the globus pallidus and substantia nigra pars reticulata. These nuclei have been historically united with the group of the basal ganglia. There are, however, other nuclei that lie ventrally to the striatum and the globus pallidus that may also be considered to be within the basal ganglia group. The nuclei ventral to the striatum, the nucleus accumbens and olfactory tubercle, are sometimes called the ventral striatum. They receive inputs from the limbic and olfactory area of the cortex and are similar to the striatum in receiving dopaminergic inputs from the ventral tegmental area. The ventral pallidum differs from the GP in that it receives direct inputs from the amygdala and projects to the limbic area of the cortex. These nuclei are assumed to play a role within the limbic structures of the brain, possibly contributing to motivation and emotions (Pessoa et al. 2019).

9.2 Inputs and Outputs of the Basal Ganglia The cerebral cortex is a major source of input to the basal ganglia, with numerous projections coming in from all of the cortical lobes in the brain. Cortical input into the caudate nucleus and putamen originates in different areas of the cerebral cortex. The caudate nucleus receives input from the parietal and frontal lobes, which are involved in integrating multimodal sensory information, as well as from areas in the frontal lobe involved in eye movements (figure 9.2). In contrast, the putamen receives input from primary and secondary somatosensory and visual areas, and this input topographically maps onto different regions of the putamen. In addition, the putamen receives input from the premotor and motor cortices. These pathways into the caudate and putamen remain parallel and segregated even in the output structures of the basal ganglia. Cortical neurons make projections onto the striatal neurons; these projections are glutamatergic—that is, they are excitatory and use

glutamate as the neurotransmitter. Most cortical projections to the striatum are to medium spiny neurons. The input from the cortex to the spiny neurons is convergent as the axons from cortical neurons terminate on fewer spiny neurons. The large dendritic trees of the spiny neurons receive input from different cortical, brainstem, and thalamic structures, allowing for the integration of information from multiple neural regions. The projections from the motor and somatosensory areas into the putamen follow a somatotopic mapping (i.e., inputs from the arm, face, and leg areas are kept separate throughout the basal ganglia). For example, neurons responding to the leg areas are concentrated in the dorsolateral putamen, and those from the arm are located in more ventromedial areas.

Figure 9.2    (left)

The main cortical structures that project to the basal ganglia and the input nuclei of the basal ganglia, the caudate and the putamen. (right) The internal projections within the basal ganglia.

Medium spiny neurons also receive information from local interneurons in the striatum. The activity of these neurons is also modulated by dopaminergic neurons in the substantia nigra pars compacta. A schematic drawing of a spiny neuron is shown in figure 9.3. Note the typical spines on the dendrite of such a neuron and the convergence of projections from the cerebral cortex, substantia nigra, and other spiny neurons. These inputs use different neurotransmitters: glutamate, dopamine, acetylcholine, and GABA.

The medium spiny neurons from the caudate nucleus and putamen make inhibitory projections onto both segments of the globus pallidus and the substantia nigra pars reticulata using GABA as the neurotransmitter; these projections are both inhibitory and convergent. There are fewer neurons in the pallidum and substantia nigra than in the striatum. As mentioned earlier, an interesting feature of these projections is that the motor pathways remain largely segregated through the basal ganglia networks and are believed to serve different motor functions, such as motor planning, motor execution, and motor sequencing. The efferent neurons from the motor areas of the globus pallidus and substantia nigra pars reticulata project to motor-related areas of the ventral lateral and ventral anterior nucleus of the thalamus and the superior colliculus, respectively. The thalamic nuclei project directly to the motor areas of the cerebral cortex in the frontal lobe, completing vast parallel motor circuits that both originate and terminate in the cerebral cortex and go through the basal ganglia and the thalamus (figure 9.4). In addition to these pathways that go through the thalamus, there are direct projections from the substantia nigra pars reticulata that directly innervate neurons in the superior colliculus that project to neurons that innervate extraocular muscles and muscles controlling head movements.

Figure 9.3    Medium

spiny neurons of the striatum project to the globus pallidus, ventral pallidum, and substantia nigra. They receive excitatory inputs from the cortex and thalamus. In addition, dopamine afferents from the substantia nigra modify the responsiveness of the medium spiny neurons to excitatory input. They also receive inhibitory GABA inputs from other spiny neurons as well as excitatory glutamatergic input.

Figure 9.4    The

efferent projections from the basal ganglia (globus pallidus) project to the motor areas in the frontal cortex through the thalamus. The output from the substantia nigra pars reticulata projects to the superior colliculus. The superior colliculus is a midbrain area that is involved in the control of eye movements.

An important aspect of basal ganglia efferent output from the globus pallidus and substantia nigra pars reticulata is that it is inhibitory. The efferent neurons from these structures are spontaneously active and inhibit neurons in the thalamus and the superior colliculus. Since the medium spiny neurons are also inhibitory (and GABAergic), when transient excitatory input from the cortex reaches the striatum, it disinhibits the inhibitory neurons of the globus pallidus and substantia nigra pars reticulata and creates a burst of activity in the cortical neurons that then initiate movements. The medium spiny neurons in the putamen and caudate are active seconds before movement is initiated. This suggests that they are involved in the decision to move. PROBLEM 9.1

Would putamen neurons fire as a person is reaching for an ice cream cone, or in anticipation before the reaching movement is initiated? Why?

9.3 Direct and Indirect Pathways Within the Basal Ganglia There are two main pathways within the cortico-basal-thalamiccortical loop. The direct pathway consists of projections of the medium spiny neurons of the striatum to the internal segment of the globus pallidus (GPi) through the basal ganglia (figure 9.5). This pathway facilitates the initiation of voluntary movements by releasing cortical neurons from the tonic inhibition of the thalamic cells. The indirect pathway (figure 9.5) involves projections of another population of medium spiny neurons of the striatum to the external segment of the globus pallidus (GPe). The GPe sends projections to the GPi as well as to the subthalamic nucleus. The subthalamic nucleus also receives direct projections from the cerebral cortex through the hyperdirect pathway and makes excitatory (glutamatergic) projections to the GPi and the substantia nigra pars reticulata. Though the indirect pathway projects to the output nuclei that project to the thalamus, it actually ends up opposing the activity of the direct pathway. This is important for action selection as explained below. When cortical neurons activate the indirect pathway, the medium spiny neurons fire and inhibit the tonically active GABAergic neurons of the GPe. The subthalamic cells are glutamatergic and excitatory and project to the GABAergic GPi and substantia nigra pars reticulata neurons. When the subthalamic cells receive excitatory input from the cerebral cortex, they end up increasing the inhibitory output of the basal ganglia. This is obviously different from the output

of the direct pathway that disinhibits the cortical neurons from the tonic inhibition of the thalamic cells and consequently facilitates the initiation of voluntary movements. Thus, the direct pathway is activated in anticipation of upcoming movements, and the indirect pathway simultaneously suppresses competing motor plans from being executed. Let’s try to understand this with an example. Imagine you are driving a car and as you approach a traffic light, you see the light turn from green to yellow. Now you have multiple options; you could speed up to pass the light before it turns red, slow down to bring the car to a stop, or not do anything because you are certain that you have enough time to pass the light without hustling. Let’s say you choose to slow down; the direct pathway would facilitate moving the legs from the accelerator to the brake to stop the car, while the indirect pathway would suppress the other two motor alternatives. This has been studied in the laboratory using the go/no-go paradigm (reviewed in Aron et al. 2007). On each trial, participants are presented with one of two possible Go signals: press left arrow if target moves to the left and right arrow if it moves to the right. On a minority of the trials (typically between 25% and 33%), a Stop signal is presented after the Go signals. Participants are instructed to respond as fast as possible on the Go trials and to do their best to stop their motor response when the Stop signals occur. The timing of the Stop signal is varied systematically, and the Stop signal reaction time is calculated. This paradigm has also been combined with functional imaging to obtain the neural correlates. The imaging studies have revealed that the nervous system stops the Go movement via a frontal cortex basal-ganglia network.

Figure 9.5    The

direct and indirect pathways of the basal ganglia. The direct pathway consists of projections of the medium spiny neurons of the striatum to the internal segment of the globus pallidus and facilitates the initiation of voluntary movements by releasing the cortical neurons from the tonic inhibition of the thalamic cells. The indirect pathway opposes the activity of the direct pathway. There is also a hyperdirect pathway that conveys information from the motor, associative, and limbic brain areas on to the subthalamic nucleus (STN), bypassing the indirect inhibitor circuit and leading to excited globus pallidus/pars reticulata of the substantia nigra (GPi/SNr) activity.

PROBLEM 9.2 If a baseball batter decides not to swing for a curveball, how would the direct and indirect pathway contribute to that?

9.4 Dopamine Modulation of Basal Ganglia Circuits Within the basal ganglia, the caudate nucleus and the putamen receive dopaminergic inputs, mostly from the substantia nigra pars compacta. The medium spiny neurons of the striatum project to the

substantia nigra pars compacta and then receive dopaminergic input back from the substantia nigra pars compacta. The projections from the pars compacta provide excitatory input to the spiny neurons that project to the GPi (direct pathway) and inhibitory input to the GPe (indirect pathway). This is made possible by different types of dopamine receptors, D1 (direct pathway) and D2 (indirect pathway), on the medium spiny neurons (figure 9.6). It has been hypothesized that dopaminergic neurons are involved in “reward-related” changes in motor behavior, or reinforcement learning. Here, “reward” is used in an abstract sense. Whereas animals can be rewarded with food for performing a task successfully, rewards almost certainly have a different meaning for humans. For example, when you are learning to drive, you might pick up good or bad habits based on outcomes of your decisions and the praise received from your instructor. The praise itself might serve as a reward. Apparently, the firing rate of dopaminergic cells signals the difference between the expected reward and the received reward during a motor action. The release of dopamine strengthens the synapses between neurons that fire whenever an action with a high reward is performed. So, if you bring your car to a smooth stop and instantly receive praise from your instructor, that behavior might get reinforced and eventually become a habit. It is important to note that dopaminergic neurons in the direct pathway only fire during the learning process and stop firing when the action becomes a habit. Similarly, if an action is performed that results in a punishment (e.g., you are rebuked by the instructor for making a hasty and unsafe driving decision), that action might be inhibited, possibly with contributions from the indirect pathway. As stated earlier, movements become habitual or stereotyped when they lose their dependence on explicit or implicit rewards. The basal ganglia may facilitate habit formation by strengthening stimulus–response associations. This relationship is beautifully described by Ashby and colleagues (Ashby et al. 2010) in a theoretical model of stimulus–response associations facilitated by the basal ganglia (figure 9.7). Imagine that two corticostriatal inputs

code sensory events (S1, S2) and synapse on striatal output neurons that lead to two distinct motor actions (R1, R2). Let’s imagine that R1 leads to the delivery of a reward and causes a transient or phasic increase in midbrain dopamine activity and a release of dopamine in the striatum and strengthening of one synapse, say S2 to R1. This synapse continues to strengthen with repeated reinforcement until an asymptotic level of strength is reached. In contrast, synapses that are activated in the absence of the phasic dopamine-reward signal (S1 to R1) undergo long-term depression, reducing the possibility that S1 will depolarize cells to produce neural activation to produce R1. Thus, dopamine-mediated long-term potentiation strengthens the synapses (S2 to R1) and increases the chance that the motor action (R1) that is rewarded occurs in response to the same sensory stimulus (S2) in the future.

Figure 9.6    The

substantia nigra is the source of important dopaminergic input to the basal ganglia; loss of neurons in this area is the cause of Parkinson’s disease. In the direct pathway (shaded) of the basal ganglia, when the striatum is excited, it inhibits the tonically active internal segment of the globus pallidus. That in turn disinhibits the VA/VL complex of the thalamus and excites the motor cortex. In the indirect pathway, the excited striatum inhibits the tonically active neurons of the external segment of the globus pallidus (GPe). The GPe projects to the subthalamic nucleus, which also receives excitatory input from the cortex. The excitatory projections from the subthalamic nucleus to the internal segment of the globus pallidus (GPi) counter the disinhibitory actions of the direct pathway. Adapted from Purves et al. (2017).

Figure 9.7    Corticostriatal

inputs S1 and S2 encode different sensory events that eventually cause different behavioral responses, R1 and R2. If R1 produces a reward, it causes an increase in dopamine activity in the basal ganglia. This will strengthen the active synapses between S2 and R1 and increase the probability that the reward-producing behavior R1 will occur in response to the sensory event S2.

PROBLEM 9.3 A person is learning a skill that requires the initiation of rapid eye movement (a saccade) at the onset of a visual stimulus. If the basal ganglia played a role in the acquisition of this skill, would you expect the reaction time to increase or decrease with practice?

9.5 Motor Circuits Involving the Basal Ganglia Figure 9.8 illustrates major pathways originating from different areas of the cerebral cortex, passing through the basal ganglia and the thalamus, and terminating back in the cortex. Inputs to the basal ganglia may originate in different cortical areas such as the motor cortex, the premotor area, the supplementary motor area, the somatosensory cortex, and the superior parietal cortex (which lies dorsally to the somatosensory areas). The projections from the somatosensory cortical areas to the putamen are organized

somatotopically (i.e., one more primitive drawing of a human figure may be found on the surface of the putamen). This somatotopy is relatively preserved in the projections from the putamen to both internal and external segments of the globus pallidus. Both direct and indirect loops participate in the motor circuit of the basal ganglia; they are both mediated by thalamic neurons. Most of the thalamic projections to the cortex are directed at the premotor cortex and supplementary motor area. These areas have connections with each other (mostly inhibitory) and with the motor cortex, and all of them project directly to brainstem motor centers and to the spinal cord.

Figure 9.8    The

motor and oculomotor loops of the basal ganglia.

Most somatosensory and motor areas of the cortex project exclusively to matrix, while many striosomes receive inputs from limbic structures. Remember that limbic structures include the hypothalamus, the fornix, the hippocampus, the amygdaloid nucleus, and the cingulate gyrus of the cerebral cortex. They are believed to be involved in such elements of behavior as attention, motivation, and emotion. Striosomes, which receive projections from limbic

structures, in turn, project on dopaminergic cells in the midbrain. Midbrain neurons then project back upon the matrix and striosomes. The latter projections may modulate the effectiveness of cortical inputs to the same neurons. So this circle provides means for the brain to change the effectiveness of transmission in the basal ganglia motor loop based on attentional and emotional factors.

9.6 Activity of the Basal Ganglia During Movements The role of the motor network that involves the basal ganglia has been examined in animal studies and by clinical observations of movements in patients with basal ganglia disorders. These studies have shown that this network is involved in action selection, movement preparation, movement sequencing, and reinforcement learning. The medium spiny neurons increase their firing rate before an impending movement. In particular, neurons in the putamen fire before limb movements are initiated and caudate neurons before eye movements are initiated. This firing can sometimes occur seconds before the movement is initiated, suggesting that these neurons are involved in action selection and movement preparation. The involvement of the basal ganglia in action selection also implicates it in reinforcement-based motor learning that is driven by rewards and punishments. As stated earlier, this is accomplished through simultaneous activation of the direct and indirect pathways. Animal studies have shown that, at rest, there is substantial activity of neurons in the globus pallidus and in the pars reticulata of the substantia nigra (at frequencies of about 50 to 100 Hz), while neurons in other structures of the basal ganglia are rather quiet. For example, the baseline discharge of neurons in the striatum is typically under 1 Hz. Neurons in the GPi fire at a relatively constant high rate, while neurons in the GPe demonstrate high-frequency burst-like activity (DeLong et al. 1983).

PROBLEM 9.4 Suggest a functional reason that the neurons in the globus pallidus have a high rate of activity at rest. Many neurons in the basal ganglia show phasic modulation of their firing frequency during voluntary movements of the contralateral side of the body. Some of these neurons show correlation of their firing frequency with such movement parameters as velocity, force, and amplitude (Crutcher and DeLong 1984; Middleton and Strick 2000). Discharge patterns of other neurons, however, are both movement and context dependent. In particular, movement is associated with an increase in the frequency of action potentials generated by neurons in different nuclei of the basal ganglia. This increase is seen somatotopically—that is, it is seen in separate groups of neurons during arm, leg, and facial movements (DeLong and Georgopoulos 1979). A change in the discharge rate may be seen about 20 ms prior to movement. Though most striatal neurons are active before movement initiation, some also show changes in their activity in association with movement termination rather than with movement initiation. Changes in the firing patterns of cells in other structures of the basal ganglia typically occur rather late. For example, in reaction time tasks, most of the cells show changes in their firing after movement initiation, although there have been reports of relations between changes in the basal ganglia activity and movement initiation (Hauber 1998). Note that many neurons of the motor cortex change their firing prior to the movement initiation. So it is possible to conclude that neurons of the basal ganglia do not initiate movements under these experimental conditions and that they are related more to the control of movements that are already underway. Another important characteristic of the basal ganglia neurons is that their firing correlates more closely with movement direction than with forces that are needed to perform a movement (Crutcher and DeLong 1984).

9.7 Movement Disorders Associated With the Basal Ganglia The two most common movement disorders associated with basal ganglia dysfunction are Parkinson’s disease and Huntington’s disease. Parkinson’s disease is a hypokinetic (decrease in voluntary movement) disorder that was first described by James Parkinson in 1817. The main symptoms of the disease are tremor during rest that lessens during movement and sleep, slowness of movement (bradykinesia), muscular stiffness and rigidity, speech difficulties, and lack of facial expressions. When walking, patients with Parkinson’s disease take shorter steps, have a stooped posture, and have a reduced, often asymmetrical arm swing. The loss of dopaminergic neurons in the substantia nigra pars compacta contributes to this disease. Huntington’s disease was first reported by George Huntington in 1872. This disease is a hyperkinetic (increase in undesired movements) disorder and is characterized by an increase in involuntary movements, abnormal gait, coordination deficits, and rapid and jerky movements. This disease is caused by gradual atrophy of the striatum (caudate and putamen). When the medium spiny neurons do not provide sufficient inhibitory input to the GPe, the cells in the GPe become very active and reduce the excitatory input from the subthalamic nucleus to the GPi. This causes a decrease in the inhibitory output of the basal ganglia and makes the cortical motor neurons respond to small inputs, resulting in undesirable movements. These disorders will be covered in more detail in chapter 37.

9.8 Other Functions of the Basal Ganglia

The function of the basal ganglia is not limited to motor control. Two additional circuits play roles in modulating nonmotor aspects of behavior. These circuits originate in different areas of the cortex, pass through the basal ganglia and the thalamus, and terminate in areas outside the motor and premotor cortices. The first circuit serves cognitive functions and originates in the dorsolateral prefrontal cortex and involves the caudate nucleus. A number of recent studies have shown that this loop is related to such functions and processes as short-term memory, attention, and cognition (reviewed in Pessoa et al. 2019). The second circuit regulates emotional and motivational behavior and is also involved in mood regulation. This loop originates in the orbitomedial prefrontal cortex, amygdala, and hippocampus, and passes through the ventral sector of the striatum. Disorders in these circuits are associated with psychiatric disorders, such as hallucinations, delusions, obsessivecompulsive disorder, depression, and anxiety.

CHAPTER 9 IN A NUTSHELL The

basal

subcortical in

motor

ganglia

are

nuclei

that

control,

a are

motor

group

of

involved learning,

executive functions, and regulation of emotions. The basal ganglia have input nuclei,

output

nuclei.

Input

nuclei, nuclei

and

intrinsic

structures

are

the caudate nucleus and the putamen, and they receive incoming information from cortical and other sources. The output nuclei consist of the internal segment of the globus pallidus (GPi)

and

the

substantia

reticulata

(SNr).

nigra

These

pars

structures

send basal ganglia information to the thalamus. The intrinsic nuclei consist of the external segment of the globus pallidus

(GPe),

the

subthalamic

nucleus, and the substantia nigra pars compacta (SNc), and they are located between the input and output nuclei. The basal ganglia need dopamine as an input for proper functioning. Dopamine is

critical

motor

for

reinforcement-based

learning,

and

dopamine

dysfunction is associated with several movement

disorders,

Parkinson’s

disease

disease.

and

such

as

Huntington’s

Chapter 10 Cerebellum KEY TERMS AND TOPICS cerebrocerebellum spinocerebellum vestibulocerebellum cerebellar peduncles cerebellar nuclei Purkinje cells inferior olive vestibulo-ocular reflex cerebellar ataxia error-based motor learning The cerebellum is a large structure in the caudal part of the brain, which contains more than half the neurons in the brain. The symptoms of cerebellar damage in humans as well as in experimental animal models provide compelling evidence in support of its involvement in motor control. The cerebellum receives afferent input from the cerebral cortex, spinal cord, and vestibular nuclei. In fact, the cerebellum receives many more input fibers (afferents) than it has output fibers (efferents); the ratio is about 40:1. As with the basal ganglia, the output neurons of the cerebellum do not directly

project to spinal α-motoneurons. A substantial number of efferent projections from the cerebellar nuclei, which mediate all the output projections of the cerebellum, are to cortical neurons, to the red nucleus, and to vestibular nuclei. It is widely believed that one of the main movement-related functions of the cerebellum is to provide closed-loop feedback through error detection between the intended movement and the actual movement. This can occur either while a movement is underway or across different repetitions of a movement as a form of motor learning. This form of motor learning is often referred to as error-based learning. Damage to the cerebellum causes major problems in postural control, movement coordination across joints and muscles, and motor learning and adaptation. The cerebellum has also been implicated in cognitive functions and has been linked to developmental problems across a variety of conditions including autism, Asperger’s syndrome, and Down syndrome (see chapters 33 and 38).

10.1 Overall Structure of the Cerebellum The human cerebellum has two hemispheres separated by a midline ridge. The cerebellum is broadly divided into three parts that receive inputs from different areas of the nervous system. The largest and the most lateral area is called the cerebrocerebellum, and it receives extensive input from the cerebral cortex. Medial to the cerebrocerebellum is the spinocerebellum, which receives afferent input from the spinal cord, mostly from distal limb muscles (figure 10.1). The medial ridge that separates the two hemispheres is called the vermis, evolutionarily the oldest part of the cerebellum, and it primarily receives input from proximal limb muscles. The third and final major area of the cerebellum is the vestibulocerebellum, and it is in the most inferior part of the cerebellum. It includes two areas called the nodulus and flocculus. The vestibulocerebellum is

primarily concerned with posture control and maintenance of equilibrium. The cerebellum connects to the rest of the central nervous system through three pathways called the cerebellar peduncles (figure 10.1). These are the superior cerebellar peduncle, the middle cerebellar peduncle and the inferior cerebellar peduncle. These peduncles are the sources of all afferent input into and efferent output from the cerebellum. The deep cerebellar nuclei (figure 10.2) are the source of all efferent output of the cerebellum and form part of the cerebellar system of neural circuits connected to the red nucleus, vestibular nuclei, sensorimotor regions (primary motor and premotor areas), associative cortices (parietal cortex), and limbic system. The deep cerebellar nuclei send their output through the superior cerebellar peduncle, which is primarily an efferent pathway. The middle cerebellar peduncle is primarily an afferent pathway that takes neural information into the cerebellum. The inferior cerebellar peduncle contains both afferent and efferent pathways. Efferent neurons in the inferior cerebellar peduncle project to the vestibular nuclei and reticular formation (see chapter 11). Afferent projections in this peduncle arise from the vestibular nuclei and the spinal cord. PROBLEM 10.1 Which part of the cerebellum is involved in posture stabilization?

The flattened cerebellar surface with the three major subdivisions. (b) The cerebellar peduncles in the flattened view. (c) The sagittal view of the cerebellum. Figure

10.1    (a)

Figure 10.2    The

frontal and parietal areas project to the cerebellum through the ipsilateral pontine nuclei. Axons from the pontine nuclei decussate and enter the contralateral cerebellum. These fibers are the largest source of input to the cerebellum.

10.2 Inputs and Outputs of the Cerebellum Two major excitatory afferent systems act as inputs into the cerebellum. These are mossy fibers and climbing fibers. The mossy fibers originate from a variety of brainstem nuclei and from neurons in the spinal cord whose axons form the spinocerebellar tracts. The spinocerebellar tracts primarily convey somatosensory information. Different portions of the cerebellum receive mossy fibers from different sources. The medial zone (closest to the vermis) receives information mostly of vestibular, somatosensory, visual, and auditory modalities. The intermediate zone receives proprioceptive and somatosensory information from the spinal cord, as well as

information from the motor cortex mediated by nuclei in the pons. The lateral zone receives information mediated by pontine nuclei from different areas of the cerebral cortex, including the motor cortex. Mossy fibers make excitatory synapses on the granule cells. The axons of the granule cells ascend into the molecular layer, where each axon splits into two and joins the system of parallel fibers. Each granule cell receives inputs from many mossy fibers (this is an example of convergence of neural information), while each mossy fiber innervates a few hundred granule cells (this is an example of divergence). Each Purkinje cell receives inputs from numerous parallel fibers (up to 200,000). The system of climbing fibers is organized very differently. These fibers originate in the medulla, in the inferior olivary nucleus (also known as inferior olives). Their axons enter the cerebellar cortex and wrap around the soma and proximal portions of the dendrites of Purkinje cells. Their synapses are excitatory and very strong. Each Purkinje cell receives synaptic inputs from only one climbing fiber that forms more than a hundred synapses on the soma and the dendrites of the Purkinje cell it innervates. One climbing fiber may innervate a few Purkinje cells. A single action potential in a climbing fiber always induces a complex action potential in Purkinje cells it innervates (i.e., its action is obligatory). The largest source of mossy fiber input to the cerebellum is from the frontal, prefrontal, and parietal areas of the cerebral cortex. These cortical axons primarily project to the cerebrocerebellum through the ipsilateral pontine nuclei (figure 10.2). The axons from the pontine nuclei then decussate and enter the contralateral cerebellum via the middle cerebellar peduncle. The decussation implies that the input from one hemisphere of the cerebral cortex is received and processed by the contralateral cerebellar hemisphere. The output of the cerebrocerebellum is projected through the dentate nucleus via the superior cerebellar peduncle. These output axons exit the cerebellum, decussate, and enter the contralateral thalamus before projecting to the motor, premotor, and prefrontal areas of the cerebral cortex. These circuits through the cerebrocerebellum are

thought to be primarily involved in the planning and execution of complex movements. The projections to the prefrontal areas may also play a role in cognitive aspects of motor and nonmotor behaviors. The spinocerebellum consists of the vermis and intermediate zones of the cerebellar cortex. The vermis receives somatosensory (tactile and proprioceptive) input from the spinal cord and also receives visual, vestibular, and auditory input. The somatosensory input is topographically mapped onto the spinocerebellum and provides representations of the body in the cerebellum. The spinal and vestibular input into the spinocerebellum enters through the inferior cerebellar peduncle and remains ipsilateral. This means that the cerebellum contains topographic maps of the same side of the body. Output projections from the vermis go through the fastigial nuclei and the inferior cerebellar peduncle and reach cortical and brainstem (reticular formation) areas involved in the control of proximal muscles of the body and limbs, in particular for posture and locomotion. The vermis is also involved in the control of eye movements. In contrast to the vermis, the intermediate zones of the spinocerebellum also receive somatosensory information from the limbs and send output axons through the interposed nucleus and superior cerebellar peduncle to the thalamus. Projections from the thalamus to the frontal lobe provide input to neurons that form the corticospinal tract (see chapter 8). This tract affects spinal circuits participating in the control of distal muscles that are involved in fine motor control. The vestibulocerebellum is the phylogenetically oldest part of the cerebellum and consists of the flocculonodular lobe. It receives projections from the vestibular and visual systems through the inferior cerebellar peduncle. Projections from the vestibulocerebellum also go through the inferior cerebellar peduncle to the vestibular complex in the brainstem. These nuclei control eye movements as well as neck and head movements. PROBLEM 10.2

If there is focal damage to the central part of the cerebellar cortex, which types of movements will be affected?

10.3 Pathways Within the Cerebellum There are three distinct layers in the cerebellar cortex with different kinds of neurons that serve very different functions. The deepest layer, the granule cell layer (also called granular layer), is the input layer of the cerebellum (figure 10.3). The axons from the pontine nuclei and from the brainstem and spinal cord that form the input to the cerebellum are part of the mossy fiber system, and they terminate in this layer. Within the granule cell layer, mossy fibers make excitatory synapses on the granule cells that give rise to axons called parallel fibers. The granule cell layer contains structures called glomeruli, where cells from the granular layer make synaptic contacts with the bulbous expansions of afferent mossy fibers. A single glomerulum consists of an incoming mossy fiber, clusters of small dendrites (called rosettes) from a few dozen granule cells, and the axons of Golgi cells. A single mossy fiber may innervate many glomeruli. Climbing fibers from the contralateral inferior olives project on Purkinje cells, which are the sole output neurons of the cerebellum. The activity of Purkinje cells is modulated by two types of GABAergic interneurons called basket cells and stellate cells. Purkinje cells have elaborate dendritic trees (see figure 10.3), and these cells themselves are GABAergic and make inhibitory projections to the deep cerebellar nuclei and the vestibular nuclei in the brainstem. Though the mossy and climbing fibers provide afferent input to the cerebellum, their collaterals also provide excitatory input to the deep cerebellar nuclei. Thus, the deep cerebellar nuclei end up receiving both excitatory and inhibitory input.

Parallel fibers—which receive input from the granule cells— ascend to the outermost layer of the cerebellum, called the molecular layer, and make excitatory synapses on the Purkinje cells. Purkinje cells are GABAergic inhibitory projection neurons whose cell bodies are in the Purkinje cell layer. The molecular layer is the processing layer of the cerebellum. Parallel fibers also provide input to the stellate cells. Thus, projections from the climbing fibers eventually make synapses on the Purkinje cells through this pathway. This layer also contains the dendrites of Golgi cells, which are inhibitory neurons and have their cell bodies in the granular cell layer.

Figure 10.3    The

cerebellar cortex is organized into three layers: the molecular layer, the Purkinje cell (PC) layer, and the granular layer (GL). Purkinje cells, Golgi cells, stellate cells, and basket cells are inhibitory neurons. Granule cells are excitatory. Cerebellar afferents are the mossy and climbing fibers, and both are excitatory. The cerebellar cortex receives inputs from mossy fibers originating in various brainstem and spinal cord nuclei and from climbing fibers originating from the inferior olive. Climbing fibers contact Purkinje cells and the deep cerebellar nuclei. The only output of the cerebellar cortex is provided by the Purkinje cells, which project to the deep cerebellar nuclei. © 2021 Consalez, Goldowitz, Casoni, and Hawkes. Redistributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org /licenses/by/4.0/).

The GABAergic Purkinje cells make inhibitory projections to the deep cerebellar nuclei and are the only output cells of the cerebellar cortex. This implies that the output of the cerebellum to its nuclei is completely inhibitory.

The cerebellum’s organization reflects a series of modules with excitatory and inhibitory cells. In each module, mossy fibers provide target cells in the deep cerebellar nuclei with inhibitory input (indirectly through the cerebellum) and excitatory input (directly through collaterals). This creates both excitatory and inhibitory local circuits within the cerebellum (figure 10.4). With this form of input, each of these modules subserves two important functions: (a) continuous control of ongoing movement, and (b) long-term changes in control to facilitate motor learning.

Figure 10.4    Mossy

and climbing fibers provide strong excitatory input to the Purkinje cells. Purkinje cells are GABAergic and project to the deep cerebellar nuclei; they are the only output cells of the cerebellar cortex. The output of the Purkinje cells is completely inhibitory.

PROBLEM 10.3 GABAergic Purkinje cells provide the inhibitory output of the cerebellar cortex. So all the output of the cerebellum is inhibitory. But the deep cerebellar nuclei receive excitatory input from the mossy and climbing fibers. What might be the role of such an arrangement?

10.4 Distinct Cerebellar Regions Control Discrete Motor Functions As stated earlier, the cerebellum is divided into three areas: the cerebrocerebellum, spinocerebellum, and vestibulocerebellum. The cerebrocerebellum primarily receives information from the cerebral cortex. The cerebrocerebellum loop starts with the cortical projections to the pontine nuclei and proceeds through the middle cerebellar peduncle to the contralateral cerebrocerebellum, to the dentate nucleus, and back to the cortex of the large hemispheres via the thalamus. The cerebrocerebellum has been implicated in motor planning of hand movements. It has also been implicated in the temporal control of movements, movement initiation, and the timing of different components of movements. These findings have led to the hypothesis that the cerebrocerebellum may be involved in the timing of motor and serial events (Ivry and Keele, 1989; Diedrichsen et al. 2007). Damage to the cerebrocerebellum affects patients’ ability to judge the passage of time and consequently impairs their ability to judge if one time interval was longer or shorter than another. The spinocerebellum consists of the vermis and intermediate parts of the cerebellar hemisphere. The spinocerebellar tracts provide extensive somatosensory input from the spinal cord about limb position, touch, and pressure. The dorsal spinocerebellar tract

conveys proprioceptive information from muscle and joint receptors to the spinocerebellum. This feedback provides the cerebellum with a continuous and real-time estimate of the sensory consequences of movement, irrespective of whether the movement is generated actively or passively. In contrast, the ventral spinocerebellar tract only provides sensory feedback during active movements. This has led to the idea that the cerebellum processes active and passive movements differently and that it may be involved in comparing the sensory consequences of the movement with the actual movement (Person 2019). Purkinje neurons in the spinocerebellum project somatotopically to different descending motor pathways. First, the vermis sends axons to the fastigial nucleus, and the fastigial nucleus projects bilaterally to the brainstem, the reticular formation, and the vestibular nuclei. This way the vermis provides input to the medial descending motor pathways (see chapter 11) that primarily control postural (neck and trunk) muscles and proximal limb muscles. Purkinje neurons in the intermediate parts of the cerebellar hemispheres project to the interposed nucleus. These neurons exit through the superior cerebellar peduncle and decussate to terminate on the red nucleus (see section 11.4). Axons from the red nucleus decussate and descend to the spinal cord, forming the rubrospinal tract. The remaining axons from the interposed nucleus terminate in the thalamus. Thalamocortical neurons then project to the primary motor cortex (M1), where the corticospinal tracts originate. In this way, the intermediate cerebellum contributes to the control of distal limb muscles. The vermis is also involved in regulation of two types of eye movements, saccades and smooth pursuits. Eye movements will be described in more detail in chapter 14. Briefly, saccades are rapid eye movements that shift gaze between targets, and smooth pursuit eye movements are used to track moving objects. Lesions in the vermis impair the accuracy of both types of eye movements. The vestibulocerebellum receives sensory input from the vestibular system (i.e., the otolith organs and the semicircular canals that relay information on the head’s movement with respect to

gravity). The otolith organs and semicircular canals project to the vestibular nuclei in the brainstem that provide input to the vestibulocerebellum. The output of the vestibulocerebellum bypasses the deep cerebellar nuclei and directly reaches the vestibular nuclei. Purkinje neurons in the medial parts of the vestibulocerebellum project to the lateral vestibular nucleus to modulate the lateral and medial vestibulospinal tracts. These tracts control head and neck muscles and limb extensors and primarily contribute to posture regulation. Purkinje neurons in the lateral parts of the vestibulocerebellum project to the medial vestibular nucleus that controls eye movements and coordination between head and eye movements (i.e., the vestibulo-ocular reflex). The vestibuloocular reflex (see chapter 14) is a gaze-stabilizing reflex: the vestibular system transforms sensory signals related to head movements into motor commands to generate compensatory eye movements in the opposite direction of the head movement, ensuring the stabilization of gaze direction. This reflex is critical to stabilizing our gaze on someone’s face while we are nodding our head in agreement. PROBLEM 10.4 A person is having difficulty reading road signs while walking. Which part of the cerebellum might be damaged?

10.5 Cerebellar Control of Movement Both Purkinje cells and deep cerebellar nucleus neurons discharge during voluntary movement. These cells are tonically active at rest but change their discharge rates as movements occur. Their discharge rate varies as a function of movement speed and direction, as well as whether the muscles are relaxed or contracted.

More importantly, the change in the firing frequency with respect to movement initiation is similar to the initiation of activity in the primary motor cortex. This suggests that the cerebellum and the primary motor cortex work together for movement control. The importance of cerebellar involvement in movement control has been observed through studies of rapid arm movements. Ballistic arm movements exhibit triphasic muscle activity where the agonist muscle fires first to initiate the movement (see chapter 23). This is followed by a burst in the antagonist muscles to slow down the movement and bring the arm to rest (figure 10.5). The contraction of the antagonist starts very soon after the agonist and before any sensory feedback can be incorporated by the nervous system. Finally, there is a second burst in the activity of the agonist to prevent oscillations of the endpoint (e.g., the hand). In patients with cerebellar deficits, the timing of the onset of the antagonist activity is delayed until the limb has moved past the target (Flament and Hore 1986). In other words, the patients have to rely on sensory feedback to accomplish this movement, whereas healthy persons seem to perform the movement using feedforward neural control.

Figure 10.5    In

healthy individuals, muscle activity during rapid movements (e.g., elbow flexion) exhibits a triphasic pattern. The agonist fires first (AG1) at the beginning of the movement. This is followed by the antagonist around the peak of the movement velocity (ANT2) to slow down the limb and terminate the movement. Finally, the agonist fires again (AG3) to prevent oscillations at the end of the movement. In patients with cerebellar disorders, the antagonist’s activity is delayed (dashed line).

10.6 Consequences of Cerebellar Lesions on Movements One of the defining features of a spinocerebellar lesion is an inability to make smooth and coordinated limb movements. These lesions cause movements to become fractured into jerky and inaccurate components. This is called cerebellar ataxia. Lesions of the vermis in the spinocerebellum impair the ability of the oculomotor system to

reduce motor errors. Specifically, these lesions can cause dysmetric eye movements in the form of hypermetric saccades (overshooting targets) or hypometric saccades (falling short of targets), and the oculomotor system is unable to adequately correct for those errors (Barash et al. 1999). Damage to the vestibulocerebellum affects the ability to keep postural balance during an upright stance. Since the vestibulocerebellum is also involved in the control of eye movements, lesions in this part of the cerebellum affect the ability to maintain a steady gaze on a fixed location. Consequences of cerebellar lesions will be covered in more detail in chapter 38.

10.7 Cerebellar Contribution to Motor Learning The idea that the cerebellum is involved in motor learning of new skills was based on observations of animals with experimental cerebellar injuries of differing severity, up to the complete removal of the cerebellum. After the animals recovered, they demonstrated an ability to use their movement repertoire that had been learned prior to the surgery. However, they were unable to learn new motor skills. These and other studies led to a prominent theory that inputs from the climbing fibers provide a teaching signal that causes changes in synaptic binding within the cerebellum. Changes in synaptic binding occur through processing of sensory feedback. But how can sensory processing in the cerebellum contribute to motor learning? The cerebellum forms what are called closed-loop networks for motor control. As stated earlier, the cerebellum receives input from the inferior olive in the medulla oblongata, which in turn receives information from the cerebral cortex. Collateral outputs from the cerebellum are also sent to the red nucleus in the midbrain, which projects back to the inferior olive, providing a mechanism for cerebellar output to feed back into the cerebellar input, forming an important closed-loop network (figure 10.6). This network provides a

mechanism for the cerebellum to modulate its own input and is considered to be involved in learning through error reduction in motor performance.

Figure 10.6    The

red nucleus, inferior olive, and cerebellum form a closed-loop feedback system that facilitates motor learning through error correction.

The main proposed mechanism is error reduction in motor performance through long-term depression in the synapses between parallel fibers and Purkinje cells (Hansel and Linden 2000; Hirano 2018). Long-term depression reduces the functional strength of excitatory synapses for hours or even longer. In contrast, longterm potentiation involves strengthening of synapses that leads to a long-lasting increase in synaptic transmission between neurons. When a movement is inaccurately performed, the climbing fibers respond to those errors and depress the strength of the synapses between the parallel fibers and the Purkinje cells. If another erroneous movement occurs, the parallel fiber inputs that carry the

flawed motor signal are further suppressed. Eventually, after enough repetitions and suppression of the error signal in the climbing fibers, a more appropriate pattern of activity emerges in the Purkinje cells. PROBLEM 10.5 If a person sustains an injury to the inferior olive only, which aspect of motor behavior might be affected the most?

10.8 Cerebellar Interactions With the Basal Ganglia and Cortex The basal ganglia and the cerebellum are distinct systems that perform different functions but project to the same cortical areas through distinct thalamic nuclei. In the past, it was thought that the cerebellum and the basal ganglia only interacted at the level of the cortex through distributed modules (Houk and Wise 1995). These modules are hypothetical structures that consist of recurrent loops connecting the spiny neurons of the basal ganglia, the Purkinje cells of the cerebellum, and the pyramidal neurons of the cortex. These modules are hypothesized to function in a parallel cooperative manner for motor planning and execution. More recently, direct projections between the cerebellum and the basal ganglia have been found (reviewed in Bostan and Strick 2018). The subthalamic nucleus in the basal ganglia makes disynaptic projections to the cerebellar cortex, and the dentate nucleus in the cerebellum is the source of projections to the striatum. These observations have provided anatomical support for the idea of distributed modules by identifying the neural substrates that serve as nodes to form an integrated network between the cerebellum, the

basal ganglia, and the cortex for motor control and cognitive function.

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Chapter 11 Brainstem and Extrapyramidal Tracts KEY TERMS AND TOPICS reticular formation red nucleus superior colliculus vestibular nuclei cranial nerves descending tracts The neural structures in the brainstem are primarily involved in postural control, locomotion, and reflex-based gaze control. The output neurons from four structures—the reticular formation, superior colliculus, vestibular nuclei, and red nucleus—project to the spinal cord to innervate interneurons that ultimately lead to changes in the activation of axial and larger proximal limb muscles that serve the postural and locomotor functions. Recall that cortical motor areas are involved in the control of complex and fine motor skills that involve distal muscles, such as those involved in reaching and grasping movements, writing, and typing. The brainstem areas work together with cortical motor areas to support these actions by facilitating necessary postural control. Within the neural control hierarchy

developed by Bernstein (1947), descending projections from the brainstem structures ensure background corrections for actions controlled by cortical areas.

Figure 11.1    The

brainstem is made up of the midbrain, pons, and medulla oblongata. It connects the cerebrum of the brain to the spinal cord and cerebellum. It is involved in both sensory and motor functions.

11.1 Brainstem Anatomy The brainstem consists of the midbrain, pons, and medulla oblongata (figure 11.1), and it serves as a conduit between the brain and the spinal cord. It acts as a passageway for the ascending tracts from the spinal cord, the sensory and motor tracts of the head and neck, and the descending motor tracts from the cortex. There are also many local neural networks in the brainstem that regulate eye movements. It is also the source or the destination of most of the 12

cranial nerves that are involved in motor and sensory functions of the head, neck, and eyes. The irregular shape of the brainstem reflects the fact that it houses many different nuclei and white matter tracts. The inferior olives, which are a part of a closed-loop cerebellar network (see chapter 10), are a prominent landmark on the lateral brainstem. The corticospinal tracts go through the medullary pyramids, which form a prominent bulge on the ventral brainstem. The pons is rostral to the medulla, and the pontine nuclei of the pons are a source of major input to the cerebellum. The cerebellum is attached to the pons through the cerebellar peduncles (see chapter 10), which contain both afferent and efferent tracts to and from the cerebellum.

11.2 Reticular Formation The reticular formation is a collection of nuclei of different size scattered over the brainstem in an ill-defined manner. The phrase “reticular” itself is derived from the Latin word rete, meaning net, which alludes to the diffuse structure of this neural region. The reticular formation extends from the midbrain to the medulla, but in contrast to other subcortical areas such as the red nucleus, the reticular formation has no clearly defined cytoarchitectural boundary. The neurons within the reticular formation facilitate limb motor, oculomotor, autonomic, sensory, circadian, and mood-related functions. The axons of neurons in the reticular formation form the reticulospinal tract, a descending tract that terminates in the medial spinal cord. From here, local interneurons project to α-motoneurons that activate axial and proximal limb muscles. Despite its diverse functions, we will focus only on how the reticular formation contributes to control of posture and balance. The neurons of the reticular formation course through the midbrain, pons, and medulla. The reticular formation at the level of the midbrain is called the midbrain reticular formation, at the level of the pons is called the pontine reticular formation, and at the level of the medulla is called the medullary reticular formation (see figure 11.2). Each of

these areas serves a different function. The mesencephalic locomotor region is located in the midbrain reticular formation and is considered to be involved in locomotor rhythm generation (Roseberry et al. 2016) and the control of tonic activation of postural muscles (Garcia-Rill and Skinner 1987; Takakusaki 2017). Neurons in this region project to the medulla and then further to the spinal cord. These projections are assumed to participate in the initiation and regulation of locomotion, in particular based on classical studies of locomotion in decerebrate cats induced by electrical stimulation of this area (Shik et al. 1966; also see chapter 26).

Figure 11.2    Neurons

in the reticular formation are scattered in different parts of the brainstem. The reticular formation at the level of the midbrain is called the mesencephalic reticular formation. At the level of the lower pons, it is called the pontine reticular formation. At the level of the medulla, it is called the medullary reticular formation. The superior colliculus is in the posterior segment of the midbrain.

The paramedian pontine reticular formation is a part of the pontine reticular formation and is a collection of cells in the pons that is involved in the control of two types of eye movements, saccades and smooth pursuits (Keller 1974). Saccades are rapid eye movements that shift the gaze from one part of the visual field to

another. Smooth pursuit eye movements are slower tracking movements of the eyes that keep a moving visual stimulus on the fovea. This region contains neurons that are involved in the control of saccades. Finally, the reticular formation neurons in the medulla integrate sensory feedback signals and descending signals from the cortical motor neurons and cerebellum and organize the output to the spinal cord. The motor centers in the reticular formation receive projections from the motor cortex. These projections assist the reticular formation in the control of posture in a feedforward manner to offset the effects of impending limb movements on postural stability (Schepens and Drew 2004; Cordo and Nashner 1982). For example, if you reach to grab a cup from a high kitchen shelf, your center of pressure (the point of application of the vertical resultant force acting from the support) will move closer to the edge of the base of support, and your posture may become unstable (also see chapter 24). The reticular formation contributes to contraction of the lower limb muscles in a feedforward manner, before any of the upper limb muscles are activated (anticipatory postural adjustments) so that posture remains stable, and you don’t fall or have to make a protective step. The reticular formation is also involved in the startle response, a rapid motor response to a sudden and unexpected loud auditory stimulus (Koch et al. 1992). The startle response has two components. The first component is reflexive and occurs at short latencies. It can be seen primarily in extensor muscles of the extremities and has been interpreted as a “fight or flight” response. The second component occurs at longer latencies that resemble voluntary reaction times (figure 11.3). The reflex component of the response originates in the auditory nerve fibers that project to the cochlear nucleus, which is the first processing hub in the auditory system. From there, neurons project to the pontine reticular formation. From there, output neurons of the brainstem project bilaterally to the spinal cord areas and lead to activation of craniocervical muscles. The first burst of muscle activity in the sternocleidomastoid muscles has been recorded within 55-80 ms

after stimulus presentation, supporting the reflexive nature of this component. The second component involves an “orienting” response toward the spatial location of the stimulus and occurs later (>200 ms) (Brown et al. 1991; Dreissen and Tijssen 2012; Nieuwenhuijzen et al. 2000).

Figure 11.3    EMG

responses in lower limb muscles to auditory stimulation during locomotion. The EMG data were averaged and subtracted from both individual and averaged stimulus trials. Figure shows two facilitatory startle responses at short (~80-100 ms) and long latencies (~150-200 ms). Adapted from Nieuwenhuijzen et al. (2000).

PROBLEM 11.1 The startle response shows a phenomenon called prepulse inhibition. When a weak auditory stimulus (that does not elicit a startle response) is followed by a strong stimulus within 0.5 s that would normally elicit a response, the weak stimulus suppresses the response of the strong stimulus. In Huntington’s disease

patients, the prepulse inhibition is reduced. What would this suggest about the interactions between the basal ganglia and the reticular formation?

11.3 Superior Colliculus The superior colliculus is another brain structure in the midbrain part of the brainstem that transforms sensory input from multiple sensory modalities into motor output (figure 11.2). Output neurons in the superior colliculus project to neurons in the reticular formation that in turn project to the spinal cord, leading to the activation of muscles, primarily axial and proximal limb muscles (Werner 1993; Stuphorn et al. 1999; Philipp and Hoffmann 2014). The firing patterns of cells in these areas resemble those of neurons in other sensorimotor regions, such as the motor cortex and premotor areas, and it appears that these neurons are involved in the control of reaching movements. However, the precise role that they play in conjunction with neurons from the cortical areas is still unknown. One of the main functions of the superior colliculus is to direct sensory structures, such as the eyes, toward visual stimuli of interest. This behavior is known as orienting and includes both head movements and saccades that redirect the gaze. The superficial layers of the superior colliculus receive direct projections from the retina, providing sensory input, and the intermediate and deep layers serve the oculomotor function by controlling saccadic eye movements. The deep layer contains an organized motor map in each hemisphere for controlling movements aimed at visual stimuli in the contralateral visual field. Thus, visual sensory inputs originating in the left hemifield reach the right superior colliculus, which in turn generates leftward orienting movements, and vice versa. This multilayer structure of the superior colliculus allows it to serve an important function, rapid transformation of sensory signals into motor output.

The superior colliculus receives substantial projections directly from retinal axons and cortical visual association areas (Boehnke and Munoz 2008). They also receive input from the ascending somatosensory and auditory pathways. In fact, many cells in the superior colliculus are multimodal, showing responses to visual, auditory, and somatosensory stimuli derived from cortical and ascending inputs. This allows the superior colliculus to integrate sensory information across multiple modalities. The multisensory neurons in the superior colliculus also receive descending input from multisensory neurons in the association cortices (parietal and frontal cortex). Multisensory integration allows for consolidation of sensory information from specific sensory modalities (vision, audition, etc.) by pooling of sensory information from different modalities into a single multisensory stream to facilitate faster motor responses (Senkowski et al. 2008). Imagine that you are sitting in a dark room and are asked to make a pointing movement toward a stimulus that can either suddenly flash or make an audibly loud sound. You will be able to initiate the pointing movement sooner if the stimulus both flashes and emits a sound at the same time, compared to a situation when it only flashes or emits a sound.

11.4 Red Nucleus The red nucleus is a relatively large group of cells located in the rostral midbrain and is reddish pink in color, likely because of the presence of iron-protein complexes (figure 11.2). The ascending and descending projections from the red nucleus were first studied in monkeys by Hans Kuyper and Don Lawrence in 1968. They found that the descending tracts originating from the red nucleus terminate in the lateral regions of the spinal cord, where α-motoneuronal pools are located, innervating distal limb muscles. This suggests that the red nucleus may be involved in the control of upper extremity muscles. However, the rubrospinal tract, the descending tract that originates in the red nucleus, originates from magnocellular neurons,

and these neurons constitute only a small fraction of the neurons in the red nucleus in primates and humans, making it unlikely that the red nucleus is a significant contributor to the neural control of movements in higher mammals. A majority of the neurons in the red nucleus are parvocellular neurons that do not project to the spinal cord but instead facilitate communication between the red nucleus and the cerebellum through the inferior olive. This implicates the red nucleus in motor networks involving the cerebellum, especially in functions that involve limb posture control (Herter et al. 2015). PROBLEM 11.2 You are talking to a friend at an outdoor party when suddenly through your peripheral vision you see a large object (an inflated ball) rapidly approach your head. What kind of motor response would you expect to make, and which brainstem structure would make that possible?

four components of the vestibular nuclei serve important functions for controlling eye movements and postural equilibrium. The efferent projections from the vestibular nuclei project to the nuclei of other cranial nerves (III, IV, and VI). Lat = lateral; Sup = superior; Med = medial; Inf = inferior. Figure

11.4    The

11.5 Vestibular Nuclei Located in the medulla and pons of the hindbrain, the vestibular nuclei are a highly interconnected complex consisting of four major nuclei that integrate information from the vestibular afferents, the somatosensory receptors, and the cerebellum (figure 11.4). They are also the origins of the vestibulospinal tracts that play a major role in maintaining equilibrium, posture control, and eye movements during head rotations. Projections from these nuclei affect the activity of extraocular muscles as well as of postural muscles of the back,

neck, and extremities. Thus, the vestibular nuclei are responsible for feedback, or responding to a disturbance of body posture and stability. The lateral vestibular nucleus serves the vestibulospinal reflex. This reflex contributes to the control of vertical posture by its effects on the proximal extensor muscles of the limbs. The medial vestibular nucleus mediates the vestibulo-ocular reflex (VOR). This reflex is a gaze-stabilizing reflex where sensory signals encoding head movements are transformed into signals to extraocular muscles, which generate compensatory eye movements in the opposite direction of the head movement. As a result, we can fixate gaze on objects during head movements. To maintain balance, this nucleus also controls head and neck movements via the medial vestibulospinal tracts. The third nucleus is the superior vestibular nucleus, and it facilitates the coordination of posture and movements by contributing to postural adjustments, as well as by providing neural signals for eye movements. It is the most rostral of the vestibular nuclei. Finally, the inferior vestibular nucleus is the most caudal nucleus. It receives information on head tilt and gravity from the otolith organs. PROBLEM 11.3 Which brainstem structure would play an important role in posture stabilization if we were unexpectedly pushed from behind?

12 cranial nerves of the nervous system shown along a transverse view of the brainstem and cortex. Figure

11.5    The

11.6 Cranial Nerves The brainstem is the source and target of a vast majority of the 12 cranial nerves in the nervous system (figure 11.5). The cranial nerves are involved in sensory and motor functions of the head and neck and create local circuits in the brainstem for integrating both afferent and efferent information. Though the cranial nerves are considered a part of the peripheral nervous system, not all cranial nerves are arrayed along the brainstem. Two cranial nerves, the olfactory nerve (I) and the optic nerve (II), enter the forebrain directly. Except for the trochlear nerve (IV), the remaining cranial nerves leave and enter on the ventral surface of the brainstem. The trochlear nerve emerges from the dorsal side of the brainstem and originates at the level of the inferior colliculus. The sensory and

motor functions of the cranial nerves and their points of origin on the brainstem are listed in table 11.1.

11.7 Descending Tracts Descending tracts convey motor information from the brain areas to the spinal cord and cranial nuclei, and can be broadly divided into two categories, pyramidal and extrapyramidal tracts. The pyramidal tracts, the corticospinal and corticobulbar tracts, originate in the cerebral cortex and carry axons to the spinal cord and brainstem. The pyramidal tracts are described in greater detail in chapter 8. Briefly, the corticospinal tract affects the neuronal apparatus of the spinal cord involved in the control of the musculature of the limbs and the trunk. The corticobulbar tract affects motor cranial nerves that innervate the musculature of the head and the neck. The corticospinal tract originates mainly from the primary motor cortex, premotor cortex, supplementary motor areas, and somatosensory cortex. The extrapyramidal tracts originate in different areas of the brainstem. These pathways are the reticulospinal, colliculospinal or tectospinal, rubrospinal, and vestibulospinal tracts (figure 11.6). The main roles of these pathways are in providing background corrections such as regulating posture during voluntary movements. Table 11.1    Cranial Nerves and Their Main Sensorimotor Functions Sensory or Cranial nerve

Nerve

motor

Function

I

Olfactory

Sensory

Smell

II

Optic

Sensory

Vision

III

Oculomotor

Motor

Eye movements

IV

Trochlear

Motor

Eye movements

V

Trigeminal

Sensory and motor

Somatic sensation from face, mastication muscles

Sensory or Cranial nerve

Nerve

motor

Function

VI

Abducens

Motor

Eye movements

VII

Facial

Sensory and motor

Facial expression muscles, taste from tongue

VIII

Vestibulocochlear

Sensory

Hearing, balance sense

IX

Glossopharyngeal

Sensory and motor

Sensations from tongue, chemoreceptors

X

Vagus

Sensory and motor

Vocal cord muscles, swallowing

XI

Spinal accessory

Motor

nerve XII

Hypoglossal nerve

Shoulder and neck muscles

Motor

Tongue movement

The reticulospinal tract originates in the pontomedullary reticular formation and is an important descending tract for motor control and a hub for sensorimotor integration that allows the nervous system to make limb movements while stabilizing overall posture. The pontomedullary reticular formation receives input from the motor areas of the cerebral cortex. The tract that starts in the medulla constitutes the lateral reticulospinal tract, and the fibers in this tract descend bilaterally in the spinal cord near the corticospinal axons. The fibers from the pontine region travel in the ventromedial region of the spinal cord. Both these tracts descend ipsilaterally and project to axial and proximal limb muscles and are important regulators of posture. The pontine and medullary nuclei that give rise to the reticulospinal tracts receive cortical input from the premotor cortex and to a lesser extent from the supplementary motor cortex. This system is called the cortico-reticular system. Because reticulospinal systems primarily influence extensor muscles, including the paravertebral extensors as well as those of the limbs, the corticoreticulo-spinal system provides the cortex with the means to

influence antigravity extensor musculature in parallel with its regulation of purposeful actions while standing. The tectospinal tract (or the colliculospinal tract) is a bilateral nerve tract that originates from cells in the superior colliculus and projects to the neurons in the cervical spinal cord that coordinate eye, head, and neck movements. The axons in this pathway descend around the periaqueductal gray matter and then decussate at the point called the dorsal tegmental decussation. Along with the reticulospinal and vestibulospinal tracts, the fibers of this tract are a part of the medial system of the descending tracts.

Figure 11.6    The

approximate origins of the four main brainstem tracts involved in

motor control.

The tectospinal tract is considered to be mainly involved in orienting eyes and head toward auditory and visual stimuli. It is involved in responding to sudden and loud auditory stimuli, aka the startle response. The afferent sound is detected by the brainstem, which processes the sound and responds by activating cervical muscles. The tectospinal tract connects with interneurons in the cervical spinal cord, which then project to neck motor nuclei. In this way, the auditory stimuli cause the instinctive movement of the head and neck toward the perceived sound. One surprising discovery made by Nudo and Masterton (1989) was that the number of fibers

in the tectospinal tract in mammals is surprisingly small. Raccoons and cats have 628 and 909 fibers in the tectospinal tract, respectively, but in seven species of primates that these authors studied, they only found an average of 220 fibers. Thus, it is unclear how important a role this pathway plays in human motor control. The vestibulospinal tracts are one of the medial pathways in the extrapyramidal system, and they arise from the vestibular nuclei of the hindbrain. The vestibulospinal neurons receive neural input from the vestibular division of the eighth cranial nerve labyrinthine receptors in the inner ear, from the vestibulocerebellum mediated by the fastigial nucleus, and from some proprioceptive afferent input from the spinal cord. These tracts are involved in the initiation of coordinated postural extensor activity in the limbs and trunk. The first major projection of the vestibular complex to the spinal cord is the lateral vestibulospinal tract, which arises from the lateral and inferior vestibular nuclei at the level of the pons and medulla and projects to all levels of the ipsilateral spinal cord, where it terminates in the ventral gray horn and leads to changes in the activation of proximal limb muscles. This tract activates the limb extensor muscles when the vestibular system communicates deviation from upright posture (vestibulospinal reflex). This reflex induces changes in the activity of limb muscles at the level of the lumbar spinal cord when unexpected head movements stimulate labyrinthine receptors and destabilize posture. The second projection of the vestibular complex is the medial vestibulospinal tract, which arises from the medial and inferior vestibular nuclei at the level of the pons and medulla and descends bilaterally into the spinal cord. This tract innervates spinal segments that control the muscles involved in supporting the head and therefore only passes to the cervical region. This tract controls head position through reflex activation of neck muscles (vestibulocervical reflex) when the head suddenly rotates to indicate an unstable posture. Note that the vestibulocervical reflex is also a vestibulospinal reflex, but it acts at cervical spinal levels instead of lumbar levels.

The final descending tract in the extrapyramidal system is the rubrospinal pathway. The fibers of this pathway originate in the red nucleus. However, unlike the other three pathways described earlier, this tract is located in the lateral white matter of the spinal cord, and the axons of this pathway terminate in the lateral regions of the spinal cord. Recall that the neural circuits involved in the control of distal muscles of the upper extremity are located in the lateral white matter. This would suggest that the rubrospinal pathway may be involved in fine upper extremity motor control. However, as stated earlier, this hypothesis is questionable because the axons of the rubrospinal tract arise from large magnocellular neurons, and these neurons are a relatively small percentage of the neurons in the red nucleus of primates and humans. Therefore, it is unclear if this pathway plays a major role in motor control in primates and humans.

CHAPTER 11 IN A NUTSHELL The

reticular

colliculus,

formation, red

superior

nucleus,

and

vestibular nuclei are four subcortical regions involved in motor control. The descending these

tracts

areas

originating

are

called

reticulospinal, rubrospinal,

from the

tectospinal, and

vestibulospinal,

respectively. The reticular formation is located in the rostral midbrain to the caudal medulla. It is involved in the coordination of axial and proximal limb

muscles,

standing

and

in

particular

walking.

The

during superior

colliculus

is

a

major

hub

for

processing sensory information and for reflexive

actions

orienting

movements

from

salient

stimuli.

The

nucleus

that toward

visual main

is

involve

and

role in

of

or

away

auditory the

red

facilitating

communication between motor nuclei in the

cortex

vestibular

and

the

nuclei

cerebellum. are

the

The

major

destination of the axons that form the vestibular cranial the

division

nerve.

vestibular

muscles

and

The

of

the

eighth

projections

nuclei

proximal

control limb

from axial

muscles.

They play an important role in gaze stabilization. There are a total of 12 cranial nerves that serve sensory and motor

functions,

and

most

arise from the brainstem.

of

them

Problems for Part II

Self-Test Problems 1. Under the action of a new drug, the outputs of all the cerebellar nuclei are increased 10-fold. What changes in movements can be expected during standing, walking, and reaching? 2. The neuronal population vector in a brain structure points consistently in the direction of hand movement when a monkey performs a reaching task from a standard position to targets distributed along a circle (center-out task). The researcher draws a conclusion that the brain structure encodes a hand velocity vector in space. Offer alternative interpretations of this finding. 3. A subject is asked to imagine performing a motor task, such as a fast arm movement. No actual movement or change in the muscle activation levels occurred. In what structures of the central nervous system would you expect to see changes in the background activity of the neurons? In what structures involved in the generation of actual movement would you expect to see no changes in the neuronal activity? 4. The coils of two transcranial magnetic stimulators have been placed over the right and left primary motor cortices. When one of them generates a single stimulus, a response is seen in the contralateral arm muscles at a latency of about 20 ms. When the other stimulator produces a stimulus a few milliseconds prior to the first one, the response decreases. What neurophysiological mechanisms are likely to be involved in the modulation of the response? 5. A drug has been discovered that increases the efficacy of the projections from the putamen to the external part of the globus pallidus by a factor of 10. A healthy person takes a single dose of the drug. What changes would you expect to see in their motor performance? 6. If a patient with Parkinson’s disease makes a saccade to a target, where would you expect the saccade to land? On the

target, short of the target, or beyond the target? Why?

For Those Addicted to Multiple-Choice Tests You have 20 minutes. Circle only one answer (statement) for each question. Write a short phrase explaining why you chose this answer. 1. The output neurons of the cerebellum a. project on alpha-motoneurons in the spinal cord b. excite their target neurons c. project on the locomotor generator in the spinal cord d. can generate action potentials of different shapes e. are the smallest cells in the cerebellum Why? 2. The two major pathways through the basal ganglia differ in the following ways: a. One of them is a positive feedback loop and the other is a negative feedback loop. b. One of them projects on the thalamus, while the other one projects directly on the cortex. c. One of them involves projections on the cerebellum, while the other does not. d. Only one of them is modulated by signals from the substantia nigra. e. All of the above Why? 3. How do we know that basal ganglia neurons are involved with a decision to move? a. Neurons in the basal ganglia fire long before movement initiation. b. Neurons in the basal ganglia fire after motor cortex neurons. c. Neurons in the basal ganglia contain a topographic map of the body.

d. The basal ganglia receive extensive projections from the cerebellum. e. All of the above Why? 4. How do the roles of the premotor cortex and motor cortex differ for the control of limb movements? Select the correct statements. a. The primary motor cortex is responsible for movement initiation. b. The premotor cortex is involved in motor planning. c. The corticospinal tract consists of axons originating from both the premotor cortex and the motor cortex. d. The primary motor cortex has more monosynaptic connections to α-motoneurons than the premotor cortex. e. All of the above Why? 5. The cerebellum does not project to the spinal cord. Then how does cerebellar activity influence how motor neurons in the spinal cord affect movement? a. The cerebellum projects through the thalamus to the primary motor cortex and is indirectly involved in movement planning and posture control. b. The cerebellum is responsible for the initiation and termination of movement. c. The cerebellum is involved in movement coordination. d. Both a and b are correct. e. Answers a, b, and c are correct. Why?

Part III Sensory Basis of Motor Control

Chapter 12 Central Processing of Somatosensory Information KEY TERMS AND TOPICS first-order neurons second-order neurons third-order neurons proprioceptive system primary and secondary somatosensory cortex integration of somatosensory input with other sensory modalities injuries to somatosensory pathways In this chapter, we continue the discussion of mechanisms involved in processing sensory information. Chapter 6 reviewed peripheral sensory endings sensitive to such mechanical variables as muscle length, velocity and force, joint angle, and skin deformation. Here we cover transmission of this information through the central nervous system to cortical areas believed to play an important role in perceiving relevant variables and guiding limb movements in the environment. This topic is to be continued in chapters 28, 29, and

30, where we discuss in more detail both perceptual and motor functions that rely on somatosensory information.

12.1 First-Order Neurons The first-order neurons in the peripheral nervous system carry information about somatosensory (tactile and proprioceptive) stimuli to the central nervous system. The cell bodies of these first-order neurons are located in the dorsal root ganglia of the spinal nerves. These neurons are pseudounipolar, meaning that they have a cell body with a T-shaped axon (but no dendrites). The distal end of the axon innervates somatosensory receptors (sensory endings), and the proximal end synapses with second-order neurons in the spinal cord of the brainstem. When these first-order axons enter the dorsal horn of the spinal cord, they send collateral branches into different spinal segments and synapse on motor neurons in the ventral horn or interneurons. A major portion of the incoming axons travel rostrally and ipsilaterally in a bundle called the dorsal column to the lower medulla. The dorsal column is organized topographically with fibers from the lower limbs traveling medially in a bundle called the gracile tract. The fibers from the upper limbs and the trunk travel in a more lateral bundle called the cuneate tract. These tracts terminate in different subdivisions of the dorsal column nuclei, called the gracile nucleus and the cuneate nucleus, respectively, where they synapse on second-order neurons (figure 12.1).

Figure 12.1    The

ascending pathways of the somatosensory system. The dorsal column carries signals from the same side of the body to the medulla. The cuneate nucleus in the medulla receives afferent input from the hand and forelimb. The gracile nucleus is more medial to the cuneate nucleus and receives information from the lower body. Second-order neurons in the medial lemniscus carry information to the thalamus. Third-order neurons from the thalamus carry information to the somatosensory cortex.

The axons entering the dorsal roots divide into ascending and descending systems. It is important that some neurons entering the dorsal roots synapse directly on motoneurons in the ventral horn. This circuit forms the basis of the monosynaptic stretch reflex. The stretch reflex or the myotatic reflex (an obsolete term) refers to a muscle contraction in response to stretching of muscle fibers. The proprioceptive afferent axons in the ascending branches travel along with axons of tactile afferents in the dorsal column.

12.2 Second-Order Neurons The dorsal column nuclei are the source of input to the second-order neurons, which then project to the thalamus. These axons, called the internal arcuate fibers, cross the midline of the body and form a tract called the medial lemniscus. The crossing-over of tracts is called decussation and seems to occur in vertebrates because of an axial twist of the forebrain during evolution (de Lussanet and Osse 2012). The axons of the medial lemniscus carrying tactile and proprioceptive information from the lower limbs and upper limbs travel separately before they enter the ventral posterior lateral (VPL) nucleus of the thalamus. Surprisingly, and in contrast to the organization of neurons in the dorsal column and later in the somatosensory cortex, the axon bundle in the medial lemniscus rotates 90º laterally and flips the axons from second-order neurons carrying information from the upper body into the medial section of the tract and the axons from second-order neurons carrying information from the lower body into the lateral section. Therefore, if

an injury occurs in the lateral section of the medial lemniscus, it will likely affect the lower body.

12.3 Third-Order Neurons Third-order neurons from the thalamus send their axons via the internal capsule to the ipsilateral postcentral gyrus, the primary somatosensory cortex. These neurons will terminate in layer IV of the somatosensory cortex. The internal capsule is a white matter structure composed of myelinated fibers that carry information from the brainstem to the cerebral cortex and vice versa.

12.4 Proprioceptive System There is a key difference between the proprioceptive and tactile systems. In particular, axons carrying proprioceptive information reach both the primary somatosensory cortex and the cerebellum. The pathway to the somatosensory cortex is considered critical for sensing limb position, force, and stereognosis, whereas the proprioceptive pathway to the cerebellum is involved in “unconscious” proprioception and in the control of the timing of muscle contractions. This “unconscious” proprioceptive information from muscles and the Golgi tendon organs is carried from one side of the body to the same side of the cerebellum (ipsilaterally) through the spinocerebellar tract. First-order proprioceptive neurons that enter the spinal cord via the dorsal roots travel through the dorsal column and synapse on Clarke’s nucleus. This nucleus is found approximately from levels T1 to L3 of the spinal cord. The second-order neurons from Clarke’s nucleus project their axons via the ipsilateral posterior column of the spinal cord in a tract called the dorsal spinocerebellar tract. Most axons traveling in the dorsal spinocerebellar tract arise from the cells of Clarke’s nucleus. The dorsal spinocerebellar tract ascends to the level of the medulla and then enters the cerebellum. Interestingly, collaterals of the axons from the dorsal spinocerebellar tract

decussate and join the medial lemniscus on the way to the thalamus. This suggests that even the pathways that we consider to be involved in unconscious proprioception indirectly communicate with the primary somatosensory cortex. The functional role of these pathways is not entirely clear, but it is believed that they may be involved in long-term motor learning and formation of motor memories. PROBLEM 12.1 Why would the nervous system only send a copy of the proprioceptive information, and not tactile information, to the cerebellum?

12.5 Primary and Secondary Somatosensory Cortex The primary somatosensory cortex (S1) in the postcentral gyrus is a primary receptor of sensory data from the skin, muscles, tendons, and joints of the body. It comprises four distinct Brodmann’s regions (1, 2, 3a and 3b) and mainly receives information from the ventral posterior complex of the thalamus. Each of these four Brodmann areas contains a distinct somatotopic map of the body; the lower limbs and trunk are represented more medially, and the upper limbs and face are represented more laterally in S1. Neurons in areas 1 and 3b respond primarily to tactile stimuli. Area 3a receives proprioceptive information, originating mainly from the muscle spindles. Area 2 neurons respond to both tactile and proprioceptive stimulation (figure 12.2). Area 3b sends many projections to areas 1 and 2, and consequently plays a very important role in the processing of tactile information and integration of tactile and proprioceptive information. Lesions to area 3b will almost certainly have significant consequences for the loss of tactile sensation.

Figure 12.2    Brodmann

areas 1, 2, 3 of the primary somatosensory cortex. Area 3a is more ventral than area 3b in the postcentral gyrus. The output of the primary somatosensory area reaches Brodmann areas 5 and 7 in the parietal cortex, where it gets integrated with sensory information from other stimuli.

In the 1950s, Penfield and Rasmussen published a detailed account of how different body parts are represented in S1 (Penfield and Rasmussen 1950). They showed that different body parts do not have a proportionate size-based representation in S1. The face and fingers have much larger representations in S1. In contrast, the trunk and proximal upper and lower limbs have much smaller representations. This organization reflects the fact that humans need high spatial acuity and dedicated neural circuits for complex motor maneuvers such as object manipulation, speech production, and generation of facial expressions. The density of sensory afferents is much greater in the face and fingers than in the other parts of the body, which have a smaller representation in S1. This organization of S1 has also been called the sensory homunculus (see figure 12.3). Note that the sensory homunculus is a topographic map of the contralateral side of the body parts along the postcentral gyrus of the cerebral cortex. The homunculus is where the sensations from the body parts are processed and mapped.

S1 neurons send out somatosensory information to other cortical areas, such as the Brodmann areas 5 and 7 in the parietal cortex (figure 12.2). For example, all S1 areas project to the secondary somatosensory cortex (S2). Unlike S1, which primarily responds to contralateral stimulation, tactile stimulation leads to bilateral activation in S2. S2 is involved in the processing and integration of somatosensory stimuli for further high-order processing and functions. S2 is also known to project to limbic areas, the amygdala and the hippocampus, and these projections are considered to be involved in memory and learning of tactile information. More recent studies suggest that S2 plays a role in the conversion of touch sensation to a conscious perception (Rossi-Pool et al. 2021).

Figure 12.3    Frontal

view of the sensory homunculus is a map of the body in the somatosensory cortex. Adjacent regions of the body are represented next to each on the map. Body parts with smaller receptive fields of tactile neurons have a disproportionately larger representation in the somatosensory cortex.

12.6 Integration of Somatosensory Input With Other Sensory Modalities Neurons in S1 also project to areas 5 and 7 in the parietal cortex. The projections to the parietal cortex relay the current muscle state (muscle length, velocity, and force) to the visual areas in the parietal cortex. The parietal cortex is also the site for the integration of somatosensory and visual information with information from the vestibular system (chapter 13). By virtue of these projections, parietal areas integrate and process multisensory information. These parietal areas then project the processed and integrated signals from multiple modalities to the premotor and motor cortex in the frontal cortex for preparation and execution of goal-directed movements.

12.7 Injuries to Somatosensory Pathways Tabes dorsalis occurs because of an untreated syphilis infection, and it causes slow degeneration of the nerve cells and fibers that carry somatosensory information to the brain. These nerves are in the dorsal columns and carry somatosensory information from the same side of the body. The disease occurs more frequently in males than in females and begins commonly during midlife. Persons with tabes dorsalis are severely impaired in functionally important movements such as standing and walking. They can perform these tasks only with eyes open (i.e., using visual information to substitute for the lacking or severely impaired somatosensory information). If not treated properly, tabes dorsalis can lead to paralysis. Stroke-induced lesions to the somatosensory cortex affect both proprioceptive function (Kenzie et al. 2014; Findlater and Dukelow

2017) and tactile acuity (Tyson et al. 2008). The loss of these functions has a direct impact on motor behavior. In any activity of daily living, where people don’t overtly look at the arm during the execution of a task, loss of proprioceptive function will have a deleterious impact on the ability to dexterously control the arm during skill execution (also see chapter 39 for stroke-related deficits). PROBLEM 12.2 Tabes dorsalis is a disorder in which there is demyelination of the axons in the dorsal column of the spinal cord. If an individual with this disorder has suffered unilateral damage to axons, would somatosensory function be altered on the ipsilateral side of the body or the contralateral side? There is a rare disorder, peripheral large-fiber neuropathy, that is accompanied by loss of conduction of action potentials along firstorder myelinated afferents. Patients with this condition, sometimes referred to imprecisely as “deafferented persons,” have no segmental reflexes and do not feel their bodies (Cole and Paillard 1995). They have to learn how to perform functional movements with the help of visual information, and even after many years of adaptation, they still present slow and deliberate movements with impaired interjoint coordination (Rothwell et al. 1982a; Sainburg et al. 1993; Sarlegna et al. 2010).

CHAPTER 12 IN A NUTSHELL Somatosensory in

the

information

peripheral

originates

receptors

in

the

skin, muscle spindles, and tendons and makes its way to the central nervous system

through

a

series

of

neurons.

The

first-order

neurons

carry

information from the ipsilateral side of the body to the spinal cord and the lower medulla. This bundle of axons is called the dorsal column. The firstorder neurons in this column synapse on

the

second-order

decussate

and

information

neurons

that

carry

somatosensory

the

contralateral

to

nuclei of the thalamus. The bundle of axons

that

neurons

carry

are

lemniscus. carry

the

called

The

the

primary primary

the

third-order

information

through

second-order

from

internal

the

somatosensory

thalamus to

the

cortex. cortex

topographically

organized.

and

are

legs

neurons

capsule

somatosensory

the

medial

The

(S1)

The

represented

is

trunk more

medially, and the hand and the face areas are represented more laterally. Information

from

S1

is

projected

to

higher-order sensory areas such as S2 and

areas

cortex

for

integration modalities.

5

and

7

further with

in

the

parietal

processing other

and

sensory

Chapter 13 Vestibular and Auditory Systems KEY TERMS AND TOPICS otolith organs semicircular canals stereocilia, kinocilium vestibular nuclei vestibulocochlear nerve vestibulo-ocular reflex oscillopsia vestibulocervical reflex vestibulospinal reflex cochlea inferior colliculus primary auditory cortex Wernicke’s area The vestibular system provides the sense of whole-body balance and information about head position in space. It also allows the nervous system to initiate fast compensatory movements to restore balance in response to both externally generated and self-imposed

mechanical perturbations. The vestibular system also projects to cortical areas to provide perception of gravity, movement, and orientation. In addition, the vestibular nuclei also provide signals to motoneurons innervating extraocular muscles and play a critical role in the vestibulo-ocular reflex. These reflexes are important for stabilizing gaze in space during head movement. The auditory system allows us to localize the origin of sound in space, as well as understand speech and language. There are neuroanatomical pathways that reciprocally connect the auditory and motor cortices and provide a link for motor-related neural signals to influence auditory cortical activity, but the functional significance of these pathways is not yet clear.

13.1 Transduction in the Vestibular System The peripheral vestibular system encodes translational and rotational head motion in three dimensions using two different sensors: the otolith organs, which detect linear motion, and the semicircular canals, which detect rotational motion. Otolith organ afferents respond to linear accelerations in all three dimensions, including static head tilts relative to gravity. This makes the otoliths well suited to convey to the central nervous system changes in head orientation and to contribute to the sense of vertical balance. In contrast, semicircular canal afferents encode angular velocity of the head during yaw, pitch, and roll in three dimensions (see figure 13.1). The peripheral component of the vestibular system is the labyrinth, a set of continuous chambers that consists of two otolith organs, the saccule and the utricle, and the three semicircular canals. Between the membranous labyrinth and the bony walls is the perilymph, whose ion composition is close to that of the cerebrospinal fluid. Ion pumps provide the unusual ion composition of the endolymph so that its potential is +80 mV with respect to the surrounding perilymph. Hair cells within the inner ear have an

intracellular potential of −60 mV, which adds up to 140 mV of electrical driving potential to drive K+ across open transduction channels into the hair cell. This depolarizes the hair cell and opens voltage-gated channels for K+ and Ca++ located in the hair cell.

Figure 13.1    (a)

The vestibular organs in the inner ear consist of otolith organs (i.e., utricle and saccule, which sense linear acceleration) and three almost orthogonal semicircular canals, which sense rotational acceleration. The vestibular nerve projects signals from otoliths and semicircular canals to the central nervous system. (b) The vestibular system encodes linear movement in three-dimensional space denoted as front, back, left, right, up, and down directions (by otolith organs) and rotational movements (i.e., yaw by the horizontal canal and pitch and roll by both anterior and posterior canals).

Linear motion of the head is detected by the two otolith organs, the saccule and the utricle. These two similar organs lie against the walls of the inner ear. The receptors for these two organs, maculae, are hair cells. Overlying the hair cells is a gelatinous layer called otolithic membrane that consists of calcium carbonate crystals called otoconia. The relatively heavier otoconia add inertia to the otolithic membrane. So, when the head tilts, the gravitational pull causes the membrane to move relative to the macula, and the resulting parallel force displaces the hair bundles and produces a change in the electric potential on the receptor membrane. Stereocilia are the key mechanosensors of hair cells, and the orientation of the stereocilia toward the kinocilium changes the receptor potential. Kinocilium is the longest cilium located on the hair cell next to many stereocilia. When the stereocilia lean toward the kinocilium, the cell is depolarized, and there is an increase in the vestibular nerve activity. In contrast, when the stereocilia tilt away from the kinocilium, the cell is hyperpolarized, and there is a decrease in afferent nerve activity. In the utricle, the kinocilia are oriented toward the middle line called striola, and in the saccule they are oriented away from it. The different orientations of the saccule and utricle allow the vestibular system to detect head tilts in different directions. Semicircular canals detect head rotations arising from either voluntary movements or from angular accelerations caused by external forces, such as on a roller coaster ride. The three semicircular canals, almost at right angles to each other, encode head rotations along three perpendicular axes. Each of the three canals has at its base an expansion called an ampulla that houses the crista. The crista contains hair cells that extend out into a gelatinous mass called the cupula, which extends along the entire length of the ampulla. In contrast to the saccular and macular hair cells, all hair cells in the crista are organized with their kinocilia pointing in the same direction (see figure 13.2).

Figure 13.2    The

ampulla of the semicircular canal and a cross-sectional view of the vestibular hair cells. Head rotation causes the membranous canal to distort the cupula.

When head rotation occurs in the same plane as a semicircular canal, the inertia produces a force across the cupula, moving it away from the direction of the head rotation. When the cupula moves in one direction, the entire population of hair cells is depolarized, and vice versa; movement in the opposite direction causes hair cell hyperpolarization. Orthogonal rotations have no effect on the cupula. The semicircular canals work in pairs in the opposite ears. Head rotations move the cupula in opposite directions for the two opposite canals, causing one to depolarize and another to hyperpolarize. The hair cells in the canals toward which the head is turning are depolarized, and those on the opposite side are hyperpolarized. Translational movements, in contrast, produce equal forces on the two sides of the cupula, so no hair cells are displaced. This allows the semicircular canals to encode only rotational movements arising from either voluntary movements or external forces. PROBLEM 13.1 If an animal has a damaged otoconia, which type of head movement would it have difficulty detecting?

13.2 Vestibular Afferents Respond to Head Motion Axons of the otolith organs and semicircular canals exhibit spontaneous levels of high activity. Thus, they can convey information by both increasing and decreasing their firing rates. For otolith organs, the firing rates increase or decrease based on the direction of the head tilt. The response rate of the neurons remains elevated (or depressed) as long as the head remains tilted— meaning that the tonic activity of the neurons encodes the static force on the head. In contrast, when there is a sudden translational movement of the head, such as what the head experiences when a vehicle suddenly accelerates, there is a transient increase or decrease in the firing rate of the otolith organs. The firing rate of the receptors in the semicircular canals increases when the head rotation accelerates and the cupula is deflected in one direction, and the firing activity decreases when the head decelerates and the cupula is rotated in the opposite direction. This receptor apparatus is very sensitive and can detect angular acceleration as small as 0.1°/s2. Note that physical displacements of the cupula are less than 10 nm, comparable to those produced by low-amplitude sound in the auditory system. During rotation at constant speed, the firing rate returns to baseline levels. Head rotations at constant speed can be encountered during flights and slow rides in amusement parks. PROBLEM 13.2 A woman finds her shoelaces undone, and she bends down and tilts her head downward to tie her shoes. She then straightens her head back up again. How would the firing rate of the vestibular nerve change during this activity?

13.3 Central Projections From the Otolith Organs and Semicircular Canals The vestibular organs communicate via cranial nerve VIII (vestibulocochlear nerve), which synapses in the brainstem and the cerebellum. The cell bodies of the neurons of the vestibular section of the vestibulocochlear nerve are in the vestibular nerve ganglion (also called Scarpa’s ganglion). These neurons are bipolar. The peripheral processes innervate the otolith organs and the semicircular canals, and the central processes project to the vestibular nuclei and the cerebellum. The vestibular nuclei are located in the medulla and pons of the hindbrain. Afferent signals from the otolith organs and semicircular canals converge in the vestibular nuclei. An important thing to note is that the receptor potentials generated by the hair bundles in the otolith organs do not distinguish between static head tilts and translational motions of the head. Otolith organs are excited tonically by static head tilts and phasically by translational movements of the head, whereas the semicircular canals are only excited by head rotations that accompany tilts. Otolith afferents respond to inertial motion (e.g., head motion of a passenger when a bus suddenly accelerates) and a change in head orientation relative to gravity. To disambiguate head motion arising from different sources, the vestibular system also uses signals from the semicircular canals and combines those signals more centrally in the vestibular nuclei and the cerebellum. In fact, the mixing of the signals from otolith organs and the semicircular canals in the vestibular nuclei makes it possible for the nervous system to disambiguate translational and rotational head movements. Thus, when there is a head tilt, integration of information from both the otolith organs and the semicircular canals in the vestibular nuclei and

the cerebellum can be used to disambiguate head tilts from translational movements of the head. The cerebellum, specifically the vestibulocerebellum and spinocerebellum (see chapter 10), is a major destination of vestibular afferent information, and the cerebellum in turn projects back to the vestibular nuclei. The major nodes in the cerebellum include the flocculus, nodulus, uvula, and rostral fastigial nuclei. The nodulus and uvula integrate information from otolith organs and semicircular canals to disambiguate head tilts from translation. Another important role played by the cerebellum is that it differentiates vestibular signals that arise from self-motion and external forces. For example, if a ballet dancer slips and their head rotates backward, the vestibular system will trigger protective reflexes, but if the same posture is acquired by the dancer during a performance, then the cerebellum will suppress any protective reflexes. It has been hypothesized that predictive signals in the cerebellum cancel out the ascending vestibular information in the rostral fastigial nucleus (reviewed in Cullen 2019) during self-motion (see figure 13.3). An alternative interpretation is that voluntary movements are produced by changes in referent body configurations (see chapter 21), which are used as the origins of the coordinate systems to measure and interpret information from relevant sensory receptors (see chapter 28). When signals from vestibular receptors change without a change in the referent body configuration, they are interpreted as deviations from that configuration caused by external forces (perturbations) and lead to quick corrective changes in muscle activation. If the referent configuration changes to produce a voluntary movement, similar changes from the vestibular system do not produce such corrections. In addition to the cerebellum, the information from the vestibular nuclei also reaches the thalamus on its way to the cerebral cortex. The regions in the cerebral cortex include Brodmann’s area 3a, 2v, and the parietoinsular vestibular cortex. Activation in these regions is important for perceptions arising from vestibular sensations. The parietoinsular vestibular cortex is also a multisensory area that responds to proprioceptive and visual information. This suggests that

most cortical processing of vestibular information is multisensory in nature. PROBLEM 13.3 A figure skater has sustained a concussion that has temporarily disrupted communication in the ascending vestibular pathways to the cerebellum. How could the skater’s performance be affected on skills such as the layback spin?

Figure 13.3    The

vestibular projections to the cortex and the cerebellum. The inputs from the vestibular labyrinth project to the vestibular nuclei. From there the projections extend to both the cerebellum and the cortex.

13.4 Central Pathways That Stabilize Gaze, Posture, and Head Movements

The vestibular system stabilizes eye movements and posture by initiating a variety of reflexes. In that way, the vestibular system by definition is multisensory because it integrates information from the visual as well as the somatosensory systems. Neurons in the vestibular nuclei, the first processing node for afferent vestibular information in the brainstem, themselves receive converging visual input. In addition, vestibular nuclei also receive other sensory inputs, including those from the proprioceptive and auditory systems. This makes the system for postural control inherently multisensory in nature and underscores the importance of multisensory input for maintaining upright stance and for performing many activities of daily living that require precise spatiotemporal coordination between multiple sensory systems. One such activity that requires precise spatiotemporal coordination is the ability to read street names while walking. When we walk, our head undergoes passive oscillations in upwarddownward and left-right directions. During these oscillations, the vestibulo-ocular reflex acts to stabilize gaze on a point in space. Eye muscles contract in a coordinated manner to stabilize the gaze with respect to the external world during both rotational and translational head movements. This gaze stabilization allows us to read texts on street signs and billboards without having to focus too hard. The neural circuitry for this reflex is shown in figure 13.4. Briefly, when the head moves, the otolith organs and semicircular canals communicate those movements via the vestibular nerve to the vestibular nuclei in the brainstem. The vestibular nuclei project to the contralateral abducens nuclei. From the abducens nuclei, one pathway directly makes excitatory projections to the ipsilateral lateral rectus muscles. The second pathway makes excitatory projections to the contralateral oculomotor nucleus and the medial rectus muscle. At the same time, the vestibular nuclei also inhibit the ipsilateral abducens nuclei. This architecture causes the left (right) lateral rectus and the right (left) medial rectus muscles to be activated together to compensate for rightward (leftward) head movement. Damage to the vestibulo-ocular reflex can cause a condition called

oscillopsia. Patients suffering from oscillopsia would encounter difficulties fixating their gaze on visual targets while their head is moving. The vestibulocervical and vestibulospinal reflexes are changes in muscle activation induced by movements of the head. The goal of these fast reflexes is to maintain the head in an upright posture. The vestibulocervical reflex acts on the neck muscles and the vestibulospinal reflex acts on the limb muscles to stabilize the position of the head in space. The vestibulocervical reflex is mediated by the medial vestibular nucleus and descending axons in the medial longitudinal fasciculus that reach the cervical spinal cord. When posture is perturbed, the semicircular canals are activated, and the head muscles act reflexively to pull the head upright. Head movement produced by the vestibulocervical reflex is also accompanied by forelimb (arm) extension and hindlimb (leg) flexion to protect the body.

Figure 13.4    The

neural network involved in the control of the vestibulo-ocular reflex. This is a gaze-stabilizing reflex: the sensory signals encoding head movements (sensed through the semicircular canals) are transformed into motor commands to generate compensatory eye movements in the opposite direction of the head movement. This ensures stable vision during head movement. The neural network involves vestibular afferents, central neurons, oculomotor neurons, and extraocular eye muscles and can operate without cortical input and control. Dashed and solid lines indicate inhibitory and excitatory actions.

The vestibulospinal reflex is mediated by the lateral and medial vestibulospinal tracts as well as the reticulospinal tracts. The otolith organs project to the lateral vestibular nucleus. The axons of the projections from this nucleus in the lateral vestibulospinal tract reach the ipsilateral spinal cord and excite the extensor motoneuronal pools and inhibit the flexor motoneuronal pools. Thus, the strong activation of the extensor muscles in the trunk and limbs supports balance and maintenance of upright posture. PROBLEM 13.4

A person reports feeling dizzy while nodding their head in agreement while looking at someone’s face. What would be the most likely cause of this disorder?

13.5 Peripheral Auditory System Sound waves are pressure waves that move in three-dimensional space caused by the vibration of air molecules. Sound waves carry energy, and the energy increases with the amplitude and frequency of the waves. In particular, the higher the frequency, the higher the energy. The audible frequency range for healthy humans is between 20 and 20,000 Hz. The ear consists of three parts: the external, middle, and inner ear. The external ear gathers the sound energy, focuses it on the eardrum, and amplifies its pressure. The main role of the middle ear is to prepare the sound energy that is traveling in a low-resistance air medium for a high-resistance aqueous medium of the inner ear. If the middle ear did not perform this function, most of the sound energy would reflect off the ear. The cochlea of the inner ear is where the original signal is transduced by the sensory hair cells and transformed into electrical nerve impulses in the auditory nerve fibers. The cochlea is a fluid-filled coiled structure that contains the organ for hearing. The cochlea consists of sensory hair cells that are displaced by the traveling sound waves. The hair bundles consist of stereocilia, and these inner hair cells project to the auditory nerve fiber. Unlike the hair cells of the crista or the maculae of the saccule and utricle of the vestibular system, hair cells of the cochlear duct in humans (and in most mammals) do not have kinocilia. The kinocilia disappear shortly after birth in most mammals. Thus, displacement of the hair bundle toward the tallest stereocilia opens mechano-electrical transduction channels that allow K+ ions to flow into the hair cells (down the electrochemical gradient) and depolarize them. That opens voltage-gated Ca++ channels, allowing calcium entry and

release of neurotransmitters. Movement in the opposite direction hyperpolarizes the hair cells. As the stereocilia move, the graded potential follows the movement of the stereocilia. The receptor potential leads to transmitter release from the hair cell. That in turn triggers action potentials in the cranial nerve VIII fibers. Hair cells only release neurotransmitters when they are depolarized.

13.6 Central Auditory Projections From the Cochlea The auditory nerve and the vestibular nerve together constitute the cranial nerve VIII. The auditory nerve enters the cochlear nuclei in the brainstem and from there projects to both the ipsilateral and contralateral superior olives (see figure 13.5). The superior olive plays a crucial role in localizing the spatial location of a sound. The pathways from both the superior olives and cochlear nuclei project to the midbrain auditory center, the inferior colliculus. The inferior colliculus neurons exhibit spatial selectivity for the origin of the sound source and also process the temporal patterns of sound.

Figure 13.5    The

anatomy of the ear and the major auditory pathway through the brainstem, thalamus, and cerebral cortex.

13.7 Auditory Integration Humans use two different strategies for spatial localization of a sound source. For low frequencies (