The Clinical Science of Neurologic Rehabilitation, Second Edition

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The Clinical Science of Neurologic Rehabilitation,

Second Edition

BRUCE H. DOBKIN, M.D.

OXFORD UNIVERSITY PRESS

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ix

Positron Emission Tomography • Single Photon Emission Computerized Tomography • Functional Magnetic Resonance Imaging • Transcranial Magnetic Stimulation • Magnetoencephalography • High Resolution Electroencephalography • Intrinsic Optical Imaging Signals • Near-Infrared Spectroscopy • Magnetic Resonance Spectroscopy • Transcranial Doppler • Combined Methods

LIMITATIONS OF FUNCTIONAL NEUROIMAGING STUDIES 160 General Limitations • Subtraction Studies • Timing of Studies

METABOLIC IMAGING AT REST AFTER INJURY 163 Stroke • Aphasia • Traumatic Brain Injury • Persistent Vegetative State ACTIVATION STUDIES: FUNCTIONAL REORGANIZATION AFTER INJURY 167

Sensorimotor Reorganization After Central Nervous System Lesion • Peripheral Nerve Transection

TRAINING-INDUCED REORGANIZATION 176

Sensorimotor Training • Aphasia • Cognition • Cross-Modal Plasticity NEUROPHARMACOLOGIC MODULATION 184

Monaminergic Agents • Other Agents SUMMARY 185

4. NEUROSTIMULATORS AND NEUROPROSTHESES 193 PERIPHERAL NERVOUS SYSTEM DEVICES 194

Functional Neuromuscular Stimulation • Nerve Cuffs CENTRAL NERVOUS SYSTEM DEVICES 198

Neuroaugmentation • Spinal Cord Stimulators • Brain–Machine Interfaces • Sensory Prostheses

ROBOTIC AIDS 203

Upper Extremity • Lower Extremity TELETHERAPY 206

SUMMARY 206

Part II. Common Practices Across Disorders 5. THE REHABILITATION TEAM 213

THE TEAM APPROACH 213 The Rehabilitation Milieu

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PHYSICIANS 215

Responsibilities • Interventions NURSES 218

Responsibilities • Interventions PHYSICAL THERAPISTS 219

Responsibilities • Interventions for Skilled Action OCCUPATIONAL THERAPISTS 231

Responsibilities • Interventions for Personal Independence SPEECH AND LANGUAGE THERAPISTS 235 Responsibilities • Interventions for Dysarthria and Aphasia NEUROPSYCHOLOGISTS 242

SOCIAL WORKERS 243

RECREATIONAL THERAPISTS 243 OTHER TEAM MEMBERS 244 SUMMARY 244

6. APPROACHES FOR WALKING 250 NORMAL GAIT 250

NEUROLOGIC GAIT DEVIATIONS 252

Hemiparetic Gait • Paraparetic Gait • Gait with Peripheral Neuropathy • Gait with Poliomyelitis

QUANTITATIVE GAIT ANALYSIS 258

Temporal Measures • Kinematics • Electromyography • Kinetics • Energy Expenditure

APPROACHES TO RETRAINING AMBULATION 262 Conventional Training • Task-Oriented Training • Assistive Devices SUMMARY 268

7. ASSESSMENT AND OUTCOME MEASURES FOR CLINICAL TRIALS 271

PRINCIPLES OF MEASUREMENT 272

Types of Measurements • Reliability and Validity • Choosing Measurement Tools MEASURES OF IMPAIRMENT 275

Consciousness • Cognition • Speech and Language • Sensorimotor Impairment Scales BEHAVIORAL MEASURES 288

Behavioral Modification • Neurobehavioral Scales MEASURES OF DISABILITY 289

Activities of Daily Living • Instrumental Activities of Daily Living • Mixed Functional Scales

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MEASURES OF HEALTH-RELATED QUALITY OF LIFE 298 Instruments • Adjustment Scales • Style Of Questions

MEASURES OF HANDICAP 302

MEASURES OF COST-EFFECTIVENESS 303

STUDY DESIGNS FOR REHABILITATION RESEARCH 303

Ethical Considerations • Types of Clinical Trials • Confounding Issues in Research Designs • Statistical Analyses

SUMMARY 314

8. ACUTE AND CHRONIC MEDICAL MANAGEMENT 323 DEEP VEIN THROMBOSIS 323

Prevention

ORTHOSTATIC HYPOTENSION 324 THE NEUROGENIC BLADDER 325 Pathophysiology • Management

BOWEL DYSFUNCTION 329 Pathophysiology • Management

NUTRITION AND DYSPHAGIA 330 Pathophysiology • Assessment • Treatment PRESSURE SORES 334

Pathophysiology • Management PAIN 336

Acute Pain • Chronic Central Pain • Weakness-Associated Shoulder Pain • Neck, Back, and Myofascial Pain

DISORDERS OF BONE METABOLISM 348 Heterotopic Ossification • Osteoporosis

SPASTICITY 348 Management

CONTRACTURES 357 MOOD DISORDERS 358

Posttraumatic Stress Disorder • Depression SLEEP DISORDERS 363

SUMMARY 364

Part III. Rehabilitation of Specific Neurologic Disorders 9. STROKE 375

EPIDEMIOLOGY 375 Fiscal Impact • Stroke Syndromes

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MEDICAL INTERVENTIONS 377

Frequency of Complications • Secondary Prevention of Stroke INPATIENT REHABILITATION 385

Eligibility for Rehabilitation • Trials of Locus of Treatment • Discharge OUTPATIENT REHABILITATION 389

Locus of Treatment • Pulse Therapy • Sexual Function • Community Reintegration OUTCOMES OF IMPAIRMENTS 392

Overview of Outcomes • The Unaffected Limbs • Impairment-Related Functional Outcomes

OUTCOMES OF DISABILITIES 399

Overview of Outcomes • Upper Extremity Use • Ambulation • Predictors of Functional Gains

CLINICAL TRIALS OF FUNCTIONAL INTERVENTIONS 404

Trials of Schools of Therapy • Task-Oriented Approaches • Concentrated Practice • Assistive Trainers • Adjuvant Pharmacotherapy • Functional Electrical Stimulation • Biofeedback • Acupuncture

TRIALS OF INTERVENTIONS FOR APHASIA 420

Rate of Gains • Prognosticators • Results of Interventions • Pharmacotherapy TRIALS FOR COGNITIVE AND AFFECTIVE DISORDERS 425 Memory Disorders • Visuospatial and Attentional Disorders • Affective Disorders SUMMARY 436

10. ACUTE AND CHRONIC MYELOPATHIES 451 EPIDEMIOLOGY 451

Traumatic Spinal Cord Injury • Nontraumatic Disorders MEDICAL REHABILITATIVE MANAGEMENT 458

Time of Onset to Start of Rehabilitation • Specialty Units • Surgical Interventions • Medical Interventions

SENSORIMOTOR CHANGES AFTER PARTIAL AND COMPLETE INJURY 466

Neurologic Impairment Levels • Evolution of Strength and Sensation • Changes in Patients with Paraplegia • Changes in Patients with Quadriplegia • Mechanisms of Sensorimotor Recovery

FUNCTIONAL OUTCOMES 473 Self-Care Skills • Ambulation

TRIALS OF SPECIFIC INTERVENTIONS 477

Mobility • Strengthening and Conditioning • Upper Extremity Function • Neural Prostheses • Spasticity

LONG-TERM CARE 485

Aging • Sexual Function • Employment • Marital Status • Adjustment and Quality of Life

SUMMARY 489

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11. TRAUMATIC BRAIN INJURY 497 EPIDEMIOLOGY 498

Economic Impact • Prevention PATHOPHYSIOLOGY 499

Diffuse Axonal Injury • Hypoxic-Ischemic Injury • Focal Injury • Neuroimaging NEUROMEDICAL COMPLICATIONS 503

Nutrition • Hypothalamic-Pituitary Dysfunction • Pain • Seizures • Delayed-Onset Hydrocephalus • Acquired Movement Disorders • Persistent Vegetative State ASSESSMENTS AND OUTCOME MEASURES 510

Stages of Recovery • Disability

PREDICTORS OF FUNCTIONAL OUTCOME 513

Level of Consciousness • Duration of Coma and Amnesia • Neuropsychologic Tests • Population Outcomes

LEVELS OF REHABILITATIVE CARE 515 Locus of Rehabilitation • Efficacy of Programs

REHABILITATION INTERVENTIONS AND THEIR EFFICACY 519 Overview of Functional Outcomes • Physical Impairment and Disability • Psychosocial Disability • Cognitive Impairments • Neurobehavioral Disorders • Neuropsychiatric Disorders

SPECIAL POPULATIONS 535

Pediatric Patients • Geriatric Patients • Mild Head Injury ETHICAL ISSUES 537

SUMMARY 538

12. OTHER CENTRAL AND PERIPHERAL DISORDERS 547 DISORDERS OF THE MOTOR UNIT 548

Muscle Strengthening • Respiratory Function • Motor Neuron Diseases • Neuropathies • Myopathies

PARKINSON’S DISEASE 557 Interventions

MULTIPLE SCLEROSIS 559

Epidemiology of Disability • Pathophysiology • Rehabilitative Interventions • Clinical Trials PEDIATRIC DISEASES 565

Cerebral Palsy • Myelomeningocele BALANCE DISORDERS 567

Frailty and Falls in the Elderly • Vestibular Dysfunction ALZHEIMER’S DISEASE 570

EPILEPSY 570

CONVERSION DISORDERS WITH NEUROLOGIC SYMPTOMS 570

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CHRONIC FATIGUE SYNDROME 571

ACQUIRED IMMUNODEFICIENCY SYNDROME 571 SUMMARY 571

INDEX 579

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PART I

NEUROSCIENTIFIC FOUNDATIONS

FOR REHABILITATION

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1 Organizational Plasticity in Sensorimotor and

Cognitive Networks

SENSORIMOTOR NETWORKS Overview of Motor Control Cortical Motor Networks

Somatosensory Cortical Networks Pyramidal Tract Projections Subcortical Systems

Brain Stem Pathways Spinal Sensorimotor Activity

STUDIES OF REPRESENTATIONAL PLASTICITY

Motor Maps Sensory Maps

BASIC MECHANISMS OF SYNAPTIC PLASTICITY

Hebbian Plasticity

Cortical Ensemble Activity

Long-Term Potentiation and Depression Molecular Mechanisms

Growth of Dendritic Spines Neurotrophins

Neuromodulators

COGNITIVE NETWORKS Overview of the Organization

of Cognition

Explicit and Implicit Memory Network

Working Memory and Executive Function Network

Emotional Regulatory Network Spatial Awareness Network Language Network

SUMMARY

Function follows structure. The central (CNS) and peripheral (PNS) nervous system matrix is a rich resource for learning and for retraining.

This chapter begins with the structural frame- work of interconnected neural components that contribute to motor control for walking, reaching, and grasping, and to cognition and mood. I then review what we know about cel- lular mechanisms that may be manipulated by physical, cognitive, and pharmacologic therapies to lessen impairments and disabilities. These discussions of functional neuroanatomy provide a map for mechanisms relevant to neural repair, functional neuroimaging, and theory-based practices for neurologic rehabilitation.

Injuries and diseases of the brain and spinal cord damage clusters of neurons and discon- nect their feedforward and feedback projections. The victims of neurologic disorders often improve, however. Mechanisms of activity-dependent learning within spared modules of like-acting neurons are a fundamental property of the neurobiology of functional gains.

Rehabilitation strategies can aim to manipulate the molecules, cells, and synapses of networks that learn to represent some of what has been lost. This plasticity may be no different than what occurs during early development, when a new physiologic organization emerges from intrinsic drives on the properties of neurons and their synapses. Similar mechanisms drive how living creatures learn new skills and abilities.

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Activity-dependent plasticity after a CNS or PNS lesion, however, may produce mutability that aids patients or mutagenic physiology that impedes functional gains.

Our understanding of functional neuroanatomy is a humbling work in progress. Al- though neuroanatomy and neuropathology may seem like old arts, studies of nonhuman primates and of man continue to reveal the connections and interactions of neurons. The brain’s macrostructure is better understood than the microstructure of the connections between neurons. It is just possible to imagine that we will grasp the design principles of the 100,000 neurons and their glial supports within 1 mm³of cortex, but almost impossible to look forward to explaining the activities of the 10 billion cortical neurons that make some 60 tril- lion synapses.¹Aside from the glia that play an important role in synaptic function, each cubic millimeter of gray matter contains 3 km of axon and each cubic millimeter of white matter includes 9 meters of axon. The tedious work of understanding the dynamic interplay of this matrix is driven by new histochemical approaches that can label cells and their projections, by electrical microstimulation of small ensembles of neurons, by physiological recordings from single cells and small groups of neurons, by molecular analyses that localize and quantify neurotransmitters, receptors and gene products, and by comparisons with the architecture of human and nonhuman cortical neurons and fiber arrangements.

Functional neuroimaging techniques, such as positron emission tomography (PET), functional magnetic resonance imaging (fMRI), and transcranial magnetic stimulation (TMS) allow comparisons between the findings from animal research and the functional neuroanatomy of people with and without CNS lesions. These computerized techniques offer insights into where the coactive assemblies of neurons lie as they simultaneously, in parallel and in series, process information that allows thought and behavior. Neuroimaging has both promise and limitations (see Chapter 3).

What neuroscientists have established about the molecular and morphologic bases for learning motor and cognitive skills has become more critical for rehabilitationists to understand.

Neuroscientific insights relevant to the restitu- tion of function can be appreciated at all the main levels of organization of the nervous sys-

tem, from behavioral systems to interregional and local circuits, to neurons and their dendritic trees and spines, to microcircuits on ax- ons and dendrites, and most importantly, to synapses and their molecules and ions. Expe- rience and practice lead to adaptations at all levels. Knowledge of mechanisms of this activity-dependent plasticity may lead to the design of better sensorimotor, cognitive, pharmacologic, and biologic interventions to enhance gains after stroke, traumatic brain and spinal cord injury, multiple sclerosis, and other diseases.

SENSORIMOTOR NETWORKS

Motor control is tied, especially in the rehabilitation setting, to learning skills. Motor skills are gained primarily through the cerebral organization for procedural memory. The other large classification of memory, declarative knowledge, depends upon hippocampal activity. The first is about how to, the latter is the what of facts and events. Procedural knowledge, compared to learning facts, usually takes considerable practice over time. Skills learning is also associated with experience-specific organizational changes within the sensorimotor network for motor control. A model of motor control, then, needs to account for skills learning. To successfully manipulate the controllers of movement, the clinician needs a multilevel, 3-dimensional point of view. The vista includes a reductionist analysis, examining the properties of motor patterns generated by networks, neurons, synapses, and molecules. Our sight- line also includes a synthesis that takes a systems approach to the relationships between networks and behaviors, including how motor patterns generate movements modulated by action-related sensory feedback and by cognition.

The following theories, all of which bear some truth, focus on elements of motor control.

Overview of Motor Control

Mountcastle wrote, “The brain is a complex of widely and reciprocally interconnected systems,” and “The dynamic interplay of neural activity within and between these systems is the very essence of brain function.” He proposed:

“The remarkable capacity for improvement of

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function after partial brain lesions is viewed as evidence for the adaptive capacity of such distributed systems to achieve a goal, albeit slowly and with error, with the remaining neural apparatus.”²

A distributed system represents a collection of separate dynamic assemblies of neurons with anatomical connections and similar functional properties.³The operations of these assemblies are linked by their afferent and efferent mes- sages. Signals may flow along a variety of pathways within the network. Any locus connected within the network may initiate activity, as both externally generated and internally generated signals may reenter the system. Partial lesions within the system may degrade signaling, but will not eliminate functional communication so long as dynamic reorganization is possible.

What are some of the “essences” of brain and spinal cord interplay relevant to understanding how patients reacquire the ability to move with purpose and skill?

No single theory explains the details of the controls for normal motor behavior, let alone the abnormal patterns and synergies that emerge after a lesion at any level of the neuraxis. Many models successfully predict aspects of motor performance. Some models offer both biologically plausible and behaviorally relevant handles on sensorimotor integration and motor learning. Among the difficulties faced by theorists and experimentalists is that no simple ordinary movement has only one motor control solution. Every step over ground and every reach for an item can be accomplished by many different combinations of muscle activations, joint angles, limb trajectories, velocities, accel- erations, and forces. Thus, many kinematically redundant biological scripts are written into the networks for motor control. The nervous system computates within a tremendous number of degrees of freedom for any successful movement. In addition, every movement changes features of our physical relationship to our surrounds. Change requires operations in other neural networks, such as frontal lobe connections for divided attention, planning, and working memory.

Models of motor behavior have explored the properties of neurons and their connections to explain how a network of neurons generates persistent activity in response to an input of brief duration, such as seeing a baseball hit out of the batter’s box, and how networks respond

to changes in input to update a view of the environment for goal-directed behaviors, such as catching the baseball 400 feet away while on the run.⁴A wiring diagram for hauling in a fly ball, especially with rapidly changing weights and directions of synaptic activity, seems im- possibly complex. Researchers have begun, however, to describe some clever solutions for rapid and accurate responses that evolve within interacting, dynamic systems such as the CNS.⁵ Each theory contains elements that describe, physiologically or metaphorically, some of the processes of motor control. These theories lead to experimentally backed notions that help explain why rehabilitative therapies help patients.

GENERAL THEORIES OF MOTOR CONTROL

Sherrington proposed one of the first physiologically based models of motor control. Sen- sory information about the position and velocity of a limb moving in space rapidly feeds back information into the spinal cord about the cur- rent position and desired position, until all computed errors are corrected. Until the past decade or two, much of what physical and occupational therapists practiced was described in terms of chains of reflexes. Later, the theory expanded to include reflexes nested within Hughling Jackson’s hierarchic higher, middle, and lower levels of control. Some schools of physical therapy took this model to mean that motor control derives in steps from voluntary cortical, intermediate brain stem, and reflexive spinal levels.⁶ Abnormal postures and tone evolve, in the schools of Bobath and Brunnstrom (see Chapter 5), from the release of control by higher centers. These theories for physical and for occupational therapy imply that the nervous system is an elegantly wired machine that performs stereotyped computations on sensory inputs. Lower levels are sub- sumed under higher ones. This notion, however, is too simple. All levels of the CNS are highly integrated with feedforward and feedback interactions. Sensory inputs are critical, however.

Another theory of motor control suggests that stored central motor programs allow sensory stimuli or central commands to generate movements. Examples of stored programs include the lumbar spinal cord’s central pattern generators for stepping and the cortical “rules”

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that allow cursive writing to be carried out equally well by one’s hand, shoulder, or foot.

This approach, however, needs some elabora- tion to explain how contingencies raised by the environment and the biomechanical character- istics of the limbs interact with stored programs or with chains of reflexes. A more elegant theory of motor control, perhaps first suggested by Bernstein in the 1960s, tried to account for how the nervous system manages the many degrees of freedom of movement at each joint.⁷ He hypothesized that lower levels of the CNS control the synergistic movements of muscles.

Higher levels of the brain activate these synergies in combinations for specific actions.

Other theorists added a dynamical systems model to this approach. Preferred patterns of movement emerge in part from the interaction of many elements, such as the physical properties of muscles, joints, and neural connections. These elements self-organize according to their dynamic properties. This model says little about other aspects of actions, including how the environment, the properties of objects such as their shape and weight, and the demands of the task all interact with movement, perception, and experience.

Most experimental studies support the ob- servations of Mountcastle and others that the sensorimotor system learns and performs with the overriding objective of achieving movement goals. All but the simplest motor activities are managed by neuronal clusters distributed in networks throughout the brain. The regions that contribute are not so much functionally localized as they are functionally specialized. Higher cortical levels integrate sub- components like spinal reflexes and oscillating brain stem and spinal neural networks called pattern generators. The interaction of a dynamic cortical architecture with more automatic oscillators allows the cortex to run sensorimotor functions without directly needing to designate the moment-to-moment details of parameters such as the timing, intensity, and duration of the sequences of muscle activity among synergist, antagonist, and stabilizing muscle groups.

For certain motor acts, the motor cortex needs only to set a goal. Preset neural routines in the brain stem and spinal cord carry out the details of movements. This system accounts for how an equivalent motor act can be accomplished by differing movements, depending on

the demands of the environment, prior learning, and rewarded experience. Having achieved a behavioral goal, the reinforced sensory and movement experience is learned by the motor network. Learning results from increased synaptic activity that assembles neurons into functional groups with preferred lines of communication.⁸ Thus, goal-oriented learning, as opposed to mass practice of a simple and repet- itive behavior, ought to find an essential place in rehabilitation strategies.

Several experimentally based models suggest how the brain may construct movements.

Target-directed movements can be generated by motor commands that modulate an equilibrium point for the agonist and antagonist muscles of a joint.⁹ During reaching movements, for example, the brain constructs motor commands based on its prediction of the forces the arm will experience. Some forces are external loads and need to be learned. Other forces depend on the physical properties of muscle, such as its elasticity. The computations used by neurons to compose the motor command may be broadly tuned to the velocity of movements.¹⁰ Using microstimulation of closely related regions of the lumbar spinal cord, Bizzi and colleagues have also defined fields of neurons in the anterior horns that store and represent specific movements within the usual workspace of a limb, called primitives.¹¹ Combinations of these simple flexor and extensor actions may be fashioned by supraspinal inputs into the vast variety of movements needed for reaching and walking. The motor cortex, then, determines which spinal modules to activate, along with the necessary coefficient of activation, presumably working off an internal, previously learned model of the desired movement. The representations for the movement, described later, are stored in sensorimotor and associa- tion cortex. Thus, some simplifying rules generate good approximations to the goal of the reaching or stepping movement. Systems for error detection, especially within connections to the cerebellum, simultaneously make fine adjustments to reach the object.

A variety of related concepts about neural network modeling for the generation of a reaching movement have been offered.^12,13 Much work has gone into what small groups of cortical cells in the primary motor cortex (M1) encode. The activity of these neurons may encode the direction or velocity of the hand as it

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moves toward a target¹⁴or the forces at joints or the control of mechanical properties of muscles and joints.¹⁵ Other theories suggest how ever larger groups of neurons may interact to carry out a learned or novel action.^16,17

Motor programs can also be conceptualized as cortical cell assemblies stored in the form of strengthened synaptic connections between pyramidal neurons and their targets, such as the basal ganglia and spinal cord for the prepa- ration and ordered sequence of movements.¹⁸ Indeed, multiple representations of aspects of movement are found among the primary and secondary sensorimotor cortices. The neurons of each region have interconnections and cell properties that promote some common responses, such as being tuned in a graded and preferred fashion to the direction or velocity of a reaching movement, to perceived load, and to other visual and proprioceptive information, including external stimuli such as food.¹⁹Many other frames of reference, such as shoulder

torques, the equilibrium points of muscle movements mentioned above, and the position of the eyes and head also elicit neuronal discharges when a hand reaches into space. As a motor skill is trained, cells in M1 adapt to the tuning properties and firing patterns of other neurons involved in the action.²⁰Learning-dependent neuronal activity, in fact, has been found in experiments with monkeys with single cell recordings of neurons in all of the motor cortices. Each distributed neighborhood of neurons is responsible for a specific role in aspects of planning and directing movements.

The matrix of cortical, subcortical, and spinal nodes in this network model of motor control are described later, along with some of the at- tributes that they represent.

Figure 1–1 diagrams anatomical nodes of the sensorimotor system, emphasizing the map for locomotor control with some of its most prominent feedforward and feedback connections.

These reverberating circuits calibrate motor

Figure 1–1. Prominent cortical, subcortical, and spinal modules and their connections within the sensorimotor networks for locomotor control.

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control. Each anatomic region has its own diverse neuronal clusters with highly specified inputs and outputs. These regions reflect the distributed and parallel computations needed for movement, posture, coordination, orientation to the environment, perceptual information, drives, and goals that formulate a particular action via a large variety of movement strategies. The distributed and modular organization of the sensorimotor neurons of the brain and spinal cord provide neural substrates that arrange or represent particular patterns of movement and are highly adaptable to training.

No single unifying principle for all aspects of motor control is likely. The one certain fact that must be accounted for in theories about motor control for rehabilitation is that the nervous system, above all, learns by experience. The rehabilitation team must determine how a person best learns after a brain injury. At a cellu- lar level, activity-dependent changes in synaptic strength are closely associated with motor learning and memory. Later in the chapter, we will examine molecular mechanisms for learning such as long-term potentiation (LTP), which may be boosted by neuropharmacologic interventions during rehabilitation. After a neurologic injury, these forms of adaptability or neural plasticity, superimposed upon the remaining intact circuits that can carry out task subroutines, can be manipulated to lessen impairments and allow functional gains.

To consider the neural adaptations needed to gain a motor skill or manage a cognitive task, I selectively review some of the anatomy, neurotransmitters, and physiology of the switches and rheostats drawn in Figure 1–1. Most of the regions emphasized can be activated by tasks performed during functional neuroimaging procedures, so rehabilitationists may be able to weigh the level of engagement of these network nodes after a brain or spinal injury and in response to specific therapies. The cartoon map of Figure 1–1 is a general road atlas. It allows the reader to scan major highways for their connections and spheres of influence.

Over the time of man’s evolution, these roads have changed. Over the scale of a human life- time, built along epochs of time from millisec- onds to minutes, days, months, and years, the maps of neuronal assemblies, synapses, and molecular cascades that are embedded within the cartoon map evolve, devolve, strengthen and weaken. After a CNS or PNS injury or dis-

ease, the map represents what was, but not all that is. If some of the infrastructure persists, a patient may solve motor problems by practice and by relearning.

The following discussion of structure and function takes a top-down anatomic approach, given that diseases and injuries tend to involve particular levels of the neuraxis. Within each level, but with an eye on the potential for interactive reorganization throughout the distributed controllers of the neuraxis, I select especially interesting aspects of biological adaptability within the neuronal assemblies and distributed pathways that may be called upon to improve walking in hemiparetic and paraparetic patients and to enhance the use of a paretic arm.

Cortical Motor Networks

PRIMARY MOTOR CORTEX

Neurophysiologic and functional imaging studies point to intercoordinated, functional assemblies of cells distributed throughout the neuraxis that initiate and carry out complex movements. These neuronal sensorimotor assemblies show considerable plasticity as maps of the dermatomes, muscles, and movements that they represent. In addition, they form multiple parallel systems that cooperate to manage the diverse information necessary for the rapid, precise, and yet highly flexible control of multijoint movements. This organization subsumes many of the neural adaptations that contribute to the normal learning of skills and to partial recovery after a neural injury.

The primary motor cortex (M1) in Brod- mann’s area (BA) 4 (Fig. 1–2), lies in the central sulcus and on the precentral gyrus. It receives direct or indirect input from the adjacent primary somatosensory cortex (S1) and receives and reciprocates direct projections to the secondary somatosensory cortex (SII), to nonprimary motor cortices including BA 24, the supplementary motor area (SMA) in BA 6, and to BA 5 and 7 in the parietal region. These links integrate the primary and nonprimary sensorimotor cortices.

Organization of the Primary Motor Cortex

The primary motor cortex has an overall somatotopic organization for the major parts of the

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body, not unlike what Penfield and Rasmussen found in their cortical stimulation studies in the 1940s.²¹In addition, separable islands of cortical motoneurons intermingle to create a more complex map for movement than the neatly por- trayed traditional cartoons of a human homunculus.²²For example, M1 has separate clusters of output neurons that facilitate the activity of a single spinal motoneuron. Cortical elec- trostimulation mapping studies in macaques reveal a central core of wrist, digit, and intrinsic hand muscle representations surrounded by a horseshoe-shaped zone that represents the shoulder and elbow muscles. The core zones representing the distal and proximal arm are

bridged by a distinct region that represents combinations of both distal and proximal muscle groups. These bridging neurons may specify multijoint synergistic movements needed for reaching and grasping.²³This arrangement also is a structural source for modifications in the strength and distribution of connections among neurons that work together as a skill is learned.

Some individual neurons overlap in their control of muscles of the wrist, elbow, and shoulder.^24,25In addition, representations for movements of each finger overlap with other fingers and with patches of neurons for wrist actions.^26,27They, too, are mutable controllers and a mechanism for neuroplasticity.

Figure 1–2. Brodmann’s areas cytoar- chitectural map over the (A) lateral and (B) medial surfaces of the cortex.

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A single corticospinal neuron from M1 may project to the spinal motoneurons for different muscles to precisely adjust the amount of muscle coactivation.²⁸ Branching M1 projections, however, rarely innervate both cervical and lumbar cord motor pools. Strick and colleagues found that only 0.2% of neurons in M1 were double-labeled retrogradely in macaques from both lower cervical and lower lumbar seg- ments, compared to 4% that were double-labeled from the upper and lower cervical seg- ments.²⁹The individual and integrated actions of multiple cortical representations to multiple spinal motoneurons reflect important aspects of motor control, as well as another anatomic basis for representational neuroplasticity.

Functional neuroimaging studies in humans performed as they make individual flexor–

extensor finger movements point to overlapping somatotopic gradients in the distributed representation of each finger.^30,31 A 2–3 mm anatomical separation was found between the little finger (more medial) and the second digit (more lateral). A reasonable interpretation of the data is that the cortical territory activated by even a simple movement of any joint of the upper extremity constitutes a relatively large fraction of the representation of the total limb because representations overlap considerably.²⁵ This overlap is consistent with the consequences of a small stroke in clinical practice. A stroke confined to the hand region of M1 tends to af- fect distal joints more than proximal ones and tends to involve all fingers approximately equally (see Color Fig. 3–5 in separate color insert).

The M1 encodes specific movements and acts as an arranger that pulls movements together. The relationships of the motoneurons for representations of movements are dynam- ically maintained by ongoing use. Horizontal and vertical intracortical and corticocortical connections modulate the use-dependent inte- grations of these ensembles.³² Intermingled functional connections among these small ensembles of neurons offer a distributed organization that provides a lot of flexibility and stor- age capacity for aspects of movement. These assemblies manage the coordination of multijoint actions, the velocity and direction of movements, and process the order of stimuli on which a motor response will be elicited to carry out a task.¹⁶ The assemblies also make rapid and slow synaptic adaptations during learning.

Thus, a cortical motoneuron can activate a small field of target muscles; and an assembly of interacting motoneurons within M1 can represent the selective activation of one or more complex movements. The allocation of cortical representational space in M1 and adjacent somatosensory areas depends on the synaptic efficacy associated with prior experience among neuronal assemblies that represent a movement or skin surface. Temporally coincident inputs to the assemblies of the sensorimotor cortex during practice produce skilled synergistic, multijoint movements.³³This arrangement is a basis for neuronal representational plasticity, which involves practice-induced fluxes in the strength of neural liaisons. This view of cortical maps, as opposed to the more rigid cartoon of the homunculus, especially makes sense when one considers that a reaching and grasping movement can incur rotations at the shoulder, elbow, wrists, and fingers with 27° of freedom using at least 50 different muscles. Many of these muscles have multijoint actions and provide postural stability for a range of different movements.³⁴

Primary Motor Cortex and Hand Function

What aspects of hand movement are encoded by M1? The M1 has been described as a com- putational map for sensorimotor transforma- tions, rather than a map of muscles or of particular movement patterns.¹⁹ Its overlapping organization contributes to the control of the complex muscle synergies needed for fine coordination and forceful contractions.³⁵After le- sioning M1 in a monkey, the upper extremity is initially quite impaired. The hand can be re- trained, however, to perform simple movements and activate single muscles. This rehabilitation leads to flexion and extension of the wrist, but the monkey cannot learn to make smooth diagonal wrist movements using muscles for flexion and radial deviation.²⁸The animal accomplishes this motion only in a step- wise sequence. The M1, then, activates and inactivates muscles in a precise spatial and temporal pattern, including the controllers for fractionated finger movements. Using some clever hand posture tasks to dissociate muscle activity, direction of movement at the wrist, and the direction of movement in space, Kakei and colleagues showed that substantial numbers of

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neurons in M1 represent both muscles and di- rectional movements.³⁶

The primary motor cortex motoneurons have highly selective and powerful effects on the spinal motor pools to the hand, especially for the intrinsic hand muscles of primates, which includes humans, with good manipula- tive skills.³⁷ This cortical input lessens the spinal reflex and synergistic activity that better serves postural and proximal limb movements.

The coding of movement patterns and forces during voluntary use of the hand relates to the coactivation of assemblies of neurons acting in parallel, not to the rate of firing of single neurons.³⁸In single cortical cell recordings in M1, the burst frequency codes movement velocity and the burst duration codes the duration of the movement. Velocity correlates with the amount of muscle activation. The force exerted by muscles is a summed average of the ouput of single cells that fire at variable rates and the synchronization of assemblies of M1 neurons during specific phases of a motor task.³⁹ Sin- gle cell activity in the motor cortex is most in- tense for reaching at a particular magnitude and direction of force.¹⁴ The direction of an upper extremity movement may be coded by the sum of the vectors of the single cell activities in motor cortex in the direction of the movement.⁴⁰

The activity of a single corticomotoneuron can differ from the activity of an assembly of neighboring motoneurons. When a small assembly of cells becomes active, the discharge pattern of a neuron within that population may change with the task. As the active population evolves to include cells that had not previously participated or to exclude some of the cells that had been active, the assembly becomes a unique representation of different information about movement.

Thus, M1 is involved in many stages of guid- ing complex actions that require the coordination of at least several muscle groups. The M1 computes the location of a target, the hand trajectory, joint kinematics, and torques to reach and hold an object—the patterns of muscle activation needed to grasp the item—and relates a particular movement to other movements of the limb and body. These parameters may be manipulated by therapists during retraining functional skills. The degree to which discharges from M1 represent the extrinsic at- tributes of movements versus joint and muscle-

centered intrinsic variables is still unclear. A remarkable study in monkeys sheds additional light.

Brief electrical microstimulation reveals a homunculus-like organization of muscle twitch representations. Longer trains lasting 500 ms, which approximates the time scale of neuronal activity during reaching and grasping, at sites in the primary motor and premotor cortex of monkeys evokes a map of complex postures featuring hand positions near the face and body. Indeed, out of over 300 stimulation sites, 85% evoked a distinct posture. The map from cortex to muscles also depends on arm position in a way that specifies a final posture. For example, when the elbow started in flexion, stimulation at one site caused it to extend to its final posture. When starting in extension, the elbow flexed to place the hand at the same position. Spontaneous movements of the hand to the mouth followed the same pattern of motion and EMG activity as stimulation-evoked movements. Thus, within the larger arm and hand representation, stimulation-evoked postures were organized across the cortex as a map of multijoint movements that positioned the hand in peripersonal space. Primary motor cortex represented particularly the space in front of the monkey’s chest. Premotor cortex stimulation always included a gripping posture of the fingers when the hand-to-mouth pattern was evoked, presumably related to the action of feeding. All the evoked postures suggested typ- ical behaviors such as feeding, a defensive movement, reaching, flinching, and others.

Evoked postures were also found for the leg, in which stimulation elicited movements that converged the foot from different starting positions to a single final location within its ordinary workspace, much like what has been found with lumbar spinal cord microstimulation (see section, Spinal Sensorimotor Activity).

Functional imaging studies reveal a small activation in ipsilateral motor cortex during simple finger tapping. A study by Cramer and colleagues found a site of ipsilateral activation when the right finger taps to be shifted approximately 1 cm anterior, ventral, and lateral to the site in M1 activated by tapping the left finger.⁴¹ This bilateral activity may be related to the uncrossed corticospinal projection, to an aspect of motor control related to bimanual actions, or to sensory feedback. The M1 in mon-

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keys contains a subregion located between the neuronal representations for the digits and face in which approximately 8% of cells are active during ipsilateral and bilateral forelimb movements.⁴² Ipsilateral activations by PET and fMRI may actually include BA 6 rather than M1, since the separation of M1 from SMA and from BA 6 is difficult enough in postmortem brains and far more unreliable in functional imaging studies.⁴³Many nonprimary motor areas are also activated by simple finger movements,⁴⁴ suggesting that the same regions of the brain participate in simple and complex actions, but that the degree of activation increases with the demands of the task.

Since motoneurons in M1 participate in, or represent particular movements and contribute to unrelated movements, cells may functionally shift to take over some aspects of an impaired movement in the event a cortical or subcortical injury disconnects the primary cortical activa- tors of spinal motoneurons. As described later in this chapter and in Chapters 2 and 3, these motor and neighboring sensory neurons adapt their synaptic relationships in remarkably flexible ways during behavioral training. Future experimental studies of the details of these computations, of the neural correlates for features of upper extremity function, and of the relationships between neuronal assemblies in distributed regions during a movement will have practical implications for neurorehabilitation training and pharmacologic interventions.

The Primary Motor Cortex and Locomotion

Supraspinal motor regions are quite active in humans during locomotion.^45,46 In electro- physiologic studies of the cat, motoneurons in M1 discharge modestly during locomotion over a flat surface under constant sensory condi- tions. The cells increase their discharges when a task requires more accurate foot placement, e.g., for walking along a horizontally positioned ladder, compared to overground or treadmill locomotion. Changing the trajectory of the limbs to step over obstacles also increases cortical output.⁴⁷As expected, then, M1 is needed for precise, integrated movements.

Some pyramidal neurons of M1 reveal rhyth- mical activity during stepping. The cells fire especially during a visually induced perturbation

from steady walking, during either the stance or swing phase of gait as needed. These neurons may be especially important for flexor control of the leg. A pyramidal tract lesion or lesion within the leg representation after an anterior cerebral artery distribution infarct almost always affects foot dorsiflexion and, as a consequence, the gait pattern. Transcranial magnetic stimulation studies in man show greater activation of corticospinal input to the tibialis anterior muscle compared to the gastrocnemius.⁴⁸The tibialis anterior muscle was more excitable than the gastrocnemius during the stance phase of the gait cycle in normal subjects who walked on a treadmill. This phase requires ankle dorsiflexion at heel strike (see Chapter 6). For functional neuroimaging studies of the leg, the large M1 contribution to dorsiflexion of the ankle makes ankle movements a good way to activate M1 (see Color Fig. 3–8 in separate color insert). The considerable in- terest in this movement within M1 also suggests that a cognitive, voluntary cueing strategy during locomotor retraining is necessary to best get foot clearance during the swing phase of gait and to practice heel strike in the initial phase of stance. The alternative strategy to flex the leg enough to clear the foot, when cortical influences have been lost, is to evoke a flexor reflex withdrawal response.

For voluntary tasks that require attention to the amount of motor activity of the ankle movers, M1 motoneurons appear equally linked to the segmental spinal motor pools of the flexors and extensors.⁴⁹ This finding suggests that the activation of M1 is coupled to the timing of spinal locomotor activity in a task- dependent fashion, but may not be an essential component of the timing aspects of walking, at least not while walking on a treadmill belt. Spinal segmental sensory inputs, described later in this chapter, may be more critical to the temporal features of leg movements during walking. The extensor muscles of the leg, such as the gastrocnemius, especially depend on polysynaptic reflexes during walking modulated by sensory feedback for their antigravity function.⁵⁰ Primary motor cortex neurons also represent the contralateral paraspinal muscles and may innervate the spinal motor pools for the bilateral abdominal muscles.⁵¹ Potential overlapping representations between paraspinal and proximal leg muscle represen-

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tations may serve as a mechanism for plasticity with gait retraining.⁵²

Primary motor cortex also contains the giant pyramidal cells of Betz. These unusual cells re- side exclusively in cortical layer 5. They account for no more than approximately 50,000 of the several million pyramidal neurons in each precentral gyrus. Approximately 75% sup- ply the leg and 18% project to motor pools for the arm,⁵³but Betz cells constitute only 4% of the neurons of the leg representation that are found in the corticospinal tract.⁵⁴ The Betz cells appear to be important innervators of the large, antigravity muscles for the back and legs.

They phasically inhibit extension and facilitate flexion, which may be especially important for triggering motor activity for walking. Consis- tent with this tendency, pyramidal tract lesions tend to allow an increase in extension over flexion in the leg.

Ankle dorsiflexion and plantar flexion activate the contralateral M1, S1, and SMA in human subjects, although the degree of activity in functional imaging studies tends to be smaller than what is found with finger tapping (see Fig. 3–7). With an isometric contraction of the tibialis anterior or gastocnemius muscles, the bilateral superior parietal (BA 7) and premotor BA 6 become active during PET scanning, probably as a result of an increase in cortical control of initiation and maintenance of the contraction.⁵⁵Greater exertion of force and speed of movement give higher activations, similar to what occurs in M1 when finger and wrist movements are made faster or with greater force. When walking on uneven surfaces and when confronted by obstacles, BA6 and 7, S1, SMA, and the cerebellum participate even more for visuomotor control, balance, and selective movements of the legs. An increase in cortical activity in moving from rather stereotyped to more skilled lower extremity movements also evolves as a hemiparetic or paraparetic person relearns to walk with a reciprocal gait (see Fig. 3–8).

NONPRIMARY MOTOR CORTICES The premotor cortex and SMA exert what Hughlings Jackson called “the least automatic”

control over voluntary motor commands.

These cortical areas account for approximately 50% of the total frontal lobe motoneuron con-

tribution to the corticospinal tract and have specialized functions. Each of the six cortical motor areas that interact with M1 has a separate and independent set of inputs from adjacent and remote regions, as well as parallel, separate outputs to the brain stem and spinal cord.⁵⁶Table 1–1 gives an overview of their rel- ative contributions to the corticospinal tract and their functional roles. These motor areas also interact with cortex that does not have direct spinal motoneuron connections. For example, although motorically silent prefrontal areas do not directly control a muscle contraction, they play a role in the initiation, selection, inhibition, and guidance of behavior by representational knowledge. They do this via soma- totopically arranged prefrontal to premotor, corticostriatal, corticotectal, and thalamocorti- cal connections.⁵⁷

Functional imaging has revealed a somatotopic distribution of activation during upper extremity tasks in SMA, dorsal lateral premotor, and cingulate motor cortices.⁵⁸Somatotopy in the secondary sensorimotor cortices, at least for the upper extremity, may be based on a functional, rather than an anatomical representation.⁵⁹For example, the toe and foot have access to the motor program for the hand for cursive writing, even though the foot may never have practiced writing. An fMRI study that compared writing one’s signature with the dominant index finger and ipsilateral big toe revealed that both actions activated the intra- parietal sulcus and premotor cortices over the convexity in the hand representation.⁵⁹ The finding that one limb can manage a previously learned task from another limb may have implications for compensatory and retraining strategies after a focal brain injury.

Premotor Cortex

Whereas M1 mediates the more elementary aspects of the control of movements, the premotor networks encode motor acts and program defined goals by their connections with the frontal cortical representations for goal-directed, prospective, and remembered actions.

BA 6 has been divided into a dorsal area, in and adjacent to the precentral and superior frontal sulcus, and a ventral area in and adjacent to the caudal bank of the arcuate sulcus at its inferior limb. In the dorsal premotor area,

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of Macaques

CORTICAL AREA

Cingulate Cingulate Cingulate Premotor Premotor

M1 SMA Dorsal Ventral Rostral Dorsal Ventral

Total number of CS neurons:

Forelimb (low cervical) 15,900 5200 4600 2600 2200 6100 300

Forelimb (high cervical) 10,400 5000 1900 2300 2500 7200 2300

Hindlimb (L-6–S-1) 23,900 5800 3700 2500 400 5200 6

Total frontal lobe 46 15 9 7 4 17 2

CS projections (%)

Functional movement roles Execute action Self-initiated Movement Reward-based Visually guided Grasp by visual

selection; sequence motor reaching guidance

learned from memory selection

sequence;

Bimanual action M1, primary motor cortex; SMA, supplementary motor area; CS, corticospinal.

Source: Adapted from data from Cheney et al., 2000.³⁹⁶

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separate arm and leg representations are found along with both distal and proximal upper extremity representations.²⁹In humans, the dorsal premotor region is activated by motor tasks of any complexity. The ventral premotor region, near the frontal operculum, activates with complex tasks such as motor imagery, observ- ing another person grasping an item, and pre- shaping the hand to grasp an object. The ventral region has connections with the frontal eye fields and visual cortex, putting it in the middle of an action observation and eye–hand network that appears to help compensate for M1 lesions of the hand. Lesions of the ventral premotor and dorsal precentral motor areas over the lateral convexity cause proximal weakness and apraxia (see Chapter 9).

Supplementary Motor Area

Based upon PET studies in humans, the SMA includes a pre-SMA, which is anterior to a line drawn from the anterior commissure vertically up through BA 6, and the SMA proper, just caudal to this.⁶⁰ Tasks that require higher order motor control such as a new motor plan activate the pre-SMA, whereas simple motor tasks activate the caudal SMA. After an M1 lesion in the monkey, these premotor areas contribute to upper extremity movements, short of coordinated cocontractions and fractionated wrist and finger actions.²⁸Lesions of the SMA cause akinesia and impaired control of bimanual and sequential movements, especially of the digits, consistent with its role in motor planning.⁶¹

The SMA plays a particularly intriguing role within the mosaic of anatomically connected cortical areas involved in the execution of movements. Electrical stimulation of the SMA produces complex and sequential multijoint, synergistic movements of the distal and proximal limbs. Surface electrode stimulation over the mesial surface of the cerebral cortex in humans prior to the surgical excision of an epilep- tic focus has revealed the somatotopy within SMA and suggests that it is involved not only in controlling sequential movements, but also in the intention to perform a motor act.

As an example of hemispheric asymmetry, stimulation of the right SMA produced both contralateral and ipsilateral movements, whereas left-sided stimulation led mostly to contralateral activity.⁶²In humans, the SMA is

involved in initiating movements triggered by sensory cues. The SMA is also highly involved in coordinating bimanual actions and simulta- neous movements of the upper and lower extremities on one side of the body.⁶³The practice of bimanual tasks is sometimes recom- mended after a brain injury to visuospatially and motorically drive the paretic hand’s actions with patterns more easily accomplished by the normal hand (see Chapter 9). The success of this strategy may depend upon the intactness of secondary sensorimotor cortical areas.

Cingulate Cortex

At least 3 nonprimary motor areas also contribute to motor control from their locations in BA 23 and 24 along the ventral bank of the cingulate cortex, at a vertical to the anterior commissure and immediately rostral to the more dorsal SMA.⁶⁴The representation for the hand is just below the junction of BA 4 and the posterior part of BA 6 on the medial wall of the hemisphere. In BA 24, a rostral cingulate zone is activated by complex tasks, whereas a smaller caudal cingulate zone is activated by simple actions.⁶⁰The posterior portion of BA 24 in cingulate cortex sends dense projections to the spinal cord, to M1, and to the caudal part of SMA.⁶⁵ This BA 24 subregion also interacts with BA 6. The rostral portion targets the SMA.

Functional imaging studies usually reveal activation of the mesial cortex during motor learning and planning, bimanual coordination of movements, and aspects of the execution of movements, more for the hand than the foot.

Limited evidence from imaging in normal subjects suggests that all the nonprimary motor regions are activated, often bilaterally to a mod- est degree, by even simple movements such as finger tapping.⁴⁴The activations increase as behavioral complexity increases. As noted, after a CNS injury, greater activity may evolve in M1 and nonprimary motor cortices when simple movements become more difficult to produce.

The portion of the corticospinal tract from the anterior cingulate projects to the intermediate zone of the spinal cord. The anterior cingulate cortex also has reciprocal projections with the dorsolateral prefrontal cortex, discussed later in this chapter in relation to working memory and cognition. The anterior cingulate receives afferents from the anterior and midline thalamus and from brain stem nuclei

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that send fibers with the neuromodulators dopamine, serotonin, noradrenaline, and a variety of neuropeptides, pointing to a role in arousal and drives. The difficulty in spontaneous initiation of movement and vocalization associated with akinetic mutism that follows a lesion disconnecting inputs to the cingulate cortex can sometimes improve after treatment with a dopamine receptor agonist. On the other hand, the dopamine blocker haloperidol de- creases the resting metabolic rate of the anterior cingulate.⁶⁶The anterior cingulate, in line with its drive-related actions, participates in translating intentions into actions.⁶⁶For example, area 24 is activated in PET studies mainly when a subject is forced to choose from a set of competing oculomotor, manual, or speech responses.⁶⁵ The anterior cingulate presumably participates in motor control by facilitat- ing an appropriate response or by suppressing the execution of an inappropriate one when behavior has to be modified in a novel or chal- lenging situation. The region may be especially important for enabling new strategies for motor control in patients during rehabilitation.

SPECIAL FEATURES OF MOTOR CORTICES

Rehabilitationists can begin to consider the contribution of the cortical nodes in the motor system to motor control, to anticipate how the activity of clusters of neurons may vary in relation to different tasks, to test for their dysfunction, and to adapt appropriate interventions. For example, patients with lesions that interrupt the corticocortical projections from somatosensory cortex to the primary motor cortex might have difficulty learning new motor skills, but they may be able to execute existing motor skills.⁶⁷The lateral premotor areas, especially BA 46 and 9, receive converging visual, auditory, and other sensory inputs that integrate planned motor acts. As discussed later in the section on working memory (see Working Memory and Executive Function Network, these regions have an important role in the temporal organization of behaviors, including motor sets and motor sequences.⁶⁸In the pres- ence of a lesion that destroys or disconnects some motor areas, a portion of the distributed functional network for relearning a movement or learning a new compensatory skill may be activated best by a strategy that engages non-

primary and associative sensorimotor regions.

Therapists may work around the disconnection of a stroke or traumatic brain injury with a strategy that is cued by vision or sound, self- paced or externally paced, proximal limb-directed, goal-based, mentally planned or practiced, or based on sequenced or unsequenced movements. Task-specific practice that utilizes diverse strategies may improve motor skills in part by engaging residual cortical, subcortical, and spinal networks involved in carrying out the desired motor function.^69,70Strategies that engage neuronal assemblies dedicated to imagery and hand functions are of immediate in- terest as rehabilitation approaches.

Observation and Imitation

Functional activation studies reveal that many of the same nodes of the motor system produce movement, observe the movements of other people, imagine actions, understand the actions of others, and recognize tools as objects of action.⁷¹ Motor imagery activates approximately 30% of the M1 neurons that would execute the imagined action. Observation and imitation of a simple finger movement by the right hand preferentially activated two motor- associated regions during an fMRI study by Ia- coboni and colleagues: (1) Broca’s ventral pre- motor area that encodes the observed action in terms of its motor goal, i.e., lift the finger, and (2) the right anterior superior parietal cortex that encodes the precise kinesthetic aspects of the movement formed during observation of the movement, i.e., how much the finger should be raised.⁷²Mirror neurons are a sub- set of the neurons activated by both the observation of a goal-directed movement, e.g., another person’s hand reaching for food, and by the subject’s action in reaching for an item.

Mirror neurons represent action goals more than movements. They may be critical for the earliest learning of movements from parents.

Thus, the brain’s representation of a movement includes the mental content that relates to the goal or consequences of an action, as well as the neural operations that take place before the action starts (see Experimental Case Study 1–1). In a sense, the cognitive systems of the brain can be thought of as an outgrowth of the increasing complexity of sensory manipulations for action over the course of man’s evolution.

Indeed, one of the remarkable changes in how

The Clinical Science of Neurologic Rehabilitation, Second Edition