Theories and models of motor control

We begin this section with a summary and historical perspective of motor control theories (Table 4-1). The control of human movement has been described in many different ways. The production of reflexive, automatic, adaptive, and voluntary movements and the performance of efficient, coordinated, goal-directed movement patterns involve multiple body systems (input, output, and central processing) and multiple levels within the nervous system. Each model of motor control that is discussed in this section has both merit and disadvantage in its ability to supply a comprehensive picture of motor behavior. These theories serve as a basis for predicting motor responses during patient examination and treatment. They help explain motor skill performance, potential, constraints, limitations, and deficits. They allow the clinician to (1) identify problems in motor performance, (2) develop treatment strategies to help clients remediate performance problems, and (3) evaluate the effectiveness of intervention strategies employed in the clinic. Selecting and using an appropriate model of motor control is important for the analysis and treatment of clients with dysfunctions of posture and movement. As long as the environment and task demands affect changes in the CNS and the individual has the desire to learn, the adaptable nervous system will continue to learn, modify, and adapt motor plans throughout life.

Body structures and functions that contribute to the control of human posture and movement

Keen observation of motor output quality during the performance of functional movement patterns helps the therapist determine activity limitations and begin to hypothesize impairments within sensory, motor, musculoskeletal, cardiopulmonary, and other body systems. The following section presents and defines some of these key factors, including sensory input systems, motor output systems, and structures and functions involved in the integration of information in the CNS.

Control of voluntary movement

Table 4-2 shows the body system processes involved in motor control, their actions, and the body structures included. The following section explains these processes in more detail.

Information processing

The processing of information through the sensory input, motor output, and central integrative structures occurs by various methods to produce movement behaviors. These methods allow us to deal with the temporal and spatial components necessary for coordinated motor output and allow us to anticipate so that a response pattern may be prepared in advance. Serial processing is a specific, sequential order of processing of information (Figure 4-1) through various centers. Information proceeds lockstep through each center. Parallel processing is processing of information that can be used for more than one activity by more than one center simultaneously or nearly simultaneously. A third and more flexible type of processing of information is parallel-distributed processing.¹⁴ This type of processing combines the best attributes of serial and parallel processing. When the situation demands serial processing, this type of activity occurs. At other times parallel processing is the mode of choice. For optimal processing of intrinsic and extrinsic sensory information by various regions of the brain, a combination of both serial and parallel processing is the most efficient mode. The type of processing depends on the constraints of the situation. For example, maintaining balance after an unexpected external perturbation requires rapid processing, whereas learning to voluntarily shift the center of gravity to the limits of stability requires a different combination of processing modes.

In summary, information processing reinforces and refines motor patterns. It allows the organism to initiate compensatory strategies if an ineffective motor pattern is selected or if an unexpected perturbation occurs. And, most important, information processing facilitates motor learning.

Movement patterns arising from self-organizing subsystems

Coordinated movement patterns are developed and refined via dynamic interaction among body systems and subsystems in response to internal and external constraints. Movement patterns used to accomplish a goal are contextually appropriate and arise as an emergent property of subsystem interaction. Several principles relate to self-organizing systems: reciprocity, distributed function, consensus, and emergent properties.¹⁵

Reciprocity implies information flow between two or more neural networks. These networks can represent specific brain centers, for example, the cerebellum and basal ganglia (Figure 4-2). Alternatively, the neural networks can be interacting neuronal clusters located within a single center, for example, the basal ganglia. One model to demonstrate reciprocity is the basal ganglia regulation of motor behavior through direct and indirect pathways to cortical areas. The more direct pathway from the putamen to the globus pallidus internal segment provides net inhibitory effects. The more indirect pathway from the putamen through the globus pallidus external segment and subthalamic nucleus provides a net excitatory effect on the globus pallidus internal segment. Alteration of the balance between these pathways is postulated to produce motor dysfunction.^16,17 An abnormally decreased outflow from the basal ganglia is postulated to produce involuntary motor patterns, which produce excessive motion such as chorea, hemiballism, or nonintentional tremor. Alternatively, an abnormally increased outflow from the basal ganglia is postulated to produce a paucity of motions, as seen in the rigidity observed in individuals with Parkinson disease (see Chapter 20).

Distributed function presupposes that a single center or neural network has more than one function. The concept also implies that several centers share the same function. For example, a center may serve as the coordinating unit of an activity in one task and may serve as a pattern generator or oscillator to maintain the activity in another task. An advantage of distributing function among groups of neurons or centers is to provide centers with overlapping or redundant functions. Neuroscientists believe such redundancy is a safety feature. If a neuronal lesion occurs, other centers can assume critical functional roles, thereby producing recovery from CNS dysfunction.18–22

Consensus implies that motor behavior occurs when a majority of brain centers or regions reach a critical threshold to produce activation. Also, through consensus extraneous information or information that does require immediate attention is filtered. If, however, a novel stimulus enters the system, it carries more weight and receives immediate attention. A novel stimulus may be new to the system, may reflect a potentially harmful situation, or may result from the conflict of multiple inputs.

Emergent properties may be understood by the adage “the whole is greater than the sum of its parts.” This concept implies that brain centers, not a single brain center, work together to produce movement. An example of the emergent properties concept is continuous repetitive activity (oscillation). In Figure 4-3, A, a hierarchy is represented by three neurons arranged in tandem. The last neuron ends on a responder. If a single stimulus activates this network, a single response occurs. What is the response if the neurons are arranged so that the third neuron sends a collateral branch to the first neuron in addition to the ending on the responder? In this case (Figure 4-3, B), a single stimulus activates neuron No. 1, which in turn activates neurons No. 2 and No. 3, causing a response as well as reactivating neuron No. 1. This neuronal arrangement produces a series of responses rather than a single response. This process is also termed endogenous activity.

Another example of an emergent property is the production of motor behavior. Rather than having every MP stored in the brain, an abstract representation of the intended goal is stored. At the time of motor performance, various brain centers use the present sensory information, combined with past memory of the task, to develop the appropriate motor strategy. This concept negates a hardwired MP concept. If MPs were hardwired and if an MP existed for every movement ever performed, the brain would need a huge storage capacity and would lack the adaptability necessary for complex function.

Motor control section summary

Motor control theories have been developed and have evolved over many years as our understanding of nervous system structure and function has become more advanced. The control of posture and movement is a complex process that involves many structures and levels within the human body. It requires accurate sensory inputs, coordinated motor outputs, and central integrative processes to produce skillful, goal-directed patterns of movement that achieve desired movement goals. We must integrate and filter multiple sensory inputs from both the internal environment of the body and the external world around us to determine position in space and choose the appropriate motor plan to accomplish a given task. We combine individual biomechanical and muscle segments of the body into complex movement synergies to deal with the infinite “degrees of freedom” available during the production of voluntary movement. Well learned motor plans are stored and retrieved and modified to allow for flexibility and variety of movement patterns and postures. When the PNS or CNS is damaged and the control of movement is impaired, new, modified, or substitute motor plans can be generated to accomplish goal-directed behaviors, remain adaptable to changing environments, and produce variable movement patterns. The process of learning new motor plans and refining existing behaviors by driving neuroplastic changes in the nervous system is discussed in the next sections of this chapter. The control of posture and balance is also discussed in Chapter 22.

An illustration of motor learning principles

Motor learning is the product of an intricate balance between the feed-forward and feedback sensorimotor systems and the complex central processor—the brain—for the end result of acquiring and refining motor skills. People go through distinct phases when they learn new motor skills.

Observe the sequential activities of the child walking off the park bench in Figure 4-4, A through C. A clear understanding of this relationship of walking and falling is established. In frame A, the child is running a feed-forward program for walking. The cerebellum is procedurally responsible for modulating appropriate motor control over the activity and will correct or modify the program of walking when necessary to attain the directed goal. Unfortunately, a simple correction of walking is not adequate for the environment presented in frame B. The cerebellum has no prior knowledge of the feedback presented in this second frame and thus is still running a feed-forward program for stance on the left leg and swing on the right leg. The cerebellum and somatosensory cortices are processing a massive amount of mismatched information from the proprioceptive, vestibular, and visual receptors. In addition, the dopamine receptors are activated during the goal-driven behaviors, creating a balance of inhibition and excitation. Once the executive or higher cognitive system recognizes that the body is falling (which has been experienced from falling off a chair or bed), a shift in motor control focus from walking to falling must take place. To prepare for falling, the somatosensory system must generate a sensory plan and then relay that plan to the motor system through the sensorimotor feedback loops. The frontal lobe will tell the basal ganglia and the cerebellum to brace and prepare for impact. The basal ganglia are responsible for initiating the new program, and the cerebellum carries out the procedure, as observed in Figure 4-4, C. The child succeeds at the task and receives positive peripheral and central feedback in the process. It is possible that this experience has created a new procedural program that in time will be verbally labeled “jumping.” The entire process of the initial motor learning takes 1 to 2 seconds. Because of the child’s motivation and interest (see Chapter 5), the program is practiced for the next 30 to 45 minutes. This is the initial acquisition phase and helps the nervous system store the MP to be used for the rest of the child’s life. If this program is to become a procedural skill, practice must continue within similar environments and conditions. Ultimately the errors will be reduced and the skill will be refined. Finally, with practice, the program will enter the retention phase as a high-level skill. The skill can be modified in terms of force, timing, sequencing, and speed and is transferrable to different settings. This ongoing modification and improvement are the hallmarks of true procedural learning. Modifications within the program will be a function of the plasticity that occurs within the CNS throughout life as the child ages and changes body size and distribution. Similar plasticity and the ability to change, modify, and reprogram motor plans will be demanded by individuals who age with chronic sensorimotor limitations. Unfortunately, in many of these individuals, the CNS is not capable of producing and accommodating change, which creates new challenges as they age with long-term movement dysfunctions (see Chapters 27, 32, and 35).

Stages of motor learning

Several authors have developed models to describe the stages of motor learning. These models are presented in Table 4-3. Regardless of the model, it is widely accepted that the process of learning a motor task occurs in stages. During the initial stages of learning a motor skill, the intent of the learner is to understand the task. To be able to develop this understanding requires a high level of concentration and cognitive processing. In the middle and later stages, the individual learns to refine the movement, improve efficiency and coordination, and perform the skill within different environmental contexts. The later stages are characterized by automaticity and a decreased level of attention needed for successful completion of the task. It is important to emphasize early that because the activities performed by a learner during each stage of learning will be different, the role of the clinician, the types of learning activities, and the clinical environment must also be different.

The learning model described by Fitts and Posner³⁹ consists of a continuous progression through three stages: cognitive, associative, and autonomous.

A learner functions in the cognitive stage at the beginning of the learning process. The person is highly focused on the task, is attentive to all that it demands, and develops an understanding of what is expected and involved in performance of the skill. Many errors are made in performance; questions are asked; cues, instructions, and guidance are given by the clinician; and demonstrations are found to be helpful in this phase of learning. Performance outcomes are variable and inconsistent, but the improvements achieved can be profound.

During the associative stage the learner refines movement strategies, detects errors and problem solves independent of therapist feedback, and is becoming more efficient and reliable at achieving the task goal. The length of time spent in this phase tends to be dependent on the complexity of the task. The ability to associate existing environmental inputs with motor plans for improved timing, accuracy, and coordination of activities to accomplish a task goal is improved. Although variability in performance decreases, the client continues to explore solutions to best solve a movement problem.

Focused practice with repetition over time leads to the automatic performance of motor skills in the autonomous stage of learning. The individual is in control of the learned movement plan and is able to use it with little cognitive attention while involved in other activities. Skills are performed with preferred, appropriate, and flexible speed, amplitude, direction, timing, and force. Consistency of performance is a hallmark of this phase, as is the ability to detect and self-correct performance errors. Individuals who do not have the cognitive skill to remember the learning can go through a much longer repetitive practice schedule to learn the motor skill, but there will be very little carryover into other functional movements or activities.40–42

In summary, the overall process of the stages of motor learning as introduced by Fitts and Posner³⁹ suggests that first a basic understanding of a task be established, along with a motor pattern. Practice of the task then leads to problem solving and a decrease in the degrees of freedom during performance, resulting in improved coordination and accuracy. As the learner continues to practice and solves the motor task problem in different ways and with different physical and environmental constraints, the movement plan becomes more flexible and adaptable to a wide range of task demands.

Bernstein¹⁰ presented a more biomechanical perspective as he addressed the problem of degrees of freedom during motor learning. He also broke the motor learning process down into three stages: novice, advanced, and expert. He proposed that these three stages are necessary to allow a learner to reduce the large number of degrees of freedom that are inherent in the musculoskeletal system, including structure and function of muscles, tendons, joints. He proposed that as a person learns a new motor skill, he or she gains coordination and control over the multiple interacting variables that exist in the human body to master the target skill.

The novice stage is defined by the coupling of movement parameters—degrees of freedom—into synergies. During this stage some joints and movements may be “frozen” or restrained to allow successful completion of the task. An example of this is posturally holding the head, neck, and trunk rigid while learning to walk on a narrow surface.

The advanced stage is achieved by combining body parts to act as a functional unit, further reducing the degrees of freedom while allowing better interaction and consideration for environmental factors. He considers that motor plans must be adapted to the dynamic environmental conditions in which the task must be performed. In this stage the learner explores many movement solutions, reduces some degrees of freedom, develops more variable movement patterns, and learns to select appropriate strategies to accomplish a given task. This stage of motor learning is accomplished through practice and experience in performing a task in various environments. To achieve this stage the learner progressively releases some couplings, allowing more degrees of freedom, greater speed and amplitude of movement, and less constraints on the action. Performance of the task becomes more efficient, is less taxing on the individual, and is executed with decreased cognitive effort. Variability of performance becomes an indicator that a level of independence in the activation of component body parts during a given task has indeed been achieved.

In Bernstein’s expert stage, degrees of freedom are now released and reorganized to allow the body to react to all of the internal and external mechanisms that may act on it at any given time. At the same time, enhanced coactivation of proximal structures is learned and used to allow for greater force, speed, and dexterity of limb movements.⁴³

Gentile presented a two-stage model of motor learning.^44,45 She considered motor learning from the goal of the learner and strongly considered how environmental conditions influence performance and learning.

Stage one requires the client to problem solve strategies to get the idea of a movement and establish a motor pattern that will successfully meet the demands of the task. As with the models presented previously, this process demands conscious attention to the components of the task and environmental variables to formulate a “map” or framework of the movement pattern. Once this framework is established, the client has a mechanism for performing the task; however, errors and inconsistency in performance accuracy are often present.⁴⁶

During stage two the client attains improved consistency of performance and the ability to adapt the movement pattern to demands of specific physical and environmental situations. Greater economy of movement is achieved, and less cognitive and physical effort is expended to reach the task goal. Practice in appropriately challenging conditions leads to consistent, efficient, correct execution while maintaining adaptive flexibility within the motor plan, allowing the client to react quickly to changing conditions of the task.

The three motor learning theories just presented simplify a complex process into simple stages to give a broad picture of the development of skilled movement performance. Each theory can be used to assist the therapist in the process of teaching and facilitating long-term learning or relearning of motor skills before and after insult to the nervous system. The ultimate goal of motor learning is the permanent acquisition of adaptable movement plans that are efficient, require little cognitive effort, and produce consistent and accurate movement outcomes.

Variables that affect motor learning

The ecological model (constraints theory) of motor control and learning states that motor learning involves the person, the task, and the environment.⁴⁷ For a purposeful and functional movement to occur, the individual must generate movement to successfully meet the task at hand, as well as the demands of the environment where the task must be performed. For motor learning to be successful, several variables related to each of these three constructs must be taken into account.

Variables related to the individual

The clinician must first differentiate general motor performance factors that are under the control of the individual’s cognitive and emotional systems and those that are controlled by the motor system itself. These concepts are presented in Figure 4-5. There are many cognitive factors such as arousal, attention, and memory, as well as cortical pathways related to declarative or executive learning, that have specific influences over behaviors that are observed after neurological insult.^48,49 Other factors such as limbic connections to cortical pathways affected by motivation, fear and belief, and emotional stability and instability also dramatically affect motor performance and declarative learning. Some of these factors may also limit activity and participation. Therapists need to learn how to discriminate among motor output, somatosensory input, cortical processing, and limbic emotional state problems and identify how the latter two systems affect motor output. With that differentiation, clinicians should also be able to separate specific motor system deficits from motor control problems arising from dysfunction within other areas of the CNS. Last, the patient’s fitness level; current limitations in strength, endurance, power, and range of motion; or pain level may also influence learning.^35,50–55

Variables related to the task

The two major variables related to the task itself that must be considered when facilitating motor learning include practice of the task and feedback related to task performance.

Practice.

Practice is defined as “repeated performance in order to acquire a “skill.”⁵⁶ As the definition implies, several repetitions of the task are usually required to be able to achieve skillful performance of a task. With other variables being constant, more practice results in more learning.³⁵ To be effective, these repetitions must involve a process of problem solving rather than just repetition of the activity.⁵⁷ The therapist can manipulate several variables related to practice to optimize motor learning of an individual with a movement dysfunction secondary to a neurological insult.

Practice conditions.

The term practice conditions refers to the manner in which the task or exercise is repeated with respect to rest periods, the amount of exercise, and the sequence in which these tasks or exercises are performed.

According to apportionment of practice in relation to rest periods, massed tasks or exercises can be classified as massed practice or distributed practice. Massed practice is when the rest period is much shorter in relation to the amount of time the task or exercise is practiced.⁵⁸ This is contrasted against distributed practice, in which the time between practice sets is equal to or greater than the amount of time devoted to practicing a particular task or activity, such that the rest period is spread out throughout the practice.⁵⁹ In terms of neurological physical therapy practice, it is important to consider the effect of physical and mental fatigue when training. For example, physical fatigue sets in during massed practice of a particular balance exercise activity in standing and may cause a patient to fall. Moreover, individuals who are cognitively impaired may not respond positively to sustained activity that requires considerable concentration and therefore might fail in the performance of the skill. On the other hand, to be functional and useful in daily life, certain activities have to be performed without significant amounts of rest periods. For example, taking significant rest breaks when ambulating for even a short distance limits an individual’s ability to use walking in a functional manner. Sometimes a patient needs more rest periods in the initial stages of learning a skill to compensate for impairments in muscular endurance or cardiopulmonary function, with the intent of decreasing these rest periods to achieve skill performance that reflect how that activity is used in real-life situations. Therefore therapists should consider the skill demands and the desired results when choosing one practice type versus another.⁵⁹

Complete tasks or activities can usually be divided into smaller subcomponents. The way those subcomponents are practiced relative to the entire task or activity can also be manipulated to optimize motor learning. To practice the entire task or parts of the task, whole learning, pure-part learning, progressive-part learning, or whole-part learning may be used. Figure 4-6 summarizes these concepts.

Whole learning suggests that the learner practice the entire movement as one activity. Asking a person to stand up incorporates the entire activity of coming to stand from sitting. Simple movements such as rolling, coming to sit, coming to stand, and walking might best be taught as a whole activity as long as the individual has all the component parts to practice the whole.

In pure-part learning the therapist introduces one part first, then this part is practiced by the learner before another new part is introduced and practiced. Each part is critical to the whole movement, but which one is learned first does not matter. Learning a tennis serve is an excellent example of an activity that can be taught as a pure-part. Learning to toss the ball vertically to a specific spot in space is a very different and a separate part from swinging the tennis racket as part of the serve. Learning to squeeze the toothpaste onto the brush is a very different movement strategy from brushing the teeth.

Progressive-part learning is used when the sequence of the learning and the component parts need to be programmed in a specific order. Line dancing is an activity taught using progressive parts. Individuals with sequencing deficits often need to be taught using progressive parts or the individual will mix up the ordering of parts during an activity. Therapists see this in the clinical arena when an individual stands up from a wheelchair and then tries to pick up the foot pedals and lock the brakes. Given that problem, that patient needs to practice progressive part learning by first locking the brake, then picking up the foot pedals and finally standing. If the activity is not practiced using progressive-part learning, the patient will have little consistency in how the parts are put together, thereby placing that individual at high risk of failing at the functional task.

Whole-part learning can be used when the skill or activity can be practiced between the whole and the parts. In the clinical environment, a common application of this concept is whole to part to whole learning.⁶⁰ First the therapist has the client try the whole activity, such as coming to stand or reaching out to turn the door handle. Next, the therapist has the client practice a component part. Finally the whole activity is practiced as a functional pattern. In this way therapists work on the functional activity, then work on correcting the impairment or limitation, such as power production, range, or balance, and then go back to the functional activity in order to incorporate the part learning into the whole. An example might be asking a patient to first stand up from a chair. As he tries to stand he generates too much power, holds his breath, and cannot repeat the activity more than once. The therapist decides to practice a component part by first assisting the patient to a relaxed standing posture, then having him eccentrically begin to sit into a partial squat, and then having him return to standing. As the patient practices, he will increase the range of lengthening and eventually will sit and return to stand. Once that is accomplished, he will continue to practice sit to stand to sit to stand as a whole activity.

According to the sequence in which component tasks are practiced, blocked or random practice may be used. In blocked practice the patient first practices a single task over and over before moving to the next task. On the other hand, in random practice, the component tasks are practiced without any particular sequence. The contextual interference effect explains the difference in motor performance found when comparing these two types of practice. Studies have shown performance may be enhanced by using blocked practice; however, learning is not enhanced by using this type of practice. Random practice has been shown to enhance learning because this type of practice forces the learners to come up with a motor solution each time a task is performed.^61,62

Feedback.

The use of feedback is another important variable related to motor learning. Feedback is defined as the use of sensory information—visual, auditory, or somatosensory—to improve performance, retention, or transfer of a task. Internal feedback pertains to sensory information that the patient receives that can be used to improve performance of that particular task or activity in the future. The therapist provides extrinsic or augmented feedback with the intent of improving learning of the task. In people with neurological dysfunctions, extrinsic feedback is important because the patient’s intrinsic feedback system may be impaired or absent.

Extrinsic feedback can further be classified as knowledge of performance (KP) or knowledge of results (KR). KP is given concurrently while the task is being performed and can therefore also be called concurrent feedback. Feedback given concurrently, especially during the critical portions of the task, allows the patient to successfully perform the activity.

KR pertains to feedback given at the conclusion of the task (therefore also called terminal feedback) and provides the patient information about the success of his or her actions with respect to the activity. KR can be classified as faded, delayed, or summary. In faded feedback the therapist provides more information in the beginning stages of learning of the skill and slowly withdraws that information as the patient demonstrates improvement in the performance of the task. With delayed feedback, information is given to the patient when a period of time has elapsed after the task has been completed. The intent of this pause between the termination of task and feedback is to give the patient some time to process the activity and generate possible solutions to the difficulties encountered in the previous performance of the task. In contrast, summary feedback is provided after the patient has performed several trials of a particular task without receiving feedback. Previous studies showed that subjects who were given more frequent feedback performed better during the task acquisition stage of learning but worse on retention tests compared with those who received summary feedback.^63,64

Additional concepts related to long-term learning are presented in Figure 4-7.

Systems interactions: motor responses represent consensus of central nervous system components

Motor behavior reflects not only motor programming but also the interaction of cognitive, affective, and somatosensory variables. Without a motor system, neither the cognitive nor the emotional systems have a way to express and communicate inner thoughts to the world. The cognitive and emotional systems can positively or negatively affect motor responses. The significance of the somatosensory or perceptual-cognitive cortical system must be emphasized. The somatosensory association areas play a critical role in the ideational and constructional aspects of the MP itself. When there are deficits within this system, clients will often demonstrate significant distortions in motor control even without a specific motor impairment. An example of this problem might be an individual who had a stroke and developed a “pusher syndrome.” The motor behavior shown by this client would be pushing off vertical generally in a lateral or posterolateral direction.⁶⁷ Physically correcting the client’s posture to vertical or asking the patient to self-correct will not eliminate the original behavior. Pusher syndrome does not stem from a motor problem but rather from a perceptual problem of verticality from thalamic nuclei radiating false information to the somatosensory cortices. Although a therapist might want to augment intervention by trying to push the patient to vertical, the patient will resist that movement pattern. Functional training becomes frustrating to both the patient and the therapist because the impairment does not fall within the motor system itself. Reliance on the use of vision and environmental cues might be the best intervention strategy for this type of problem because the impairment is within the sensory processing centers.⁶⁸ Asking the patient to find midline and reach across midline, then acknowledging success, along with a lack of falling help the somatosensory system to relearn and thus begin to inherently correct to vertical. Verbalizing to the patient that you (the therapist) acknowledge that she or he feels as if she or he is falling when placed in the vertical position demonstrates to the client that you have accepted the patient and his or her perceptions. Simultaneously maintaining tactile contact to prevent the patient from falling effectively lets the limbic system relax and reduces its need to trigger motor reactions. This example creates conflict between the cognitive system’s information from the thalamus and motor system feedback. The thalamus is saying vertical is “X,” and the motor system is saying “if X then I am falling.” When the goal is not to fall, then the cognitive system will generally override the thalamic information and learn to accept a new concept of vertical. Taking all these variables into the treatment environment optimizes the potential that the patient will self-correct during a functional activity such as reaching with weight shift.

If a patient’s insult falls within the limbic or emotional system, then motor behavior could also be affected. The motor dysfunction will be different from the dysfunction reflecting damage either in the sensory cortices or associated with information sent to them. For years it has been common knowledge that individuals who are depressed will demonstrate motor signs of withdrawal (e.g., flexion). If the posture of flexion was created by a chemical response related to depression, then somatosensory retraining would have a limited effect on behavior. Similarly, functional training may initially modify the impairments, but without changes within the limbic system itself no permanent change will be achieved. Instead, augmenting the input to alter the emotional system and then reinforcing self-control could create the best potential outcome.

For many clinical problems, functional retraining of the motor system through attended, sequenced, repetitive practice could lead to greater functional gains, although the body system impairment(s) may never be eliminated. That is, muscle strengthening and programming coactivation to enable joint stability could restore client independence. Given the complexity of impairments and function in a patient with a neurological insult, a therapist may need to use all three types of intervention procedures to affect all areas of the CNS simultaneously. The decision of which intervention is most appropriate or which should be emphasized falls within the professional judgment of the clinician. There is no easy recipe to decide which intervention is best for all people. It is the problem-solving skills of the therapist and one’s keen analysis of movement function and dysfunction that lead to the best solution. Obviously, patient involvement and desired outcomes are also critical components leading to this decision.

Integration of sensory information in motor control

Understanding neural adaptation must include attention to sensory as well as motor systems. In virtually all higher-order perceptual processes, the brain must correlate sensory input with motor output to assess the body’s interaction with the environment accurately. A problem in the somatic motor system affects the motor output system. Both systems are independently adaptive, but functional neural adaptation involves the interaction of both sensory and motor processing.

The sensory system provides an internal representation of both the inside and outside worlds to guide the movements that make up our behavioral repertoire. These movements are controlled by the motor systems of the brain and the spinal cord. Our perceptual skills are a reflection of the capabilities of the sensory systems to detect, analyze, and estimate the significance of physical stimuli. (See the section on augmented therapeutic intervention in Chapter 9 for a detailed discussion of each sensory system.) Our agility and dexterity represent a reflection of the capabilities of the motor systems to plan, coordinate, and execute movements. The task of the motor systems in controlling movement is the reverse of the task of sensory systems in generating an internal representation. Perception is the end product of sensory processing, whereas an internal representation (an image of the desired movement) is the beginning of motor processing.

Sensory psychophysics looks at the attributes of a stimulus: its quality, intensity, location, and duration. Motor psychophysics considers the organization of action, the intensity of the contraction, the recruitment of distinct populations of motor neurons, the accuracy of the movements, the coordination of the movements, and the speed of movement. In both the sensory and motor systems, the complexity of behaviors depends on the multiplicity of modalities available. In sensation, there are the distinct modalities of pain, temperature, light touch, deep touch, vibration, and stretch, whereas in the motor system can be found the modalities of reflex responses, rhythmic motor patterns within and between limbs, automatic and adaptive motor responses, and voluntary fine and gross movements.96–116 Although all motor movements require integration of sensory information for motor learning, once motor control is attained the system can run on very little feedback. The relationship of incoming sensory information is particularly complex in voluntary motor movements that constantly adapt to environmental variance. For voluntary motor movements, the motor system requires contraction and relaxation of muscles, recruitment of appropriate muscles and their synergies, appropriate timing and sequencing of muscle contraction and relaxation, the distribution of the body mass, and appropriate postural adjustments. As stated, once an MP is learned, it does not take the same amount of sensory information to run the program in a feed-forward manner within the motor system as long as the information to the cerebellum is able to run and adjust all aspects of the program. (See Chapter 21 and the section on motor control in this chapter.) To learn new programs, the CNS must go through the process of receipt of sensory input, perceptual processing, communication with the frontal lobes, and relays to basal ganglia and cerebellum, followed by intentional, goal-directed execution of the motor plan.

Within each movement, there must be adjustments to compensate for the inertia of the limbs and the mechanical arrangement of the muscles, bones, and joints both before and during movement to ensure and maintain accuracy. The control systems for voluntary movement include (1) the continuous flow of sensory information about the environment, position, and orientation of the body and limbs and the degree of contraction of the muscles; (2) the spinal cord; (3) the descending systems of the brain stem; and (4) the pathways of the motor areas of the cerebral cortex, cerebellum, and basal ganglia. Each level of control is based on the sensory information that is relevant for the functions it controls. This information is provided by feedback, feed-forward, and adaptive mechanisms. These control systems are organized both hierarchically and in parallel. These systems also control activation of sensations and motor movements as well as inhibition (e.g., globus pallidus). Furthermore, some parts of the brain are needed for new learning (e.g., cerebellum) and others for maintained learning (e.g., globus pallidus, hippocampus). The hierarchical but interactive organization permits lower levels to generate reflexes without involving higher centers, whereas the parallel system allows the brain to process the flow of discrete types of sensory information to produce discrete types of movements.^117,118

Ultimately, the control of graded fine motor movements involves the sensory organ of the muscle, the muscle spindle, which contains the specialized elements that sense muscle length and the velocity or changes in spindle length. In conjunction with the tendon organ, which senses muscle tension, the muscle spindle provides the CNS with continuous information on the mechanical state of the muscle. Ultimately the firing of the muscle spindles depends on both muscle length and the level of gamma motor activation of the intrafusal fibers. Similarly, joint proprioceptors relay both closed and open chain input and mobility (range) information from within the joint structures to the CNS. This illustrates the close relationship between sensory and motor processing and the integral relationship between the two.¹¹⁹

Foundation for the study of neuroplasticity

The principal models for studying cortical plasticity have been based on the representations of hand skin and hand movements in the New World owl monkey (Aotus) and the squirrel monkey (Saimiri). These primate models have been chosen because their central sulci usually do not extend into the hand representational zone in the anterior parietal (S1) or posterior frontal (M1) cortical fields. In other primates the sulci are deep and interfere with accurate mapping. Albeit there are differences in hand use among primates, in all of the primates the hand has the largest topographical representation for the actual size of the extremity, the detail of this representation is distinct, and the hand has the greatest potential for skilled movements and sensory discrimination. However, the findings from studies of this cortical area are applicable across the different cortices as well as the other cornerstones of the brain such as the thalamus, basal ganglia, brain stem, and cerebellum.^120,121 See Figure 4-8 to identify specific anatomical locations and their respective classifications.

To understand neural adaptation and to be able to apply the principles to practice, it is necessary to objectively measure the changes. Positive changes in neural structure can be measured by using a variety of imaging techniques (e.g., magnetic resonance imaging [MRI], functional MRI [fMRI], magnetoencephalography, magnetic source imaging [MSI]). The types of outcomes that can be expected electrophysiologically and functionally are summarized in Table 4-4. At this time, imaging techniques are applied primarily for research purposes or to rule out other pathology. The specific type of intervention to address the principles of neuroplasticity may vary, but the outcomes must be clearly documented.

Principles of neural adaptation

To achieve maximum neural adaptation, there are some basic principles to follow (Box 4-1). Learning is the key to neural adaptation. Plasticity is the mechanism for encoding, the changing of behaviors, and both implicit and explicit learning. During neural adaptation, the fundamental questions are as follows: As we learn, how does the brain change its representations of inputs and actions? What is the nature of the processes that control the progressive elaboration of performance abilities? In different individuals, what are the sources of variance for emergence of improved performance? What changes in cortical plasticity facilitate the development of “automatic” motor behaviors? Why are some behaviors hard to change? What limits plasticity processes? What are the critical elements of brain circuitry, genes, synapses, neural chemistry, neuronal networks, and neural connections for restoration of lost function? What guidelines need to be followed to drive the greatest change in brain structure and function? How do spontaneous compensatory behavioral strategies contribute to or interfere with restoring lost neuronal function? How does the unaffected side contribute to or interfere with neuroplastic changes and restoration of function? Does damage to the brain alter the neuronal response to learning (e.g., cascade of cellular activity for healing altered circuitry, new neural connections)?

The most informative studies on neuroplasticity are those specifically directed toward defining the changes induced by learning. One approach has been to document the patterns of distributed neural response representation of specific inputs before and after learning. In particular, neuronal responses have been measured in the primary auditory, somatosensory, and motor cortices in animals. These animal studies have been paired with behavioral studies in humans. Both the animal and the human studies provide strong evidence documenting the ability of the brain to functionally self-organize. This capacity for change occurs not only during development but also in adulthood, specifically after learning-based activities. The basic processes for neural adaptation are discussed in the following paragraphs.

We know that if infants are deprived of sensory and motor experiences during development, the brain does not develop normally. For example, without exposure to light, there is a reduction in the number of neurons in the visual cortex.¹²² Similarly, if infants are not exposed to sound, there is a reduction in the neurons in the auditory cortex.¹²³ Even in adults, when neural circuits are not used over an extended period of time, they begin to degrade, and the unused area of the brain is allocated to serve another part of the body.¹²⁴ Similarly, if task performance is practiced, then the topography expands and becomes more detailed, as might occur in someone who is blind and reads Braille.¹²⁵ It is also interesting to note that although a person is blind, the visual cortical areas may become active when the individual is reading Braille.¹²⁶ Similarly a person who is deaf may demonstrate activation of the auditory cortex when visual stimuli are presented.

There seems to be a minimal level of repetitive practice needed to acquire a new skill that will be maintained over time. In fact, this may lead to specialization or change in the underlying neurophysiological processing.127–129 This specialization develops in response to selective cortical neuron responses specialized to demands of sensory, perceptual, cognitive, and motor skill learning.^130–133 This adaptation has been clearly documented in animal studies. For example, if an animal is trained to make progressively finer distinctions about specific sensory stimuli, then cortical neurons come to represent those stimuli in a progressively more specific and progressively “amplified” manner.

Through the course of progressive skill learning, a more refined basis for processing stimuli and generating actions critical to skilled tasks is enabled by the multidimensional changes in cortical responses. Consequently, specific aspects of these changes in distributed neuronal response are highly correlated with learning-based improvements in perception, motor control, and cognition.134–137 In these processes the brain is not simply changing to record and store content, but the cerebral cortex is also selectively refining its processing capacities to fit each task at hand by adjusting its spectral or spatial and temporal filters. Ultimately it establishes its own general processing capabilities. This “learning to learn” determines the facility with which specific classes of information can be stored, associated, and manipulated. These powerful self-shaping processes of the forebrain machinery are operating not only on a large scale during development but also during experience-based management of externally and internally generated information in adults. This self-shaping with experience allows the development of hierarchical organization of perception, cognition, motor, and executive management skills.

The process of coincidence-based input co-selection leads to changes in cortical representation. Coincident, temporally and spatially related events that fire together are strengthened together. In skill learning, this principle of concurrent input co-selection results from repetitive practice that includes the following:

The basis of the functional creation of the detailed, representational cortical maps converting temporal to spatial representations is related to the Hebbian change principle.¹⁴² The Hebbian plasticity principle applies to the development of interconnections between excitatory and inhibitory inputs within the cortical pyramidal neurons and their connections to extrinsic inputs and outputs. On the basis of the Hebbian principle, the operation of coincidence-based synaptic plasticity in cortical networks results in the formation, strengthening, and continuous recruitment of neurons within neuronal “assemblies” that “cooperatively” represent behaviorally important stimuli.

Anatomical input sources and limited projection overlap both to enable change by establishing input-selection repertoires and to determine the limits for change. There are relatively strict anatomical constraints at the “lower” system levels, where only spatially (spectrally) limited input coincidence-based combined outcomes are possible. In the “higher” system hierarchies, anatomical projection topographies are more powerful, with neurons and neuronal assemblies developing that respond to complex combinations of features of real-world objects, events, and actions.

To effectively drive representational changes with coincident input-dependent Hebbian mechanisms, temporally coordinated inputs are prerequisite, given the short durations (milliseconds to tens of milliseconds) of the time constants that govern synaptic plasticity in the adaptive cortical machinery (see reference 145 for review). Consistently uncorrelated or low–discharge-rate inputs induce negative changes in synaptic effectiveness. In addition, stimuli occurring repetitively simultaneously can also degrade the representation. These negative effects also contribute importantly to the learning-driven “election” of behaviorally important inputs.

Attentional control flexibly defines an enabling “window” for change in learning.¹⁸² Progressive learning generates progressively more strongly represented goals, expectations, and feedback^196,197 across all representational systems that are undergoing change and to modulatory control systems weighing performance success and error. Strong intermodal behavioral and representational effects have also been recorded in experiments that might be interpreted as shaping expectations.^198,199 These shaping expectations would be similar to those observed in a human subject using multisensory inputs such as auditory, visual, and somesthetic information to create integrated phonological representations, to create fine motor movement trajectory patterns that underlie precise hand control, or to make a vocal production.

Changes in synapse turnover, synapse number, synaptic active zones, dendritic spines, and the elaboration of terminal dendrites have been demonstrated to occur in a behaviorally engaged cortical zone.^{144,202–207} Through many changes in local structural detail, the learning brain is continuously physically remodeling its processing machinery, not only across the course of child development but also after behavioral training in an adult who has had a neural insult.