Adaptability and of the Human System:...

NEURAL PLASTICITY VOLUME 8, NOS. 1-2, 2001

Adaptability and Flexibility of the Human Motor System:Implications Neurological Rehabilitation

Theo Mulder and Jacqueline Hochstenbach’3

lInstitute ofHuman Movement Sciences and 2 Department ofRehabilitation Medicine,3Neuropsychological Centerfor Brain Damage Aftercare, University ofGroningen,

Groningen, The Netherlands

ABSTRACT

This article stresses the plasticity of theadult sensorimotor cortex in response tovarious injuries or environmental changes. Thedominant role of sensory input is discussed. Anumber of studies are presented that show howinput may lead to learning and change. Learningis discussed in relation to recovery. It is shownhow concepts from the field of motor controland learning may be used for improving neuro-logical rehabilitation. Specific attention is givento the variability of input, the meaningfulnessof input, and the role of the learning context.The learning context and the applicationcontext should have essential characteristics in

common, otherwise transfer of learning will be

non-optimal. It is argued that learning land-scapes are necessary in order to treat patientsin such a way that the learned skills are

transferable to situations outside the hospital.

KEY WORDS

recovery, neurological rehabilitation, motor disorders,brain damage

INTRODUCTION

Each year hundreds of thousands of people are

hit by brain damage. Most ofthem suffer from the

consequences of a stroke. In general, one can arguethat about 500 cases occur annually in a populationof 250,000 (Dombovy, 1993). Stroke is the thirdcommonest cause of death after heart disease andcancer in the western society and the most frequentcause of severe disability (Khaw, 1996). Althoughstroke is seen as a disease of old age, with agebeing the most important risk factor, approximately25% of all stroke victims are younger than 65years and thus disabled during the productiveyears oftheir lives.

Although primary prevention still seems to bethe most important means of reducing theextensive effects of stroke, it is not applicable toall risk factors. In recent years, research has beenincreasingly devoted to the effects of restorativepharmacological interventions and neuroprotectivesimmediately following infarction, but until nowthe results are ambiguous (James, 1997). Anincreasing number of researchers even wonderwhether the possibility of neuroprotection is a

valid concept in humans and whether further researchis still sensible (Lodder, in press). This means thatafter surviving the acute phase, most patients andtheir families still are confronted with a complexmixture of sensorimotor, cognitive, and behavioralproblems (Hoehstenbach et al., 1998). These patientsare referred to a rehabilitation center, be it that thepercentage of referrals may differ substantiallyacross different countries. In the Netherlands,about 5% to 10% of all stroke patients are referredto a rehabilitation center.

(C) Freund & Pettman, UK, 2001 131

I32 T. MULDER AND J. HOCHSTENBACH

Although many agree upon the usefulness ofrehabilitation, it is very difficult to assess the efficacyof neurological rehabilitation. Many variablesinfluence the end result, and most of the studiesdiffer in methodology so that comparability islimited (see also Wagenaar, 1990, Kwakkel, 1998).In this article, we will not focus on the efficacy ofneurological rehabilitation in terms of an analysisof costs and benefits but ask whether neurologicalrehabilitation may be improved by linking it moreclosely to modem developments in neurobiology,movement science, and neuropsyehology. Indeed,in spite of the massive amounts of time and moneythat are invested in neurological rehabilitation, theresults are not always convincing. To answer theabove mentioned question, we will describe in grossterms some recent insights into the intrinsic plasticityof the neuromotor system. We argue that theseinsights are relevant for the (re-)learning of motorskills after brain damage.

THE INTRINSIC PLASTICITY OF THENEUROMOTOR SYSTEM

The largest part of the 20th century wasdominated by a rather pessimistic view on theplasticity of the brain. It was argued that a hard-wired brain with localization of function left noroom for plasticity (see Bach-y-Rita, in press).Furthermore, it was argued that the adult brain hadno intrinsic capacity to recover from damage. Thefocus in treatment, therefore, was very often onfunctional compensation.

During the eighties of the last century, however,a shift in thinking occurred, mainly as a result ofthe studies performed by Merzenich and co-workers.Merzenich et al. (see Merzenich & Kaas, 1983)were able to show that neural maps on the sensori-motor cortex were not rigid but very dynamic. Themaps changed under the influence of input. Wheninput was withdrawn, the maps more or less

shriveled up, whereas when input was increased,the maps extended in space. Furthermore, theyshowed that previously existing synapses could bedramatically modified and that new synapses couldbe formed. Many other studies showed that centralsensory representations could be reorganized, notonly as a result of changes in the peripheral inputin an experimental context (Kaas et al., 1983) butalso after amputation (Hall, et al., 1990), spinalcord injury (Topka et al., 1991; Bruehlmeier et al.,1998), deafferentation (Brasil-Neto et al., 1992),after isehaemie nerve block (Brasil-Neto et al.,1993), and aider stroke (Traversa et al., 1997).

In earlier work, Spear (1997) showed thatneurons in the lateral supra-sylvian gyms thatnormally are unresponsive to specific visual inputbecame responsive to these stimuli when the visualcortical areas were impaired. Cohen et al. (1999)showed the existence of cross-modal plasticity inthe blind. Areas activated in sighted subjects duringthe performance of visual tasks became activatedin blind subjects in association with tactile orauditory discrimination tasks. They indicated,however, that the susceptible period for this formof functionally relevant cross-modal plasticity didnot extend beyond the age of 14 years. Calford &Tweedale (1990) mentioned that the adaptiveplasticity even showed inter-hemispheric transfer.They showed that in flying foxes (Pteropusscapulatus) the receptive fields ofneuron assemblies,which originally represented the thumb that hadbeen anaesthetized, expanded within a few minutesafter the injection. The receptive fields in theopposite hemisphere representing the unaffectedthumb, however, also expanded.

These results clearly emphasized the plasticityof the system, and Nudo et al. (1996) indicated thatthis plasticity could be exploited for rehabilitativetraining. After an isehemie infarct that destructedthe hand-territory in the primary motor cortex,squirrel monkeys were trained in skilled hand-use.Nudo et al. were able to obtain evidence for a

ADAPTABILITY AND FLEXIBILITY OF THE HUMAN MOTOR SYSTEM 133

functional reorganization. In some instances, thehand representation expanded into regionsformerly occupied by representations of the elbowand shoulder. More important was that thisfunctional reorganization was accompanied by abehavioral recovery of skilled hand function. Theirresults suggested that after local damage to themotor cortex, rehabilitative training may facilitatereorganization and that the undamaged motorcortex plays a role in recovery. In other words, themotor cortex reorganizes in association with theacquisition of skills.

Recently, Stefan et al. (2000) showed that an

enduring change in the excitability of corticaloutput circuits could be induced by synchronouslypairing low-frequency peripheral stimulation ofsomatosensory afferents with transcranial magneticstimulation over the motor cortex. They arguedthat this paired associative stimulation activatedintracortical fibers. Remarkably few stimulus pairswere necessary to induce this change in corticalexcitability. The plastic effect was already presentafter 30 minutes, or 90 stimulus pairs. The effectlasted between 30 and 60 minutes, which refers toa Long Term Potential-like (LTP) phenomenon, asLTP by definition lasts >30 minutes (see, Stefan etal., 2000).

Gaining more insight into the mechanismsbehind cortical plasticity is extremely importantand a necessary requirement for the developmentofnovel treatment and training procedures.

The above mentioned examples clearly indicatethat sensory input is critical for the maintenance ofstable input-output relations. Absence of any inputor a degraded input from a limb has an almostimmediate effect on the cortical representation ofthat limb. Against this background Rosinni et al.,(1994, 176) argued that, "continuous peripheral inputfrom the whole of a given body district is a

conditio sine qua non for the maintenance of normalsomatotopic cortical organization related to thatbody part." Ramachandran & Hirstein (1998)

showed what happened when afferent input to thebrain was shut off completely. After amputation ofa limb, patients experience very vivid phantomsensations, that is, they still experience thepresence of a leg or hand, in spite of the fact thatthe limb has been removed. These patients reportbizarre changes across time, such as telescoping orshrinkage ofthe phantom limb so that, for exampletheir amputated foot finally is felt directlyconnected to the knee or hip. Also, the overall sizeof the limb may shrink, even to the size of a stamp.Their results also indicated that the removal of alimb resulted in a number of remarkable reorgani-zations. For example, when the investigator strokedthe face of a patient, the patient experienced asimilar sensation in his phantom hand. Water thatruns down the face was experienced as water notonly running down the face but also running downthe amputated hand. The authors explained thisphenomenon in terms of the re-mapping of brainareas. Indeed, in the Penfield ’homunculus’ (therepresentation of body parts onto the surface of thebrain) it can be observed how the hand area isbordered below by the face area. Due to theamputation, input from the hand area was lost andconsequently sensory fibers originating from theface invaded the ’empty’ area of the hand andbegan to drive the cells there. As a result of thisneural invasion, it became possible to ’touch’ thephantom hand by touching the face. The same

happened in the shoulder area that is representedjust above the hand area in the Penfield’homunculus’, touching points on the shoulderevoked sensations in the phantom hand (see alsoRamachandran & Blakeslee, 1998; Spitzer, 1999).

All the above described examples stress thecrucial role of information for the maintenance ofsensory maps. As soon as the information is

withdrawn, the maps decay. The effect of this

decay is not limited solely to the sensory domainbut has implications also for the motor domain. Alarge number of studies showed that animals who

134 T. MULDER AND J. HOCHSTENBACH

have been deafferented after having learned a skillcontinue to perform the skill, but with distinctperformance limitations. They are less fast, lessfluent, and less coordinated (see, Magill, 1998).Also for learning, sensory information is cruciallyneeded. Numerous studies showed that in conditionswhere no information was fed back concerning theresults of the performed movements, learning wasabsent or minimal (Schmidt, 1988).

LEARNING

Although learning forms a classic topic inpsychology, it is still difficult to define un-ambiguously. Normally, learning is defined as arelatively permanent change in behavior as a resultof practice (Schmidt, 1988; Magill, 1998). Thisdefinition focuses totally on the end-result oflearning and ignores the process of learning. It is,however, very difficult to observe learning in vivo,since it must be shown that the cellular changesare specifically related to the effects of experienceand not to some other property of the milieu or tospontaneous development. Although learningdepends on changes in neurons and their circuitry,the basic mechanisms behind these changes arestill far from understood. During the last decades,many experiments have been performed that haveimproved our insight into the basic characteristicsof motor learning. These studies indicated that as a

consequence of learning,new dendrites may sprout, or there might beextension of already existing branches;existing synapses may change or new onescreated;changes in the axons may take place; or

new neurochemicals may be produced.

In spite of the many obscurities that still exist,it is generally accepted that learning is based on

the intensification of the connectivity between

neurons. The co-activation of connected cellsresults in a modification of weights so that theprobability increases that a post-synaptic cell willfire when a pre-synaptic cell fires. This, in fact, isthe essence of Donald Hebb’s insight, pictured inhis highly influential book The Organization ofBehavior (Hebb, 1949). It took, however, morethan 20 years until physiological evidence for thisepoch-making idea could be obtained.

In 1973, Bliss & Lomo showed that wheninput fibers to the hippocampus were stimulatedby brief high-frequency volleys, a long-lastingincrease of the connection strength between theinput fibers and their target neurons resulted. WhatBliss & Lomo discovered became known as longterm potentiation (LTP). Their finding attractedconsiderable attention because it provided a modelof how converging inputs from various sources,including local intracortical fibers, cortico-corticaland thalamo-cortical afferents could interact toreshape local patterns and representations. Theirexperimental results supported to a large extent theideas of Hebb (see also Churchland & Sejnowski,1992).

In search for the basic mechanisms of learning,numerous experiments were performed on hippo-campal neurons. However, these experiments wereinfluenced also by some remarkable studiesperformed by neuropsychologists (see, Milner et

al., 1968). These psychologists studied patientswho underwent a bilateral resection of the mesialtemporal lobe structures for the management ofintractable epilepsy. It was found that after theoperation, the patients were left almost totallyamnesic. They could not remember events that hadhappened as recently as 5 minutes before, evenwhen the events were salient and important to

them. They had lost the ability to learn and retainnovel information, although they were unimpairedin memorizing events that had taken place beforethe surgery. Warrington & Weiskrantz (1974)reported the intriguing result that these patients


learned tasks, such as the picture-completion task,at a normal rate, although they were amnesic anddenied that they had ever seen the pictures theycompleted correctly. This indicated that some formof learning exists that is implicit and that takesplace even when the learner has no awareness ofthe learned material.

The LTP-phenomenon was not limited to thehippocampus but was also shown in a number ofbrain areas, such as the auditory cortex (Cruikshank& Weinberger, 1996), the somatosensory cortex(Crair & Malenka, 1995), and the visual cortex(Hirsch & Gilbert, 1993). Recently, LTP has beendemonstrated in cortical areas, known for theircapacity to reorganize themselves spontaneouslywhen input is changed (Aroniadou-Anderjaska &Keller, 1995).

Hence, as a result of input, synaptic weightschange and this change is termed learning. Spitzer(1999, 51) in his well written monograph arguesthat learning takes place by gradually changing thesynaptic weights and the connectivity betweengroups of neurons. This means that learning has tooccur slowly because only small changes of theweights enable the networks to extract generalfeatures from the input and to distil rules. Ifsynaptic weights were changed in large increments,the target would be missed. Large changes mightlead to wild oscillations of the network around thedesired output rather :than slowly progressingtowards a stable input-output relationship.

MOTOR LEARNING AND RECOVERY

Processes playing a role in recovery afterdamage to the neuro-motor system are partlyidentical to learning. The damage forces thesystem to reorganize and to create a novel order. Astroke, for example, results in a dramatic break-down of many central control systems, leading tosevere sensorimotor and cognitive disorders. A

limb-amputation leaves the central machinery intactbut alters the layout of the afferent input to thebrain so that central systems have to adapt to thisaltered input. A progressive neuromuscular disease(e.g., Charcot Marie Tooth, type Ia) leads to changesin the afferent input to the brain, but as thesechanges emerge slowly across the years, they leavethe brain ample time to adapt to these changes (seeMulder et al., in press). Hence, whether the damageis central or peripheral, whether the damage appearssuddenly or as the result of a slowly progressingdisease, in all these cases the neural system has toreorganize, has to change, has to re-learn.Learning, adaptation, and recovery, therefore, arerelated processes. Two types of learning may bedistinguished: learning as a result of self-organization and learning as a result of exercise.The examples mentioned above all stress the self-organizing character of the system, in that theobtained changes took place as a result ofresponse-produced input. Indeed, in all theseexperiments, there was no supervisor and notraining protocol. When two fingers that arenormally separated from each other are connectedto ach other by surgery, it can be observed thatthe separate representations of the individualfingers in the brain disappear, and the two fingersinduce a single fusiform representation (see Allardet al., 1991). No exercise is needed for thesechanges, they take place as a result of the ’design’of the system. Information shapes the control.

However, not all changes take place in such anautonomous way, sometimes we have to train andexercise in order to reach our goals. The relearningof gait, reaching, or speech after brain damageclearly is the result of an interaction between theabove described spontaneously occurring mecha-nisms and a carefully designed learning program.In the next part of the paper, we will focus on thedesigning of such a program, and we will arguethat learning may be improved when recentinsights of neuro-plasticity and motor learning are


integrated with the methods ofmotor rehabilitation.Four basic roles for motor (re-)learning are

distinguished here (see also, Mulder & Hochsten-bach, in press):

1. input (information) is a sine qua non for learning;2. input must be variable;3. input must be meaningful,4. the site of training must be related to the site of

application (principle of equivalent situations).

Input is a sine qua non for learning

As has been described above, learning is theresult of synaptic changes. These changes, however,take place only when the brain is fed with activity-dependent information. Without any input orinformation the networks decay. Immobilization,therefore leads to the ’shrinkage’ of neuronalnetworks. It is known that the continuous input ofsensory feedback during gait does influence thestrength of neuronal connections in the spine. Ineats it has been shown that after spinal cord injury,step-like movements only reappear when afferentinformation is fed into the spinal cord (Wemig etal., 1998).

Also in spinal-cord injured humans it has beenshown that some relearning of walking could beestablished as a result of intensive exercise on atreadmill (Dietz et al., 1998; see also, van deCrommert et al., 1998). Spinal cord circuits, as wellas supraspinal centers ( in patients with incompletelesions), are capable of significant reorganizationas a result of activity-dependent input. Withoutthis input, no reorganization takes place. The sameis true for stroke patients; substantial improvementof gait is possible as a result of exercise andtraining. Each step, each new loco-motor taskcreates a flow of afferent input which forms thebasis for learning.

Input should be variable

However, input as a repetitive train of identicalsensory stimulation is not effective. The inputshould be variable. When identical input isrepeated, the input looses its informational valueand the system will quickly adapt to it. Neuralnetworks are shaped by both input and variation.Note, however, that variation is not identical tochaos or random input. Indeed, the worst thing fora learning system is random input. If the input israndom, no structure can be extracted from it andno learning takes place (Spitzer, 1999, but see alsoRitter & Schulten, 1986; Singer, 1986). The same,however, is true for identical inputs. When eachmovement produces identical information, thesystem is not able to distill knowledge (rules) fromthese movements, which can be transferred toother movements or to movements made in a novelcontext. The unique characteristic of movement,however, is that each response in fact is a novelone. That is, no response is produced in exactly thesame way as before. Something about the responsecondition or context is always unique and leads tothe imrhediate modification of the present response.In order to be able to cope with the instabilities inthe environment, it is necessary to vary theconditions and performance-characteristics of themovements during learning or therapy. By varyingthe performance, also the performance-producedfeedback (sensory input to the brain) is changing,which is important for shaping neural networkswith a high generalization value. When a learningsystem is confronted with identical informationacross time, it will certainly learn from thatinformation, but the learned skill will not beflexible and may not be generalized to othersituations or movements that differ from the onelearned on the basis ofthe available information.

The great Russian physiologist, Nicolai Bemstein,was well aware of these arguments when he stated


that learning is repetition without repetition (seeWhiting, 1984). What he meant was that repetitionis necessary, but the repeated movements or actionsshould be different. Skill (re-)learning only resultswhen the repeated input is variable. Also Spitzer(1999) stresses the importance of variable input,but he adds to it the need for small variations.When across attempts the input differs too muchand too fast, the system will not be able to distilltransferable information from these attempts.

The implications for retraining gait after strokeare clear: a patient should be exercised in a numberof conditions which create changes in sensory input(e.g. walking on fiat floors, sand, grass, gravel, up-hill, down-hill). These conditions create differentflows of input.

Input should be meaningful

Input should be variable, but it also should bemeaningful. Merely presenting input patterns is notenough for adequate learning. The learner shouldbe attentive to the offered information. The tasksemployed in rehabilitation should, therefore, besignificant for the patient. Without this significancethe learning effect will be minimal. It is well knownthat information with an emotional implication isremembered better than neutral information (LeDoux, 1996). McGaugh et al., (1993) showed thatif rats are given an injection of adrenaline,immediately after learning they show an enhancedmemory for the learned task. This suggests that ifadrenaline is released naturally from the adrenalglands, the learned task will be remembered better.Since emotional arousal usually results in therelease of adrenaline, it might be expected thatlearning in situations with an emotional content or

with a clear meaning for the person will be superiorto other situations. McGaugh et al. (1990; cited inLeDoux, 1996, 207) gave additional evidence forthe role adrenaline plays in the memory enhancingeffect of emotional arousal. They asked adult

subjects to read two versions of a story about a boyriding a bike. Some of the subjects where asked toread the version in which the boy takes a ride onhis bike and goes home. He and his mom drive tothe hospital to pick up his dad, a doctor. The otherversion was that the boy takes a ride on his bike, ishit by a car, and rushed to the hospital, where hisdad is a doctor. The words in the two stories arematched as closely as possible, with only theemotional implications manipulated. After readingthe story, and before being tested for recall, onegroup of subjects is injected with a placebo whilethe other group is injected with a drug that blocksthe effect of adrenaline. For the placebo-treatedsubjects, those that read the emotional storyremembered many more details than those thatread the neutral story. However, for the subjectsreceiving the adrenaline blockade, there was nodifference in the memory of the emotional andnon-emotional stories. All subjects performed likethe placebo group that read the neutral story.Adrenaline blockade indeed prevented the memoryenhancing effects of emotional arousal.

Spitzer (1999, 144) addressed the importanceof meaningful input by indicating that unimportantor meaningless events do not cause cortical changes,even if they occur with the same frequency asunimportant ones. When two groups of animalshave to learn a certain discrimination task and onlyone group is rewarded for its attempts, then onlythis group shows a learning effect and a change ofthe cortical representation. So, training has an

effect only when subjects pay attention to thestimuli, and subjects will pay attention to a task or

stimulus when it has significance.Corbetta et al. (1991) questioned whether

attending to specific features of the environmenthas a measurable effect on brain functioning.Normal subjects watched a computer screendisplaying up to thirty objects of a certain colorand form, moving at a certain speed. The subjectshad to attend to color or form or movement.


Corbetta et al. recorded the brain activity by meansof PET during rest, as well as when attending tothe selected features. When we pay attention tospecific aspects of the environment, the activity ofthe area that processes the selected informationincreases. The PET results indicated, that whensubjects concentrated on color, form, or movement,the cortical areas that became active were identicalwith or close to the areas known to be involved inthe processing of color, form or motion. Hence, acertain event or a certain task that may increase theactivity in a related brain area is increased.Increased activity, however, implies increasedsynaptic transmission and more learning. Attentionleads to increased activity, and activity is aprerequisite for learning.

These arguments are very similar to Neisser’s(1976) arguments concerning the anticipatory cycle,almost 25 years ago. He showed how attentionprimes the system for activity by reducing thenumber of possible actions. Furthermore itstrengthens the development of control programs(or "schemata" in the words ofNeisser).

Baeh-y-Rita (in press) gave another argumentfor the important role of meaningfulness. Heindicated that neuromodulators may play a role inchanging the excitation threshold of neurons. Moodstates (attention, emotion, motivation) influencethese neuromodulators and by this the rate andefficacy of learning.

PRINCIPLE OF EQUIVALENT SITUATIONS

This principle has its roots in motor research atthe beginning of the 1900s, particularly in theidentical elements theory of Thomdike (1914).The theory stated that when the learning takesplace in context X and the application will takeplace in context Y, then for an optimal transfer it isnecessary that both contexts have as much as

possible elements in common. Elements are the

general characteristics of the task or performancecontext. Holding (1976), who up-dated the insightsof Thomdike, argued that the amount and thedirection of transfer is related to the similarity ofthe stimulus and response characteristics of thelearning and application situation. Related tomotor tasks (e.g., walking in a hospital vs. walkingon a street) this means that the more similaritiesthese two tasks have, the more transfer will takeplace. However, it is important to note thatsimilarities are not limited to the motor skills only,also the characteristics of the learning environmentare stored in memory during the learning process.When the learning or treatment context differsessentially from the application context, lesstransfer will take place. Hence, the similaritybetween skills plus the similarity between contextsdetermine the amount of transfer that will takeplace after learning. However, since researchaddressing the problem of learning transfer hasbeen minimal during recent years, we should bemodest in giving suggestions for solving theproblem.

CONCLUSIONS

In this paper, we argued that the recent insightin neural plasticity and learning may play a rolefor improving treatment after damage of the neuro-motor system. We stressed the crucial role ofsensory input. Indeed, on the basis of the mentionedexperimental results, it is clear that input forms asine qua non for change and learning. We arguedthat manipulating the input may offer additionalopportunities for spinal cord patients, patients withamputated limbs, and stroke patients. Furthermore,it was argued that concepts derived from researchinto motor learning may be used in neurologicalrehabilitation. We stressed the importance ofvariability and meaning and we emphasized therole of the context, the learning environment. The


latter is important since many therapists tend toignore this role and expect significant transfer oflearning even when the therapeutic context differsessentially from the conditions outside the hospital.In fact, a learning landscape is needed that enablesthe therapist to exercise under conditions that areecologically relevant, that is to say, under conditionsthat have many elements in common with the dailylife situation. These learning landscapes shouldform part of any modem design of a rehabilitationcenter. Until now, only a few centers haveappreciated these principles. This article containsalso arguments against the employment of rigidlyformalized treatment methods that ignore theindividual character of the damage by assumingthat all patients may be treated according to thesame protocol. Hence, neuroscience, neuropsy-chology, and motor control theory have somethingto offer for neurological rehabilitation, even at thevery concrete level.

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