| | The Neural Substrates of Motor Recovery After Focal Damage to the Central Nervous SystemAbstract Ward NS. The neural substrates of motor recovery after focal damage to the central nervous system. ObjectiveTo discuss how reorganization of the surviving central nervous system tissue might subserve the improvements in function that are commonly seen over weeks, months, and sometimes years after stroke. Data SourcesOriginal scientific studies. Study SelectionThe studies reviewed all used noninvasive techniques such as functional magnetic resonance imaging, electroencephalography, magnetoencephalography, and transcranial magnetic stimulation. Only studies using motor paradigms in stroke patients were reviewed. Data ExtractionData were reviewed and assessed by the author. Data SynthesisCurrently, results suggest that functionally relevant changes do occur in cerebral networks in human stroke patients. For example, it is apparent that initial attempts to move a paretic limb after stroke are associated with widespread activity within the distributed motor system in both cerebral hemispheres. This reliance on nonprimary motor output pathways is unlikely to support full recovery, but improved efficiency of the surviving networks is associated with behavioral gains. ConclusionsThis review discusses how a better understanding of the relation between these changes and recovery will facilitate the development of novel therapeutic techniques that are based on neurobiologic principles and that are designed to minimize impairment in appropriately targeted patients suffering from stroke. HEALTH CARE SYSTEMS worldwide are dominated by people with chronic diseases and conditions. For example, in the United States, this population accounts for 80% of all health care costs,1 and in the United Kingdom neurologic damage accounts for nearly half of severely disabled adults.2, 3 When reversal of pathology is incomplete, treatment relies on rehabilitation. Treatment strategies aimed at helping patients adapt to impairment are the cornerstone of this approach, but treatments aimed at reducing impairment appear to be less well developed. Over the last decade, advances in our understanding of how the normal brain is organized at the molecular, cellular, and systems level has improved enormously. Advances in our understanding of the mechanisms of impairment lag behind, and consequently the translation of new knowledge into clinical benefits for patients with a variety of neurologic disorders is slow.4 Thus, the clinical neurosciences have a unique contribution to make toward developing rehabilitation strategies. Studying the working human brain  The tools available for studying the motor system in the working human brain, in either health or disease, are different from those used in animal models. In human subjects, experiments are performed at the level of neuronal systems rather than single cells or molecules. Both approaches have something to learn from the other, and it is likely that for a complete understanding of the way the brain responds to injury, both will be required. Functional brain imaging allows reorganization of the damaged human brain to be studied in vivo. The main techniques involved are positron emission tomography (PET), functional magnetic resonance imaging (fMRI), electroencephalography (EEG), and magnetoencephalography (MEG). The detailed theoretic background to these techniques is beyond the scope of this review. In brief, however, PET and fMRI rely on the assumption that neuronal activity is closely coupled to a local increase in cerebral blood flow secondary to an increase in metabolism. PET relies on mapping the distribution of inert, freely diffusible radioactive tracers deposited in tissue as a function of regional cerebral blood flow (CBF). fMRI comprises different methods, but the studies described here use blood-oxygenation–level dependent (BOLD) imaging techniques. During an increase in neuronal activation there is an increase in local CBF, but only a small proportion of the greater amount of oxygen delivered locally to the tissue is used. There is a resultant net increase in the tissue concentration of oxyhemoglobin and a net reduction in paramagnetic deoxyhemoglobin in the local capillary bed. The magnetic properties of hemoglobin depend on its level of oxygenation, so this change results in an increase in local tissue-derived signal intensity on T2*-weighted magnetic resonance images. When using fMRI to study neural responses in patients with cerebrovascular disease, there are several technical issues to consider. A number of studies have shown that in patients with impaired cerebrovascular reserve or advanced narrowing of the cerebral arteries, the BOLD signal may be reduced or even become negative.5, 6, 7, 8 There is no evidence that the BOLD signal is erroneously detected in these patients, and thus there is potential for false-negative rather than false-positive results. Furthermore, it is not clear how the BOLD signal is affected by a number of parameters, including time after stroke and large or small vessel disease. A multimodal approach using different imaging techniques (BOLD, perfusion, hypercapnic challenge) and concurrent neurophysiologic methods (EEG, MEG, transcranial magnetic stimulation [TMS]) may be useful when addressing the influence of multiple physiologic variables. Both EEG and MEG measure the electric activity in the brain more directly than fMRI. Electromagnetic signals produced by current flow in the apical dendrites of pyramidal cells in the cerebral cortex can be detected by either technique. Although the temporal accuracy of EEG and MEG can be measured in milliseconds compared with seconds for fMRI, the spatial accuracy of fMRI is superior to that of EEG and MEG. TMS is a noninvasive tool that allows stimulation of the cerebral cortex. A magnetic field is induced by a figure-of-8 coil held over the scalp, which causes depolarization of underlying pyramidal cells. The consequences of this depolarization can be assessed directly by (1) the size of motor-evoked potential (MEP) in a target muscle; (2) the time taken to induce an MEP (latency); and (3) the stimulation intensity required to elicit an MEP (threshold). These simple measurements allow characterization of the corticospinal system made up of cortical circuitry, the motoneuron pool, and spinal interneuronal relays. Changes in these measurements have been recorded in stroke patients, and they are thought to reflect different degrees of damage to the cerebral motor system. Reorganization in the motor system after stroke Group Studies When functional imaging techniques became available to investigators interested in studying brain reorganization after stroke, an obvious approach was to compare brain activation during movement in patients who had recovered from a motor impairment with that of healthy controls. Early group studies of stroke patients described greater recruitment within a number of motor-related cortical regions compared with controls during a finger tapping task.9, 10, 11, 12, 13 This led to the suggestion that non-primary (or secondary) cortical motor regions had indeed facilitated recovery in these patients. This idea had been proposed by Strick14 some years before, based on an understanding of the organization of the cortical motor system. Normal distal motor function is facilitated largely though the corticospinal pathway, from the cortical motor system to the spinal cord motoneurons. The majority of corticospinal fibers originate in the primary motor cortex, but there are smaller contributions from other cortical regions. In primates it is known that primary motor cortex (M1), arcuate (or lateral) premotor area (PM), and supplementary motor area (SMA) are each part of parallel, independent motor networks with (1) separate projections to spinal cord motoneuron and (2) interactions at the level of the cortex.14 There is a high degree of similarity between the corticospinal projections from the hand regions of M1, PM, and SMA leading to the suggestion that a number of motor networks acting in parallel could generate an output to the spinal cord necessary for movement, and that damage in one of these networks could be compensated for by activity in another.15, 16 The Relation Between Reorganization and Recovery The relation between motor-related brain activation patterns and recovery was further addressed when patients with different degrees of recovery were studied. In 1 such study, a group of chronic stroke patients with infarcts sparing primary motor cortex were scanned during a hand grip with visual feedback task using fMRI.17 The patients exhibited varying degrees of recovery, and the more affected patients appeared to recruit more of the primary and secondary motor systems in both affected and unaffected hemispheres, whereas patients with the best outcome had a “normal” activation pattern when compared with controls. In fact a negative linear correlation was seen between magnitude of task-related activation and outcome in cortical motor areas such as ventral ipsilesional M1, contralesional M1, bilateral dorsolateral premotor cortex (PMd), SMA, cingulate motor areas, and parietal cortices. One explanation for this result would be that the patients with poorer recovery were merely trying harder, because increased task-related effort is likely to lead to extra motor system recruitment. The experiment was, however, carefully designed so that (1) patients with poorer outcome were gripping at lower absolute forces but equivalent proportional forces to the patients with better outcome and (2) online monitoring of motor performance of both hands was performed in order to rule out mirror movements and to allow accurate modeling of actual performance (see Baron et al18 for further discussion of issues in experimental design). Furthermore, a postscanning questionnaire suggested that no patients found the task more effortful than any other. Thus, neither mirror movements nor differences in effort are likely explanations for the differences across subjects. A subsequent study showed that impaired functional integrity of the corticospinal system, as measured with TMS, is associated with less recruitment of contralesional M1, but greater recruitment of secondary motor networks in both hemispheres.19 This response is presumably an attempt by the brain to generate motor output to spinal cord motoneurons by using residual motor areas and pathways. Neither result immediately supports the idea that secondary motor areas are the substrate for recovery. In primates, projections from secondary motor areas to spinal cord motoneurons are less numerous and less efficient at exciting spinal cord motoneurons than those from M1.20 Thus, another interpretation of these results is that subcortical stroke patients with poorer outcome have greater damage to the fast direct projections from M1 to spinal cord motoneurons21 and thus use secondary motor areas to generate a motor output. The descending pathways through which (bilateral) secondary cortical motor regions generate this motor output are not clear. Although direct projections from PMd and SMA to spinal cord motoneurons exist (at least in primates), another possibility is that signals descend via the reticulospinal projections to cervical propriospinal premotoneurons.22, 23 Propriospinal projections have divergent projections to muscle groups operating at multiple joints.24, 25 This solution might account for the multijoint “associated” movements such as the synergistic flexion seen when patients with only poor and moderate recovery attempt isolated hand movements. Further support for the idea that the secondary motor areas of both hemispheres are helping rather than hindering recovery comes from experiments using TMS. If single or multiple pulses of TMS are delivered over a particular area, there is evidence that the function of that area will be temporarily disrupted. Thus if TMS to secondary motor areas can temporarily impair a motor behavior, then it suggests that this region is functionally useful in that task. Temporary disruption of ipsilesional PMd26 as well as contralesional PMd27 using TMS appears to disrupt a reaction time task in chronic subcortical stroke patients but not in healthy controls. This is highly suggestive that PMd (in both hemispheres) is functionally useful in these patients in a way that it is not in controls. Furthermore, TMS to contralesional PMd is more disruptive in patients with greater impairment27 showing that PMd in the unaffected hemisphere is used more by those with poorer outcome, possibly because the connections of ipsilesional PMd are damaged by infarction in such patients. However, if TMS to contralesional PMd is able to disrupt a discrete finger movement, this suggests it may be working through more direct pathways than the reticulospinal and proprospinal pathways discussed above. This serves to illustrate how little we still understand about how cortical motor areas influence movement in the damaged brain. It is unlikely that the response to focal injury involves the simple substitution of 1 cortical region for another, because nodes within a remaining motor network may take on new roles. For example, in some stroke patients, signal change in premotor cortices increases linearly as a function of hand grip force, a characteristic normally associated with M1. This new role for premotor cortices occurs predominantly in chronic stroke patients with significant impairment, rather than good recoverers or in control subjects,17 once again reflecting the finding that greatest reorganization occurs after focal damage to the motor system in those patients with greatest need. Furthermore, it appears that the relation between motor recruitment pattern and degree of recovery (at the time of scanning) holds true at 10 to 14 days poststroke as well as in the chronic phase,28 suggesting that secondary motor areas are available to participate in the generation of a motor task very early after stroke. It is important to stress that this reorganization is often not successful in returning motor function to normal. The more of the normal functional architecture that survives, the greater will be the potential for full recovery. In patients with damage to primary sensorimotor cortex, for example, tests of fractionated finger movement correlated more strongly with the proportion of surviving “normal” sensorimotor cortex (as defined by functional activation maps in healthy controls) than with total infarct volume.29 The Role of Ipsilesional Primary Motor Cortex Whereas an intact ipsilesional M1 is clearly beneficial for recovery, the role of M1 in the unaffected hemisphere remains controversial. Ipsilateral (contralesional) M1 can be thought of as another “secondary” node in the motor network, one that contributes to motor performance as required. However, it is important to consider the evidence regarding its role after stroke because it has become a target for manipulation in therapeutic intervention.30 Anatomic studies suggest that both direct (cortico-motoneuronal) and indirect (cortico-reticulospinal) pathways from ipsilateral M1 end in projections only to axial and proximal stabilizing muscles rather than hand muscles,31 although more recent evidence suggests that the reticulospinal and propriospinal projections, which are bilateral, may be useful for motor recovery in some stroke patients.22 In healthy subjects, repetitive TMS to ipsilateral M1, which temporarily disrupts activity in the region, results in errors in both complex and simple motor tasks using the ipsilateral hand.32 This suggests that ipsilateral M1 may play a role in planning and organization of normal hand movement. Other experiments have gone further and shown the functional utility of ipsilateral M1 in compensating for repetitive TMS-induced disruption to contralateral M1.33 Ipsilateral M1 certainly plays a major role in restitution of motor function after perinatal brain injury,34, 35 but whether it can play such a role after damage in the adult brain remains controversial. Many functional imaging studies have observed motor task−related brain activity in contralesional M1 in stroke patients.9, 11, 13, 17, 36 Contralesional hemisphere activity has also been shown in stroke patients using EEG.37 The fine temporal resolution of EEG was able to detect that this activity occurred after the motor response had been made, suggesting that it was not related to movement initiation in these patients. However, because EEG lacks fine spatial resolution, it is not certain that this result related to contralesional M1. However, a similar approach using an event-related fMRI design has shown that contralesional M1 activity peaked seconds before ipsilesional M1 in stroke patients, in comparison to controls in whom the opposite relation was observed.36 This change in the characteristics of motor system activation might point to a change of role in different patients, but it does not prove a functional role during movement. In studies involving adult patients with small subcortical infarcts, disruption of contralesional M1 function by TMS has not impaired performance in simple motor tasks, calling into question the functional significance of increased contralesional M1 activation in these patients.27, 38 It has recently been suggested that contralesional M1 may impair recovering motor function in patients with small subcortical stroke by exerting an abnormally high degree of interhemispheric inhibitory drive toward ipsilesional M1 during attempted voluntary movement of the affected hand.39 This has led some to suggest that suppressing activity in contralesional M1 might be beneficial. However, care needs to be taken before generalizing these findings into patient groups beyond those with characteristics of the study group. Patients with moderate or poor outcome activate the unaffected hemisphere cortical motor regions more than good recoverers,17, 27 presumably because these regions in the affected hemisphere are either damaged or disconnected (fig 1). This difference in utilization of motor regions depending on clinical state is illustrated by a study in which motor output, as assessed by task-related EEG coherence (in the β range) was found to come predominantly from the affected hemisphere in well-recovered patients, and from the unaffected hemisphere in less well-recovered patients.40 Thus some anatomic lesions might result in contralesional M1 activity contributing positively to motor performance. Although projections from ipsilateral M1 are thought not to contribute greatly to distal motor function, these properties might change under certain circumstances. In addition, the degree to which a particular brain region contributes to performance clearly depends on the demands of the task, and TMS to contralesional M1 does disrupt timing of more complex finger movements.8 A recent study showed unmasking of ipsilateral M1 projections in cats treated with 4-aminopyridine, a potassium channel blocker.41 The motor systems of cats, primates, and humans are different, but it raises the possibility that reorganization of the motor system can occur under certain favorable conditions. What drives functionally relevant cerebral reorganization? In the chronic stroke brain, there is a reconfiguration of the cerebral motor system. It is less effective than that in the intact brain but will nevertheless attempt to generate some form of motor signal to spinal cord motoneurons in the most efficient way. The exact configuration of this new motor system will be determined most obviously by the extent of the anatomic damage, including the extent to which the damage affects cortical motor regions, white matter pathways, and even which hemisphere is affected.42 This anatomic explanation accounts for the fact that some patients do better than others. However, given that it is unlikely that regeneration of tissue contributes significantly to functional recovery, it does not account for the recovery of function that occurs over weeks and months in individual patients. How does the reorganized state evolve? There are fewer longitudinal functional imaging studies involving stroke patients than cross-sectional studies, and only a handful have studied patients on more than 2 occasions. One study used fMRI to scan subcortical stroke patients while performing a hand grip task an average of 8 times over 6 months (and sometimes up to 12mo) after stroke.43 The results showed an initial (within 2wk poststroke) overactivation in many primary and nonprimary motor regions. Thereafter functional recovery was associated with a focusing of task-related brain activation patterns toward a “normal” lateralized pattern. It is obviously impossible to know whether the brain activation patterns returned to prestroke levels, but this is unlikely, given persistent structural damage. In general, longitudinal studies have shown a focusing of activity toward the lesioned hemisphere motor regions that is associated with improvement in motor function,44, 45 with some patients showing persistent recruitment of secondary motor areas.46 If one considers the results from the cross-sectional studies, it is clear that brain activation patterns will not return to normal in all cases. Thus, rather than representing a focusing toward normal motor activation patterns (ie, prestroke), it is more likely that longitudinal changes represent increase in efficiency in the use of surviving motor networks. Thus, one would predict that in patients with damage to ipsilesional M1 and premotor regions, in whom there was an early reliance on contralesional motor structures, longitudinal reductions in brain activation would still be associated with recovery, but the focusing might be toward the unaffected hemisphere. The comparison between the longitudinal focusing that has been observed with improvements in motor function after stroke and that seen during motor skill learning in healthy subjects47 has been made previously.18 It is certainly plausible that a highly preserved neural system such as that subserving motor skill learning in the brain will be used after stroke in order to maximize the ability of surviving motor networks to generate voluntary movement. However, the degree to which this is successful will depend on the integrity of such networks. Thus focusing will tend toward the most efficient system available, and the degree to which this is achieved could be taken as a measure of the efficiency of the therapy that has preceded that point in time. In summary, the brain activation pattern of an individual patient at any given time point represents the state of reorganization within that system. This will depend on a number of factors. The influence of the anatomic lesion has been discussed. The ability of the residual motor system to become more efficient (and subserve improvement in motor function) will depend on a number of other factors, not least the biologic age of the subject and the premorbid state of their brain, but also current drug treatments. Furthermore, levels of neurotransmitters and growth factors that are able to influence the ability of the brain to respond to afferent input (ie, how plastic it is) will be determined by their genetic status. All of these factors will influence the potential for activity-driven change within the intact motor networks, the putative mechanism of therapy-driven improvements in motor performance. Conclusions How does this help us to understand how best to treat the impairment suffered by patients after stroke? On one level, treatments can be considered as inputs that interact with a system, in this case the damaged poststroke brain. The aim of this input is generally to optimize the functional organization of the damaged system. An important point is that an input will succeed in driving functionally useful change only to the extent that the brain regions and networks with which it interacts are intact and are able to influence motor output pathways. Other treatments are designed as ways of conditioning the brain to make it more likely that activity-driven change will occur in response to afferent input. For example, repetitive TMS48 or drugs such as amphetamine49 will not induce activity-driven change themselves but may enhance the effect of physiotherapy if delivered just before the treatment session. Once again, the likelihood of their success will depend on a number of factors relating to whether the network with which the treatment interacts is intact. For example, repetitive TMS designed to increase excitability and thus facilitate activity-driven change in the affected hemisphere M1 is unlikely to have any success in patients with large middle cerebral artery territory infarcts. As yet, the mechanisms of action of these interventions are not well understood, but the concepts discussed here provide a framework within which to explore whether and how interventions of different types work in all types of patients. It is in this context that modern neuroimaging techniques may be able to shed light on poststroke functional organization in individual subjects. Techniques such as diffusion tensor imaging tractography50 and voxel based morphometry51 will allow some objective assessment of residual anatomy, and fMRI can provide insights into the functional organization of the residual systems. Ultimately this should facilitate an understanding of the mechanisms of interventions designed to reduce impairments and also allow the stratification of patients based on the likely response to an intervention. Supplier References 1. 1Hoffman C, Rice D, Sung HY. Persons with chronic conditions (Their prevalence and costs). JAMA. 1996;276:1473–1479. MEDLINE 2. 2Office of Population Censuses and Surveys. OPCS surveys of disability in Great Britain, 1: The prevalence of disability among adults. London: HMSO; 1988;. 3. 3Wade DT, Hewer RL. Epidemiology of some neurological diseases with special reference to work load on the NHS. Int Rehabil Med. 1987;8:129–137. MEDLINE 4. 4The Academy of Medical Sciences. Restoring neurological function: putting the neurosciences to work in neurorehabilitation. London: AMS; 2004. Available at: http://www.acmedsci.ac.uk/images/project/Restorin.pdf. Accessed August 25, 2006. 5. 5Hamzei F, Knab R, Weiller C, Rother J. The influence of extra- and intracranial artery disease on the BOLD signal in fMRI. Neuroimage. 2003;20:1393–1399. MEDLINE |
CrossRef
6. 6Rossini PM, Altamura C, Ferretti A, et al. Does cerebrovascular disease affect the coupling between neuronal activity and local haemodynamics?. Brain. 2004;127(Pt 1):99–110. MEDLINE |
CrossRef
7. 7Carusone LM, Srinivasan J, Gitelman DR, Mesulam MM, Parrish TB. Hemodynamic response changes in cerebrovascular disease: implications for functional MR imaging. AJNR Am J Neuroradiol. 2002;23:1222–1228. MEDLINE 8. 8Lotze M, Markert J, Sauseng P, Hoppe J, Plewnia C, Gerloff C. The role of multiple contralesional motor areas for complex hand movements after internal capsular lesion. J Neurosci. 2006;26:6096–6102.
CrossRef
9. 9Cao Y, D’Olhaberriague L, Vikingstad EM, Levine SR, Welch KM. Pilot study of functional MRI to assess cerebral activation of motor function after poststroke hemiparesis. Stroke. 1998;29:112–122. MEDLINE 10. 10Chollet F, DiPiero V, Wise RJ, Brooks DJ, Dolan RJ, Frackowiak RS. The functional anatomy of motor recovery after stroke in humans: a study with positron emission tomography. Ann Neurol. 1991;29:63–71. MEDLINE |
CrossRef
11. 11Cramer SC, Nelles G, Benson RR, et al. A functional MRI study of subjects recovered from hemiparetic stroke. Stroke. 1997;28:2518–2527. MEDLINE 12. 12Weiller C, Chollet F, Friston KJ, Wise RJ, Frackowiak RS. Functional reorganization of the brain in recovery from striatocapsular infarction in man. Ann Neurol. 1992;31:463–472. MEDLINE |
CrossRef
13. 13Weiller C, Ramsay SC, Wise RJ, Friston KJ, Frackowiak RS. Individual patterns of functional reorganization in the human cerebral cortex after capsular infarction. Ann Neurol. 1993;33:181–189. MEDLINE |
CrossRef
14. 14Strick PL. Anatomical organization of multiple motor areas in the frontal lobe: implications for recovery of function. Adv Neurol. 1988;47:293–312. MEDLINE 15. 15Dum RP, Strick PL. Spinal cord terminations of the medial wall motor areas in macaque monkeys. J Neurosci. 1996;16:6513–6525. MEDLINE 16. 16Rouiller EM, Moret V, Tanne J, Boussaoud D. Evidence for direct connections between the hand region of the supplementary motor area and cervical motoneurons in the macaque monkey. Eur J Neurosci. 1996;8:1055–1059.
CrossRef
17. 17Ward NS, Brown MM, Thompson AJ, Frackowiak RS. Neural correlates of outcome after stroke: a cross-sectional fMRI study. Brain. 2003;126(Pt 6):1430–1448. MEDLINE |
CrossRef
18. 18Baron JC, Cohen LG, Cramer SC, et al. First International Workshop on Neuroimaging and Stroke Recovery (Neuroimaging in stroke recovery: a position paper from the First International Workshop on Neuroimaging and Stroke Recovery). Cerebrovasc Dis. 2004;18:260–267. MEDLINE |
CrossRef
19. 19Ward NS, Newton JM, Swayne OB, et al. Motor system activation after subcortical stroke depends on corticospinal system integrity. Brain. 2006;129(Pt 3):809–819.
CrossRef
20. 20Maier MA, Armand J, Kirkwood PA, Yang HW, Davis JN, Lemon RN. Differences in the corticospinal projection from primary motor cortex and supplementary motor area to macaque upper limb motoneurons: an anatomical and electrophysiological study. Cereb Cortex. 2002;12:281–296. MEDLINE |
CrossRef
21. 21Heald A, Bates D, Cartlidge NE, French JM, Miller S. Longitudinal study of central motor conduction time following stroke. 2. Central motor conduction measured within 72 h after stroke as a predictor of functional outcome at 12 months. Brain. 1993;116(Pt 6):1371–1385. 22. 22Mazevet D, Meunier S, Pradat-Diehl P, Marchand-Pauvert V, Pierrot-Deseilligny E. Changes in propriospinally mediated excitation of upper limb motoneurons in stroke patients. Brain. 2003;126(Pt 4):988–1000. MEDLINE |
CrossRef
23. 23Stinear JW, Byblow WD. The contribution of cervical propriospinal premotoneurons in recovering hemiparetic stroke patients. J Clin Neurophysiol. 2004;21:426–434. MEDLINE |
CrossRef
24. 24Mazevet D, Pierrot-Deseilligny E. Pattern of descending excitation of presumed propriospinal neurones at the onset of voluntary movement in humans. Acta Physiol Scand. 1994;150:27–38. MEDLINE |
CrossRef
25. 25Pierrot-Deseilligny E. Transmission of the cortical command for human voluntary movement through cervical propriospinal premotoneurons. Prog Neurobiol. 1996;48:489–517. 26. 26Fridman EA, Hanakawa T, Chung M, Hummel F, Leiguarda RC, Cohen LG. Reorganization of the human ipsilesional premotor cortex after stroke. Brain. 2004;127(Pt 4):747–758. MEDLINE |
CrossRef
27. 27Johansen-Berg H, Rushworth MF, Bogdanovic MD, Kischka U, Wimalaratna S, Matthews PM. The role of ipsilateral premotor cortex in hand movement after stroke. Proc Natl Acad Sci U S A. 2002;99:14518–14523. MEDLINE |
CrossRef
28. 28Ward NS, Brown MM, Thompson AJ, Frackowiak RS. The influence of time after stroke on brain activations during a motor task. Ann Neurol. 2004;55:829–834. MEDLINE |
CrossRef
29. 29Crafton KR, Mark AN, Cramer SC. Improved understanding of cortical injury by incorporating measures of functional anatomy. Brain. 2003;126(Pt 7):1650–1659. MEDLINE |
CrossRef
30. 30Ward NS, Cohen LG. Mechanisms underlying recovery of motor function after stroke. Arch Neurol. 2004;61:1844–1848. MEDLINE |
CrossRef
31. 31Brinkman J, Kuypers HG. Cerebral control of contralateral and ipsilateral arm, hand and finger movements in the split-brain rhesus monkey. Brain. 1973;96:653–674. MEDLINE 32. 32Chen R, Gerloff C, Hallett M, Cohen LG. Involvement of the ipsilateral motor cortex in finger movements of different complexities. Ann Neurol. 1997;41:247–254. MEDLINE |
CrossRef
33. 33Strens LH, Fogelson N, Shanahan P, Rothwell JC, Brown P. The ipsilateral human motor cortex can functionally compensate for acute contralateral motor cortex dysfunction. Curr Biol. 2003;13:1201–1205. MEDLINE |
CrossRef
34. 34Vandermeeren Y, Sebire G, Grandin CB, Thonnard JL, Schlogel X, De Volder AG. Functional reorganization of brain in children affected with congenital hemiplegia: fMRI study. Neuroimage. 2003;20:289–301. MEDLINE |
CrossRef
35. 35Cao Y, Vikingstad EM, Huttenlocher PR, Towle VL, Levin DN. Functional magnetic resonance studies of the reorganization of the human hand sensorimotor area after unilateral brain injury in the perinatal period. Proc Natl Acad Sci U S A. 1994;91:9612–9616. MEDLINE |
CrossRef
36. 36Newton J, Sunderland A, Butterworth SE, Peters AM, Peck KK, Gowland PA. A pilot study of event-related functional magnetic resonance imaging of monitored wrist movements in patients with partial recovery. Stroke. 2002;33:2881–2887.
CrossRef
37. 37Verleger R, Adam S, Rose M, Vollmer C, Wauschkuhn B, Kompf D. Control of hand movements after striatocapsular stroke: high-resolution temporal analysis of the function of ipsilateral activation. Clin Neurophysiol. 2003;114:1468–1476. Abstract | Full Text |
Full-Text PDF (439 KB)
|
CrossRef
38. 38Werhahn KJ, Conforto AB, Kadom N, Hallett M, Cohen LG. Contribution of the ipsilateral motor cortex to recovery after chronic stroke. Ann Neurol. 2003;54:464–472. MEDLINE |
CrossRef
39. 39Murase N, Duque J, Mazzocchio R, Cohen LG. Influence of interhemispheric interactions on motor function in chronic stroke. Ann Neurol. 2004;55:400–409. MEDLINE |
CrossRef
40. 40Serrien DJ, Strens LH, Cassidy MJ, Thompson AJ, Brown P. Functional significance of the ipsilateral hemisphere during movement of the affected hand after stroke. Exp Neurol. 2004;190:425–432. MEDLINE |
CrossRef
41. 41Jankowska E, Cabaj A, Pettersson LG. How to enhance ipsilateral actions of pyramidal tract neurons. J Neurosci. 2005;25:7401–7405.
CrossRef
42. 42Zemke AC, Heagerty PJ, Lee C, Cramer SC. Motor cortex organization after stroke is related to side of stroke and level of recovery. Stroke. 2003;34:e23–e28. 43. 43Ward NS, Brown MM, Thompson AJ, Frackowiak RS. Neural correlates of motor recovery after stroke: a longitudinal fMRI study. Brain. 2003;126(Pt 11):2476–2496. MEDLINE |
CrossRef
44. 44Calautti C, Leroy F, Guincestre JY, Baron JC. Dynamics of motor network overactivation after striatocapsular stroke: a longitudinal PET study using a fixed-performance paradigm. Stroke. 2001;32:2534–2542.
CrossRef
45. 45Marshall RS, Perera GM, Lazar RM, Krakauer JW, Constantine RC, DeLaPaz RL. Evolution of cortical activation during recovery from corticospinal tract infarction. Stroke. 2000;31:656–661. MEDLINE 46. 46Feydy A, Carlier R, Roby-Brami A, et al. Longitudinal study of motor recovery after stroke: recruitment and focusing of brain activation. Stroke. 2002;33:1610–1617.
CrossRef
47. 47Hikosaka O, Nakahara H, Rand MK, et al. Parallel neural networks for learning sequential procedures. Trends Neurosci. 1999;22:464–471. MEDLINE |
CrossRef
48. 48Ziemann U. Improving disability in stroke with RTMS. Lancet Neurol. 2005;4:454–455. Full Text |
Full-Text PDF (35 KB)
|
CrossRef
49. 49Feeney DM. From laboratory to clinic: noradrenergic enhancement of physical therapy for stroke or trauma patients. Adv Neurol. 1997;73:383–394. MEDLINE 50. 50Newton JM, Ward NS, Parker GJ, et al. Non-invasive mapping of corticofugal fibres from multiple motor areas—relevance to stroke recovery. Brain. 2006;129:1844–1858.
CrossRef
51. 51Ashburner J, Friston KJ. Voxel-based morphometry—the methods. Neuroimage. 2000;11(6 Pt 1):805–821. MEDLINE |
CrossRef
Wellcome Department of Imaging Neuroscience, Institute of Neurology, London, England  Reprint requests to Nick S. Ward, Wellcome Department of Imaging Neuroscience, Institute of Neurology, 12 Queen Sq, London, WC1N 3BG, England
Supported by the Wellcome Trust, UK. No commercial party having a direct financial interest in the results of the research supporting this article has or will confer a benefit upon the authors(s) or upon any organization with which the author(s) is/are associated. PII: S0003-9993(06)01282-2 doi:10.1016/j.apmr.2006.08.334 © 2006 American Congress of Rehabilitation Medicine. Published by Elsevier Inc. All rights reserved. | |
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