Organization of the human motor system as studied by functional magnetic resonance imaging

European Journal of Radiology 30 (1999) 105 – 114

Organization of the human motor system as studied by functional magnetic resonance imaging Venkata S. Mattay *, Daniel R. Weinberger Clinical Brain Disorders Branch, Intramural Research Program, National Institute of Mental Health, NIH, 10 Center Dri6e, Room 3C-101, Bethesda, MD 20892, USA Received 8 March 1999; accepted 25 March 1999

Abstract Blood oxygenation level dependent functional magnetic resonance imaging (BOLD fMRI), because of its superior resolution and unlimited repeatability, can be particularly useful in studying functional aspects of the human motor system, especially plasticity, and somatotopic and temporal organization. In this survey, while describing studies that have reliably used BOLD fMRI to examine these aspects of the motor system, we also discuss studies that investigate the neural substrates underlying motor skill acquisition, motor imagery, production of motor sequences; effect of rate and force of movement on brain activation and hemispheric control of motor function. In the clinical realm, in addition to the presurgical evaluation of neurosurgical patients, BOLD fMRI has been used to explore the mechanisms underlying motor abnormalities in patients with neuropsychiatric disorders and the mechanisms underlying reorganization or plasticity of the motor system following a cerebral insult. © 1999 Published by Elsevier Science Ireland Ltd. All rights reserved. Keywords: BOLD fMRI; Functional MRI; Motor abnormalities; Neuroimaging

1. Introduction Several attributes of blood oxygenation level dependent functional magnetic resonance imaging (BOLD fMRI), namely the lack of radiation exposure, its noninvasive approach, superior temporal and spatial resolution and the capability to create individual subject maps, have made it a popular technique to study the functional organization of the human brain in recent years. Prior to the advent of fMRI, investigators used nuclear imaging and electrophysiological methods to complement the knowledge base provided by cortical stimulation and lesion studies in experimental animals and humans. While early studies of motor paradigms with fMRI were committed to validate the technique, investigators have also tried to exploit the advantages * Corresponding author. Tel.: +1-301-435-4594; fax: + 1-301-4020743. E-mail address: [email protected] (V.S. Mattay)

of fMRI to better understand the organization of the human motor system. Since its inception [1,2] BOLD fMRI has seen a profound development in its scope and utility. We will discuss these developments, with particular reference to their contribution to understanding motor organization and to clinical applications.

2. Motor studies in the methodological development of BOLD fMRI While BOLD fMRI has become a widely accepted brain-mapping tool, it is subject to the concern that activation signals come from larger vessels downstream from the actual site of neuronal activation and the precise site of neuronal activation is not known. Motor paradigms have been used to cross validate fMRI activation with activation patterns detected by other brain

0720-048X/99/$ - see front matter © 1999 Published by Elsevier Science Ireland Ltd. All rights reserved. PII: S 0 7 2 0 - 0 4 8 X ( 9 9 ) 0 0 0 4 9 - 2

106

V.S. Mattay, D.R. Weinberger / European Journal of Radiology 30 (1999) 105–114

mapping techniques, such as positron emission tomography (PET), magnetoencephalography (MEG), electroencephalography (EEG) and intraoperative cortical brain mapping. Ramsey et al. [3] compared the areas of activation depicted by three-dimensional BOLD fMRI with those obtained with oxygen-15-labeled water (H15 2 O) PET while subjects performed a simple finger opposition task. While they found a high degree of correlation in the size of the activated regions and in the average magnitude of signal change in the activated voxels within the primary sensorimotor cortex, the mean distance between centers of mass of the activated regions in the primary sensorimotor cortex (PSM) for fMRI versus PET was 6.7 mm. Similarly, Dettmers et al. [4] compared fMRI with PET while subjects performed repetitive Morse key presses at 1 Hz with the right index finger at a range of different forces. They found that while all subjects demonstrated activation in the primary motor cortex and supplementary motor cortex, the locations of activation peaks differed by 2–8 mm between imaging methods. They also found that the ratio of percentage regional cerebral blood flow (rCBF) change to percentage fMRI signal change was similar across all force levels. Sadato et al. [5] compared the effect of repetition rate of a simple movement on the activation patterns depicted by BOLD fMRI and H15 2 O PET. They reported that while the percent change in BOLD signal intensity linearly increased from 1 to 4 Hz, the area of activation increased up to 2 Hz and tended to decrease at higher frequencies. In contrast, with PET they found an increase in rCBF with movement frequencies up to 2 Hz and then a plateau of rCBF at faster frequencies. They concluded that while a partial volume effect precludes dissociation of volume and magnitude of change with PET, fMRI due to its higher spatial resolution is better able to dissociate area and magnitude of change. Stippich et al. [6] compared fMRI to MEG while subjects performed self-paced finger movements. They found the mean distance between fMRI activity and the corresponding MEG dipoles in the motor cortex to be approximately 10.1 mm. They concluded that this difference might reflect the different underlying substrates of neurophysiology measured by the different techniques. Krings et al. [7] demonstrated concordance between the hemodyanamically based fMRI maps and the electrophysiologically based transcranial magnetic stimulation (TMS) maps of the human primary sensorimotor cortex in normal subjects and with direct cortical stimulation in two patients with a mass lesion in their dominant hemisphere. They found a close relationship between peak fMRI activation and peak TMS amplitude, i.e. with increasing distance from the central sulcus both the motor evoke potential (MEP) amplitude and the strength of fMRI activation decreased. They also reported concordant interhemispheric differences and a somatotopic shift

both for fMRI activation and TMS response. In general, all these studies report a fairly high degree of correspondence in the activated areas depicted by fMRI and the other methods. While there are differences in the center of mass locations of the activated areas across the different techniques, these are minor and likely reflect the different underlying substrates of neurophysiology measured by the different techniques, as well as the vagaries of the algorithms used to coregister the image datasets.

3. fMRI studies of motor organization It is well known from brain mapping studies using nuclear imaging and electrophysiological methods that even the simplest of motor behaviors is a complex process and involves many different areas of the brain. Motor control is thought to be achieved by a series of parallel systems formed by somatotopically organized, descending projections that link the various motor-related areas of the cortex more directly with spinal motor circuits. Initial fMRI studies of the motor system were restricted by limited brain coverage precluding the study of the whole motor system. Considerable progress in MR technology including very rapid gradient systems now allows reliable mapping of the entire brain [8]. Using a multislice echoplanar imaging technique, we successfully mapped all the cortical areas subserving motor function in individual subjects [8,9]. Other groups have since reported other whole brain fMRI approaches with variations in voxel dimensions, temporal resolution and susceptibility to artifacts [10]. While the basal ganglia particularly the dorsal striatum and globus pallidus are thought to be critically involved in motor control, their exact role remains unclear. Based on a review of non-human primate and positron emission tomographic (PET) studies, Brooks [11] proposed that the basal ganglia are involved in the determination of movement parameters, preparation for movement, enabling movement to become automatic, facilitation of sequential movements, inhibition of unwanted movements, adaptation to novel circumstances, facilitation of rewarded action, as well as motor learning and planning. However, PET does not have the effective spatial resolution to reliably distinguish between sub-regions of the basal ganglia nuclei and their specific role in motor control. BOLD fMRI by virtue of its greater spatial resolution, in principle could help delineate the differential role of the subcomponents of the basal ganglia in motor control. To date, however, most BOLD fMRI studies at 1.5 T have revealed reliable basal ganglia activation only on group analysis [8,9,12,13]; activation in individual subject analysis was less reliable. Reichenbach et al. [14], on the other hand, reported successful contralateral putamenal

V.S. Mattay, D.R. Weinberger / European Journal of Radiology 30 (1999) 105–114

activation during a simple flexion/extension movement of the thumb in individual subjects. The relatively poor reliability in detecting basal ganglia activation in individual subjects at 1.5 T may be multifactorial: (1) signal intensity changes in basal ganglia are smaller than those seen in cortical motor areas, a hypothesis supported by results from PET studies [15,16]; (2) greater iron deposition in the basal ganglia than in the cortex resulting in lower MR signal changes; and (3) proximity of these structures to areas with high susceptibility artifact such as ventricles leading to increased noise. The preceding reports were of studies at 1.5 T and the disparity across studies in successful individual subject basal ganglia activation may also be related to the stringency of the statistical criteria utilized. Interestingly, recently Lehericy et al. [17] reported reliable basal ganglia activation at a higher field strength (3 T) even during a simple motor task such as sequential self-paced flexion/ extension movements of the toes or fingers. In this study, while reproducible, the mean signal changes in the basal ganglia were lower by at least a factor of two than those observed in the cortex.

4. Somatotopy While subjects performed voluntary movements of the hand, arm and foot, Rao et al. [18] explored the somatotopic organization of the primary motor cortex, and found a pattern of functional activity that followed a topographical organization: finger movements resulted in signal intensity changes over the convexity of the motor cortex; toe movements produced changes either at the interhemispheric fissure or on the dorsolateral surface adjacent to the interhemispheric fissure; and elbow movement changes overlapped the more medial signal intensity changes observed with finger movements. Subsequent to this, Sanes et al. [19] explicitly addressed within hand somatotopy using perfusionsensitive MRI techniques. Finding overlapping representations observed for wrist and various finger movements, they concluded that there is no somatotopic layout in the primary motor (M1) hand area. However, Kleinschmidt et al. [20], using a higher-resolution MRI technique (0.78×1.56 × 4 mm, B 0.5 cm3 resolution) re-examined this issue by addressing somatotopy both in terms of functional segregation and of cortical response preference. As a first step, spatial representations of self-paced isolated finger movements were mapped by using motor rest as a control state. An additional experimental design involved contrasting individual finger movements as the control task. While the first approach confirmed previous reports of extensive overlap in spatial representations, the second approach revealed foci of differential activation that displayed an orderly mediolateral progression in accor-

107

dance with the classical cortical motor homunculus. These investigators concluded that somatotopy within the hand area of the primary motor cortex does not present as qualitative functional segregation but as quantitative predominance of certain movements or digit representation embedded in an overall joint hand area. Sakai et al. [21] examined the role of the anterior and posterior lobes of the cerebellum in motor control. While subjects tapped their fingers paced by tone sequences with or without tone omission, they found that the cerebellar anterior lobe ipsilateral to the movement was activated to a similar degree irrespective of the presence or absence of tone omission. In contrast, the lateral part of the bilateral posterior lobe was highly activated for the tone sequence with random omission, compared with either that without omission or that with regular omission. The authors concluded that the cerebellar anterior lobe is involved in motor execution, while the lateral part of the posterior lobe is involved in on-line motor adjustment to unpredictable sensory stimuli. In the previously mentioned study by Lehericy et al. [17], the authors while demonstrating reliable basal ganglia activation in individual subjects at 3 T also looked at the somatotopical organization within the basal ganglia; consistent with primate anatomical [22,23] and microstimulation studies [24], movements of toes activated more dorsal areas than hand movements.

5. Temporal organization of motor areas Initially, the prolonged hemodynamic response delay and limitations in traditional block-design approaches precluded investigators from extracting temporal information about neural processing. More recently, however, Richter et al. [25] using high temporal resolution fMRI (200 ms per image and event-related design) were able to extract some temporal information about neural processing, and the relative roles of primary motor cortex (M1), premotor area (PM) and supplementary motor area (SMA) during a delayed, cued complex finger movement task. Their observations were consistent with results from single neuronal recordings in monkeys and showed that the M1, PM and SMA are active during both movement preparation and movement execution. The intensity of activity in the primary motor cortex, however, was weaker during movement preparation than during movement execution; in PM and SMA, the activity was similar during both periods. In contrast to this, Samuel et al. [26] demonstrated that task associated neuronal responses of prefrontal and rostral mesial premotor cortex are greater at the initiation of motor planning and preparation, but that significant activity in these areas is not maintained during continued repetitive task performance. They hypothe-

108

V.S. Mattay, D.R. Weinberger / European Journal of Radiology 30 (1999) 105–114

size that this may be the result of reduced preparatory and attentional demand during the late components of the movements, probably resulting from the subjects becoming accustomed to performing the tasks. Rubia et al. [27] investigated neural activity associated with time estimation, stimulus anticipation and motor timing. They reported increased MR signal intensity in the left rostral prefrontal cortex, medial frontal cortex, SMA and supramarginal gyrus during a low frequency synchronization motor task. This suggests that these brain regions form a distributed neural network for cognitive time management processes, such as time estimation and motor output timing. The medial frontal cortex showed a biphasic pattern of response during both synchronization conditions, presumably reflecting frequency independent motor output related attention.

6. Neurobiological correlates of motor skill acquisition The unique advantage of repeatability of fMRI makes it an ideal tool to track changes in neuronal activity over time. This allows repeated mapping of cortical representations as a consequence of long-term practice and provides a way to examine over an extended period of time the neurobiological correlates of skill learning in the human brain. There are inconsistencies in the results of prior imaging studies that were aimed at looking at the effects of motor sequence learning. While some studies [15,28,29] reported a decrease in the activation of many areas with learning, other studies [30 – 33] reported increases in certain areas. Single-unit recordings in non-human primates show that there are cells that increase their firing early in learning [34 – 36], and with further training many cells show a subsequent decrease [35 – 37]. This suggests that it is important to measure activation over the whole course of learning. In the studies by Grafton and colleagues [30,31] only the early phase of learning was studied. To make measurements throughout the course of learning, Toni et al. [38] charted the time course of changes in BOLD signal intensity over a period as long as 40 min during which the subjects learned a sequence eight moves long by trial and error until it became automatic. Using a set of polynomial basis functions, they examined both linear and non-linear changes over time. Their results were consistent with the results from the afore mentioned single-unit studies in non-human primates and showed increased activity early in learning, followed by a decrease as learning progressed. Toni et al. [38] also examined the effects of learning in other brain areas that subserve motor function. In the right dorsolateral prefrontal cortex, there was considerable activation during the early phases of learning, followed by a decrease as the sequence was acquired. In

the anterior cingulate cortex, there was an initial sharp increase followed by sustained activation during the first 15 trials, followed by a slow decrease to baseline levels. The dorsal premotor cortex was highly activated early in learning, but during the second half of learning there was a relative decrease in activation. In contrast, SMA activation increased as learning progressed. In the parietal cortex, there were increases early in learning, followed by sustained activity. The left caudate, ipsilateral putamen and contralateral cerebellum were activated early during learning and then decreased to baseline levels. The contralateral putamen remained active throughout learning. In the ipsilateral lateral cerebellar, there was a small increase in activation with time. Hikosaka [39] examined the neural correlates of sequential procedural learning in the SMA and found that a localized area in the SMA was particularly active during learning of new sequential procedures and not movements per se. An area posterior to this area (SMA proper) was active for the performance of sequential movements and not learning.

7. Effects of rate and force of movement on brain activation Several fMRI studies have tried to further elucidate the function of the different motor areas by independently varying the conditions such as the rate and force under which motor actions are performed. With increased rate of movement, Wexler et al. [40] found greater activity only in the contralateral motor area. Rao et al. [41] also had reported similar results. Jancke et al. [42] performed a parametric analysis of the ‘rate effect’ in the sensorimotor cortex. They examined subjects at different frequencies of movement ranging from 0.5 to 5 Hz, and reported that at rates faster than 1 Hz (1.5–5 Hz), a BOLD response occurred that was linearly and positively related to movement frequency. For the slower frequencies there was an initial sharp increase of the BOLD response from 0.5 to 1 Hz followed by a drop for 1.5 Hz. Thickbroom et al. [43] examined BOLD effects in the primary sensorimotor cortex during a purely isometric motor task and the relationship of the BOLD response to the magnitude of the force. With increasing levels of force, they found spread of a relatively constant BOLD response over a wider volume of cortex, rather than an increase in the magnitude of the response from a fixed region. They hypothesized that while increased neuronal firing at higher force levels leads to a greater localized increase in blood oxygenation, it is then spread by blood flow to adjacent regions in such a way that a balance is maintained in blood oxygenation concentration within vessels for all force levels.

V.S. Mattay, D.R. Weinberger / European Journal of Radiology 30 (1999) 105–114

8. Neural substrates underlying motor imagery Motor imagery may be defined as the act of mental rehearsal of simple or complex motor acts that is not accompanied by overt body movements. Several groups have explored the neural substrates subserving this aspect of motor function using fMRI [44 – 46]. Porro et al. [44] and Roth et al. [45] found that during motor imagery, the percentage increases in signal intensity in the primary motor cortex were 30% of that seen during the actual motor execution task. Based on this, they suggested that overlapping neural networks in the primary motor and somatosensory areas are activated during mental representation and actual performance of motor acts. These findings, while contradicting earlier PET studies [47–49] that failed to show activation of the primary sensorimotor cortex during mental rehearsal, probably reflect the superior sensitivity of fMRI methods to detect subtle changes. The role of the cerebellum in motor imagery was examined by Luft et al. [46]. They found that while motor imagery and execution share common cerebellar circuitry, there was additional activation in the lateral cerebellum during imagery. This may reflect a role of the neocerebellum, perhaps related to neocortical connections during motor imagery. Additionally, in the motor cortex, the activated areas that were common during imagery and motor execution showed lower signal changes during imagery compared to motor execution.

9. Neural substrates underlying production of motor sequence Several studies using PET characterized the sensory and motor areas involved in the production of specific finger movement sequences. Some studies implicated the SMA in the production of sequential movements, such as finger-thumb opposition sequences and finger tapping sequences [50–55]. In contrast, other studies have suggested that SMA activation may even occur during simple movements such as flexion/extension movements of the hand or finger or shoulder movement [56– 58] and is not exclusively limited to sequential movements. Other associative motor areas such as the premotor area [55,59], anterior cingulate [55,60,61], primary somatosensory area [54,55], and basal ganglia [55] have been less frequently implicated. The disparity in findings across these studies may be due to differences in motor paradigms and sensitivity of the imaging techniques utilized. Using BOLD fMRI, Gordon et al. [62] examined the activation of motor cortical and subcortical areas during performance of well-learned sequences of finger movements as required in typing. Typing involves pur-

109

poseful, goal directed and sensory encoded movements and offers several advantages for the study of assembly of movement sequences in contrast to many of the above mentioned tasks. They found that the production of simple repetitive key-presses with the index finger primarily involved the activation of contralateral primary motor cortex, although a small activation of the supplementary motor area and other regions was observed as well. The sequencing of key presses involved bilateral M1 and a stronger activation of the SMA and to a lesser extent the premotor area, cingulate gyrus, caudate, and lentiform nuclei. They found that the activation of these areas did not exclusively depend on the complexity of the movements, since they were often activated during simple movements such as alternating keypresses. While somatosensory and parietal regions were also activated during typing sequences, the activation of the parietal areas did not exclusively depend on the spatial requirements of the task since they found similar activation during finger-thumb opposition (movements within intra-personal space). Based on this they hypothesized that the parietal activation may be related to the temporal requirements of the task. They concluded that the assembly of well-learned, goal directed finger movement sequences involves the SMA, other secondary motor areas as well as somatosensory and parietal areas.

10. Hemispheric control of motor function Previous studies have tended to find greater ipsilateral activation of the left hemisphere typically during left hand movements [63–66], implying left cerebral dominance for motor control. However, as the nondominant hand is generally less motorically facile, and as other studies of complex movements with the dominant hand have reported ipsilateral activation [54,67,68], the possibility existed that ipsilateral activation was really a functional sign of the degree of motoric familiarity or automaticity. To specifically address the relationship of complexity and unfamiliarity of the task to ipsilateral activation, in contrast to the earlier studies [63–66], we examined subjects during a more complex (less familiar) task with the dominant hand also. Furthermore, the single slice approach used by Kim et al. [63], Schroder et al. [64], and Singh et al. [65,66] precludes one from examining the whole expanse of the motor cortex let alone the motor system. To circumvent this problem we used a whole-brain imaging method while subjects performed simple and complex motor tasks. The simple motor task (SM) entailed the subject tapping the thumb to the other four digits in a sequential manner and in the complex motor task (CM) the subjects were asked to tap the thumb to the other four digits in a random self-generated se-

110

V.S. Mattay, D.R. Weinberger / European Journal of Radiology 30 (1999) 105–114

quence. We demonstrated ipsilateral cortical activity during both dominant and non-dominant hand motor tasks, but more so in the less familiar tasks regardless of the hand or hemisphere involved (i.e. non-dominant hand SM task and dominant hand CM task). In general, however, the activation was greatest in the contralateral cortical motor areas. The degree of ipsilateral cortical activity varied in the different cortical motor regions and across the different tasks. In the individual subject analysis, this was more prominent and seen in more subjects during the non-dominant hand SM task and dominant hand CM task than during dominant hand SM task. Similarly, in the group maps, ipsilateral activation was seen in the primary sensorimotor and lateral premotor regions in the non-dominant hand SM task group map and dominant hand CM task group map. In this study, the CM task with the non-dominant hand was not performed. Interestingly, preliminary analysis in an ongoing study from our group (Mattay et al., unpublished observations) in strongly right handed subjects and in left handed subjects performing SM and CM tasks with both the dominant and non-dominant hand reveals that the extent of ipsilateral primary sensorimotor cortex activation was greater during the less familiar, more complex task (CM) than during the more familiar, less complex task (SM), irrespective of the hand used (dominant vs. non-dominant) or handedness of the subject. These results further support our earlier findings [9] that recruitment of the ipsilateral primary sensorimotor cortex is associated with less automatic motor behavior per se and is more a reflection of task complexity than of cerebral organization, irrespective of the hand used or the handedness of the subject. Dassonville et al. [69] examined the role of handedness on activation of the cortical motor areas. During a left-to-right repeating sequence task (predictable task) and a randomized (unpredictable) motor task with dominant and non-dominant hands in both right handed and left handed subjects, they found that there was a negative correlation between the degree of handedness and activation ipsilateral to the dominant hand, primarily in the motor cortex. This suggests that those subjects who had the strongest hand preference had the least amount of activation ipsilateral to the preferred hand during movement. Based on these findings they suggest that handedness is not categorical as far as brain activation is concerned and may represent a more continuous variable. They concluded that the degree of contralateral activation indicates the direction of handedness and that their results support the notion that patients with a high degree of handedness would be more incapacitated in the use of the dominant hand after damage to the contralateral motor areas than those with a low degree of handedness because the latter are likely to have greater residual input from the ipsilateral motor areas.

11. Clinical applications Examples of fMRI studies of the motor system in clinical disorders include those that were aimed at: (1) understanding the mechanisms underlying motor abnormalities in patients with neuropsychiatric disorders such as schizophrenia, Tourette’s syndrome and Parkinson’s disease; (2) understanding the mechanisms underlying reorganization or plasticity of the motor system following a cerebral insult; and (3) validating fMRI as a tool for presurgical evaluation of neurosurgery patients

11.1. Mechanisms underlying motor abnormalities in patients with neuropsychiatric disorders 11.1.1. Patients with schizophrenia Neurological soft signs, including mirror movements, have been found to be more prevalent in schizophrenic patients [70]. Several lines of evidence from cytoarchitectural [71] neurophysiological [72,73] and neuropsychological [74], literature suggest a breakdown in intracortical functional connectivity in the pathogenesis of schizophrenia. Evidence from functional imaging literature suggests that this breakdown in intracortical functional connectivity may lead to an impairment of the physiological mechanisms responsible for ‘focalizing’ cortical activity in patients with schizophrenia [75,76]. Patients with schizophrenia have been found to be less well lateralized than normal subjects on tests of handedness, dichotic listening asymmetries and lateralized cognitive tasks [77,78]. Previous studies of motor activation in schizophrenia have reported decreased activity in the cortical motor regions in some studies [76] and normal activity in others [79,80]. More recently, we found that patients with schizophrenia, show abnormal functional lateralization of the sensorimotor cortex during motor tasks [12]. While normal motor control is predominantly in the contralateral hemisphere, we found that in patients with schizophrenia, this lateralization of motor function may be anomalous, especially in the primary sensorimotor cortex and lateral premotor region. We found greater ipsilateral activation in the primary sensorimotor and lateral premotor regions in patients during motor tasks resulting in a decrease in laterality quotient, a parameter reflecting relative lateralization. We also found decreased supplementary motor area and striatal activation in the patients when compared to normals, which further suggests that there is disruption of functional motor network connections in schizophrenia. Consistent with other neuroimaging data [79,80], in our study also there was no significant difference in the degree of activation of the contralateral primary sensorimotor region between normal subjects and patients.

V.S. Mattay, D.R. Weinberger / European Journal of Radiology 30 (1999) 105–114

11.1.2. Patients with Tourette’s syndrome Biswal et al. [81] using a finger tapping task reported greater activation in the sensorimotor cortex and supplementary motor area of patients with Tourette’s syndrome than normal controls. The implications of this finding, using a limited brain coverage approach without estimates of patient movement and image noise, is unclear. A well-controlled study in a larger number of patients stratified by severity of attention deficit and obsessive compulsive disorder may shed more light. 11.1.3. Patients with Parkinson’s disease It is well known that Parkinson’s disease (PD) is associated with disruption of the nigrostriatal dopaminergic system and that one of the major cortical outputs of the basal ganglia is to supplementary motor area. It is also thought that this functional deafferentation of the supplementary motor area is responsible for the development of akinesia, a salient clinical feature of PD. Hypofunctioning of supplementary motor area during movements has been demonstrated by nuclear functional brain imaging studies [82,83]. Similarly, reversal of this phenomenon has been successfully demonstrated by these methods when akinesia is treated with dopaminergic drugs [84,85]. Tada et al. [85] were the first to report on the motor abnormalities related to Parkinson’s disease with fMRI. Consistent with earlier brain imaging studies, they found decreased movement related activity in the SMA in patients. In an ongoing fMRI study from our group, preliminary analysis on two patients with PD, while demonstrating hypoactivity in the supplementary motor area, also shows reversal of this hypoactivity following administration of dopaminergic drugs. 11.2. Plasticity and reorganization of the motor system A special property of the mammalian brain is its capacity for adaptation to change, otherwise referred to as plasticity. fMRI is well suited for understanding the reorganization or plasticity of the motor system following a cerebral insult such as a cerebrovascular accident, neoplasm, trauma, or surgical resection. Rossini et al. [86], examined the reorganization of the hand sensorimotor area in a patient affected by right hemiparesis with progressive full motor recovery along with persisting motor aphasia 12 months after an ischemic stroke in the middle cerebral artery distribution. They found an asymmetrical enlargement and posterior shift of the left sensorimotor area in the affected hemisphere. This finding was corroborated by two other brain mapping techniques (magnetoencephalography (MEG) and focal magnetic transcranial stimulation (TCS) studies). Graveline et al. [87] studied

111

two patients who had an entire cortical hemispherectomy, and reported activation of the associative motor areas in the ipsilateral hemisphere and not the primary motor cortex during motor tasks with the hemiparetic hand, suggesting not only the transfer of motor function from one hemisphere to the other but also regionalization of brain plasticity. In six of eight recovering hemiparetic or hemiplegic patients, Cao et al. [88] demonstrated extended activation of the ipsilateral sensorimotor cortex. A similar extension of ipsilateral motor cortex activity was reported by Yoshiura et al. [89] in patients with brain tumors and paresis. Taken together, these various studies suggest that following injury to the motor system, a compensatory reorganization (accessing or recruiting preexisting uncrossed motor neural pathways) develops.

11.3. fMRI in presurgical e6aluation Another important clinical application of fMRI is in the presurgical evaluation of patients for neurosurgery. The central sulcus is a major anatomical and functional reference in neurosurgery, and its identification is crucial for procedures aimed at removing centrally located lesions. While routine clinical use of fMRI for this purpose needs substantially more study, several preliminary studies have been reported on successful mapping of the primary sensorimotor cortex in patients with epilepsy, CNS tumors and vascular malformations [90–92]. Significant efforts are also being made to facilitate accurate cortical localization for guiding surgical intervention. Towards this end, Debus et al. [93] introduced a MR environment compatible stereotactic set-up. Immobilizing the skull of the patients for stereotactic treatment planning either with a self developed stereotactic ceramic frame and bony fixation or with an individual precision mask system made of light cast, they successfully mapped the sensorimotor cortex in ten patients. Similarly, advances that facilitate real time functional MRI in the surgical suite are underway. Gering et al. [94] described a technique for successful intraoperative mapping of the sensorimotor areas in real time with fMRI at 0.5 T, and advocate the use of this technique in guiding surgical intervention. Studies comparing the localization accuracy of fMRI to intraoperative localization have generally shown good correlation [95–97]. These studies, however, relied on subjective comparison of operative photographs to make this assessment. More recently, Maldjian et al. [98] utilizing intraoperative fMRI and a real time neurosurgical navigation system demonstrated an objective method of evaluating fMRI localization accuracy.

112

V.S. Mattay, D.R. Weinberger / European Journal of Radiology 30 (1999) 105–114

12. Future perspectives While the clinical studies discussed in this review are encouraging, the small number of subjects involved limits the conclusions that can be drawn. Nonetheless, by virtue of its many advantages, fMRI holds great promise and has vast potential to further enhance our understanding of human brain function, including that of the motor system. More work on large numbers of subjects and patients, combined use of fMRI and other brain mapping techniques with superior temporal resolution such as MEG and TMS, and development of MR compatible electrophysiological recording equipment will certainly contribute towards this goal. Some of the current limitations of fMRI are the time needed to perform a study (generally 45 – 60 min), and the labor-intensive and time-consuming image processing. However, with the rapid evolution of MRI technology and image processing methods, one can anticipate overcoming these obstacles in the near future. References [1] Kwong KK, Belliveau JW, Chesler DA, Goldberg IE, Weisskoff RM, Poncelet BP, Kennedy DN, Hoppel BE, Cohen MS, Turner R, et al. Dynamic magnetic resonance imaging of human brain activity during primary sensory stimulation. Proc Natl Acad Sci USA 1992;89:5675–9. [2] Ogawa S, Tank DW, Menon R, Ellermann JM, Kim SG, Merkle H, Ugurbil K. Intrinsic signal changes accompanying sensory stimulation: functional brain mapping with magnetic resonance imaging. Proc Natl Acad Sci USA 1992;89:5951– 5. [3] Ramsey NF, Kirkby BS, Gelderen P, Berman KF, Duyn JH, Frank JA, Mattay VS, Horn JD, Esposito G, Moonen CTW, Weinberger DR. Functional mapping of human sensorimotor cortex with 3D BOLD fMRI correlates with H15 2 O PET rCBF. J Cereb Blood Flow Metab 1996;16:755–64. [4] Dettmers C, Connelly A, Stephan KM, Turner R, Friston KJ, Frackowiak RSJ, Gadian DG. Quantitative comparison of functional magnetic resonance imaging with positron emission tomography using a force-related paradigm. Neuroimage 1996;4:201 – 9. [5] Sadato N, Ibanez V, Campbell G, Deiber MP, LeBihan D, Hallett M. Frequency-dependent changes of regional cerebral blood flow during finger movements: functional MRI compared to PET. J Cereb Blood Flow Metab 1997;17:670 – 9. [6] Stippich C, Freitag P, Kassubek J, Soros P, Kamada K, Kober H, Scheffler K, Hopfengatrner R, Bilecen D, Radu E, Vieth J. Motor, somatosensory and auditory cortex localization by fMRI and MEG. Neuroreport 1998;9:1957–7. [7] Krings T, Buchbinder BR, Butler WE, Chiappa KH, Jiang HJ, Cosgrove CR, Rosen BR. Functional magnetic resonance imaging and transcranial magnetic stimulation: complementary approaches in the evaluation of cortical motor function. Neurology 1997;48:1406–16. [8] Mattay VS, Frank JA, Santha AKS, Pekar JJ, Duyn JH, McLaughlin AC, Weinberger DR. Whole brain functional mapping with isotropic MR imaging. Radiology 1996;201:399 – 404. [9] Mattay VS, Callicott JH, Bertolino A, Santha AK, Van Horn JD, Tallent KA, Frank JA, Weinberger DR. Hemispheric control of motor function: a whole brain echo planar fMRI study. Psychiatry Res 1998;83:7–22.

[10] Yang Y, Glover GH, VanGelderen P, Mattay VS, Santha AK, Sexton RH, Ramsey NF, Moonen CT, Weinberger DR, Frank JA, Duyn JH. Fast 3D functional magnetic resonance imaging at 1.5T with spiral acquisition. Magn Reson Med 1996;36:620–6. [11] Brooks DJ. The role of the basal ganglia in motor control: contributions from PET. J Neurol Sci 1995;128:1–13. [12] Mattay VS, Callicott JH, Bertolino A, Santha AK, Tallent KA, Goldberg TE, Frank JA, Weinberger DR. Abnormal functional lateralization of the sensorimotor cortex in patients with schizophrenia. Neuroreport 1997;8:2977 – 84. [13] Menon V, Glover GH, Pfefferbaum A. Differential activation of dorsal basal ganglia during externally and self paced sequences of arm movements. Neuroreport 1998;9:1567 – 73. [14] Reichenbach JR, Feiwell R, Kuppuswamy K, Bahn M, Haacke M. Functional magnetic resonance imaging of the basal ganglia and cerebellum using a simple motor paradigm. Magn Reson Imaging 1998;16:281 – 7. [15] Jenkins IH, Brooks DJ, Nixon PD, Frackowiak RSJ, Passingham RE. Motor sequence learning: a study with positron emission tomography. J Neurosci 1994;14:3775 – 90. [16] Sadato N, Zeffiro TA, Campbell G, Konishi J, Shibaski H, Hallett M. Regional cerebral blood flow changes in motor cortical areas after transient anesthesia of the forearm. Ann Neurol 1995;37:74 – 81. [17] Lehericy S, van de Moortele PF, Lobel E, Paraids AL, Vidailhet M, Frouin V, Neveu P, Agid Y, Marsault C, Le Bihan D. Somatotopical organization of striatal activation during finger and toe movement: a 3-T functional magnetic resonance imaging study. Ann Neurol 1998;44:398 – 404. [18] Rao SM, Binder JR, Hammeke TA, Bandettini PA, Bobholz JA, Frost JA, Myklebust BM, Jacobson RD, Hyde JS. Somatotopic mapping of the human primary motor cortex with functional magnetic resonance imaging. Neurology 1995;45:919–24. [19] Sanes JN, Donoghue JP, Thangaraj V, Edelman RR, Warach S. Shared neural substrates controlling hand movements in human motor cortex. Science 1995;268:1775– 7. [20] Kleinschmidt A, Nitschke MF, Frahm J. Somatotopy in the human motor cortex hand area. A high-resolution functional MRI study. Eur J Neurosci 1997;9:2178 – 86. [21] Sakai K, Takno R, Hikosaka O, Miyauchi S, Sasaki Y, Putz B, Fujimaki N. Separate cerebellar areas for motor control. Neuroreport 1998;9:2359 – 63. [22] Alexander GE, Crutcher MD. Functional architecture of basal ganglia circuits; neuronal substrates of parallel processing. Trends Neurosci 1990;13:266 – 71. [23] Kunzle H. Bilateral projections from the precentral motor cortex to the putamen and other parts of basal ganglia. An autoradiographic study in macaca fasciularis. Brain Res 1975;88:195–209. [24] Alexander GE, DeLong MR. Microstimulation of the primate neostriatum. II. Somatotopic organization of striatal microexcitable zones and their relation to neuronal response properties. J Neurophysiol 1985;53:1417 – 30. [25] Richter W, Andersen PM, Georgeopoulos AP, Kim SG. Sequential activity in human motor areas during a delayed cued finger movement task studied by time-resolved fMRI. Neuroreport 1997;8:1257 – 61. [26] Samuel M, Williams SCK, Leigh PN, Simmons A, Chakraborti S, Andrews CM, Friston KJ, Goldstein LH, Brooks DJ. Exploring the temporal nature of hemodynamic responses of cortical motor areas using functional MRI. Neurology 1998;51:1567–75. [27] Rubia K, Overmeyer S, Taylor E, Brammer M, Williams S, Simmons A, Andrew C, Bullmore E. Prefrontal involvement in ‘temporal bridging’ and timing movement [in process citation]. Neuropsychologia 1998;36:1283 – 93. [28] Jueptner M, Stephan KM, Frith KM, Brooks DJ, Frackowiak RSJ, Passingham RE. Anatomy of motor learning. I. Frontal cortex and attention in action. J Neurophysiol 1997;77:1313–24.

V.S. Mattay, D.R. Weinberger / European Journal of Radiology 30 (1999) 105–114 [29] Jueptner M, Frith KM, Brooks DJ, Frackowiak RSJ, Passingham RE. Anatomy of motor learning. II. Subcortical structures and learning by trial and error. J Neurophysiol 1997;77:1325–37. [30] Grafton ST, Hazeltine E, Ivry R. Functional mapping of sequence learning in normal humans. J Cogn Neurosci 1995;7:497 – 510. [31] Hazeltine E, Grafton ST, Ivry R. Attention and stimulus characteristics determine the locus of motor-sequence encoding. A PET study. Brain 1997;120:123 –40. [32] Doyon J, Owen AM, Petrides M, Szikilas V, Evans AC. Functional anatomy of visuomotor skill learning in human subjects examined with positron emission tomography. Eur J Neurosci 1996;8:637 – 48. [33] Karni A, Meyer G, Jezzard P, Adams MM, Turner R, Ungerleider LG. Functional MRI evidence for adult motor cortex plasticity during motor skill learning. Nature 1995;377:155–8. [34] Mitz AR, Godschalk M, Wise SP. Learning-dependent neuronal activity in the premotor cortex: activity during the acquisition of conditional motor associations. J Neurosci 1991;11:1855–72. [35] Ojakangas CL, Ebner TJ. Purkinge cell complex and simple spike changes during a voluntary arm movement learning task in the monkey. J Neurophysiol 1992;68:2222–36. [36] Chen LL, Wise SP. Neuronal activity in the supplementary eye field during acquisition of conditional oculomotor associations. J Neurophysiol 1995;73:1101–20. [37] Llundberg T, Apicella P, Schultz W. Responses of monkey dopamine neurons during learning of behavioral reactions. J Neurophysiol 1992;67:145 –63. [38] Toni I, Krams M, Turner R, Passingham RE. The time course of changes during motor sequence learning: a whole-brain fMRI study. Neuroimage 1998;8:50–61. [39] Hikosaka O, Sakai K, Miyauchi R, Takino R, Sasaki Y, Putz B. Activation of human presupplementary motor area in learning of sequential procedures: a functional MRI study. J Neurophysiol 1996;76:617 – 21. [40] Wexler BE, Fulbright RK, Lacadie CM, Skudlarski P, Kelz MB, Constable T, Gore JC. An fMRI study of the human cortical motor system response to increasing functional demands. Magn Reson Imaging 1997;15:385–96. [41] Rao SM, Bandetinni PA, Binder JR, Bobholz JA, Hammeke TA, Stein EA, Hyde JS. Relationship between finger movement rate and functional magnetic resonance signal change in human primary motor cortex. J Cereb Blood Flow Metab 1996;16:1250 – 4. [42] Jancke L, Specht K, Mirzazade S, Loose R, Himmelbacj M, Lutz K, Shah NJ. A parametric analysis of the ‘rate effect’ in the sensorimotor cortex: a functional magnetic resonance imaging analysis in human subjects. Neurosci Lett 1998;252:37–40. [43] Thickbroom GW, Phillips BA, Morris I, Byrnes ML, Mastaglia FL. Isometric force-related activity in snesorimotor cortex measured with functional MRI. Exp Brain Res 1998;121:59–64. [44] Porro CA, Francesscato MP, Cettolo V, Diamond ME, Braldi P, Zuiani C, Bazzocchi M, di Prampero PE. Primary motor and sensory cortex activation during motor performance and motor imagery: a functional magnetic resonance imaging study. J Neurosci 1996;16:7688 – 98. [45] Roth M, Decety J, Raybaudi M, Massarelli R, Delon-Martin C, Segabarth C, Morand S, Gemignani A, Decorps M, Jeannerod M. Possible involvement of primary motor cortex in mentally stimulated movement: a functional magnetic resonance imaging study. Neuroreport 1996;7:1280–4. [46] Luft AR, Skaleej M, Stefanou A, Klose U, Voigt K. Comparing motion and imagery-related activation in the human cerebellum: a functional MRI study. Hum Brain Mapping 1998;6:105–13. [47] Decety J, Perani D, Jeannerod M. Nature 1994;371:600–2. [48] Stephan KM, Fink GR, Passingham RE. J Neurophysiol 1995;73:373 – 86.

113

[49] Parsons LM, Fox PT, Downs J. Nature 1995;375:54 – 8. [50] Orgogozo JM, larsen B. Activation of the supplementary motor area during voluntary movement in man suggests it works as a supramotor area. Science 1979;206:847 – 50. [51] Roland PE, Larsen B, Lassen NA, Skinhoj E. Supplementary motor area and other cortical areas in organization of voluntary movements in man. J Neurophysiol 1980;43:118 – 34. [52] Roland PE, Skinhoj E, Lassen NA, Larsen B. Different cortical areas in man in organization of voluntary movements in extrapersonal space. J Neurophysiol 1980;43:137 – 50. [53] Grafton ST, Mazziotta JC, Woods RP, Phelps ME. Human functional anatomy of visually guided finger movements. Brain 1992;115:565 – 87. [54] Rao SM, Binder JR, Bandettini PA, Hammeke TA, Yetkin FZ, Jesmanowicz A, Lisk LM, Morris GL, Mueller WM, Estkowski LD, et al. Functional magnetic resonance imaging of complex human movements. Neurology 1993;43:2311 – 8. [55] Shibaski H, Sadato N, Lyshkow H, Yonekura Y, Honda M, Nagamine T, Suwazono S, Magata Y, Ikeda A, Miyazaki M, Fukuyama H, Asato R, Konishi J. Both primary motor cortex and supplementary motor area play an important role in complex finger movement. Brain 1993;116:1387– 98. [56] Fox PT, Fox JM, Raichle ME, Burde RM. The role of cerebral cortex in the generation of voluntary saccades: a positron emission tomography. J Neurophysiol 1985;54:348 – 69. [57] Colebatch JG, Deiber MP, Passingham RE, Friston KJ, Frackowiak RSJ. Regional cerebral blood flow during voluntary arm and hand movements in human subjects. J Neurophysiol 1991;65:1392 – 401. [58] Boecker H, Kleinschmidt A, Requardt M, Hanicke W, Merboldt KD, Frahm J. Functional cooperativity of human cortical motor areas during self-paced simple finger movements — a high-resolution study. Brain 1994;117. [59] Kawashima R, Yamda K, Kinomura S, Yamaguchi T, Matsui H, Yoshioka S, Fukuda H. Regional cerebral blood flow changes of cortical motor areas and prefrontal areas in humans related to ipsilateral and contralateral hand movement. Brain Res 1993;623:33 – 40. [60] Deiber MP, Passingham RE, Colebatch JG, Friston KJ, Nixon PD, Fracjkowiak RSJ. Cortical areas and the selection of movement: a study with positron emission tomography. Exp Brain Res 1991;84:393 – 402. [61] Paus T, Petrides M, Evans AC, Meyer E. Role of the human anterior cingulate cortex in the control of oculomotor, manual, and speech responses: a positron emission tomography study. J Neurophysiol 1993;70:453 – 69. [62] Gordon AM, Lee JH, Flament D, Ugurbil K, Ebner TJ. Functional magnetic resonance imaging of motor, sensory, and posterior parietal cortical areas during performance of sequential typing movements. Exp Brain Res 1998;121:153 – 66. [63] Kim S-G, Ashe J, Hendrich K, Ellerman JM, Merkle H, Ugurbil K, Georgopoulos AP. Functional magnetic resonance imaging of motor cortex: hemispheric asymmetry and handedness. Science 1993;261:615 – 7. [64] Schroder J, Wenz F, Schad LR, Baudendistel K, Knopp MV. Sensorimotor cortex and supplementary motor area changes in schizophrenia. Br J Psychiatry 1995;167:197 – 201. [65] Singh LN, Higano S, Takahashi S, Abe Y, Sakamoto M, Kurihara N, Furuta S, Tamura H, Yanagawa I, Fujii T, Ishibashi T, Maruoka S, Yamada S. Functional MR imaging of cortical activation of the cerebral hemispheres during motor tasks. Am J Neuroradiol 1998;19:275 – 80. [66] Singh LN, Higano S, Takahashi S, Kurihara N, Furuta S, Tamura H, Shimanuki Y, Mugikura S, Fujii T, Yamadori A, Sakamoto M, Yamada S. Comparison of ipsilateral activation between right and left handers: a functional MRI imaging study. Neuroreport 1998;9:1861 – 6.

114

V.S. Mattay, D.R. Weinberger / European Journal of Radiology 30 (1999) 105–114

[67] Heap M, Wyke M. Learning of a unimanual motor skill by patients with brain lesions: an experimental study. Cortex 1972;8:1 – 18. [68] Haaland YK, Delaney HD. Motor defects after left or right hemisphere damage due to stroke or tumor. Neuropsychologia 1981;19:17 – 27. [69] Dassonville P, Zhu XH, Ugurbil K, Kim SG, Ashe J. Functional activation in motor cortex reflects the direction and the degree of handedness. Proc Natl Acad Sci USA 1997;94:14015 – 8. [70] Mohr F, Hubmann W, Cohen R, Bender W, Halacher C, Honicke S, Schlenker R, Wahlheim C, Werther P. Neurological soft signs in schizophrenia:assessment and correlates. Eur Arch Psychiatry Clin Neurosci 1996;246:240–8. [71] Akbarian S, Viinuela A, Kim JJ, Potkin SG, Bunney WEJ, Jones EG. Distorted distribution of nicotinamide-adenine dinucleotide phosphate-diaphorase neurons in temporal lobe of schizophrenics implies anomalous cortical development. Arch Gen Psychiatry 1993;50:178–87. [72] Weinberger DR, Berman KF, Suddath R, Torrey EF. Evidence for dysfunction of a prefrontal-limbic network in schizophrenia: an MRI and rCBF study of discordant monozygotic twins. Am J Psychiatry 1992;149:890–7. [73] Frith CD, Friston KJ, Herold S, Silbersweig D, Fletcher P, Cahill C, Dolan RJ, Frackowiak RSJ, Liddle PF. Regional brain activity in chronic schizophrenic patients during performance of a verbal fluency task: evidence for a failure of inhibition in left superior temporal cortex. Br J Psychiatry 1995;167:343 – 9. [74] Goldberg TE, Gold JM, Braff DL. Neuropsychological functioning and time-linked information processing in schizophrenia. In: Tasman A, Goldfinger SM, editors. American Psychiatric Press Review of Psychiatry 10. Washington, DC: American Psychiatric Association, 1991:60–78. [75] Weinberger DR. Schizophrenia as a Neurodevelopmental Disorder. In: Hirsch SR, Weinberger DR, editors. Schizophrenia. Oxford: Blackwell Science, 1995:293–323. [76] Guenther W, Brodie JD, Bartlett EJ, Dewey SL, Henn FA, Volkow ND, Alper K, Wolkin A, Cancro R, Wolf A. Diminished cerebral metabolic response to motor stimulation in schizophrenics: a PET study. Eur Arch Psychiatry Clin Neurosci 1994;244:115–25. [77] Gruzelier JH, Seymour K, Wilson L, Jolley T, Hirsch S. Impairments on neuropsychological tests of temporo-hippocampal and fronto-hippocampal functions and word fluency in remitting schizophrenia and affective disorders. Arch Gen Psychiatry 1988;45:623 –9. [78] Wexler BE, Heninger GR. Alterations in cerebral laterality during acute psychotic illness. Arch Gen Psychiatry 1979;36:278 –84. [79] Weinberger DR, Mattay V, Callicott J, Kotrla K, Santha A, Gelderen P, Duyn J, Moonen C, Frank J. FMRI application in schizophrenia research. Neuroimage 1996;4:S118– 26. [80] Buckley PF, Friedman L, Wu D, Lai S, Meltzer HY, Haacke EM, Miller D, Lwein JS. Functional magnetic resonance imaging in schizophrenia: initial methodology and evaluation of the motor cortex. Psychiatry Res Neuroimaging Sect 1997;74:13 – 23. [81] Biswal B, Ulmer R, Krippendporf RL, Harsch H, Daniels DL, Hyde JS, Haughton VM. Abnormal cerebral activation associated with a motor task in Tourette’s syndrome. Am J Neuroradiol 1998;19:1509–12. [82] Playford ED, Jenkins IH, Passingham RE, Nutt J, Frackowiak RSJ, Brooks DJ. Impaired mesial frontal and putamen activation in Parkinson’s disease: a positron emission tomography study. Ann Neurol 1992;32:151–61.

.

[83] Rascol O, Sabatini U, Chollet F, Celsis P, Monstastruc JL, Marc-Vernes JP, Rascol A. Supplementary and primary sensory motor area activity in Parkinson’s disease. Regional cerebral blood flow changes during finger movements and effects of apomorphine. Arch Neurol 1992;49:144 – 8. [84] Jenkins IH, Fernandez W, Playford ED, Lees AJ, Frackowiak RSJ, Passingham RE, Brooks DJ. Impaired activation of the supplementary motor area in Parkinson’s disease is reversed when akinesia is treated with apomorphine. Ann Neurol 1992;32:749 – 57. [85] Tada Y. Motor association cortex activity in Parkinson’s disease — a functional MRI study. Rinsho Shinkeigaku 1998;38:729 – 35. [86] Rossini PM, Caltigirone C, Castriota-Scandenbeg A, Cicinelli P, Del Gratta C, Demartin M, Pizzella V, Traversa R, Romani GL. Hand motor cortical area reorganization in stroke: a study with fMRI, MEG and TCS maps. Neuroreport 1998;9:2141–6. [87] Graveline CJ, Mikulis DJ, Crawley AP, Hwang PA. Regionalized sensorimotor plasticity after hemispherectomy fMRI evaluation. Pediatr Neurol 1998;19:337 – 42. [88] Cao Y, D’Olhaberriague L, Vikingstad EM, Levine SR, Welch KMA. Pilot study of functional MRI to access cerebral activation of motor function after poststroke hemiparesis. Stroke 1998;29:112 – 22. [89] Yoshiura T, Hasuo KF M, Masuda K, Morioka T, Fukui M. Increased activity of the ipsilateral motor cortex during a hand motor task in patients with brain tumor and paresis. Am J Neuroradiol 1997;18:865. [90] Latchaw RE, Hu X, Ugurbil K, Hall WA, Madison MT, Heros RC. Functional magnetic resonance imaging as a management tool for cerebral arteriovenous malformations. Neurosurgery 1995;37:619 – 26. [91] Mueller W, Yetkin Z, Hammeke TA, Morris GL, Swanson SJ, Reichert K, Cox R, Haughton V. Functional magnetic resonance imaging mapping of the motor cortex in patients with cerebral tumors. Neurosurgery 1996;39:515 – 21. [92] Atlas SW, Howard RS, Maldjian J, Alsop D, Detre JA, Listerud J, Esposito MD, Judy KD, Zager E, Stecker M. Functional magnetic resonance imaging of regional brain activity in patients with intracerebral gliomas: findings and implications for clinical management. Neurosurgery 1996;38:329 – 38. [93] Debus J, Essig M, Schad LR, Wenz F, Baudenstel K, Knopp MV, Engenhart R, Lorenz WJ. Functional magnetic resonance imaging in a stereotactic setup. Magn Reson Imaging 1996;14:1007 – 12. [94] Gering DT, Weber DM. Intraoperative, real-time, functional MRI. J Magn Reson Imaging 1998;8:254 – 7. [95] Puce A, Constable T, Luby ML, McCarthy G, Nobre AC, Spencer DD, Gore JC, Allison T. Functional magnetic resonance imaging of sensory and motor cortex: comparison with electrophysiological localization. J Neurosurg 1995;83:262–70. [96] Yousry TA, Schmind UD, Jassoy AG, Schmidt D, Eisner WE, Reulen H, Reiser MF, Lissner J. Topography of the cortical motor hand area: prospective study with functional MR imaging and direct motor mapping at surgery. Neuroradiology 1995;195:23 – 9. [97] Jack CRJ, Thompson RM, Butts RK, et al. Sensory motor cortex correlation of presurgical mapping with functional MR imaging and invasive cortical mapping. Radiology 1994;190:85– 92. [98] Maldjian JA, Schulder M, Liu W, Mun I, Hirschorn D, Murthy R, Carmel P, Kalnin A. Intraoperative functional MRI using a real-time neurosurgical navigation system. J Comput Assisted Tomogr 1997;21:910 – 2.