POSTERS: MOTOR

A Blueprint for Movement in the Human Motor Cortex

M. Rijntjes (1), C. Dettmers (1), R. Rzanny (2), S. Kiebel (1), C. Weiller (1)Dept. ofNeurology (1) and Diagnostic & lnterventional Radiology (2),

University oflena, lena, Germany

IntroductionThe relation between movement and cortical acnvity is a well-studied subject. All or most of these studies,however, have focused on the relation between activity and the movement of one extremity at a time. Still, somehigher level of movement representation is to be expected, since a movement can be learned with one extremityand performed with another. An example is a person's signature. Routinely written with the dominant hand, itcan be done with another extremity, retaining the writer's personal characteristics. We had normal volunteerswrite their signature with their dominant hand and foot, to see if common structures would be activated. Severalcontrol conditions were inserted.

MethodsWe examined 6 normal volunteers with functional magnetic resonance imaging (tMRI). All were right handedaccording to the Edinburgh inventory. They were asked to write their signature in space with the right indexfinger, in another scan with the big toe of the right foot. Control conditions were fingeropposition, foottappingand rest. Conditions were performed in random order. tMRI data were collected on a conventional 1.5T MRIscanner with a gradient ECHO sequence (TR= 100, TE=50, FA=40, voxel size 1x Ix10 mm). A transverse slice of10 mm thickness was positioned 50±4 mm above and parallel to the intercommissural line at the level of thehand field in the sensorimotor cortex. After movement correction and filtering with a Gaussian Kernel of 3x3x 10mm, statistically significant pixels (p<0.05) were identified using the general linear model and the theory ofGaussian random fields as it is implemented in the SPM96 Package (Functional Imaging Laboratory, London)(I). Comparisons were categorical (one condition versus another) and factorial (e.g. conditions with signatureversus movements without signature).

ResultsThe comparison foottapping versus rest showed activation in the supplementary motor area (SMA) andpostcentral sulcus in 4 subjects, but none in the sensorimotor cortex (SMC) and premotor cortex at hand level.Comparing fingeropposition versus rest, activation was found in the SMC in all subjects, in lateral premotorarea, SMA and postcentral sulcus in 5 subjects. Writing one's signature with either extremity activated lateralpremotor cortex in all subjects the SMA in 3 subjects. In the SMC and postcentral sulcus, activation was foundin all subjects when performing the signature with the hand, and in two subjects when writing with the foot. Thefactorial design 'conditions with signature versus movements without signature' showed activation of premotorcortex in all subjects and additional activation of the SMA and SMC in 2 subjects.

ConclusionIn the restricted area of investigation, the lateral premotor cortex at hand level was the area most consistentlyfound when writing one's signature either with the hand or with the foot. Therefore, it is concluded that this areais part of a representation for a highly automated movement of the hand, that can be recruited by anotherextremity, in this case the foot, when called upon.

References1. Friston KJ et al. Statistical parametric maps in functonal imaging: a general linear approach. Hum Brain Map,1995;2: 189-210

8229

POSTERS: MOTOR

Ipsilateral fM:RI Activation of the Human Sensorimotor Cortex ispredominantly Pre- and Postcentral, excluding the Central Region

A.C.Nirkko, C.Ozdoba, M.Wiesendanger, G.SchrothNeurology andNeuroradiology, University Hospital, CH-3010 Bern, Switzerland

Cortical activation during unilateral motor tasks is known to occur not only in the contralateral, but to a lesserdegree also in ipsilateral hemisphere, especially with left sided tasks in right-handed volunteers (I, 2).Although ipsilateral pyramidal tract projections exist to a small proportion, the functional significance of theipsilateral activation might differ from that of the contralateral side, where a major contribution by the primarysomatosensory cortex (SM1) to direct motor innervation can be expected. A different functional contributionmight reflect in a differint anatomical distribution of the activated areas in both hemispheres, which has notbeen compared yet.

Suhjects and MethodsWe used the blood oxygenation level dependent (BOLD) whole brain :fMRI technique to study simple (fingertapping) and complex (drawer pull! precision grip) manual tasks of both hands in healthy volunteers. Highresolution (1.56 x 1.56 x 4 mm) whole brain (30 slices) :fMRI was acquired using an echo planar imaging (BPI)sequence on a standard clinical 1.5 T medical scanner (Siemens Magnetom Vision). 64 whole brain image setswere aquired during alternating task (4 sets) and rest (4 sets) conditions in a total of6 minutes per experiment.For evaluation, z score maps were generated and overlaid onto the original EPI images for an exact match tothe underlying sulcus! gyrus anatomy, using self-developed software.

ResultsDurting unilateral motor hand tasks, we observed contralateral activationmainly in the primary somatosensory area (SM1) around the central sulcus.Especially in complex, but also in simple unilateral motor tasks, additionalactivation was demonstrated in frontal and parietal secondary areas aroundthe contralateral precentral and, even more, around the contralateralpostcentral sulcus. With complex tasks, the latter activity extended into theanterior part around the intraparietal sulcus (AIP). On the ipsilateral side,activation was located mainly around the precentral and around thepostcentral sulcus, with only minor ipsilateral activation at the central sulcus(SM1).

Fig. Contra- and ipsilateral activation during a manual motor task.

ConclusionsThe differing activation patterns in the contralateral and ipsilateral hemispheres indicate a different functionalcontribution to the motor tasks performed. The observed pattern is consistent with the direct efferent motoroutput required mainly in the contralateral, but not in the ipsilateral, primary sensorimotor cortex. Thesecondary pre- and postcentral areas seem to be responsible for the bilateral hemispheric activation observed inthe earlier studies (1,2).

References1. Kim S-G., Ashe J., Hendrich K., Ellermann lM., Merkle R., Ugurbil K., Georgopoulos AP., Science 1993,261:615-617.2. Li A., YetkinZ., CoxR., Haughton VM., AJNRAm. J. Neuroradiol. 1996,17:651-655.

supported by Swiss National Fund (NFP-38).

S230

POSTERS: MOTOR

Somatotopical organization of striatal activation during hand and toesmovements: A 3T tM.RI Study0

S. Lehericyl ,2, Po-F. Van de Moortele', E. Lobell, Ao-L. Paradis" M. Vidailhet'', Yo Agid3,

C. Marsault', D. Le Bihan l

lService Hospitalier Frederic Joliot, Department of Medical Research, CEA, Orsay,2Department of Neuroradiology and 3Neurology, Hopital de la Salpetriere, Paris, FRANCE

Introduction. In non-human primates, the basal ganglia are anatomically and functionally organized". On thebasis of cortico-striatal projections, the striatum is subdivided in several territories, the putamen being mainly thesensorimotor territory. The cortico-striatal motor projections are also somatotopically organized. The presentstudy aimed at determining whether a similar organization of the sensorimotor part of the striatum can beevidenced in humans using functional MRI.

Methods. Subjects: Ten right-handed volunteers were studied at 3T (Bruker whole-body system) using BOLDfMRI. Imaging: The MR protocol included: 1) 18 axial gradient echo EPI images (head coil,S mm no gap, TR:6000 msec, TE: 40 rnsec, bandwidth: 100kHz, a: 90°, FOV: 22 x 22 cm-, matrix size: 64 x 64); 2) 40 axialcontiguous inversion recovery 20 gradient echo images (2.5 mm thick reconstructed in 5 rom no gap, matrix size:256 x 256) for anatomical localization. Tasks: The tasks consisted of self-paced flexion / extension of the fingersor toes of the right and left sides successively The paradigm consisted of 6 epochs of 36 sec alternating rest andactivations. Analysis: After motion correction", data analysis was performed using a dedicated software writtenwith Interactive Data Language (RSI, Colorado) according to the following steps: 1) low-pass temporal filteringwith a gaussian kernel; 2) pixel by pixel autocorrelation' and cross-correlation with a reference waveform" of theMRI signal time course. Clusters of more than 3 contiguous pixels showing a correlation coefficient :2: 0.45 and anautocorrelation coefficient :2: 0.30 were retained as activated; 3) overlay of the activated pixels on anatomicalimages with a color scale representing the correlation coefficient, 4) calculation of the coordinates of the center ofeach activated pixel in the striatum (after correction for the difference between the acquisition and the AC-PCplanes) with respect to the anterior commissure - posterior commissure axis using multiplanar analysis of theanatomical images (Voxtool, General Electric, Milwaukee); 5) correction for intersubject variability of the size ofthe putamen.

Results. Activations were observed in the contralateral (and sometimes ipsilateral ) primary sensory-motorcortex, premotor cortex, supplementary motor area, temporal lobe, cerebellum, and thalamus. In the striatum, theputamen was activated in all subjects (contralateral hemisphere : 10110 subjects for the hand and toes; ipsilateralhemisphere: 6/10 and 4/10 for the hand and toes, respectively). The mean numbers of activated pixels in theputamen contralateral to the movements were 6.6 ± 1.6 (SEM) and 6.8 ± 1.1 for the fingers and toes,respectively. The caudate nucleus was only activated in three subjects, and with a smaller area. The globuspallidus was activated in 6/10 and 4/10 subjects for the hand and toes, respectively. Within the putamen, pixelsactivated during movements of the foot were located laterodorsally, compared to pixels activated during handmovements, with little overlap.

Conclusions. Motor activations were mainly found in the putamen. Within the putamen, pixels activated duringmovements of the foot tended to be dorsa-lateral as compared to pixels activated during movements of the hand.These data suggest that in humans, there is a segregation and somatotopical organization of corti co-striatalprojections similar to that observed in non-human primates.

References:1. Parent A and Hazrati L-N. Brain Res Rev 1995,20: 91-127.2. WoodsRPetal. J. ComputAssistTomog. 1992,16: 620-633.3. Paradis A-L et al. IEEE-EMBS, 18th Annual international conference, Amsterdam, 1996.4. Bandettini Pet al. Magn Res Moo 1993, 30: 161-173.

S231

POSTERS: MOTOR

The Motor Readiness Potential is Located in the Right Inferior Frontal Gyrus.A Combined PET and MEG Evaluation.

• t t t t··P. Johannsen, J.R. Pedersen, B. Kofoed, C. Bak, K. Saermark, A. GJedde .·PET-Center, Aarhus University Hospital, DK-8000 Aarhus C,

tDepartment ofPhysics, Technical University ofDenmark, DK-2800 Lyngby, DENMARK.e-mail: peter@tiger.pet.akh.arhusamt.dk

IntroductionAs early as 1200 ms prior to uncued voluntary finger movement, a negative electrical potential (the readinesspotential) can be registered over the frontal lobes with EEG. A similar magnetic field (readiness field) can bemeasured by magnetoencephalography MEG. Some researchers link the readiness potential/field to activity in thesupplementary motor area (1).

MethodsUsing MEG cerebral magnetic field recording, active sites were evaluated in four healthy right handed subjectsperforming uncued voluntary movements of the right index finger. Two participated in PET activation studies.MEG signals from 35 channel positions over the left hemisphere were recorded with a sample frequency of 500Hz using a 7-channel SQUID gradiometer, 0.3-50 Hz (BTi, SanDiego). Two-hundred epochs, lasting from 1.5 sbefore to 1 s after start of the movement, were averaged. After digital filtering (cutoff: 30 Hz), centers of magneticactive sites were determined with the MUSIC algorithm (2) which does not limit the number of sources that canbe identified with a time accuracy of 15 ms. With PET four tomograms were acquired at rest and during uncuedvoluntary movements of the right index finger. Relative CBF was measured with the ECAT Exact HR-47 PETcamera (Siernens/C'I'I, Knoxville). In 3D mode, acquisition of single 40 s or 60 s frames started at 60.000 cps(trues) after i.v. bolus injection of 500 MBq H2

150. Images were reconstructed with attenuation and scattercorrection and were filtered (Hann: cut off = 0.15) to 12 mm FWHM isotropic. The PET volumes were alignedand co-registered to each subject's T'I-weighted MR brain image and to the Talairach co-ordinate system (3). Ther-statistics were mapped after subtraction of resting from movement PET-volumes (4). Significance (P < 0.05) wasreached at t> 4.3 with cortex as search volume (500 cnr') (4). Using external oil capsules and the transformationscalculated above, MEG measurements were co-registered to the MR image and the Talairach co-ordinate system.

ResultsLocation and active time intervals of four sites common to the PET and MEG sessions listed by Talairach co­ordinates with Brodmann area (BA) and t-statistic. Time zero at start of movement. The vector lists the distancebetween the centers of MEG and PET sites. (L = left; RF = site of readiness field; SMA = supplementary motorarea; Ml = priman motor cortex).

L middle frontalgyms (RF)

Time(ms)

-700 to-250

Subiect A Male, 58 vearsMEG PET! Vector(BA) : (BA)t-va/ue : distance

-34,44,41 -36,36,24 19 mm(8) (9) t=2,5

Time(ms)

-900 to-250

Subiect B Female, 52 vearsMEG PET i Vector(BA) : (BA)t-va/ue : distance

24,47,33 -31,46,21 14 mm(9) (10) t=3,2

! -36,-18,46! -48,-19,56 16 mm! (4) ! (3) (=6,5

: -36,-12,46 i -48,-19,56 17 mm: (4) ! (3) t=6,5

L medial frontalgyms (SMA)

L precentral gyrus(premo tor area)

L precentral gyms(M] - hand area)

-300 to-100

-100 too

o to+100

-9,-9,57 -5,5,27(6) (6) t=4,]

i -39,-10,56 i -38,-2,59i (4) i (4/6) t=2,9 :i -45,-24,52! -40,-19,54: (3) i (4) t=3,3

14mm

8mm

7mm

-300 to-100

-100 too

-20 to+100

-7,-10,50 -8,-6,60(6) (6) t=4,4

11 mm

Discussion and conclusionThe study confirms the existence of a motor readiness field located anterior to the supplementary motor area.During voluntary uncued movements of the right index finger, the readiness field originates in the left middlefrontal gyms, with an average location of PET sites: Talairach x,y,z: -33,41,22; Brodmann area 9.

(1) Deecke L. Cognitive Brain Res. 1996; 3: 59-64.(2) Mosher JC, Lewis PS & Leahy RM. IEEE Trans. Biomed. Engineer. 1992; 39: 541-557(3) Collins DL., Neelin P., Peter TM., et al. 1. Comput. Assist. Tomogr. 1994; 18: 192-205.(4) Worsley KJ., Evans AC., Marret S., et al. J. Cereb. Blood Flow & Metab. 1992; 12: 900-918.

S232

POSTERS: MOTOR

A Simple FMRI Paradigm for Mapping theMajor Components of the Human Motor System

SCR Williams, A Simmons, M Samuel, MJ Brammer, ET Bullmore, LH Goldstein,CM Andrew, C Andrews, A Glover, MB Allin, DJ Brooks, PN Leigh

Institute ofPsy chiatry & MRC Clinical Sciences Centre, Hammersmith Hospital, London, UK.

IntroductionMost FMRI studies of brain activatio n during motor task performance have concentrated on localisation of theprimary motor cortex during, for exa mple, complex finger tapping tasks. Two rece nt abstracts have, however,reported consistent activation within the striatum using relatively sophistica ted paradigms including switching fromfinger tapping to toe-tipping and writing one's own name continuously on pape r whilst looking at the resulting text(l,2) . Our objective was to develop a simpler but equally robust task that activates the major compo nents of theextrapyramida l system with the intention of applying such a method to neuro log ical disorders invo lving motorimpairment.

Subjects and MethodsFive health y, right-handed male subjec ts (mean age 32 ± 3 years) were recruited for this study . A 1.5 T GE SignaMR system fitted with Advanced NMR EPI hardware and software was used. Fourteen, near-axial slices (7 mmthick, 0 .7 mm gap) were prescribed to encompass the whole brain. T

2' weighted gradient echo, echoplanar (EP)

images (TR=3 s, TE=40 ms, a=90°, 100 images/slice) were acquired for a total of 5 minutes for each FMRI study.Three separate studies were performed : (i) cued jo ystick movement repetitively to the left, (ii) cued joystickmovement alterna tely to the left then the right and (iii) cued joystick movement in freely selected directionsFor each paradigm, rest and motor conditions were alternated in a periodic fashion . Subjects were paced using anexterna l tone which sounded every second in combination with a projected scree n which switched every 30 seco ndsfrom continuous red (rest) to green (motor). Subjects were instructed to move the joystick with their right hand onhearing the tone and only when the scree n was green. A high reso lution, near- axial , inversion recovery EP image(TI= 180ms, TE=73ms, TR= 16s, 1.5mm in plane reso lution, 3mm slice thic kness with O.3mm gap, 8 sign alaverages) was also acqui red from each subject for subsequent anatomical registration. An automatic, 3-D techniquefor rigid body image registration and subsequent correction for variable spin history exc itation was applied to allMRI time series data(3). For derivation of a group averaged brain activation map for each task fro m the 5individuals, firstly. the power of periodic signal change at the fundam ental frequency of alterna tion between restand motor task perform ance was estimated by a pseud ogeneralised least squares fit of a sinusoida l regression modelto the motion correc ted time series. The fundamenta l power quotient (FPQ) was then estimated at each voxel of allimages . Each image was then randomly permuted 10 times and the subsequ ent FPQ estimated after eachpermutation(4). Th is resulted in 10 parametric maps of FPQ which were then regis tered with each subjec t's ownhigh resolut ion EP images as described previously(5) and then into the standard, stereotactic space of Talairach andTourn oux(6). Dat a were display ed for interpretation at a significance threshold of < 0.0005.

Results & ConclusionsOn investigation of the group averaged data , strong activation of the contralateral sensorimotor cortex, mesialfrontal cortex, prefrontal cortex and ipsilateral cerebellum was observed for all paradigms. Cons istent, contralateraldeep gray matter activation and ipsilateral prefrontal cortex was also observed in response to task (iii), the freeselection study. The areas of maximum BOLD signal response within the deep gray matter were shown to belocated within the basal ganglia but , due to the limitations of spatial resolution, and image distortion inherent with inour EPI methods, more precise localisation was not possible. Further, high resolution FMRI studies using task (iii)currently underway will allow us to more clearl y delineate the somatopy of the basal ganglia.

In conclusion, we have demonstrated consistent deep gray matter activation in the healthy human brain without theneed for intricate paradigms. The use of a joystick also affords quantitative measurements of response rate, accuracyand variance. We envisage such simple strategies will be directly applicable to many patient subgroups withmovement disorders.

References(l) Scholz V et al., NeuroImage, 1996; 3; 4 I I.(2) Scholz V et al., Neurolrnage, 1996 ; 3; 4 12.(3) Friston KJ et al., Magn. Reson. Med., 1996; 35; 246

(4) Bull more ET et al., Magn. Reson . Med ., 1996; 35 ; 261(5) Bramm er MJ et al., Neuroimage, 1996 ; 3; 54(6) Talairach J and Tourn oux P, 1988, Th ieme Verlag.

8233

POSTERS: MOTOR

Differential Evaluation offM:RI for Various Hand Movement Paradigms

c. X. Tan, R. L. Kamman, P. H. Mook, B. M. de Jong, H. DuifbuisCenter for Behavioral and Cognitive Neurosciences, Department ofRadiology

University ofGroningen, Groningen, The Netherlands

Introduction Previous fMRl demonstrated that the right primary motor cortex (PMC) was activated primarily bycontralateral finger movements, whereas the left PMC was activated by both ipsilateral and contralateralmovements[l]. Further study also showed that the bilateral supplementary motor area (SMA) and the premotor area(PA) were involved during imaginary hand movement[2]. In fMRl, the location of the activation is highly sensitiveto the characteristics of the activation paradigm and to the individual subject. Human hand movements arecontrolled by complicated neuro-network processes. Here we present several activation paradigms and a differentialparameter map to exclude some complications and to map the cortical areas.

Methods Functional images of five healthy right-handed subjects were acquired with multislice single-shotgradient-echo EPI using a 1.5 T whole body Siemens Vision system. Three slices of transverse brain images wereobtained (slice thickness 10 mm, in-plane resolution 1.56 x 1.56 mrrr' , FOV 200 x 200 mnr', echo time TE 66 ms).There were 96 time course images per slice with two cycles (12 resting images, 12 right hand activation images, 12resting images and 12 left hand activation images). During the activation periods, the volunteers were instructed todo following three activation paradigms (untrained) in a self-paced frequency of approx. 2 Hz: i) sequential tappingthe thumb with the four digits; ii) stretching of all five digits; iii) grasping a sponge with all five digits.Postprocessing using cross-correlation[3] to obtain the activated pixels from time course images of a) right handactivation vs. resting; b) left hand activation vs. resting, c) differential parameter map by student t-test from imagesof right hand activation vs. left hand activation. The confidence level in postprocessing strategy c was chosen bycomparison of the results from a and b.

Results and Discussion In all the three movement paradigms, activation was found in the contralateral PMC alongthe central sulcus. Comparing all slices, left hand activation had a wider extension along and posterior to the rightcentral sulcus, while right hand activation had more focused activation along the left central sulcus. The activationarea along the right central sulcus is approx. 30% to 90% larger (varying from subject to subject) than activation areaalong the left central sulcus, consistent with the nature of right handedness. We noted additional activation on SMA,PA and parietal areas. The areas commonly activated by either hand had been excluded by postprocessing strategy c(Figure I), leaving the activation areas that were involved in right hand movement per se plus left hand movementper se, and allowing direct comparison of the activation along the left and the right central sulcus. The differentialparameter map clearly showed the activation asymmetry in both hemispheres. For the three activation paradigms,fMRI differential parameter map showed similar activation along the central sulcus, which may suggest thoseactivations were from a cluster of muscles involved in all the three activation paradigms. We noted activationdifferences in areas other than along the central sulcus for the three paradigms. Some of those areas were able to beeliminated by postprocessing strategy c, proving they were involved in the activation of either hand.

Conclusions First, fMRl differential parameter map gave better contrast for the left and the right central sulcuswhich differentiate their activations. Second, the right and the left hand movements had asymmetric activation alongthe left and the right central sulcus. Third, fMRl of finger tapping, stretching and grasping showed similaractivations along the central sulcus at our image resolution.

Figure I. Differential (right hand vs. left hand) t map of slice 1 (activationparadigm ii).

References 1. Kim, S. et al. Science 261, 615-617 (1993)2. Rao, S. M. et al. Neurology 43, 2311 (1993)3. Strupp, 1. P. NeuroImage, 3(3):S607, June (1996)

S234

POSTERS: MOTOR

Motor cortex activation studies with a highly sensitive near infrared spectrometer

Willy N.J.M. Colier', Valentina Quaresima", Giovanna Barattelli",

Marco van der Sluijs", Berend Oeseburg! and Marco Ferrarr'

1 Department ofPhysiology and 3 Instrumentation Department, University ofNijmegen, The

Netherlands; 2 Dipartimento di Scienze e Tecnologie Biomediche, Universita L 'Aquila, Italy

Introduction: Near infrared spectroscopy (NIRS) has been used in cerebral functional activation studies to monitorchanges in concentration of oxy- and deoxy- hemoglobin ([02Hb] and [HHb] respectively). Previous studies wereperformed with a low time resolution (0.5-5 s) and a low signal-to-noise (SIN) ratio. An increase in [02Hb] wasfound by averaging the response of several subjects (up to 44), each response being the average of several motoractivation cycles (5-15) performed by each subject'. More recently, to overcome the limitations due to the poolingof the results from different subjects, a significant oxygenation change was reported for each subject averaging 5activation cycles". However, this procedure also cannot detect possible differences, occurring among the singleactivation periods. The aim of this study was to investigate single responses of the motor cortex region during afinger opposition task in individual subjects. To achieve this a novel NIRS instrument, with enhanced temporalresolution and SIN ratio, was used.

Methods: Six right-handed subjects performed 3 consecutive cycles of a sequential finger opposition task(duration: 20 s; rate: 2 Hz; rest period: 60 s). The measurements were performed with the OXYMON, a 3­wavelengths continuous wave NIRS instrument built by the University of Nijmegen. The optodes were positionedover the left motor cortex region using an inter-optode distance of3.5 em. The optode position was identified usingthe 10-20 system. The sampling frequency was 10 Hz. A pathlength factor of 6.0 was used in the data analysis.

Results: In all subjects oxygenation changes due to the finger opposition task were found. The high SIN ratio and10 Hz sampling frequency allowed clear monitoring of [02Hb] and [HHb] changes due to heart beat as well as torespiration. The figure shows the responses of 3 consecutive finger opposition cycles in one subject.

The hemodynamic responses for 3 consecutive finger opposition cycles in onesubject. Cycles lasted 20 s, followed by a 60 s rest period. It is obvious that thehemodynamic responses in the 2nd and 3rd cycle are less pronounced thanduring the first cycle. Units are in ).lM.

1.0

1.,

~[HHb)

0.'

1.0

1.'

-1.0

oo~,~/"-~-0.5

~

0.'

1.'

-1.0

1.0

0.'

1.0

1.5

~oov--..~ ...

-0.5

-1.0

0.0-,,· .•~\ ,....,

·0.' ...../"""

'l \,",,' ..,......~ ...

2nd cycle

.-...........\

0.'

.0.5 ~.¥.............

1st cycle

3rd cycle

1.0

1.0

1.,

1.'

1.0

_ ....,,,,'" ,\

\\.:,/ ;,.-0.5 -..,.

-0.5

-1.0

-1,0

-0.5

(l)Obrigetal. lAP, 1996,81:1174.(2) Hirth et al. NeuroRep, 1996, 7: 1977

Conclusion: To the best of our knowledgewe are the first to report oxygenationchanges in response to a single motorcortical activation cycle. Within the samesubject there were variations of the signalamplitude, although the time course of theresponse was similar over the 3 activationcycles. This could be attributable toseveral factors such as conditioning by theenvironment, postural changes etc.However, a single cycle is representativeof the phenomenon. The variability of thefinger opposition task responses indicatesthat reporting the results as a grandaverage is not sufficient to describe thephenomenon. In conclusion, these resultssuggest that ideal functional NIRS studiesshould be performed using very sensitiveinstruments capable of revealing the smalloxygenation changes after single brainactivation cycles.

This research was supported in part by EUcontract BMH4-CT96.1658 and by STW,The Netherlands.

S235

POSTERS: MOTOR

CEREBRAL ACTIVATION AND MOTOR TASK PERFORMANCEDURING EXTERNALLY TRIGGERED AND SELF-INITIATED

MOVEMENTI Gerdsen', J Schroder" S Frost" K Baudendistel'', M Essig2

, T .Iahn", F Wenz2,

A Linke}, MV Knopp' and LR Schad2

Dep. ofPsychiatry', Heidelberg University, FRG; German Cancer ResearchCenter', Heidelberg, FRG;University ofKonstanz', FRG

Introduction:Functional neuroimaging studies have so far produced much data on the cortical organisation of motorcenters. However, few studies have been addressed to the question of different motor sets, quantitativemodulation oflimb response and dynamics of movement.In the present study we investigated brain activation for externally triggered and self-initiatedmovements in healthy subjects. In addition, the quality of motor performance was monitored using anexternal device (2) during rotational hand movements (pronation/supination).

Methods:22 healthy, right-handed volunteers were included and divided into two groups. Brain activation wasmeasured using a 1.5T Siemens Magnetom fMRI (1). To monitor motor performance apronation/supination device (2) was adapted to the tMRI-environment. One group was asked topronate/supinate their forearm according to the pace given by a metronom (25, 50 and 75 strokes perminute). The other group received a short verbal instruction before the experiment to select speedaccording to the categories: slow, medium, as fast as possible.

Results:Analysis of motor performance: As to be expected increased velocity corresponded with higherfrequencies (df=2, F= 43.6, p<0.005). In contrast, the number of velocity and acceleration changesdecreased significantly with elevated speed (df=", F=28.5, p<0.005; and df=2, F=31.8, p<0.005,respectively) .Analysis ofcerebral activation: Higher speed led to a significantly increased activation of both, contra­and ipsilateral sensorimotor cortices (df=2, F= 8.7, p<0.005; df=2, F=4.9, p<0.05, respectively) andSMA (df=2; F= 6.9, p<0.005). When compared between externally triggered and self-initiatedconditions, externally triggered pronation/supination induced higher activation in the sensorimotorcortices and the SMA. However, this difference reached significance for the SMA only (df=l, F=4.6,p<0.05). No significant correlations between motor performance and any of the activation values werefound.

Conclusion:The present study revealed two major findings: (1) a demonstration that the activation of thesensorimotor cortices and of the SMA increases at higher speed; and (2) evidence that the SMA isactivated at a higher level during externally triggered compared to self-initiated movements.This data suggest that the SMA is involved in quantitative modulation of motor behaviour and thatexternally triggered events seem to require a higher amount of processing.

References:1. Baudendistel, K., Schad, L.R., Wenz, F., Essig, M.: Mag Res Imag 1996, 142. Jahn, T., Cohen, R., Mai , N., Ehrensperger, M., et al.: Z.klin Psycho) 1995, 24: 300-315

8236

POSTERS: MOTOR

Handedness and mirror activity:A prospective fMRI and EMG-study

Andreas Falk M.D.+, Herbert Friedrich Durwen M.D.*, GuidoMackowiak+, Ute Becker*, Edgar Miiller#, Lothar Heuser M.D.+,

Walter Gehlen M.D.*

+ Department (if Radiology & Nuclear Medicine, Knappschafts­Krankenhaus, Ruhr-University Bochum, Germany

* Department (ifNeurology, Knappschafts-Krankenhaus, Ruhr-UniversityBochum, Germany

It Medical Engineering Group, Siemenss Company, Erlangen, Germany

PURPOSE: Unilateral repetitive hand movements activate usually the contralateral motorcortex, which can be shown by fMRI. In some subjects a bilateral cortical activation of theprimary motor area can be observed.MATERIALS AND METHODS: 34 volunteers (19 riglu-z l l left-handers/4 ambidexter)had to carry out repetitive hand movements with the dominant rightlleft hand as well aswith the subdominant lefUright side. The fMRl was performed in EPT technique by use ofa commercial MRI unit.RESULTS: Bilateral cortical activation was found in fMRI in 6/19 right handers (31.6%)moving the dominant right hand in 12/19 subjects (63.2%) moving the subdominant lefthand, in the dominant left-hand group bilateral activation was seen in 8/11 cases (72.7%)for the left and 6/11 (54.7%) for the right subdominant hand. and in the ambidextrousgroup 2/4 (50%) vs. 3/4 (75% (right YS. left hand). The EMG recording of mirror activitywas found in 7/19 subjects (36.8%) using the right dominant and in 15/19 (78.9%) usingthe left subdominant hand, in the left-handed group in 9/ll (81.8%) using the left handYS. 7/11 (63.7%) using the right hand and in the ambidextrous group in 3/4 (75%) foreach hand side.CONCLUSION: Mirror activity in the EMG seems to be due to bilateral activation ofcerebral motor cortex observed in fMRI and is particularly associated with unilateral handmovements of the subdominant left side. No significant difference was found in the left­handed as well as ambidextrous group.References:1. Durwen HF, Herzog AG. Neurology 1985; 35(Suppl.l): 180.2. Durwen HF, Herzog AG. Brain Dysfunct 1992; 5:310-318.

8237

POSTERS: MOTOR

Handedness and Functional Lateralization within Cortical Motor AreasP Dassonville, X-H Zhu, K Ugurbil, S-G Kim, J Ashe

Brain Sciences Center, VAMC, Departments 0/Neurology, and Radiology and CMRR,University ofMinnesota, Minneapolis, MN 55417

IntroductionThe functional correlates of handedness within the human brain have not been extensively studied. One previousstudy has documented differences in functional activation of the motor cortex related to handedness (1). In thecurrent work we wanted to extend the investigation of relations to handedness to different cortical motor areas inthe frontal and parietal lobes .

MethodsWe studied 13 subjects (7 right-handed, 6 left-handed) during the performance of visually instructed sequentialfinger movement tasks with the right and left hand. We derived a laterality quotient for each subject on the basisof the Edinburgh inventory (2). MR images were obtained in a 4 Tesla whole body system equipped with anactively shielded head gradient coil insert and a quadrature head coil. Anatomical TI-weighted images of the wholebrain were obtained first. This volwne was subsequently imaged in the transverse plane with Tj-weighted EPI toprovide for accurate overlay of the functional images. During performance ofthe task. BOLD-based functional MR.images in the transverse plane were obtained with blipped EPI, with the total imaged volume extending from thesuperior pole of the cortex to a depth of 50 rom in 10 slices. The boundaries of the six cortical areas of interest[motor cortex, premotor cortex, supplementary motor area, pre-supplementary motor area, cingulate motor area,superior parietal lobule] were delineated in the EPI anatomical images using anatomical landmarks in the brains ofthe individual subjects. Finally, we calculated the volume ofactivation in the cortical motor areas contralateral andipsilateral to the moving hand. For the purposes of data analysis we defined functionallateralization as thedifference between ipsilateral and contralateral activation.

ResultsIn right handed subjects movement of the dominant hand was associated with a greater degree offunctionallateralization than movement of the non-dominant hand. By contrast there was no difference in the functionallateralization between dominant and non-dominant hands in the left handed subjects. There was a quantitativerelation between the difference in lateralization associated with use of the dominant and non-dominant hands andthe laterality quotient in both the right and left-handed subjects. However, this last relation was only significant inthe motor cortex.

ConclusionsThese data suggest that (i) the control ofdominant hand movement is fundamentally different in right and lefthanded subjects and this difference is reflected across all cortical motor areas, (ii) quantitative relations to thedegree of handedness were only seen in the motor cortex, which may be the most important structure in thedetermination of handedness in humans.

(1) Kim 5-G, Ashe J, Hendrich 1(, Ellerman 1M, Merkle H, Ugwbil 1(, Georgopoulos AP (1993) Functionalmagnetic resonance imaging of motor cortex: Hemispheric asymmetry and handedness. Science 261:615-617(2) Oldfield RC (1971) The assessment and analysis of handedness: The Edinburgh inventory.Neuropsychology 9:97-113

S238

POSTERS: MOTOR

Hemispheric asymmetry of hand movement representation inhuman motor cortex correlates with handedness

J. Volkmann, A. Schnitzler, O. W. Witte and H.-J. FreundDept. Neurology, Heinrich-Heine-University Dusseldorf, Germany

Introduction: Hand preference is the most prominent behavioral indicator for hemispheric specialization inhumans. About 90 % of humans are right-handed and therefore left-hemisphere dominant for manual skills.Using whole-head-magnetoencephalography (MEG) we investigated whether movement representation inhuman primary motor cortex (Ml ) differs between hemispheres and whether an effect of handedness can beobserved. Hemispheric asymmetries of motor output organization have been suggested by microstimulationstudies in monkeys, which have shown an enlargement and higher degree of spatial complexity of forelimbrepresentation in Ml opposite to the preferred hand (1).

Methods: Movement related neuromagnetic fields were recorded in ten healthy, male subjects (5 right­handers, age: 34.0±6.l years ; 5 left-banders, age: 28.2±2.5 years) for five different hand and finger movements(thumb flexion, index finger abduction, index finger extension, little finger abduction, wrist flexion). Allsubjects showed consistent hand preference in everyday activities as assessed by a handedness questionnaire (2)and compatible asymmetry of hand performance in a standardized hand dominance test (HDT) (3). Each subjectparticipated in three recording sessions on different days over a period ofthree weeks in which the sequence ofmovement conditions was randomized. A threshold detection of movement onset in the rectified surface EMGwas used to trigger off-line backaveraging of movement related fields. From the backaveraged waveforms wecomputed single equivalent dipole fits in a time window of 10 ms around the peak latency of the motor field(MF). The dipole solutions with the best goodness of fit (>0.9) around peak latencies were pooled acrossrecording sessions and used to compute mean and SD of dipole coordinates. For source localization a sphericalhead model was fitted to the individual MRI (Siemens-Magnetom" 1.5 Tesla, Tl-3D-Flash sequence) afteralignment of the MRI and MEG coordinate system based on fiducial point markers .

righthemispheredomin ance

lefthemispheredominance

right handdominance

r-,r'\. I.

.......1I," ~

-,

• "left hand

dominance

0.8

-0.8·0.4 -0.3 ·0.2 ·0,1 0 0.1 0.2 0.3 0.4

HDT (asymmetry index)

x 0.6

'"~ 0.4e-~ 0.2E~ 0..

.~ ·0.2s:a.

.~ ·0.4

'".t= .0.6

Results and Conclusions: Comparison of left- andright-handed subjects revealed a significant increase ofhand area size in primary motor cortex opposite to thepreferred hand. This expansion was due to increasedintersource distances in the dominant hemisphere. Meaneuclidian distances between dipole sources for differentmovements were 10.7±3 .5 mm in the dominant and9.5±3.5 mm in the non-dominant hemisphere (p==0.01 ,2-tai1ed t-test). The degree of hemispheric asymmetry ofhand area size in primary motor cortex was highlycorrelated with the asymmetry of hand performance in astandardized handedness test (r==-0.76, p==O.0082) (Fig. I) .The total number of pyramidal cells and therefore corticalsurface involved in each particular movement, however,did not differ between hemispheres as estimated frommagnetic source amplitudes. The expansion of hand motor representation in the dominant hemisphere maytherefore provide the neural substrate for the cortical encoding of a greater motor skill repertoire of the preferredhand.

References:1. Nuda, RJ, Jenkins, WM, Merzenich, MM, et al. J Neurosci. 1992, 12(8): 2918-2947.2 . Witelson, SF Brain . 1989, /12: 799-835 .3 . Jancke, L Perceptual and Motor Skills. 1996, 82: 735-738.

S239

POSTERS: MOTOR

Axis-orientation Discrimination System for Left Handin the right handed subjects

M. Taira*, R. Kawashima, K. Inoue, H. Fukuda

*lst. Department of Physiology, Nihon University School of Medicine, Tokyo, JAPAN,Department ofNuclear Medicine and Radiology, IDAC, Tohoku University, Sendai, JAPAN

In the previous study, we indicated that there are two separate systems for the axis-orientation discrimination, oneis for the visual control of the hand orienting movement in the left intraparietal cortex, the other is for theperception of axis-orientation in the right intraparietal cortex (l ). However, it is still unclear whether the leftintraparital cortex is specific for the right hand movement or not. The purpose of this study was to know whetherthe left intraparietal areas were also involved in the axis-orientation discrimination for left hand movement in theright handed subjects.

MethodsSix right-handed normal male volunteers participated in the study. Written informed consent was obtained fromeach subject. The regional cerebral blood flow (rCBF) was measured with a positron emission topography (PET)scanner (Shimadzu Headtome-Iv) and a bolus injection of approximately 40 mCi H2150. Each subject performedthe following four tasks during PET measurement: A: Hand-orientation (HO) task. The subjects reach the left handto insert into a slit varied its axis-orientation trial by trial. B: Control (HOctl) task for the HO task, C: Orientationdiscrimination (00) task, The subjects response to the matching stimuli that has same axis-orientation as thesample stimuli after appearing several non-matching stimuli. 0: Control (ODctl) task for the 00 task. All rCBFimages were transformed into the standard anatomical format using Human Brain Atlas system (2) and eachsubject's MRI. After the anatomical standardization procedure, subtractions of HOctl task from HO task andODcll task from 00 task were calculated for each subject on a voxel by voxel basis. Then, descriptive t-images ofHO task minus control (HO-HOctl) and 00 task minus control (OD-ODctl) were calculated to find significantchange.

ResultsThe HO task activated fields located in the left intraparietal sulcus, the left inferior frontal gyrus, the left lingualgyrus and the nucleus caudate. During the 00 task, fields of activation were found in the right intraparietal sulcus,the left superior occipital gyrus, the right superior parietal gyrus, the right superior frontal gyrus and the leftmiddle temporal gyrus.

ConclusionsOur results suggest that the left intraparietal areas may be involved in the axis-orientation discrimination for theleft hand movement of the right handed subjects and the right intraparietal areas may be involved in the axis­orientation discrimination for the perception. These results are almost same as our previous study. Kimura et al.(3) reported that the left hemisphere may playa more specific role to the control of hand movement than the righthemisphere. Thus the left intraparietal areas could be common for axis orientation discrimination in the right orleft hand movement of the right handed subject.

Referrences1. Taira M, Kawashima R, Inoue K, Fukuda H. Neuroimage 1996, 3:S297.2. Roland PE, Graufelds CJ, Wahlin J, et al. Human Brain Mapping. 1994, 1:173-184.3. Kimura 0, Archibald Y. Brain 1974, 337-350.

S240

POSTERS: MOTOR

Functional asymmetry of cortical motor control in left-handers

R. Kawashima, K. Inoue, K. Sato, H. Fukuda

Department of Nuclear Medicine and Radiology, IDAC, Tohoku University, Sendai, JAPAN

Handedness and hemispheric dominance are basic aspects of human motor function. However, little attention hasbeen paid for those of left-handers. We, therefore, used a positron emission tomography to investigate corticalmotor areas which are active in relation to unilateral dominant or non-dominant finger movements in left handedsubjects.

MethodsWe studied six normal male Isubjects to measure changes in regional cerebral blood flow (rCBF) associated withrepetitive flexion and extension movements of the index finger of unilateral or bilateral hand(s). We asked subjectsto pace their movement approximately once a second without any preceding cues with their eyes closed. After theanatomical standardization by HBA 1, percent change of relative rCBF between two globally normalized images(each movement task and control) were calculated for each subject. Then descriptive three-dimensional t-images ofeach movement task minus control was calculated. Voxels with t-values over 4.98 (p<O.005, after correction formultiple comparisons) were considered to represent regions of significantly changed rCBF. Since preciseanatomical localization was a key issue, the precision of the reformatation process was estimated on each subject'sanatomically standardized MRI.

ResultsTalairach coordinates and peak t-value of significant activation within motor areas are summarized in table I. Leftindex finger movements associated increases in rCBF in the right primary motor area (M I), the right premotor area(PMA) as well as the right supplementary motor area (SMA) when compared with control state in which we askedsubjects to hold their hands in pointing shape. Right finger movements associated increases in rCBF in the leftM I, the left PMA, the left SMA as well as in the right PMA. Bilateral finger movements associated increases inreBF bilaterally in those areas.

ConclusionsThere was a hemispheric asymmetry in the PMA during unilateral finger movements. In the left-handers, althoughmovement of both hands was simple and symmetric, they may have been a greater cerebral synaptic metabolicrequirement in order to move the non-dominant hand compare with the dominant hand, which in turn might beassociated with different hemispheric rCBF changes related to unilateral movement of either side. In other words,ipsilateral PMA activity may increase and be involved in the control of ipsilateral movements when left-handersmove their non-dominant (right) hand. Although, the hemispheric asymmetry was not evident in the MI and theSMA. Compared with previous human PET2 and fMRI3 studies, we conclude that functional organization ofhuman cortical motor areas for motor control may be different between left-handers and right-handers.

Referrences1. Roland, P.E. et al. Hum. Brain Map. 1994, 2: 1-12.2. Kawashima, R. et al. Brain Res. 1993,623:33-40.3. Kim, S.O. et al. Science 1993, 261:615-616.

Table I. Talairach coordinates (X,Y,Z) and t-value of peak activation

right Mlright PMAright SMAleft Mlleft PMAleft SMA

x44465-44-46-10-8

Y-1418-1412-18

Z53505853505361

Left9.86.66.7

8241

Ri ght Bilateral9.4

5.9 6.47. I

9.7 7.05.9 6.26.6 7.75.2 8.5

POSTERS: MOTOR

CEREBRAL ACTIVATION RELATED TO CHANGE IN BIMANUAL MOTOR RHYTHM

B.M. de Jong (1), A.T.M. Willemsen (2), A.M.J. Paans (2).

(1) Department ofNeurology, (2) PET Center,University Hospital Groningen, The Netherlands.

The cerebral organization of motor function maintains a segregated distribution of neuronalactivity related to planning and preparing the spatio-temporal components of movement. Inthis PET study we intended to identify cerebral regions involved in the change betweenbimanual motor programmes. To that end, rCBF measurements were performed whilesubjects had to execute specific motor tasks, constituted by similar movement elements ofeach single hand. Differences in rCBF were analysed by Statistical Parameter Mapping(SPM) [1], thus revealing foci of neuronal activation.

Methods.Experiment 1: Paced by a regular auditory signal, 8 normal subjects had to stretch and flexfingers in alternation. In condition A, both hands had to move in synchroneous phase,whereas in condition B, hand movements were made in counterphase. In addition, asecondary auditory signal was presented at irregular intervals, cueing subjects to make anextra movement. In condition C, subjects had to make the same movements as in either Aor B, whereas now the secondary signal indicated they had to switch between the twopatterns of movement. Each subject underwent 4 scans in balanced order, during whichcondition A and B were tested once, and C twice.Experiment 2: The same conditions were examined in 6 subjects, with the only differencethat in conditions A and B no extra movement was made on the irregular secondary signal.

Results.Experiment 1: Condition C contrasted to A and B showed activation (p<O.001, uncorrectedfor multiple comparisons) over:

(i) right medial prefrontal cortex (Talairach x,y,z 6,48,20; Z-score 3.5),(ii) right premotor cortex (22,12,48; Z-score 3.4),(iii) left posterior intraparietal sulcus (-28,-66,32; Z-score 3.4),(iv) right parieto-occipital sulcus (14,-88,32; Z-score 3.4).

Experiment 2: Comparing C with A and B revealed activation of predominantly (i) inferiorparietal lobe bilaterally (Z-score 3.5) and (ii) left posterior intraparietal sulcus (Z-score3.5), while minor activation was seen of (iii) right medial prefrontal cortex (Z-score 1.9).The latter two foci had similar positions as in experiment 1. Contrasting AB of experiment1 to AB of experiment 2, confirmed that inferior parietal lobe activation (Z-score 7.1) wasrelated to making an extra motor response.

Conclusion.Functional coherence between particularly right medial prefrontal and left posterior parietalcortex may reflect the cognitive process of retrieving and initiating [1,2] pre-organisedbimanual action, i.e., providing access to a specific motor programme.

Ref.[I] Friston, KJ., et al. Hum.Brain.Map. 1995,2: 189-210.[2] Kapur, S., et al. Neuroreport 1995; 6:1880-1884.[3] Bracewell, RM., et al. J.Neurophysioi. 1996; 76:1457-1464.

8242

POSTERS: MOTOR

Command related cortical topographic distribution ofquantitative EEG during attempted hand grip.

G.Wildschiodtz, S. Sefeldt", M. Nowak**, T.G. Bolwig, N.H. Secher*

Departments ofPsychiatry and Anaesthesia* and The Copenhagen Muscle ResearchCentre **, Rigshospitalet, Copenhagen, Denamark.

With the background of the indirect evidence to support a central nervous influence on the cardiovascularsystem during exercise, this study was performed to detect areas in the brain by the electroencephalographicactivation or deactivation responsible for planning of motion and perhaps also representing "central command"influence on the cardiovascular system. This influence is determined by feed-back and feed-forwardmechanisms (1) and regional anaesthesia of the working arm reduces the influence of afferent neural input.Until now no investigation has tried to determine the EEG correlate of "central command"

Subjects and methods8 young healthy subjects performed rhythmic handgrip before and after regional anaesthesia (Lidocaine) ofthe left arm. During these conditions and during rest quantitative topographic EEG (QTEEG) were performedusing FFT spectral analysis separating the activity in standard frequency bands (Spectrum 32, CadwellLaboratories). After transformation to Gausian distribution a calculation of the statistical probability maps waspetformed (2).

ResultsCardiovascular responses were according to reported values. The activation during excercise as defined byincrease in the Beta activity was not as clear as it is seen in the change in regional blood floow, and did notreach statistical significance. Dynamic handgrip of the right hand gave contralateral Beta activation in theposttempero-parietal region, the left hand gave more diffuse activation. After regional anaesthesia of the leftarm the Beta activation was only increased when attemting to use the left hand, but both Theta and Deltaactivity were increased generally, but only significantly in the occipital region.

ConclusionCommand related activation is not demonstrated as clear with QTEEG as with methods describing the regionalcerebral blood floow. It was not possible to define the localisation of the "central command" source. Thevariable results described after regional anaesthesia in other investigations could be explained by the diffuseEEG deactivation demonstrated by the increase of Theta and Delta activty. Higher resolution in thetopographical EEG using 64 or 128 electrodes should be tried.

References1. Kjeer, M., Secher, N.H. Sports Medicine. 1992, 13: 303-19.2. John, E.R. Am. J. EEG Tecnol. 1990,30: 251-66.

S243

POSTERS: MOTOR

Command related distribution of regional cerebral blood flowduring attempted handgrip

M. Nowak, K. S. Olsen", I. Law", S. Holm", O. B. Paulson", N. H. Seeber'

The Copenhagen Muscle Research Centre, Departments ofAnaesthesia', Neurology and ClinicalPhysiology", Rigshospitalet and Department ofAnaesthesia', Glostrup Hospital, University of

Copenhagen, Denmark

Objective: This study was performed to identify areas of the brain involved in planning of motion and maybe alsorepresenting "central command" influence on cardiovascular variables during exercise which are influenced both byfeed-back and feed-forward mechanisms ( 1). Regional anaesthesia of the working arm provides for attenuated influenceof afferent neural input.

Methods: 8 subjects performed static and 8 subjects rhythmic handgrip before and after regional anaesthesia of thearm and were exposed to post-exercise ischaemia and a cold pressor test. During these conditions, brain images wereacquired with a GE Advance PET scanner using H2

15Q as flow tracer. After alignment (2), statistical activation maps(3) of the brain (P<O.OO 1) were calculated from the images.

.~/J

--:.7/

/

Conclusions: Command related activation in the contralateral sensory-motor andsupplementary motor area as well as in the cerebellum was demonstrated forattempted handgrip as neural input from the working muscles was attenuated oreliminated. It remains unclear if these areas are responsible for the cardiovascularpressor responses (6) or if they only reflect motor activation.

Results: Cardiovascular responses were in line with reported values (4, 5). The adequacy of the arm block wasdemonstrated by greatly reduced cortical activation in response to the cold pressor test and to post-exercise muscleischaemia. Static handgrip predominantly activated the contralateral primary sensory-motor hand area. After regionalanaesthesia of the left arm, the response to right handgrip remained unchanged. There was a more markedcontralateral cerebral activation during left handgrip which also involved the supplementary motor area and in bothcases mainly ipsilateral activation of the cerebellum. Compared to statichandgrip, rhythmic handgrip caused a more pronounced contralateral activation(Fig. 1). After regional anaesthesia., the sizes of the activated areas did notchange, but during the attempted handgrip also the contralateral supplementarymotor area was included. Activation in the ipsilateral cerebellum was found in allcases but right handgrip before the block.

References:

1. Kjrer, M., Secher, N.H. Sports Medicine. 1992, 13: 303-19.

2. Woods, R.P., Cherry, S.R., Mazziotta, J.e. Journal of Computer AssistedTomography. 1992, 16: 620-33.

3.Friston, K.J. et al. Human Brain Mapping. 1995,2: 189-210.

4.Mitchell, J.H. et al. Journal of Physiology. 1989,413: 433-45.

5.J~rgensen, L.G. et al. American Journal of Physiology. 1993, 264: H553-9.

6.Cechetto, D.F., Saper, CiB, in Central Regulation of Autonomic Functions,Loewy, A.D., Spyer, K.M., Editors. 1990. p. 208-223.

Figure I: Orthogonal projections of thesignificantly activated voxels (Z>3.09,n=8) during rhythmic handgrip before(above) and after regional anaesthesia(below) compared to the respectivebaseline condition.

8244

POSTERS: MOTOR

Control of human precision grip studied with positron emission tomographyR. J. SeitzI , A. Backstrom-, K.-M. Stephan l, L. Tellmann-, H. Herzog-l, P. HoflichI ,

R. S. Johansson 2

1Dept. ofNeurology, Heinrich-Heine-University Dusseldorf, Dusseldorf, Germany, 2Dept. ofPhysiology, Umea University, Sweden, 3lnst. ofMedicine, Research Center Jiilich, Germany

IntroductionOne class of manipulative tasks concerns the handling of mechanically "stable" objects subject only to inertial andgravitational forces . In these tasks , subjects actively control all finger forces. The motor output is adapted to theobject's physical properties primarily based on memory information from previous manipulation (1). However,signals in tactile afferents are intermittently used to trigger corrective actions and to update the relevant memorysystems. A second prototypical clas s of manipulative tasks concerns the restrain of living objects that imposeunpredictable destabilizing forces to the grasp. In these tasks subjects reactively control the grasp forces not toloose the object based primarily on tactile afferent information about the load changes (2) . Little is known,however, about cerebral structures involved in force control during manipulation. Here, we use positron emissiontomography (PET) to reveal cerebral areas involved while humans perform active and reactive tasks that onaverage resulted in similar force outputs from a precision grip between the right index finger and thumb.

Materials and MethodsEight right-handed, Caucasian volunteers (25 to 52 years) were subjected to five test conditions with repetitivegrip force changes; three active ("A") and two reactive ("R") tasks. In the AC condition, subjects actively liftedand replaced a test object of constant weight, equivalent to 4 N force . In the AU and AP conditions they lifted theobject as in the AC condition, but its weight was changed between 2 Nand 6 N in an unpredictable and apredictable manner, respecti vely. In the reactive RC and RU conditions subjects restrained the object frommoving while the load force profiles generated by the subject in the AC and AU conditions, respectively, wereplayed back to the grasp through a force servo attached to the object. In the control condition, the subjects heldthe test object stationary against a maintained load corresponding to the average load force during the testconditions. For each PET scan, 40 mCi [ 150l-butanol were injected as intravenous bolus. Cerebral traceraccumulation data of 40 s were converted into rCBF-data (3). The reconstructed PET images had an in-planespatial resolution of 6 mm (FWHM). PET image analysis included pixel-by-pixel t map calculation, t­thre sholding corresponding to p<O.05 (uncorrected). and cluster analysis with clusters exceeding 17 pixels (4) .

ResultsCompared with constant holding, rCBF increases occurred in left motor and somatosensory cortex in the threeactive conditions. Lift s with unpredictable weight (AU) showed the largest increase in somatosensory cortex. Weobserved rCBF increases in right supplementary motor area in lifts with predictable weight (AC and AP), and inlateral premotor cortex in the AC condition. No significant rCBF increases occurred during the reactive task withconstant load force changes (RC) . In the reactive task with unpredictable loads (RU), there were modest rCBFincreases in left sensorimotor cortex, left secondary somatosensory area, and right supplementary motor area.

Significant mean rCBF increases in the dynamic test conditions compared to holding a maintained loadCon- Motor Somatosensory Secondary somato- Premotor Supplementaryditions cortex L cortex L sensory cortex L cortex L motor area RAC 16%, 2546mm 3 14%, 463mm3 19%, 1029mm 3 20%, 823mm 3

AP 28%,I183mm 3 24%, 874mm 3 29%, I466mm 3

AU 24%, nOmm 3 28% ,l235mm3

RCRU 8%. 386mm 3 15%. 900mm 3 21%. 437mm 3 19%. 772mm 3

ConclusionsThe control of the right-hand precision grip in self-paced lifting tasks appears to be highly dependent on neuralactivity in the contralateral motor and somatosensory cortex. The activation in the right supplementary motor areain lifts with predictable weight suggests that this area may playa role in anticipatory control of the motor outputfor objects' weight (I). Likewise the activation of the right supplementary motor area may be related tobihemispheric adjustments in these right-hand tasks . The reactive control tasks resulted in weaker rCBF increases.

References1. Johansson RS, Cole KJ (1994) Can J Physiol Pharmacol 72: 511-524; 2. Macefield VG et al. (1996) ExpBrain Res 108: 155-171; 3. Tellmann L et al. (1996) Eur J Nucl Med 9: 1237; 4. Seitz RJ et al. (1997) EJN 9:378 -389

8245

POSTERS: MOTOR

Pattern of !MRI Activation During a Manual Tracking TaskM. O. Russ", H. J. Wittsack, H. Lanfermann, F. E. Zanella

Institute f or Neuroradiology, "Clinic f or Neurology. 1. W Goethe-University, Frankfurt am Main, Germany

The aim of the study was to investigate the interaction of motor and visual cortical areas in the contro l oflocomotorfunctions. There have already been a number of fMRl studies examining activations either in the course of a simplemanual motor task or in response to visual stimulation, each conducted in isolation (1, 2). However, visuomotorcoordination as occurring in the course of natural movements does not lend itself to such a form of analysis. Wetherefore chose a tracking task in which varying visual input continuously influences motor reaction, and feedbackprocesses between vision and movement occur.

SubjectsThe subjects consisted of n=I4 healthy volunteers aged between 20 and 30 (11 female, 3 male). One subject wasleft-handed, while all others stated that they were right-handed. The majority were medical students or traineephysiotherapists. They received remuneration equivalent to $30.

MethodsThe conditions in terms of experimental design were Rest versus Control and Rest versus Tracking. During thetracking task, subjects had to follow the course of a target cursor moving irregularly on a horizontal plane byaligning it with an arrow which was moved by turning a stick (dia. 3 mm) held between thumb and forefinger. Themovement of the target cursor could be anticipated with the help of a running curve above the cursor . As subjectsturned the stick (12 using their right, 2 their left hand), the rotation movement was recorded by a PC, and reportedvia the LCD projection system as the arrow movement in the tracking task. In the control task, subjects simply hadto twiddle the stick to and fro without feedback. The monitor then showed just two arrows pointing left and right asinstruction. In the rest condition, only the word 'relax' was shown. Each set of test conditions was repeated threetimes (alternating with rest periods) in randomized order. A total of60 measurements (at intervals of 4 sees) with 15slices (5 mm) each were taken. Each condition lasted 40 seconds (5 studies Task, 5 studies Relax), total measuringtime equalling 240 sees. A 1.5 Tesla scanner (Siemens Magnetom Vision) with special EPl-equipment (GradientOverdrive) was used (EPI, matrix 128 x 128, pixel size 1.64 x 1.64 rom, TR = I ms, TE = 0.66 ms, FA = 90°, FOV= 210). Parametric maps were calculated using the STIMULATE program by J. Strupp, Medical School ofMinnesota, and the BRAINVOY AGER program of Rainer Goebel, MPI Brain Research, Frankfurt . All data werepreprocessed for motion correction , gaussian smoothing, and linear trend removal. Both correlation (auto- andcrosscorrelations) and t-test analysis were performed. Additionally, selected regions of interest were analyzed byplotting the signal time course and, statistically, by analysis of variance.

ResultsUnder the condition Control (tactile-motor, without visual feedback), consistentactivations in the sensorimotor cortex (contralateral emphasis) and in thecerebellum (ipsilateral emphasis) were apparent. During tracking, these are joinedby bilateral and more extended activations on both sides - parietal, frontal - inboth the SMA and the cingulum . Particularly striking under the tracking conditionare marked bilateral activations at the junction of the medial temporal gyrus andoccipital lobe, an area frequently referred to as MT or V5 (see figures: Activationpattern and corresponding signal time course of left and right MT combined).

ConclusionsWhen compared with simple, feedback-free twiddling movements, visuomotorcoordination during tracking activates far more extensive areas of the brain.Particularly marked activations in differential terms occurred in a region thatcould be identical to MTN5. Cerebellum activation seems to be ipsilateral,sensorimotor cortex activations contralateral, with each form especiallypronounced. The consistency of the findings across all subjects would appearto indicate that the tracking task has a very high degree of reliability wheninvestigating visuomotor coordination.

, ...~,~,~. --:,~, """"::,.""""",,""""",,""""",_, ...J

Tamec.ourH

ReferencesI .Frahm J., Merboldt KD., Hanicke W. Magn. Reson. Med. 1993,29: 139-44. I 2.Tootell RBH., et al. J. Neurosci. 1995, 15: 3215-3230.

S246

POSTERS: MOTOR

A PET study of processing visual feedback of own moving handduring visually guided reaching movements.

K.lnoue, R.Kawashima, K.Satoh, H.Fukuda

Department ofNuclear Medicine and Radiology, IDAC, Tohoku University, Sendai, Japan

To make accurate reaching movements with the arm ,complex neural transformations from visual andsomatosensory inputs through to motor outputs are required. In the present study, we investigated where in the

human brain visual feedback of hand movement was processed and utilized to make accurate pointing movements.

MethodsWe measured regional cerebral blood flow (rCBF) using positron emission tomography in nine right-handed

normal male volunteers. In all tasks, visual stimuli were presented to the subjects on the head mounted display

(HMO). All subjects performed a saccade (control) task and two reaching tasks with their right arm, a reaching

with visual feedback (RwithF) task and a reaching without visual feedback (RwithoutF) task. In the RwithF task,

the subjects monitored their moving hand near the targets as well as reaching targets (the sequence of LEDlighting) through a CCD camera. In the RwithoutF task, the subjects couldn't monitor their hand. In the lattertask,the sequence of LED lighting previously recorded on a videotape was presented on the HMD.A11 rCBF imageswere anatomically standardized I, then descriptive t-irnages of each task minus control and RwithF task minus

RwithoutF task were calculated. Voxels with t-values over 3.355 (p< O. 005) were considerd to represent regions ofsignificantly changed rCBF.

ResultsFigure I shows fields of significant activation in the RwithF minus control image (Fig. I , black and white).

Among these fields, supramarginal gyrus, posterior cingulate, premotor cortex and inferior temporal cortex of theleft hemisphere and thalamus, caudate and vermis of right hemisphere were also activated in the RwithF task

minus the RwithoutF task image (Fig. I, white).

ConclusionsIn this study,we have demonstrated fields of activation related to target reaching with the visual feedback from

the moving hand. The results indicate that the inferior parietal cortex ,the premotor cortex and the posteriorcingulate cortex of the left hemisphere of humans play inportant roles in integrating visual feedback from theirown movements and movement execution.

Reference1. Roland, P.E. et al. Hum. Brain. Map. 1994,2:1-12

Figure 1Z- - 13 Z= 1 Z=-23 Z-38 Z=48

8247

POSTERS: MOTOR

fMRI Study of Visually Guided Saccadic and Pursuit Eye MovementsL. Petit, J.E. Ingeholm, V.P. Clark, S. Courtney,

K. Keil, J. Maisog and J.V. HaxbyLaboratory ofBrain and Cognition, NIMH, Bethesda, Maryland, USA

Introduction. Most functional imaging studies of oculomotor functions have investigated the regions associatedwith horizontal saccadic eye movements. However, there are two components of the integrated system for gazecontrol, saccadic and pursuit eye movements. The goal of the present study was to investigate the functionalanatomy of these two systems using tMRI. A second goal was to test the possible existence of two functionalsubregions, one for the control of saccadic eye movements and another for pursuit eye movements, in each of theoculomotor regions.

Methods. Interleaved multi-slice gradient echo EPI scanning was used to obtain 8 series of 64 scans in 5 healthyvolunteers. Each scan consisted of 26 contiguous, 5-mm thick axial slices covering the entire brain (FOV = 24cm,TR = 3s, TE = 40ms, flip angle 90·). For each scan series, subjects performed six baseline-activation task cyclesconsisting of 15s of a control task followed by 15s of an oculomotor task. During the saccades task, subjects wereasked to execute saccadic eye movements toward a visual dot appearing at different eccentric positions on thehorizontal axis with a frequency of 2 Hz. During the pursuit task, subjects were asked to follow a visual dot startingat the primary central eye position and moving back and forth across the horizontal axis with a constant speed of25·Is and with a maximal amplitude of 12· on each side. During the control task, subjects were asked to keep theireyes open in total darkness and to avoid moving their eyes. Activity related to saccadic and pursuit eye movementswere analyzed independently, relative to activity during the baseline task, using an ANCOVA with a significancelevel of p < 0.0 I.

Results. The execution of both visually guided saccadic and pursuit eye movements induced bilateral activations inthe frontal and supplementary eye fields (FEF and SEF), in the intraparietal sulcus (IPS), in the posterior occipitalcortex (VIN2), in a lateral occipitotemporal region that corresponds to the V5/MT motion-sensitive area, and in thecerebellar vermis (VE) (Table 1). Saccade-related activations were of greater amplitude and spatial extent than werepursuit-related activations in FEF, SEF and IPS . By contrast, saccade-related activations were smaller in V5/MT. Inaddition, the mean location of the FEF pursuit-related region was more lateral and inferior than the location of theFEF saccade-related region. Such a distinction was less clear for the other activated regions. Figure 1 illustratesbilateral FEF, SEF and IPS activations in one subject.

Saccades Pu rsuitL,Ir'~R /r'~

SEE~' ~. .\ " :(, . \ SEFt ' \ ~ ~ ' FEFFEF~, -',' / <:.: ~'~Yi.I .~~ . FEF~ '! I

, ., ~. J I ·... J1~~,G:ilJrr.""'~' ~' t· ,-;T '

~ • . .~.!J I $ s : . I

'~---/ -' . .'/I~ IPS

Ta ble 1. F igure 1.

FEF SEF IPS VIN2 V5/MT VES I SA C • • • • • • • • • • • •

PUR • • • • • • • • • • •S2 SAC • • • • • • • • • • • •

PUR • • • • • • • • • • • •S3 SA C • • • • • • • • • • • •

PUR • • • • • • • • • •S4 SAC • • • • • • • • • • • •

P R • • • • • • •S5 SAC • • • • • • • • • • • •

PUR • • • • • • • • •(--) : bilateral activation; (- ): left activation; ( -): right activation L: left ; R: right

Conclusion. These findings extend previous functional imaging studies by providing evidence of specificactivation during pursuit eye movements in a set of regions known to subserve the control of saccades. Moreover,this study provides evidences that there are different subregions in the human FEF which are involved in theexecution of these two different types of eye movements. Finally, the smaller activation during pursuit performancemay reveal the existence of smaller pursuit-related regions in human FEF, SEF and IPS than the saccade-relatedregions, which is consistent with their relative sizes in the monkey .

8248

POSTERS: MOTOR

Cortical Networks for Visual-to-Motor Transformationsrevealed by Functional MRI in Humans

K. Dauchot l , J.L. Antoni, E. Guigon l , L. Pierot2, L. Spelle2, Y. Burnod l1. CREARE, UPMC. 9 Quai St Bernard, 75005 Paris , France . 2. Hopital Focn, Suresnes, France.

IntroductionElectrophysiological, metabolic . and modeling studies in monkeys reveal the networks and the operations performedby the populations of neurons in the cerebral cortex during visual-to-motor transformations (1,2) . We address thefunctional correspondence, beyond anatomical homologies, between active zones observed by fMRI in humans andpopulations of neurons studied in monkeys in similar tasks.

MethodsAxial MR images were acquired in seven normal right-handed subjects, using a standard 1.5T Signa (GEMS) with astandard head coil. Ten slices (5mm thickness) covered the active zones in the parietal and frontal cortices: z=15mmto 65mm, Talairach coordinates. Functional images (BPI sequence, TR=3s, TE=60ms, pixel size = 9.6mm2) wereacquired during four behavioral conditions related to visually guided reaching movements: a/ Saccades towardperipheral targets; b/ Right hand pointing with saccades; cl Right hand pointing without saccades; d/ Left handpointing without saccades. For each task, the paradigm (150 sec) was splitted into five periods (3xrest, 2xtask), therest condition being eye fixation on a central visual cross. Visual stimuli were projected on a vertical screen (1mfrom the subject's head), and viewed through a pair of mirrors . High resolution Tl-weighted images were used foranatomy. Data processing: compensation for the small head movements , comparison of different statistical methods(student t-test , correlation coefficient, conditioned analysis (3», clustering and double-thresholding, inter-subjectcomparison of extent and overlap of the active zones within each cortical region during different tasks (4).

ResultsA cortical network implied in visually guided reaching movements was revealed, with four main active zones (cffigure): I) the Pre-Central Zone at the intersection of the Superior Frontal and Pre-Central sulci (Brodmann areas 8and anterior 6); 2) the Central Zone around the Central Sulcus (Brodmann areas 4 and 6); 3) the Medial Zone(possibly SMA); and 4) the Parieto-Occipital Zone including part of the Superior Parietal Lobule , the posterior partof the Intraparietal Sulcus, and the Occipital Cortex. The activation in the Pre-Central Zone was similar and largelybilateral during saccades and pointing with or without saccades. The Central Zone was activated when the handmotricity was involved, contralateral for either hand pointing, and with possible ipsilateral extension for the non­dominant hand . The Parieto-Occipital Zone was activated during all four tasks; however this zone was more bilateraland extended in the saccade task, more unilateral (though not necessarily contralateral) in the pointing tasks.

ConclusionThese results show that a discrete network of cortical regions is involved in visual-to-motor transformations inhumans. For hand pointing movements, the network includes the posterior part of the parietal cortex, the premotorand motor areas; this network closely resembles the one known for monkeys (2). Further investigation should revealthe exact functions and anatomical locations of each activated regions.

(z=45mm)

I:Pre-Central Zone

2:Central Zone

3:Medial Zone

4:Parieto-OccipitalZone

at Saccades task , bl Right hand pointing with saccades cl Right hand pointing d/ Left hand pointing

References1. Burnod et al. J. Neurosci, 1992, 12:1435-1453;3. Benali H et al, IPMI ,I995:311-322, Dordretch;

2. Johnson et al. Cereb. Cortex, 1996,6:102-117.4. Anton JL et al, Neuro Report, 1996, 7:2849 - 2852.

8249

POSTERS: MOTOR

Sensitivity to movement rate and exposure duration of oculomotor systemactivation.

I. Law, C. Svarer, O. B. Paulson.The Neurobiology Research Unit, Rigshospitalet, Copenhagen, Denmark.

Introduction: The selection of experimental variables can have profound effects on the regional activationpatterns found by regional cerebral blood flow based techniques. The object of this study was to examine theeffects of movement rate and exposure duration of stimuli on the pattern of activation during the performance ofreflexive saccadic eye movements.

Methods: Thirteen normal subjects were scanned twelve times with repetitive injections of H2150 and Positron

Emission Tomography (GE advance) during the performance of reflexive saccadic eye movements tounpredictably appearing visual targets. The targets were presented with light emitting diodes on a perimeter arcwithin a visual field of _400 to 400. Two rates of eye movement were selected: 0.5 and 1.0 Hz each performed atfive target exposure duration's: 25 ms, 100 ms, 200 ms, 400 rns, and 800 ms. Additionally two resting conditionswith eyes closed were performed. Eye movement performance was measured by electrooculography. The data wasindividually aligned and analysed statistically using statistical parametric mapping (Hammersmith, UK, SPM95).

Results: I) Comparing the mean of all eye movement conditions with the mean of the two resting conditionsdisplayed significant activation in classically known oculomotor cortical areas: the frontal eye fields (FEF),supplementary eye fields (SEF), posterior parietal lobe (PPL), visual areas and the cerebellum. 2) Increasingmovement rate from 0.5 to 1.0 Hz activated the same areas, but to a lesser degree. 3) With increasing exposureduration regions in and around the calcarine sulcus was activated. 4) The most striking finding, however, was asignificant negative correlation with exposure duration in the FEP's, SEF's and PPL's identical to the areas definedin comparison I) , and the right dorsolateral prefrontal cortex (Fig. I) . The average increase in the right FEF (Z =4.4, P < 0.05, corrected) was 3.7 % ± 1.5 % (SD) at 25 ms and 1.7 % ± 1.5 % (SD) at 800 ms.

Discussion: The FEP's are not mere motor areas, but include functions involved in attention and visiospatial shortterm memory. The dependency on exposure duration of the activation of higher order cortical areas can behypothesised to arise from an increased demand during the encoding phase of a visual target of short exposureduration

Conclusion: In PET imaging the activation of the majority of components in the oculomotor system duringreflexive saccadic eye movements are influenced both by the selection of movement rates and exposure duration's.

egative correlation with exposure duration Saccades vs. Rest

- 10 4

sagittal:---~

t ro nsverse

cororiol sagittal coronal

Fig!: SPM {Z},s of significant activations (p < 0.0 I uncorrected) of comparison 4) (left) and comparison 1) (right)Each image is scaled to the maximal Z-value in each image.

S250

POSTERS: MOTOR

EXPLORING THE NEURAL BASIS OF VISUOMOTOR LEARNINGWITH PET AND ISO-LABELED H20

J. R. Moeller, C. Ghez, F. M. Ghilardi, D. Eidelberg*Columbia University and *North Shore University Hospital, Manhasset, New York

The execution of skilled limb movements is understood to require the cooperative contributions of multiple brainregions; and visuomotor learning, to be associated with both reorganization and changes in the interplay amongthese regions (I). Using positron emission tomography (PET) and 150-labeled H20, we have examined therelationship between the expression of specific movement-related brain networks and quantitative measurements ofthe accuracy of the execution and learning of control1ed motor tasks. By this means, we have sought to acquire newinformation concerning the neural basis for individual differences in motor performance in normal individuals.

Methods: We used 150-H20IPET (GE Advance , FWHM = 4.2mm) to measure regional blood flow (rCBF) duringthe performance of motor tasks matched in their kinematic and dynamic features (2) . Ten healthy, right handedsubjects (ages 23 to 55) each underwent a series of 90 second PET scans including three repetitions of each of twomotor learning tasks and a baseline motor task. In the baseline task (M I) subjects moved their dominant right handon a digitizing tablet out and back from a central location to equidistant targets in synchrony with a 1/s tone. In M 1,targets appeared predictably in a counter-clockwise sequence and were displayed, along with a cursor, on acomputer screen. We also studied new motor learning. Firstly, subjects were scanned while learning a visuomotortransformation (M2) where the same predictable targets were presented, but cursor motion was rotated by a fixedangle between 30-60°. In addition, we studied spatial sequence learning (M3) by changing the order of the targetsunpredictably. Within each 90 second scan , the subject had to discover and remember the new order of targets bytrial and error using visuospatial working memory. In M2, adaptation to the imposed rotation was recorded as aprogressive elimination of directional bias. In M3, learning was recorded as progressive increases in hit rate.

All images were smoothed, aligned and mapped into Talairach coordinate space (3). Both SPM t-rnaps ofANCOYA-normalized images (3) and t-profiles of a standardized set of ratio-normalized ROIs (4) were calculatedfrom the raw Ml, M2 and M3 images. In addition, subject subtraction profiles of ratio-normalized ROIs weresubmitted to the Scaled Subprofile Model(SSM) (5). Subject scores of the first 2 SSM principal components wereused to determine the statistical significance of the correlations between measures of motor learning and functionalregional activity. (An additional 150 -HzO/PET image (S) of the subject passively viewing a computer display oftargets and random cursor movements was subtracted from M I to confirm that the latter task provided acharacteristic motor baseline: significant activations were found in contralateral striatum, primary motor cortex (4),superior parietal lobe , and ipsilateral lateral cerebellum, and bilateral cerebellar vermis , SMA and occipital area 17(omnibus p < .(0 1)).

Results: SPM applied to the images of either learning condition minus the baseline motor task (i.e., M2-MI andM3-MI) were characterized by significant bilateral activations in cerebelIum, and contralateral activations inpremotor (6), lateral prefrontal (46 & 9: DLPFC), superior parietal (7) and visual association (19) areas (omnibus p= .05 and .01, respectively) . In the M3-M2 comparison, there was a statistical trend (p = .1) toward increasedactivation of homologous regions in the ipsilateral hemisphere in the novel sequence learning task. SSM analysis,however, revealed more substantial differences in the patterns of activation associated with the two forms oflearning. Individual differences in the rate at which directional bias decreased in M2 trials was significantlycorrelated (R t = .86, P < .001) with the expression of a regional covariance pattern characterized by relativeincreases in the contralateral SMA and medial prefrontal regions and a relative decrease in striatum. By contrast,subject differences in the rate at which accuracy increased in M3 trials was significantly correlated (W =.72, p <.00 1) with the expression of the covariance pattern with increased activation in ipsilateral hippocampus and relativedeactivations in striatum and prefrontal regions (46 & 9).

Conclusions: These results suggest that, even though the learning of visuomotor transformations and spatialsequences both utilize working memory, they each are mediated in part by different brain resources. Further, thesefindings provide the first evidence for the involvement of hippocampus in spatial learning of limb movements inhumans.

ReferencesI Georgopoulos, The Cognitive Neurosciences, Gazzaniga, M.S .(Ed), Cambridge, MA : MIT Press. 1994.507-5172 Ghez, C; et al., , Soc Neurosci Abstr 22, Part 2 (1996) 899.3 Friston, K.J., et al., Human Brain Mapping. 1995.2: 189-2104 Eidelberg, D., et al., J Cereb Blood Flow and Metab. 1994. 14: 783-801.5 Alexander, G.E ., Moeller, lR., Human Brain Mapping . 1994.2: 79-94.

S251

POSTERS: MOTOR

A comparison of externally and internally guided motor learningI. Toni, M. Krams, R.E. Passingham

WDCN, Institute of Neurology, London, U.K.

IntroductionIt has been suggested that the premotor cortex is especially involved in the learning of externally guidedmovements, and the supplementary motor cortex (SMA ) in the learning of internally generated movements (1) .This hypothesis is based on work with monkeys. We have now used PET to test this hypothesis. Subjects werescanned while they learned both a visual conditional motor task (external) or a motor sequence task (internal) . Scanswere taken both during four successive periods of learning .

MethodsIn the visual conditional task, the subjects had to learn by trial and error to associate each of 4 patterns withmovement of 1 of 4 fingers; on each trial a feedback cue informed the subjects whether the movement was correct ornot (as in ref. 2). In the sequence task, the subjects had to learn by trial and error - again using the feedback cues - asequence of finger movements, 8 moves long; visual patterns were presented on each trial to pace performance, butotherwise the patterns were not associated with particular finger movements. In the baseline condition, the subjectswere presented irrelevant visual patterns and feedback cues, but the subjects made no movements. For each task therewere 4 scans. Scan 1 was performed during initial learning, scan 2 after a further training period of 1 minute, scan 3after further training for 3 minutes, and scan 4 after further training for 5 minutes. Thus for both tasks, the first 2scans were acquired during initial learning, and the last two scans when the task had become overlearned. The datawere analysed using SPM96, and the anatomical coordinates were plotted using the template of the MontrealNeurological Institute.

ResultsDuring initial learning, the lateral premotor cortex was highly activated irrespective of whether the task was directedby external (conditional task) or internal cues (sequence task). In general, considering all 4 scans, the patterns ofactivation for cortical motor areas were similar for both tasks. However, the activation of the ipsilateral premotorcortex (38, -2, 56) decreased over the 4 scans for sequence learning but not for the conditional task. Furthermore,there was an increase in mes ial motor areas over the scans for both tasks. The SMA (-2, 0, 64) was more activatedduring overlearned performance in the sequence task but not in the visual conditional, whereas a cingulate motor area(-2,0,50) increased its activity during the visual conditional task but not the sequence task.

ConclusionsThe hypothesis was not confirmed. It did not predict the involvement of the lateral premotor cortex in initial learningof the sequence task (internal). However, the hypothesis was based on experiments in which monkeys with premotoror SMA lesions were tested during overlearned performance. The PET data suggests that the SMA is more robustlyactivated during overlearned performance of the sequence, and this finding is consistent with the animal data.However, to take into account the PET data on initial learning, it is necessary to revise the hypothesis. The datasuggests that the premotor cortex is more involved in closed loop control (as guided by external feedback cues) andthe SMA in open loop control (where the movements are internally determined).

References1. Pas singham, R.E. The Frontal Lobes and Voluntary Action , 1993, Oxford University Press2 Jenkins,I.H. et a1. J.Neurosci., 1994, 14, 3775-3790

8252

POSTERS: MOTOR

Neural mechanisms associated with the control of speech in man.K.Murphy, D.R.Corfield, G.R.Finks , R.J.S.Wise+, A.Guz & L.Adams

Department ofMedicine, Charing Cross and Westminster Medica l School, London, W6 8RF, UK,$Wellcome Department of Cognitive Neurology, London, UK & +MRC Cyclotron Unit, London ,

WJ20HS, UK.

Introduction. Speec h demands integrated co-ordination of respiratory , laryn geal and articulatory sys tems . Usi ngPET imaging , we have previously identified cerebral areas activated during volitional expiration ( 1). an essentia lelement of speech. We now wished to use these same techniques to study those areas responsib le for the motor co­ordi nation during speech.

Methods. Si x subjects were scanned, following intravenous injection of H2150 , dur ing repetiuon of the phrase

"b uy bobby a popp y" (requiring minima l language processing) performed in four different ways, spoken aloud (a).mouthed silently (b) , vocalised without articulation Cah-ahah-ah-ahah ') (c) and thought silently (d) . Respiration wasmonitored throughout the study.

Re sults. The expected modification of breathing was seen in conditions a and c and a resting breathing patterndur ing b and d . Statistical comparisons usin g SPM 95 (2) of a vs b (arti culation common) and of c vs d(articulation absent ) each highlight areas of the brain asso cia ted with control of breathin g for speech and vocalization;the combination of these two comparisons is shown in Figure IA. The results showed activation of superiortemporal areas. supplementary motor area (sma), thalamus, cere bellum and a stro ng bilateral activation of lateralsensorimotor cortex (smc l ). Similarly, com pariso n of a vs c (control of brea thing for speech and vocalizationcommon) and of b vs d (control of breath ing for speech and voca liza tion absent) eac h highlight areas associated wit harticulation alone; the co mbi nation of these compariso ns is shown in Figure! B. These result s show a large bilateralactivation (smc2) at a similar height to srnc I but more laterally sited . Th ere was no acti vation in "Broca's" area.

sagittal coronal

thalamus

cerebellum64

_~smc2

oL...- ~_....L-.-.L,;""""-............ -32

-104 6872 r--~.......,.......-:>"'""-=::-,....--,...--,

A

L...- ~_....L-~""""-............ -32Figure 1: SPM images (p<.OOI) A- Control of breathin g for speech and vocalization, B- Arti culation

B

Conclusion . Our find ings demonstrate two separate areas of the sensorimotor cortex bilaterally activated durin gcerebra l control of two eleme nts of "speaking" (without language), namely arti culation and contro l of breathing wi thvoca liza tion.

ReferencesI. Ram say, S.C ., Adams, L. , Murphy, K., Corfie ld, D.R., Grootoonk , S. , Bailey, D.L. , Frackowiak , R .S .l. ,& Guz, A. (1993) J. Physiol. 461 : 85-10 1.2. Fris ton, K.J . et at. (199 5) Hum an Brain Mapping 2: 189-2 10.

8253

POSTERS: MOTOR

Brainstem activation during tongue movement imaged with fMRI.D.R. Corfield, K. Murphy, O. Josephs#, G.R. Fink#,

R.S.J. Frackowiak#, L. Adams & R. Turners#Wellcome Department of Cognitive Neurology, Institute ofNeurology, London, UK and

Department ofMedicine, Charing Cross & Westminster Medical School, London W68RF, UK

Introduction. Functional imaging of the brainstem presents a particular challenge for fMRI because of technicaland physiological confounds. We have used voluntary movement of the tongue, which is controlled by motorneurons located in the hypoglossal nuclei of the medulla, as a paradigm to test the feasibility of such imaging.

Methods. Five subjects (aged 25-47, 1 female) were studied using a Siemens VISION scanner operating at 2Twith a gradient booster system and a head volume RF coil. Functional images were obtained with T2*-weightedEPI; each volume was acquired at a TR of 6.2 s (TE 40 ms) and consisted of 64 sequential transverse slices with anisotropic voxel resolution of 3mm and a matrix size of 64 x 64 pixels. During scanning, and in response toauditory cues, each subject performed 12 periods of 31s tongue movement alternated with 12 periods of 31s control.The tongue movement was designed to produce minimal displacement of the tongue or jaw and consisted of arhythmic (- 1 Hz) self-paced pushing of the tongue against the roof of the mouth and upper teeth. For the control,the tongue was relaxed in the same position. Data were analysed according to the General Linear Model withSPM96 (1). For each subject, images were realigned and spatially smoothed (FWHM 5.5 x 5.6 x 5.5 mm). Tominimise physiological noise, data were high pass filtered (cut-off 120s); alternatively, cardiac and respiratory datawere included as confounding effects of no interest within the statistical analysis (2). Statistical parametric maps ofsignificant signal change associated with tongue movement (p < 0.001, Z > 3.1) were generated for each individual.

Results. Significant signal foci were detected in the sensorimotor cortex, supplementary motor area, thalamus andcerebellum. In three subjects, significant foci of activation were identified in the lower brain stem (Z= 4.9, 6.6 &6.9). Qualitatively similar results were obtained using either method of physiological noise suppression.

brainstem

scnsori­motorcortex

thalamu s

Figure 1. Significant activation associated with tongue movement in one individual (shown on his T2* image).

Conclusion. Using a motor activation task we have been able to demonstrate significant signal changes withinthe brainstem that remain after the effects of movement and physiological noise have been minimised. This signal ismost likely to reflect neuronal activation within the hypoglossal motor nuclei.

Acknowledgement. We wish to thank Professor A. Guz for initially proposing this study and for his invaluableadvice throughout this work. D.R.C., 0.1., G.R.F., R.S.l.F. & R.T. are supported by the Wellcome Trust.

References1. Friston, K.l. et at. (1995) Human Brain Mapping. 2:189-210.2. Josephs, 0., Howseman, A.M., Friston, K., & Turner, R. (1996) Br. Chap. ISMRM. Abstract No. 27.

8254

POSTERS: MOTOR

Time-resolved FMRI Measurement of Brain Activityduring a Delayed Motor Task

W. Richter, P. Andersen, A. P. Georgopoulos', and S.-G. KimCenter for Magnetic Resonance Research, University ofMinnesota, Minneapolis, MN 55455

'Brain Sciences Center, Veterans Affairs Medical Center, Minneapolis, MN 55417

1. Introduction tMRI has been used in the past to map brain function by establishing steady state activity of thebrain during continuously repeated tasks. Thus it lacks information about the temporal evolution of neuralactivity during the performance of a single task. To test whether such temporal information may be obtained bytMRI, brain activity was measured during a delayed cued four-finger movement task. Single-neuron recordingstudies in monkeys have shown that primary motor cortex (MI), premotor cortex (PM), and supplementarymotor area (SMA) are active in movement preparation and movement execution in similar tasks; in hUIl(~ns,

however, several tMRI and positron emission tomographic (PET) studies have yielded contradictory results. '

2. Experimental MRI experiments were carried out with a whole body imaging system with a head gradientinsert. Axial slices for functional imaging were identified of the basis of known brain anatomy. Threecontiguous 10-mm thick slices containing the regions of interest (ROIs) were chosen. 183 single-shot blippedecho planar images were acquired (TE = 25 ms, TR = 196 ms, matrix size = 64x64, field of view = 24x24crrr). 9 normal volunteers were studied. Outlines of five white circles on a black background were shown; fourin a row (corresponding to the buttons on the keypad), and the fifth one in the center above this row. The fourcircles were sequentially filled in random order. After a variable delay period (0-7 seconds), the fiftp circle wasfilled (GO signal) and the subject executed the task by pressing the buttons in the prescribed order. The screenremained blank for the duration of the second control period. Each experiment lasted approximately 35 seconds.The absence of finger movement during the delay period was monitored by electromyography (EMG) of theextensor digitorum with surface electrodes.

The relative intensity change from baseline was integrated over the period from the commencement of thetask display until 13 seconds after the GO signal. ROIs were chosen based on both brain anatomy and functionalmaps. Time courses were generated using only pixels with the largest average activation within each ROI.

3. Results In the figure, single-trial time courses (7 seconds delay) for one subject are shown together with thetrace of the EMG recording. No movement is detected during the preparation period. There is activation in allthree areas during both the preparation and the execution periods. In SMA and PM, all subjects show activationduring both periods. The average peak intensity change in the SMA is (2.3 ± 0.8)% during preparation and (2.8± 0.6)% during execution. In the PM, it is (2.7 ± 0.5)% during preparation, and (3.3 ± 0.5)% during execution.In MI, seven of nine subjects show activation during the preparation period; the peak fractional intensity changeduring this period is (1.2 ± 1.1)% (n = 9), while all nine subjects show activation during the execution period(3.1 ± 1.2%).

4. Discussion In this experiment, tMRI providedtemporal information about neural processing and therelative roles of MI, PM, and SMA during movementpreparation and execution. In all three areas, activitywas present during movement preparation. Thisobservation agrees with neuronal recording studies inmonkeys, and some human studies. However, twosubjects showed no significant activation at all in MIduring movement preparation. This suggestsphysiological or neuropsychological differences betweensubjects; different subjects may use different strategiesto prepare for movement execution. The signalintensities in SMA and PM are only slightly lowerduring movement preparation than during movementexecution. Further studies are needed to investigate theexact roles, such as the contribution of motor vs.nonmotor components, of SMA and PM during thedelay period.

....c...c"~

i.~

.~..§,.;;;..c

~Er..

Time after commencement of display (s)

Single trial timecourses (7 seconds delay)

AcknowledgmentSupport by the NIH (Grants MH57180, RR08079, and NS 32919) is gratefully acknowledged.

References1. Kim, S.-G. et al., Int. J. of 1m. Sys. and Technol., 1995,6: 271-2792. Decety, 1. et al., Neuroreport 1992,3: 761-7643. Kim, S.-G. et al., Magn. Reson. Med. 1996,35: 895-9024. Kim, S.-G. et al., Magn. Reson. Med. (in press)

8255

POSTERS: MOTOR

fMRI Activation in a Human Lateral Parietal Area involved in Motor HandControl: Probable Homology to Secondary Somatosensory Cortex (8-11)

A.C.Nirkko, C.Ozdoba, O.Heid, G.Schroth, C.W.Hess, M.WiesendangerNeurology andNeuroradiology, University Hospital, CH-30JO Bern, Switzerland

Brain regions known to be involved in human motor control of the hand include the cerebellum, thalamus,basal ganglia and cortical areas, mainly the primary sensorimotor area (SM1), the supplementary motor area(SMA) and the premotor cortex. Neuroimaging methods, particularily positron emission tomography (PET)and functional magnetic resonance imaging (fMRI), have been successfully used to elucidate the function andlocation of these regions not only in group studies, but also in the human individual. From electrophysiologicstudies, additional areas - an anterior intraparietal area (AIP) and a secondary sensorimotor area (S-II) - areknown to be involved in motor functions (1), but no areas homologous to these have been demonstrated inhuman studies.

Subjects and MethodsWe used the blood oxygenation level dependent (BOLD) whole brain fMRI technique to study different self­paced manual simple (finger tapping) and complex (drawer pull / precision grip) manual tasks in healthyvolunteers. High resolution (1.56 x 1.56 x 4 mm) whole brain (30 slices) fMRI was acquired using an echoplanar imaging (EPI) sequence on a standard clinical 1.5 T medical scanner (Siemens Magnetom Vision). 64whole brain image sets were aquired during alternating task (4 sets) and rest (4 sets) conditions in a total of 6minutes per experiment. For evaluation, z score maps were generated after spatial filtering, using self­developed software. Activation maps were superimposed onto the original high-resolution fMRI image sets,avoiding spatial misregistration due to T2* distortions, thus allowing exact localization of activity to thecorresponding gyrallsulcal anatomy in each individual.

ResultsIn addition to visualization of activation in the above mentioned regions, wediscovered consistent activation in a previously undescribed, very lateralparietal area (LPA): the zone of activation is located just above the Sylvianfissure, between the postcentral gyrus and the supramarginal gyrus, andextends with a linear shape from near the surface of the convexity deeptowards the posterior part of the insular cortex (figure). The activation isclearly distinct from other areas, and in particular, is not continuous withthe more dorsomedially located activation at the postcentral sulcus posteriorto the SMI hand area. LPA activation is predominantly contralateral to thehand performing a motor task, but shows a significant degree of concurrentipsilateral activation. Activation is more intense with complex motor tasks,but is also present with simple finger tapping.

Fig. Activation in right lateral parietal area during complex hand activity.ConclusionsThe specific role of the LPA in motor control is not known. In some PET studies, activation around this area isdemonstrated, but has been interpreted as auditory cortex, possibly due to the necessary averaging and lowerresolution of the method. In fMRI, the region can be localized in each individual, and can be ascribed toparietal lobe: its location corresponds to the opercular part of Brodmann area 40 (Sarkissov, 1955). Possiblehomologies with the monkey S-I1 and AIP areas remain to be further investigated: altough the humanintraparietal sulcus anatomy differs from its monkey counterpart, the human area homologous to AIP morelikely corresponds to the anterior part of this sulcus, where we also see an activation during complex motortasks in our experiments. The LPA, therefore, might correspond to the S-II area.

References1. Mori, A., Babb RS., Waters RS., Asanuma H., Exp. Brain Res. 1985,58: 440-442.

supported by Swiss National Fund (NFP-38).

S256

POSTERS: MOTOR

Lateralization of Insular Cortex Activation DuringHigh and Low Intensity Dynamic Cycling Using SPECT

J.W. Williamson', R. McCoIF, D. Mathews', J.H. MitchelP

I Departments of Physical Therapy, 2Radiology, and the 3Moss Heart CenterUniversity of Texas Southwestern Medical Center, Dallas, Texas, U.S.A.

Introduction: The insular cortex has been implicated as an important cortical site for autonomic nervous regulation ofthe cardiovascular system (2,4). Previous work has shown left insular activation during mild dynamic exercise (I). Abradycardia and fall in blood pressure have been reported with left insular stimulation, conversely, stimulation of the rightinsular cortex elicited a tachycardia coupled with a rise in blood pressure (2). It has been proposed that the left insula maybe associated with cardiac parasympathetic activity while the right insula may be associated with increased sympatheticactivity. Exercise-induced elevations in heart rate up to approximately 100 beats per minute are due primarily to vagalwithdrawal, further increases are due primarily to an increased sympathetic activation (3). Our purpose was to determineif hemispheric differences exist for insular activation between low and high intensity exercise.

Methods: Three healthy, right handed, volunteers (age 24-32 yrs) were studied on three separate occasions and in arandom order during: I) seated rest on the semi-recumbent bicycle; 2) low intensity cycling (LIC) at approximately 10Watts; and 3) high intensity cycling (HIC) for which the resistance was increased to raise heart rate to approximately 160beats per minute. For each condition, relative regional cerebral blood flows (rCBF) were measured following i.v.injection of20 mCi ofTcYYm-ECD (Neurolite'") using a three headed scanner (Toshiba 9300A, Japan). Individual SPECTand MRI data from a 1.5 T machine (Gyroscan ACS-IIl, Philips Medical Systems, Shelton, CT) were coregistercd (AVS,Advanced Visual Systems, Waltham, MA) in three dimensions by computer. Volumes were normalized for whole braintotal counts for each subject and an ANOV A was used to determine significant differences for specific regions of interest(ROI). The ROI for each subject was selected using Z-maps to determine areas of brain activation. Once the ROI hadbeen positioned, counts were recorded for four consecutive brain slices for each condition. Percent changes inradioactivity from rest were also calculated for each subject.

Results: Data are presented as mean ±SD in the table and show significant increases (*; P < 0.05) in heart rate (HR),left insular cortex, and leg motor (M I) areas during low intensity cycling (LIC). Higher intensity cycling (HIC) elicitedincreases in HR, systolic blood pressure (SBP), diastolic blood pressure (DBP), mean arterial pressure (MAP), both leftand right insular cortices, and leg motor areas.

HR SBP DBP MAP Left Insula Right Insula Leg MI area(beats/min) (mmHg) (mmHg) (mmHg) (ROI counts) (ROI counts) (ROI counts)

Rest 61 ±S.7 120 ± 5.7 78 ±9.5 92 ±7.9 131 ± 4.2 132 ±7.1 153 ±IS.4

LIC 78 ±6.5 * 127 ± 7.7 76 ±9.2 93 ±7.3 144 ± 6.3* (10%) 137 ±9.5 (4%) 16S±21.7* (10%)

HIC 157 ±4.7 * 159 ±16.4* 99 ±7.5* 119 ±S.I* 145 ± 4.7* (II %) 152 ±7.4* (\5%) IS2±19.2* (\9%)

Summary & Conclusions: During LIC, with HR increased to almost SO beats/minute, there was a selective activationof the left insular cortex as well as leg motor sensory areas typically activated during leg exercise. During HIC, with HRelevated to approximately 160 beats/minute, both left and right insular cortices were activated as well as leg motor areas.These preliminary findings suggest that the left insula may be associated with cardiac vagal withdrawal during lowintensity dynamic exercise, while the right insula may be associated with an increased sympathetic activity during higherintensity dynamic exercise.

References:I. Nobrega, A.C.L., J.W. Williamson, R. McColl, et al. Human Brain Mapping [abst] SI-319, 1995.2. Oppenheimer, S.M., A. Gelb, J.P. Girvin & V.c. Hachinski. Neurology 42: 1727-1732, 1992.3. Robinson, B.F., S.E. Epstein, G.D. Beiser & E. Braunwald. Circulation Research 19: 400-411, 1966.4. Ruggerio, D.A., S. Mraovitch, A.R. Granata, et al. Journal a/Comparative Neurology 257: 189-207, 1987.

This work was supported by a Grant-in-Aid from The American Heart Association. Texas Affiliate, Inc.

S257

POSTERS: MOTOR

Thalamic activation during hand movements: A 3T!MRI Study.

s. Lehericyl,z, P.-F. Van de Moortele1, E. Lobel" A.-L. Paradis', M. Vidailhee, Y. Agid3

,

C. Marsaulr', D. Le Bihan1

IService Hospitalier Frederic Joliot, Department ofMedical Research, CEA, Orsay,Departments of 2Neuroradioiogy and 3Neurology, Hopital de la Salpetriere, Paris, FRANCE

Introduction. The thalamus is subdivided into several subterritories on the basis of cytoarchitectonic andconnections characteristics). The motor thalamus mainly consists of the ventral lateral and centre median areas.The motor thalamus is implicated in the pathophysiology of movements disorders, such as tremor or dystonia, andis the target of stereotaxic neurosurgery. The present study aimed at determining whether reliable activation couldbe evidenced in the thalamus during hand movements and its precise localization within the nucleus, in order toinvestigate the potential role of tMRr in the study of movement disorders

Methods. Subjects: Ten right-handed volunteers were studied at 3T (Broker whole-body system) using BOLDfMRI. Imaging: The MR protocol included: 1) 18 axial gradient echo EPI images (head coil, 5 mm no gap, TR:6000 msec, TE: 40 msec, bandwidth: 100kHz, a.: 90°, FOV: 22 x 22 ern", matrix size: 64 x 64); 3) 40 axialcontiguous inversion recovery 2D gradient echo images (2.5 mm thick no gap, matrix size: 256 x 256) foranatomical localization. Tasks: The task consisted of self-paced flexion / extension of the fingers of the righthand. The paradigm consisted of 6 epochs of 36 sec alternating rest and activation. Analysis: After motioncorrection', data analysis was performed using a dedicated software written with Interactive Data Language (RSI,Colorado) according to the following steps: 1) low-pass temporal filtering with a gaussian kernel; 2) pixel by pixelautocorrelation' and cross-correlation with a reference waveform" of the MRI signal time course. Clusters ofmore than 3 contiguous pixels showing a correlation coefficient?': 0.45 and an autocorrelation coefficient?': 0.30were retained as activated; 3) overlay of the activated pixels on anatomical images with a color scale representingthe correlation coefficient, 4) calculation of the coordinates of length, height and laterality of the center of eachactivated pixel in the thalamus contralateral to the hand movement as compared to the anterior commissure ­posterior commissure line (after correction for the difference between the acquisition and the AC-PC planes) usingmultiplanar analysis (Voxtool, General Electric, Milwaukee) of the anatomical images and comparison to the atlasof Hassler'; 5) correction of measurements for the width of the third ventricle, the height of the thalamus, and thelength ofthe AC-PC line to account for intersubject brain size variability.

Results. The thalamus was activated in 9/10 and 4/10 subjects in the hemisphere contralateral and ipsilateral tothe hand movements, respectively. The mean numbers of activated pixels in the thalamus contralateral to themovements was 6.1 ± 1.4 (SEM). Stereotaxic analysis of the location of each activated pixels in the thalamus inall subjects showed that these pixels were grouped into a region of the thalamus comprising the following nuclei(according to the terminology of Hassler'): ventral oral (Vo) and dorsal oral nuclei, ventral intermediate (Vim),central intermediate and dorsal intermediate nuclei, ventral caudal (Vc) and central caudal nuclei, central nucleus(Ce), medial nucleus (lateral part), nuclei intralaminaris and reticularis. More than 60% of the total number ofpixels activated in all subjects were found in the area of the Vo, Ce, Vim, and Vc nuclei (n = 10) which receivesnigral and pallidal (Vo, Ce), cerebellar (Vim) and lemniscal fibers (Vc),

Conclusions. Thalamic activations during hand movements were located within the ventro-lateral, ventralposterolateral, centromedian and medial nuclei of the thalamus, which are involved in the cortico-basal ganglia­thaiamo-cortical, lemnisco- or cerebello-thalamic circuitry". Further studies at higher spatial resolution are neededto determine more precisely the location of thalamic motor activations. These data also shows the potentiality offMRI to study the thalamus in patients with movement disorders.

References:I. Percheron et al.Brain Res. Rev. 1996,22: 93-181.2. Woods RP et aI. J. Comput Assist Tomog. 1992, 16: 620-633.3. Paradis A-L et al. IEEE-EMBS 18th Annual international conference, Amsterdam, 1996.4. Bandettini P et al. Magn Res Med 1993,30: 161-173.5. Hassler R. Atlas for Stereotaxy ofthe Human Brain. Stuttgart: Thieme; 1977. plates 23-55.6. Parent A and Hazrati L-N. Brain Res Rev 1995,20: 91-127.

S258

POSTERS: MOTOR

fMRI Activation of Basal Ganglia During Externally PacedSequences of Arm Movements

V. Menon, J. Johnson, K. O. Lim, G. H. Glover and A. Pfefferbaum

Departments of Psychiatry & Behavioral Sciences and Radiology,Stanford University School ofMedicine and VA Palo Alto Health Care System

The basal ganglia are known to be critically involved in the planning, control, elaboration and execution ofmovements. In recent years several PET studies have investigated the role of the basal ganglia in motor functionand dysfunction (I). tMRI, with its superior spatial resolution, is ideally suited to investigate the specificcontributions of the various nuclei of the basal ganglia (2). To date few studies have reported reliable tMRIactivation of the basal ganglia with tasks that can be manipulated along the motor and cognitive dimensions (1,3). In this study, we investigated tMRI activation of the basal ganglia during externally paced sequences of armmovements.

Methods

Twelve right-handed subjects performed an experiment consisting of 12 alternating 40s epochs of rest and amotor task. During the motor task, subjects continuously heard numbers between 1 and 4 (lSI = 2sec) and thenmade arm movements to corresponding labeled positions on a keypad starting from its base. tMRI images wereacquired on a conventional 1.5T scanner with a temporal resolution of 4s. Twelve axial slices (overlap acrosssubjects: -20 mm < z < 46mm in Talairach coordinates) were acquired with slice thickness of 6-7mm and in­plane resolution of 2.8mm. Images were normalized to Talairach coordinates and analyzed using SPM (4).Results reported here are for Z > 4.0 (p < 0.05, corrected for multiple comparisons).

Results

Figure 1: Multisubject average(N= 12) showing activation ofbasal ganglia nuclei.

Table 1: Activation of basalganglia nuclei across individualsubjects.

Subj. Put. GP Caud.

# L R L R L R

1 - - - -? - -~ x - x - - -

4 x - x - - -

'i x x x v y v

n x - x - -7 x - x v y

R x - x y y

<.) x - x - y

10 - - - - -11 x - x - y

1? x - x - - x

Z oO 2mm

2 " 14nwn

z .. 8mm1 - 6nvn

Z '" Omm

z .. 12mmz .. 10nvn

1 " 4rnm

z .. -2mmMultisubject averaging (n= 12)revealed significant foci ofactivation in the basal ganglia inaddition to the thalamus,cerebellum and a number ofneocortical regions. Within thebasal ganglia, distinct foci ofactivation were observed in theputamen (Put; L » R), leftglobus pallidus (GP) andcaudate nuclei (Caud; R > L)(Figure 1). Analysis of singlesubjects revealed consistentactivation of left putamen (9/12subjects) and left globuspallidus (9/12 subjects) (Table1).

Conclusions

Reliable tMRI activation of distinct foci in the putamen and globus pallidus was observed during externallypaced sequences of arm movements. In contrast, even complex sequences of finger movements do not result indetectable tMRI activatation of the basal ganglia. The present task design can be manipulated to help betterelucidate the functional role of the basal ganglia and to study motor and cognitive dysfunction in Parkinson'spatients (1, 3).

1. Brooks, DJ., Journal of Neurological Sciences. 1995, 128: 1-13.2. Bucher, SF., et al. Neurology. 1995,45: 180-182.3. Menon, V., et al. Society for Neuroscience Abs. 1996.4. Friston, KJ., et al. Human Brain Mapping. 1995,2: 189-210.

This work was supported by the Sinclair Fund, NIH (AA05965, MH30854, RR09784) and the Department of Veterans Affairs.

8259

POSTERS: MOTOR

Dissociation of neural correlates for motor executionand sensori-motor readiness within the cerebellum

Sakai K1), Takino R2), Hikosaka 0 1), Miyauchi S3), Sasaki y3),Piitz B3), Fujimaki N3)

1) Dept. ofPhysiology, Juntendo University, School of Medicine,2) Shiraume Gakuen College,

and 3) Communications Research Laboratories

Objective:The cerebellum is thought to playa key role in motor control, but its functional organization is still unclear. Here

we demonstrate that dissociated areas within the cerebellum are activated for motor execution and readiness for externalstimuli.

Methods:Six normal subjects participated in the study. The paradigm we used required the subjects to change motor actions

in response to auditory missing stimuli.Tone bursts were presented with a constant interval of 300 ms during the 'Constant' condition, and with random

omissions during the 'Miss' condition. These two conditions as well as the 'No-tone' condition were intermixed andrepeated four times. Two experiments were conducted, which required different responses to the missing stimuli. In the"No-go on Miss", the subjects were required to tap the right index fingers in response to the tones and withhold tappingon missing stimuli. In the "Go on Miss", the subjects tapped their fingers only on missing. Additional experimentswere conducted using predictable missing stimuli (missing stimuli came with a constant interval so that the subjectscould predict them).

In each experiment, a time series of 122 scans was performed using a 1.5T whole body scanner. In each scan, 10axial slices (7mm/slice) encompassing the cerebellum were obtained using a T2*-weighted gradient-echo echo-planarimaging sequence (TR/TE/FA: 0.96/ 66/ 90, FaV: 256x256, matrix: 128xI28). After motion correction, cross­correlation of the SIs with the reference function derived from the task sequence was calculated, and activation foci weredetermined as pixels with correlation coefficient above OJ (P<0.005).

Results:Comparison of 'Constant' with 'No-tone' revealed a single area of activation within the anterior lobe of the

cerebellum (H IV-V) ipsilateral to the finger movement (Fig A). Comparison of the 'Miss' with 'No-tone' disclosed twoadditional activation foci symmetrically located within the crus I of the ansiform lobules (H VII A) both in "No-go onMiss" and "Go on Miss" (Fig B and C). When the missing was predictable, the activation within the ansiform lobulesmarkedly decreased, while that within the anterior lobe remained unchanged.

(A) (B) (C)Images were obtained by comparing 'Constant'(A), 'No-go on Miss'(B), and 'Go on Miss'(C) with 'No-tone'.

ConclusionPresence of the ipsilateral anterior lobe activation even in constant tapping indicates that its functional role is

motor execution per se. In contrast, activation of the bilateral ansiform lobules is related to the change in motorresponse irrespective of 'No-go' or 'Go'. Decreased ansiform lobule activation in predictable missing condition suggeststhat the activation is related to unpredictiveness of external stimuli, the situation in which the subjects are always readyto change motor responses. We concluded that the motor execution and sensori-motor readiness are subserved within thedifferent areas of the cerebellum.

S260

POSTERS: MOTOR

High and Low Frequency Movements ActivateDistinct Areas within the Human Anterior Cerebellum:

A High-Resolution Functional MRI Study

M.F. Nitschkel , U. Melchert2, C. Hahn3, H. Handels3 , P. Trtilenbergt, K. Wesse(lDepartment ofNeurology', Radiology', andMedical Informatics';

Medical University ofLuebeck, Germany

Introduction: Previous functional MRI and PET studies on the organization of the cerebellum revealedactivation within the ipsilateral anterior lobe during hand and finger movements (1,2). These studies mainlyfocused on movements performed with a frequency of about 1 Hz. Examination of the sensorimotor cortexand SMA revealed distinct activation patterns with regard to the frequency of the movements (3,4). Thepurpose of this study was to use functional MRI, sensitized to changes in cerebral blood oxygenation,(BOLD; Blood Oxygenation Level Dependent), to map cerebellar representation of externally pacedvoluntary motor movements with low and high frequency performance.

Methods and Subjects: Functional mapping at 1.5-T (Siemens Magnetom, standard headcoil) was basedon dynamic acquisition of CBO changes (rf-spoiled FLASH, TRfTE/flip angle = 62.5 ms/30 ms/lO°, slicethickness 4 mm, measuring time 6 s, FOV 200x200 mm", pixel-size 0.78xO.78 mm"; provided by Dr.Frahm, Gottingen, Germany) in multiple sections parallel to the tentorium covering the anterior lobe (5).Each dynamic series comprised six cycles of task performance (18 s) and rest (36 s). Seven right-handedhealthy volunteers were studied for extension and flexion of the right hand at externally paced frequenciesof 0.6 or 2 Hz. Motor performance was triggered by light diode flashing at the particular frequency. Themap of activation was determined by correlating MRI pixel intensity time courses with an external referencewaveform equivalent to the stimulus protocol. Resulting maps of correlation coefficients were thresholded,color-coded, and superimposed onto corresponding anatomic images. Statistical significance wasdetermined by analyzing corresponding p-values.

Results: All subjects showed task-related activation within an ipsilateral region of the anterior cerebellum.Performing the slow frequency motor task (0.6 Hz) activation was mainly located in the intermediatehemispheric portion of Larsell lobule H IV-V. Movements with a higher frequency (2 Hz) in additionactivated an ipsilateral area, which was distinct and located anterior to the above mentioned region.

Conclusion: Ipsilateral activation of the anterior lobe of the cerebellum during hand movements, located inLarsell lobules H IV-V, is well established and the activation pattern revealed by slower frequencymovements corresponds to a more posteriorly located region in this area. High frequency movements inaddition activated an area, which was distinct and located more anterior in Larsell lobules H IV-V. Thiscould be due to additional recruitment of shorter more anterior located parallel fibers that might code forhigher frequency movements as hypothesized by Braitenberg et al. (6)

References:1. Ellermann 1M et al. NMR Biomed 1994;7:63-8.2. Nitschke MF et al. Brain 1996;119:1023-1029.3. Rao SM et al. Neurology 1993; 43:2311-2318.4. Sadato et al. Ann NeurolI994;36:323.5. Frahm J et al. NMR Biomed. 1994,7:45-536. Braitenberg et al. Behavioral and Brain Sciences, to appear 1997

8261

POSTERS: MOTOR

Cerebellar and basal ganglia activation during visually guidedand memory guided movements

M. Krams, P.L. Strick*, R.E. PassinghamWellcome Department ofCognitive Neurology, Institute ofNeurology, London, UK

* VA Med. Ctr. & SUNY-HSC, Syracuse, NY, USA

IntroductionSingle cell recordings in monkeys have shown that there are task dependent neurons in the basal ganglia andcerebellar dentate nuclei during visually guided and memory guided movements (I). We used PET to scan humansubjects while they performed the same tasks.

MethodsWe scanned 14 right handed normal subjects with H2150-PET. The data were analyzed with SPM 96 (MNI space)

and the activation scans (p<O.OOI) were coregistered with MRI structural scans. Four conditions were each repeatedthree times. In all conditions the subjects viewed seven circles arranged in a heptagon on a touch screen.A 'Remember and repeat forwards': Sequences of 5 circles were presented, each circle lighting up for 600ms. After a delay period of 1.5 s, a brief tone instructed subjects to touch the circles that had lit up in their correctorder, doing so as quickly as possible and with their right index finger. After an interval of 3.5 s a new sequencewas presented.B 'Remember and repeat backwards' : This condition was as for A, except that the subjects were required torepeat the sequence in reverse order.C 'Visually guided tracking' : As in A and B sequences of 5 circles were presented, but the subjects touchedeach circle as it lit up.D 'Baseline': This condition was as for C, except that the subjects were instructed to follow the circles withtheir eyes, but not to make any movements.

ResultsMemory conditionsI) Comparing memory guided with visually guided movements (A v C, B v C), there were activations in the leftanterior putamen (A v C: -26, +16, +04 ; B v C: -30, +16, +02) , and right cerebellar hemisphere. Comparingbackwards repetition with visual tracking (B v C), there was also an activation in the cerebellar nuclei bilaterally.2) Comparing backwards repetition with forwards repetition (B v A), there was a small peak in the right cerebellarnuclei (+12, -56, -38).3) Comparing backwards repetition with visual tracking (B v C) there was also activation inthe dorsal prefrontal cortex (-46, +14 , +38); there was only a trend for activation (p<O.OI) for forwards repetition(A v C) . Other activations will be reported elsewhere .

Visually ~uided trackinl:I) Comparing visually guided tracking with the memory conditions, there was an activation in the right inferiorcerebellar hemisphere (+34, -78, -40). 2) Compared with baseline, the right cerebellar vermis and left cerebellarhemisphere (anterior lobe) were strongly activated in visual tracking (C v D), as also in the memory conditions(A v D, B v D). The cerebellar nuclei were activated (C v D), but with lower z scores than for the memoryconditions. 3) Comparing visual tracking with baseline (C v D), there was a trend for activation in the putamen(-22, +02 , 00) (p<O.OI), at a more posterior site than the activation for the memory conditions (A v C, A v D,B v C, B v D).

DiscussionI) Both basal ganglia and cerebellum were activated during movements whether guided by vision or memory. 2) Inthe basal ganglia, the putamen was activated more anteriorly for memory guided than visually guided movements.3) Backwards repetition makes demands on the manipulation of information in memory, and it was particularlyassociated with activation of the dorsal prefrontal cortex and the cerebellar nuclei. 4) These results suggest that inboth structures, circuitry is involved whether the movements are guided by internal or external cues.

REFERENCES1. Mushiake H, Strick, PL (1995) Pallidal Neuron Activity During Sequential Arm Movements. J Neurophysiol,74:2754-2758

S262

POSTERS: MOTOR

Assessment of Human Red Nucleus Activation with fMRIYi-Jun Liu':', Yong-Lin Pu', Jia-Hong Gaol, Peter T. Fox'

'Researcb Imaging Center, "Department ofPhysiologyUniversity ofTexas Health Science Center, San Antonio, TX

Introduction The objective of this study was to use tMRI as a noninvasive tool to detect the activation ofhuman red nuclei during sensorimotor tasks. We used a conventional gradient-echo sequence, which was sensitiveto activity-related local changes of blood flow and oxygenation. Recent studies using tMRI and PET techniqueshave implicated neocerebellum in sensory discrimination using healthy human subjects (1) and abnormal activationof the red nuclei in palatal myoclonus (2) and in essential tremor patients (3). The development of the parvicellulardivision of the red nucleus (the bulk of the human red nucleus) parallels the growth of the dentate nucleus, however,little is known about its functional role (4). Our study is the first to demonstrate extensive activation of the rednuclei during finger movement and sensory discrimination in healthy human subjects.

Methods Six healthy right-handed volunteers (25 - 43 yrs) participated in this study. Each volunteer waspositioned supine inside the magnet of a 1.9 T Elscint PRESTIGE MRI system. A polarized circular head coil wasused for RF transmission and MRI signal reception. Head fixation was accomplished using a facial mask. The rednucleus in the mid-brain was identified by its low signal intensity on a T2 scout image. A single coronal slice (5mm thickness) through the centers of the red nuclei and the primary motor cortex was selected for high resolutionfunctional imaging with a T2*-weighted gradient echo sequence (TRffE/8 == 60 ms/40 ms/20o; 1 mm by I mm in­plane spatial resolution and 12 sec scan time per image). The tMRI scans were performed for three cycles. Eachcycle included three states: rest , grasp objects (GO) task and grasped object discrimination (GOD) task (1), with a 30sec interval between each state. Fifteen images were acquired for each state. A group t test, comparing the task­induced MR signal changes relative to the rest baseline, was performed on these images for each task. Only pixelswith a significant activation (p < 0.05) were used to create the functional map, which was overlayed on the T2*­weighted image to anatomically illustrate activation sites.

Results and Discussion Figure 1 shows typical tMRI images for one subject. The images show extensiveactivation of the red nuclei during a finger discrimination task (B) which may require rapid coordinated fingermovement and sensory discrimination, and much less activation during a similar movement task (A). Aconcomitant increase in activation in the motor cortex for the finger discrimination task was also apparent. Boththe activation area and the relative MR signal changes in the red nuclei were significantly larger in the GOD taskthan in the GO task across the six participants (Figure 2).

Fig.l Functional MRI (bright) overlaid on anatomical MRI,showing activation for (A) GO, and (B) GOD task.

Fig.2 Comparision of activation strength (GO vs. GOD).

o

I.10

-70] 60->0g .aS )()e 20< 10

o

(A) Fig. 1 (B) Fig. 2

Conclusions The results of our study indicated that red nuclei were involved in the control of coordinatedmovement and may playa role in sensory discrimination. To differentiate the role of the red nuclei in the wholesensorimotor system will require further activation studies using purely sensory tasks.

Reference(1) Gao, J-H., et al, Science 272: 545 - 547 (1996).(2) Boecker, H., et a1. NMR in Biomed. 11: 325 - 329 (1994).(3) Wills, AJ, et aI. Annals of Neurology 36 (4): 636 -642 (1994).(4) Keifer, J., Houk, Je., Physiology Rev. 74: 509 - 542 (1994).

8263

POSTERS: MOTOR

The Spatial Distribution of the Cortical Motor Potentials andGenerators Change After Spinal Cord Injury

Joseph B. Green, Yolanda Bialy, Elena Sora, Anthony Ricamato andRobert W. Thatcher

Rehabilitation Research and Development Center,Hines Veterans Affairs Hospital and Research Service,

Bay Pines Department of Veterans Affairs Medical Center andDepartment ofNeurology, Loyola-Stritch School ofMedicine, Hines, Illinois, U.S.A.

Our objective was to detect reorganization ofcortical motor control brought about by disconnection from afferent neuralinput from the spinal cord. We applied 128 electrode high resolution electroencephalography (Neuroscan) to record andmap the motor potentials (MP's) associated with finger and toe movements in 15 normal subjects and 10 patientsrendered weak or paralyzed from spinal cord injury (SCI). Equivalent dipole source analysis and co-registration withMagnetic Resonance Images (MRI) was accomplished using the "CURRY" software program (current reconstructionwith EEG, Phillips).

Controls and patients were instructed to perform self paced finger or toe movements every six to ten seconds; responseswere recorded in blocks of70 and the averager triggered by an EMU signal or if the subject were paralyzed, attemptsat movement were cued by avisual pattern reversal stimulus which also triggered the averager.

Paraparetics or quadriparetics who had retained or regained some degree of voluntary movement had MP's whichmapped to a more posterior (post central) location while MP's of normal subjects were precentral. The MP electricalfield maps and dipole sources are illustrated in the figure.

.Ikeda and Shibasaki (1992) demonstrated in subdural recordings in epileptic patients that both the primary motor andsensory areas contribute to the generation ofMP's with the motor area predominating. Our data suggest a reversal ofthis relationship in severely weakened, but not paralyzed SCI patients. The reason for this is unknown, but thephenomenon could be explained ifaxons descending from the sensory area had a more diffuse distribution in the spinalcord than precentral axons and thus be more likely to be spared in incomplete SCI.

MP Dipole

Control

Patient

S264

POSTERS: MOTOR

tMRI of Localized Activation of Executed and Imagined MovementsM. Lotze', W. Grodd', E. Hulsmann', M. Erbt, U. Klose', B. Kardatzkl', N. Birbaumer'

l Section MR ofthe eNS, Dept ofNeuroradiology; 2/nstitute ofMedical Psychology;University ofTuebingen, Germany

II

5 ric" eerebell .. hrrri sJiwIT4 tiche twd rmwnwnl

~~l~~~~

5 7 9

slice s

Introduction: With the advent of functional Magentic Resonance Imaging (fMRI) a new imaging modality formonitoring regional brain activity in human has emerged (I), which can easily be used to study noninvasivelyindividual activation and somatotopy of the primary motor (M 1) and sensory (S1) cortex (2). By applying fMRIto the whole brain a somatotopic representation for voluntary movements of hand, tongue and feet was found inthe cerebral cortex as well as in the cerebellum (3). In addition for imagined movements a similar activation inM I and S I has been described (4). As the role of the cerebellum in movement processing and control andespecially during the imagination of movements remains unclear, we tried to investigate the activation of thecerebellum during executed and imagined movements. Our hypothesis was that inhibition of execution duringimaginary movement may be controlled or facilitated by the cerebellum.

Methods: fMRI-data of the whole brain were acquired with a commercial 1.5 Tesla tomograph (SiemensVision) using a multislice echo planar imaging sequence (EPI) with 27 axial slices (4 mm slice thickness, 1 mmgap, 128*96 matrix , 260*162mm FOV, TE 66 ms, TR 1,8 ms a 90° , acquisition time 4 sec) . Sequential real andimaginary hand movements were performed by 10 right-handed volunteers (5 male and 5 female , 19-40 years).Executed hand movements (EM) consisted of pressing a softball with the right or the left hand. Imaginedmovements (1M) of both hands were trained prior to the fMRI examination under EMG control and with a per­sonal assessment score of intensity of imagination . Statistical evaluation of the fMRI data was performed by cal­culation of z-values, where pixels with a z-value of ::: I were declared as activated. For further evaluationanatomically defined regions of interest (ROI) in each slice [M I, S I, supplementary motor area (SMA), cerebel­lar hemispheres and vermis] were drawn and the number of activated pixels were calculated as percentage of thetotal number of pixel within each ROt lnterindividual anatomy of the cerebellum was achieved by linear trans­formation and superposition of individual data sets.

Results: Simple hand movement revealed different activation sites in S1 and M1 in both hemispheres with amedium cranial shift of appr. I cm on the left. The contralateral activity distribution of S I and M I was intraindi­vidual significant correlated in all subjects only for right hand movement. Imagined movements showed onlyappro30% activation in the contralateral M I and S I compared to real movement, while for SMA the activationremains the same. In the cerebellum (Fig. I) in all cases a significant activation during EM was detectable in theanterior ipsilateral hemisphere (maximum 4'hslice: left hand 4.8%, right hand 3.7%). For 1M the activation wasagain diminished to appr. 20% compared to EM (Fig. 2) and ipsilateral wider distributed (left: max. 1.3%; right :max. 1.9%) with a caudal shift for right hand movement (right hem: 8. slice) from Larselliobuies H IV-V to HVI (Fig. 3).

Fig. I Fig.2 Fig.3a Fig.3bFig.l : eleven axial slicesselected, covering both cerebellar hemispheres in 5mmdistance.Fig.2: activated pixel in percentper ROIof the right hemispheric slicesfor all subjectsduring EM and 1MFig 3: maximal activation of superimposed coronal slicesof 6 subjectsduring EM and 1M ofthe right hand

Discussion: Compared to real movement - even by controlled training of subjects - in imagination of movementonly 2 persons showed a significant topical correlation of activity between EM and 1M in primary motor cortex,while SMA activation was unchanged. In addition for both conditions (EM and 1M) no systematic shift incortical activity was found . In contrast in the cerebellum a caudal shift was seen between EM and 1M duringright hand movement. This shift may depend on the lack of afferent information during 1M in the anterior lobeand an inhibitory activation in the lower cerebellar hemispheres.

Literature: I. Belliveau JW, et al.: Science 1991,254,716-193. BritschP, et al.: Neurolmage 1996,3,378

2. LeonardoM, et aJ.: HumanBrain Map. 1995,3:83-924. Rao SM, et al.: Neurology 1995,45:919-924

S265

POSTERS: MOTOR

Increased functional MRI response of cortical motor areas after movementsimulation

R. Massarelh', A. Gemignani1,2, M. Baciu-Raybaudr', C. Delon-Martin1, M. Roth\M. jeannerodf, M. Guazzelli2 and C. Segebarth1

lINSERM Unit 438, Hopital Michallon, BP 217,38043 Grenoble, France/: Institute of ClinicalPsychiatry, Pisa University, 56100 Pisa, Italy;3 INSERM Unit 94, Ave. Doyen Lepine, 69500

Bran, France

Introduction. Mental simulation of a motor task has been shown to be of importance both inlearning and in preparing the movement (reviewed in 1). Recent reports (2,3) have shown thepossible involvement of the primary motor cortex (MI) during motor imagery. The purpose ofthe present study was to show whether the simulation of a motor movement immediatelybefore its execution may modify the functional MRI pattern of the intervening cortical areasduring execution.Subjects and Methods. Seven right handed healthy volunteers (six females and one male, age24-35 years) were asked to simulate opposing movement of the right fingers to the thumb,back and forth, in a rythmic sequence and then to execute the same movement. The fMRIprotocol consisted in two scans, each repeated thrice in alternance. In the first scan theparadigm included a rest period (4 series of 4 slices), followed by a simulation period (2series of 4 slices) immediately followed by the execution of the task (4 series of 4 slices) (SEtask). This sequence was repeated three times. In the second scan the paradigm consisted in arest period (6 series of 4 slices) and an execution period (4 series of 4 slices) (E task). Thissequence was also repeated three times. The capacity of each individual to perform movementsimulation was assessed with a motor imagery questionnaire (4). A gradient echo pulsesequence was utilised (TE==40ms; TR==77ms; Flip Angle 30°; FOV==192mm; matrix==64*64; slicethickness-sf mm) throughout the experiments in a clinical setting with a Philips ACSII (1.5 T)imager. High resolution 3D anatomical an 3D phase contrast MR scans were obtained fromthe corresponding portion of the brain. Functional maps were superimposed on theanatomical images after masking of the images obtained from the phase contrast scans toavoid interferences from functional activations of large vessels (5). The post-processing of theimages was performed on a Sun station using cross correlation techniques. The cortical areaswere identified according to the atlas of Talairach (6).Results and Discussion. MI, premotor and supplementary motor areas (PMA and SMArespectively), primary sensory (51) and posterior parietal cortex (PPC) were involved in theactivations observed during the tasks. Individually, a larger number of positively correlatedpixels were observed in all areas under study of the left (controlateral) hemisphere during theSE task, compared to the E task. Similarly, a larger number of negatively correlated pixelswere observed under the same conditions in the right (ipsilateral) hemisphere. An ANOVAanalysis on the seven subjects confirmed a significant increase (32 %; 2p<0.05) of positivelycorrelated signals in the left hemispheres after the SE task and of negatively correlated signals(150 %; 2p<0.001) in the right hemisphere relatively to the E task. The data suggest that thesimulation of a motor movement, prior its execution, changes the functional response to thetasks in the form of an increased number of positively correlated signals in the controlateralhemisphere and of increased number of negatively correlated signals in the ipsilateral one.References1) [eannerod M and Decety JCurr Op Neurobiol 5, 727-732, 1995.2) Leonardo M et al Hum Brain Map 3, 83-92, 1995.3) Roth M et al Neurorepori 7, 1280-1284, 1996.4) Hall CR and Pongrac JMovement imagery questionnaire Faculty of Physical Education, UniversityWestem Ontario, Canada, 1983 (translated in French by J. Decety).5) Segebarth et al Neurorepori 5, 813-816, 1994.6) Talairach J and Toumoux P Co-planar stereotactic atlas of the human brain , Thieme, New York,1988.

8266

POSTERS: MOTOR

The Roles of Pre-SMA and SMA-Proper in Motor Initiation andDecision Making; Studies using 'Event Related' fMRI

M. Humberstone, S. Clare, J. Hykin, P.G. Morris, G.V. SawleDepartments of Neurology & Physics, University of Nottingham, UK

IntroductionEcho-planar imaging at 3 Tesla is sufficiently sensitive to detect functional activity associated withsingle motor events, it provides sufficient temporal resolution to measure its time course [1]. Wehave used signal averaging techniques to perform 'Event Related' fMRI studies. In a 'Go, No-go'task in which the responses to each stimulus were analysed separately. In order to discriminatemotor execution areas (active only in response to Go stimuli) from decision making areas (active inresponse to both), we compared self cued movement trials with identically timed externally cuedtrials in order to examine the time course of functional activity prior to movement initiation and todistinguish areas involved in the planning, initiation, and maintenance of motor tasks.

Methods6 healthy subjects were used in each study. Echo-planar imaging was performed at 3.0 Tesla. Thewhole brain was imaged in 12 coronal slices every 3 seconds.In the 'Go, No-go' paradigm a visual stimulus was presented every 18 seconds. The correctresponse to a 'Go' stimulus was to press a button with the right thumb. The correct response to a'No-go' stimulus was to do nothing.In the self cued paradigm subjects initiated a movement trail by pressing a button held in the righthand. This started a display flashing at 4Hz for 30 seconds. Subjects were asked to press thebutton once for each flash then wait at least 30 seconds (without counting) before initiating the nexttrial. 10 trials were performed. In the externally cued paradigm the recorded start times for the selfcued paradigm were used to trigger each trial. Images were registered to remove movement artefactand were rescaled to remove baseline image intensity drift. The mean intensity at each time pointfrom 9 seconds before the onset of movement to 12 seconds after the end of each trial wascalculated for each pixel. A serial t-test was performed between each time point and a baselineimage set to determine regions and times of significant activation. Thresholded t-maps weresuperimposed on inversion recovery anatomical images and registered to the atlas of Talairach.

ResultsIn the 'Go, No-go' paradigm activity in left primary motor cortex and SMA-proper was seen onlyin response to Go stimuli whereas Pre-supplementary motor area (Pre-SMA) was activated 3-6seconds following both.Functional activity was consistently seen in Pre-SMA 3 seconds prior to initiation of the self cuedtrial. No activity was seen prior to the externally cued trial. Activity in left primary motor cortexappeared at the onset of both self and externally cued trials. It persisted throughout movement andcontinued 12 to 15 seconds after the end of movement. Within the SMA proper there was a peak ofactivity at the onset of movement which died away but gradually increased later in the epoch.

DiscussionThis study demonstrates the role of pre-SMA in motor decision making and in preparation for selfcued movement. Activity within SMA-proper appears to be more directly related to initiation of themovement itself and shows similar patterns of activity between self and externally cued trials. Thegradual rise in activity during each trial also suggests a role in sustaining difficult motor tasks.'Event Related' tMRI studies enable novel methods of analysis. The time series generated may bedisplayed as video to illustrate the temporal pattern of functional response.

Referencel.Humberstone M. et al Proceedings of the Society of Magnetic Resonance 1995, 2: 858

S267

POSTERS: MOTOR

FMRI Studies of the Supplementary Motor Area and Premotor CortexS. Van Oostende*, S. Sunaert*, P. Van Hecke*, B. Nuttin' and G. Marchal*Departments of "Radiology and 'Neurosurgery, University Hospital Gasthuisberg,

Katholieke Universiteit Leuven, B-3000 Leuven, Belgium.

Purpose: Functional and anatomical studies in primate brain [I] suggest a functional dichotomy of themedial (supplementary motor area, SMA) and lateral (premotor cortex, PMC) premotor areas, the firstbeing more involved in internally generated movement, the latter in movement under external, sensoryguidance. Neurophysiological studies in humans [2,3,4] are in favour of a similar functional specialisationin the human brain. Using fMRI, we have examined the relative involvement of a number of human motorareas in externally guided versus internally selected finger movements.

Methods: Six right-handed volunteers were studied. The functional images were acquired at 1.5 Tusinga gradient-echo EPI sequence with TE/TR/a = 66ms/3s/90°. Every EPI acquisition consisted of 8 sliceswith a 4 mm thickness, a I mm gap and 3.13 x 3.13 mrrr' in-plane resolution. One functional time seriesconsisted of 120 EPI acquisitions, resulting in a total scan time of 6 minutes. Additionally, TI-weighted,high-resolution images (MPRAGE) were acquired for anatomical information.

The motor tasks consisted of finger-to-thumb oppositions. Each finger was given a number and theoppositions were performed in response to the numbers, presented auditorily at a fixed rate. In the FIXtask, the subjects performed a pre-learned, fixed sequence, going always from index to little finger, TheRAND task consisted of imposed, randomly sequenced finger oppositions. In the third task, SELF, thesuhjects only heard the ticking of a metronome, at the same rate as in the previous tasks, and had tochoose themselves which finger to move, but in such a way that a random sequence was generated. In asingle functional time series 2 tasks conditions, either FIX and RAND or FIX and SELF, were alternated,with short rest periods (REST) in between. Each type of time series was run 2 times in each subject.

Using SPM95, the images were motion corrected and normalized. Statistical parametric maps (SPMs)were calculated for the contrasts FIX-REST, RAND-REST, SELF-REST, RAND-FIX and SELF-FIX.Individual as well as group analysises were performed. The activation maps were thresholded at Z = 3.09(individual) or Z = 1.65 (group) for activation height and p < 0.05 for activation extent. Since RAND andSELF were performed in different time series, no direct comparison between the two tasks was done.However, percentual fMRI signal changes for RAND vs. REST and SELF vs, REST were calculated inthe most significant pixel of each area for the contrasts RAND-REST and SELF-REST, respectively andcompared.

Results: In the individual analysis, the brain activation pattern for FIX-REST is in most subjects limitedto the contralateral primary motor cortex, the posterior part of SMA and the anterior bank of theprecentral gyrus bilaterally, a part of PMC. The SPMs of the contrasts RAND-REST and SELF-RESTyield similar activation patterns with additional activation in pre-SMA, the anterior part of SMA,bilateral PMC and bilateral superior parietal cortex. For the contrasts RAND-FIX and SELF-FIX,activation is in most subjects limited to bilateral superior parietal areas. In addition, the group analysisreveals activation in a part of contralateral PMC (the posterior part of the superior frontal sulcus, sfs) andin frontal medial areas, namely anterior cingulate cortex (ACe) and pre-SMA for RAND-FIX. Theseareas remain subthreshold for SELF-FIX. No significant differences in percent signal change betweenRAND vs. REST and SELF vs. REST are found, except in one focus, located posteriorly in thecontralateral sfs, which shows a significantly higher (p<0.05, Wilcoxon) signal change for RAND vs.REST than for SELF vs. REST.

Conclusion : None of the motor areas we examined is found to be preferably activated in internallyselected movement. On the contrary, a part of contralateral PMC, more specifically the posterior part ofthe sfs, as well as pre-SMA and ACC seem to playa more important role in the execution of motor tasksunder sensory guidance.

References :[1] Tanji J., Neurosci. Res. 1994, 19:251-268[2] Deiber M.-P. et al., Exp. Brain Res. 1991,84:393-402[3] Kawashima R. et al., J. Neurosci. 1994, 14(6):3462-3474[4] Praamstra P. et al., Exp. Brain Res. 1995, 103:429-439

8268

POSTERS: MOTOR

Movement selection without preparation does not activate the SMAM. Brett, I.H. Jenkins, J.P. Stein and DJ. Brooks

MRC Cyclotron unit, London, UK

The roles of the premotor areas in the selection of action are still controversial. One influential theory is that ofPassingham (I). He proposed that the lateral premotor cortex (LPMC) has a specific role in 'externally generated'movement, whereas the supplementary motor area (SMA) is more involved in action that is 'internally generated'.Action generation is external if the choice of action is conditional on some external sensory cue, and internal if thechoice of action is not dictated by an external stimulus. An early PET study of paced joystick movements gave onlyqualified support (2). It found that LPMC did not activate specifically when the direction of movement wasconditional on a colour cue, but SMA was more activated than other premotor areas during random movements.This result was confounded by the fact that subjects could prepare responses in the random condition. We thereforedesigned a PET study that is not confounded by motor preparation in order to test Passingham's hypothesis.

Subjects and methodsOur subjects were 8 normal right handed volunteers aged 35-58 (6 male, 2 female). We trained the subjects for 45minutes on two tasks. In the random [R] task they heard one of four musical tones; each of these tones cued them topress at random one of the four buttons under the fingers of their right hand. Tones were spaced at random between4 - 6 seconds apart. In the conditional [C] task they heard one of four further tones. Each tone was associated withone of the four buttons. and they had to press the correct button. After 45 minutes, they began 45 more minutes oftrials where the Rand C sounds were intermixed randomly so they could not predict which they would hear next.During the scanning session they continued to practice on such a mixture of tones. As each scan began, the mixturechanged to specific proportions of Rand C, and reverted to an equal mixture after 45 seconds. Each subject had 12scans: 2 rest (tones but no response); 2 in which there were all R tones during the first 45 seconds; 2 with all Ctones, and 6 with varying mixtures of Rand C. None of the subjects were aware that the mixtures had been changedduring the scans. We used a bolus injection technique with 0 15 labelled H20 in a CTI 953B PET scanner. Scanswere realigned, normalised and smoothed using standard settings in SPM 95 software.

ResultsThe figures below are from SPM 95, and show voxels activated when compared to rest in the All R (fig 1), and All C(fig 2) conditions. The SPMs are very similar, with activation in left motor and sensory cortices, bilateral parietalcortices, left thalamus and a right ventral premotor/prefrontal area. There was no SMA activation at any threshold;indeed there was evidence of SMA deactivation compared to rest in both conditions at p<O.05. Comparison of All Rwith All C confirmed greater activation of the right premotor/prefrontal region in the all R condition.

1. All random /--r- 2. All conditionalminus rest minus rest

Figures 1 and 2: transverse SPMs of activated voxels, uncorrectedthreshold of p<O.OOl; Left = posterior

ConclusionsOur study was intended to test the hypothesis that the SMA has a specific role in internal action selection. Webelieve our design has removed the effect of motor preparation that confounded previous studies; subjects could notprepare how to respond or when to respond. Our results show no evidence for a specific role of the SMA in eitheran 'internal' or 'external' mode of movement selection. Previous findings of SMA activation during randommovement may be explained by the increased motor preparation such tasks allow. Once this confound has beenremoved, the distinction between internal and external action selection may not be of fundamental importance inexplaining PET activation.

1. Passingham, R.E. in Motor areas ofthe cerebral cortex (ed, Porter, R.; Wiley, Chichester) 1987, 151-164.2. Deiber, M.P., et al. Exp Brain Res. 1991, 84,393-402.

8269

POSTERS: MOTOR

Supplementary Motor Area and Ant. Cingulate in Bimanual Phase-CouplingK.M. Stephan", F. Binkofski", S. Posse'', C. Dohle·, A. Schnitzieri P. TassI,

H.W. Miiller-Gartner2, R.J. Seitz· and H.J. Freundl

1Dep. ofNeurology, University ofDusseldorf 2 Institute ofMedicine, Research Center Julich.Germany

IntroductionIn bimanual motor acts, usually the dominant hand reaches out and manipulates the object, while the other handassists by stabilizing the object (I). The temporal structure of such bimanual movement sequences in non-humanprimates and neurological patients is impaired by lesions in the frontomedial cortex including the supplementarymotor area (SMA) and anterior cingulate (e.g. 2, 3, 4). We investigated bimanual movements which are coupledbut not goal directed and mapped the cerebral structures engaged in bimanual phase coordination using fMRl.

Materials and MethodsSix healthy right-handed Caucasian subjects (mean age 32 years) performed index finger to thumb oppositionmovements separately for the right and left hand, bimanually in-phase, and with a constant phase shift of 0.5between the hands (anti-phase). For each condition five active periods of 15 s were interleaved with five restperiods (Siemens Vision, 1.5 T, EPI-sequence (TE 66 ms; TR 3s; a 90°), voxel size 3*3*4 mm). 10 slices parallelto the AC-PC line were acquired covering the dorsal part of the brain down to the corpus callosum. Afterrealignement and filtering (4 mm width); statistically significant individual maps (p<0.005) were calculated andoverlayed on MRl scans using the SPM96b statistical package (Wellcome Department of Cognitive Neurology,London) and the MPItool (Max-Planck-Institut fur neuralogische Forschung, Cologne). The same protocol wasrepeated outside the scanner using twin-axis goniometers to record movement kinematics.

ResultsKinematic results showed regular index-finger to thumb opposition movements at similar frequencies for all fourtasks with a closer correlation between the hands during in-phase compared to anti-phase movements (paired t­test: p < 0.001). fMRl revealed activation of bilateral sensori-motor cortices and lateral and medial premotorareas in all subjects during bimanual movements (p<0.005). At a lower threshold (p<O.OI, uncorr.) three distinctfoci of activation were identified medially: dorsal SMA, ventral SMA just above the cingulate sulcus and lateralcingulate activations within cingulate sulcus. Right hand movements were mainly associated with contralateralfrontomedial activations in all three areas, left hand movements mostly with bilateral frontomedial activations.

Frontomedial activations in bimanualphase coordination

R in-phase L R anti-phase L

dorsal SMA x Xxxxx XXxxx Xxx

ventral SMA / medio-dorsal c. Xx XXXxx Xx XXXxxx

lateral anterior cingulate XXXx XXX" XXxxxx Xxxxx-The number of 'x' equals the number ofthe subjects with a significant activation within the described areas. The

size of 'x' symbolizes the deg. ofsig. (t-values) in the individuals: x : 2.33 5, t < 3.6; X : 3.65, t < 5.0; X: t'? 5.O.

The location of the foci varied considerably between hemispheres and subjects, at least partly due to theanatomical variability of the cingulate sulci. Prominent paracingulate sulci were found in four of the six subjectson the left side but only in one subject in the right hemisphere (see 5).

ConclusionsOur results demonstrate an enhanced activation of anterior cingulate and SMA areas during bimanual anti-phasemovements compared to bimanual in-phase and unimanual movements with lateralization of ventral SMAactivations to the dominant hemisphere. The importance of cingulate areas for bilateral coordination is supportedby the impaired bimanual performance of two patients with a tumour in the adjacent right mid-cingulate area (4).

References(1) Kazenikov O. et aI., (1994) Eur.1. Neurosci, 6: 203-210 (2) Brinkman C. (1984) 1. Neurosci. 4: 918-929(3) Laplane D. et aI. (1977) J. Neural. Sci. 34: 301-314 (4) Stephan K.M. et. al (1996) NeuroImage 3,3:S 418 (5) Paus T. et al. (1996) Cerebral Cortex 6: 207-214

S270

POSTERS: MOTOR

FMRI of the Supplementary Motor Area and the Premotor Cortexas a Clinical Test

B.F. W. van der Kallen, L.J.Th.O van Eming, M.W.I.M. Horstink, H.O.M. ThijssenUniversity Hospital Nijmegen, The Netherlands

IntroductionWe are interested in mapping the Supplementary Motor Area in patients with Parkison disease. Therefore we developedtwo sensory-motor tasks that we hypothized to have different activation patterns in the primary sensory-motor cortex, thesupplementary motor area (SMA) and premotor cortex using Functional MRI (FMRI).

Methods and MaterialsA pilot study included volunteers with no previous neurological trauma or deficit. The functional imaging was done ona commercial 1.5T scanner (Siemens Magnetom 63/84 SP, Erlangen Germany) with a standard head coil. The imageswere acquired with a FLASH sequence (TRITE=200/35 , 20° Flip Angle, 64x128 Matrix). Four slices (5 mm slicethickness, no gap) were positioned parrallel to the Anterior Commissure Posterior Commissure (ACPC)-plane with thecenter of the imaged volume at 67 % of the distance between the ACPC-plane and the vertex. The post-processing wasdone with a cross-correlation analysis (threshold 0.60)[1]. The subjects had to perform two sensory-motor tasks. Onetask consisted of sequentially picking up and dropping a small object with the right hand (task 1). In the second task,instead of dropping the object, the subject had to place it in a designated hole (task 2). Task periods were alternated withrest periods. Both tasks were done in a self-paced manner without visual feedback. Similar movements of the fingersand wrist are needed in both tasks. However the second task necessitated a precise placement of the small object. Amore complex sequential integration of sensory-motor and proprioceptive information is needed in task 2. The SMA hasdemonstrated to playa role in the timing and control of sequential sensory-motor movements[2]. To be able to place theobject in a hole feedback on andcorrection of direction and distance of movements are necessary. Neurons in the primarysensory-motor- and the premotor cortex have been shown to be direction and distance related[3]. Therefore moreactivation of the primary sensory-motor cortex, the premotor cortex and the SMA was expected in task 2.The regions of interest were divided in Sensory-Motor- (SMC), Parietal- (PC), Premotor- (PMC) cortex and SMA onthe basis of anatomical structures. The student t-test (paired, one-tailed) was used to test significant difference inactivation patterns between both tasks.

ResultsIn this study we examined 10 volunteers (all right handed, ages 19 - 28). The imaging data of 3 subjects had to bediscarded due to head motion. The data of the remaining 7 subjects was used for the evaluation of the sensory-motortasks. In task 1 contralateral cortical activation was seen in the SMC in all seven subjects, in the SMA in 3 subjects andthe PMC in 3 subjects. Ipsilateral activation was seen in the PMC in 1 subject and in the SMA in 1 subject. In task 2contralateral activation was seen in the SMC and PMC in all 7 subjects, the SMA in 6 and in the PC in 5 of the sevensubjects; Ipsilateral activation in the SMC in 4 subjects, the SMA in 1 and the PMC in 1 subject. The number of activatedpixels increased significantly in task 2 compared to task 1 in the contralateral SMC (p < 0.002 [paired one-tailed studentt-test]), the contralateral PMC (p < 0.01) and the contralateral SMA (p < 0.03).

ConclusionOur results show that the second task was associated with significantly more activation in the contralateral sensory-motorcortex, SMA and premotor cortex.

References1. Bandettini, PA, et al. MRM 1992, 25: 390-3972. Roland, PE, et al. J. Neurophysiol. 1980, 43: 118-1363. Kurata, K, et al, J. Neurophysiol. 1993,69: 187-200

8271

POSTERS: MOTOR

Temporal Modulation of Regional Brain Activity with f1\1R Imaging Time-ShiftMaps at High Temporal Resolution

x. Oolay'', S. Kollias2, D. Meier, A. Valavanis2, P. Boesigerr'1Institute 1,Biomedical Engineering and Medical Informatics, University and ETH, Zurich

Institute ofNeuroradiology, University Hospital, Zurich, Switzerland

IntroductionFunctional MR imaging (tMRI) is increasingly used to demonstrate noninvasively physiological activation andtopographic organization of the human brain. Due to the temporal limitation of the hemodynamic response, itis questionable whether the technique can define temporal modulation of regional brain activity. Our rationalewas to assess the ability of tMRI not only for toporaphic mapping of activated primary and secondary corticalareas but also for resolving the temporal pattern of cortical brain activation. The hypothesis was that the hemo­dynamic response parallels the sequence of electrical events in the cortex and that this sequence of events canbe detected with high temporal resolution tMRI and time shift maps constructed at different time delays fromthe onset of task performance.

Material and methodsFMRI experiments were performed in 1.5 T magnet (Philips, Gyroscan ACS-NT, standard imaging head coil)using a an EPI sequence (TR = 160 ms, TE =38, FA = 10°, in plane resolution =3 x 3 mm2). Three contigu­ous slices of 6 mm thickness were obtained covering most of the superior frontal, central, and parietal corticalareas. Four healthy volunteers, (3 right handed and one left handed) were examined during performance of acomplex, finger tapping, self paced, motor task. Subjects were provided instructions and allowed to practicethe task prior to scanning and were instructed to keep their eyes closed throughout the scanning series. Twoexperiments performed with the right or left hand consisted of two sets of activation periods, interleaved withthree resting periods, each one of 30 sec. Correlation maps were generated using a cross correlation betweeninput function and the image time-course intensity change on a pixel-by-pixel basis. Correlation maps with 600ms time shifts were generated for a period ranging between 0 and 12 seconds from the onset of the stimulus.The time delay between the tMRI signal and the stimulus period was determined by calculating the time posi­tion of the maximal cross correlation coefficient using a threshold of cc = 0.2, corresponding to a Z-value of3.2 (p < 0.0006). Visualization of the results in a movie mode allowed precise definition of the onset and decaytimes of activation for all areas of interest.

ResultsFunctional changes were detected in the contralateral, and to a lesser extend ipsilateral primary motor cortex(MI), supplementary motor area (SMA), the prernotor cortex (PM) of both hemispheres, and contralateral so­matosensory cortex (SC) in all volunteers. In all subjects, task performance with the left hand elicited largeractivation in the contralateral MI as compared to the area activated by the right hand. Differences in peak acti­vation as well as, times of onset and decay of activation were detected for the different areas. In all volunteers,the contralateral MI area activated consistently later (~= -0.8 sec.) than the SMA and PM These areas showedactivation from the early beginning of the task onset and reach peak activity at 0.22 sec. for the SMA and 0.20sec. for the PM cortex. SC cortex had peak activation at 0.28 sec., and MI at 1.08 sec.

Discussion and conclusionEarly activation of the SMA and PM is in agreement with previous observations (1-3) suggesting a role forthese areas in the planning and execution of complex movements. Although the data of this preliminary studyare limited for reaching statistical significance, it seems that time domain analysis of tMRI data at high tempo­ral resolution can detect sequential activation of functionally connected cortical areas. The validity and impor­tance of the technique in temporally resolving human cortical function awaits further experience with a largerpopulation of normal volunteers and patients harboring well defined lesions involving specific cortical areas.

ReferencesI) Lang W., Lang M. et al., Exp Brain Res. 1988,71: 579-587 2) Me Callum W.e. in Picton T.W. (Ed.), EEGHandbook, Vol 3, 1988, Elsiever, Amsterdam. 3) Erb M., Wildgruber D., et aI, 2nd Meeting on Human BrainMapping, 1996, Boston, p. S364

S272