ORAL SESSION: METHODS

Comparisons between Human and Macaque Using Shape-basedDeformation Algorithms Applied to Cortical Flat Maps

DC Van Essen, HA Drury, SC Joshi, MI MillerWashington University , St. Louis, MO, USA

Information about the arrangement of cortical areas in nonhuman primate s, especial1y the macaqu e monke y, providesa valuable guide to the interpretation of functional brain imaging studies in humans. However. such comparisonsare inherently difficult because of large inter-species differences in the pattern of cort ical convolutions and in the size(both absolute and relative) of various cortical areas. Shape-based warping algorithms applied to flat map s of thecortical surface (Joshi et al ., 1995; Drury et al., 1995) offer an attractive strategy for attacking this problem.

Methods. We modeled the cortical surface as a 2-dimensional viscoelastic fluid and applied a fluid deformationalgorithm to transform a macaque cortical map (the source) to match the shape of a human cortical map (the target ­here, the right hemisphere of the Visible Man) . To drive the deformation, the algorithm uses explicit contoursdrawn in regions known or suspected to represent corresponding locations in the source and target maps. This allowssystematic evaluation of a variety of potential correspondences that are based on geographic (gyral and sulcal) and/orfunctional landmarks.

Results. Fig . I shows the deformation of a macaque flat map to the shape of the hum an flat map, driven bygeographical1y corresponding contours along along the perimeter of each map and along the margin s of four internalsulci (calcarine, central, rhinal, and lateral sulci). The outlines of 78 cortical areas from the Fel1eman and Van Essen( 1991) partitioning scheme for the macaque were carried passively with the transformation and are illustrated before(panel A) and after (panel B) deformat ion. Macaque visual areas V I, V2, V4, the MT/MST complex (Mx),inferotemporal (IT) and posterior parietal (PP) areas are denoted, along with overal1 visual, auditory, somatosensory,and motor regions. Thi s pattern can be compared not only to cortical geography (not shown) but to the locat ions ofregions of human cortex implicated in processing of motion (Mo), form (F), and color (C) , as estimated byprojecting the stere otaxic (Talairach) coordinates from PET studies onto the Visible Human flat map (Drury and VanEssen, 1996). For example, the MTIMST complex in the deformed macaque map (Mx) is close to the human regionspecialized for motion processing (Mo), consistent with previous suggestions that these regions are homologous.This and other presumed homologie s can be used as additional constraints to guide subsequent deformations, therebyfacilitating the evaluation of candidate homologie s in surrounding cortical regions.

Fig. 1.

Conclusion. This approach establishes a framework for systematic exploration of candidate homologies in whichthe underlying assumptions are made explicit. Progress on this front wil1 be facilitated by the ability to warp fMRIactivation patterns from individual human subjects onto the Vis ible Man atlas (see abstract by Drury et al ., theseproceedings).

Drury HA, Van Essen DC, Joshi S, Miller, MI Anderson, CH and Coogan T. 1995 Soc Neurosci Abstr 2 1: 923 .Drury HA and Van Essen DC. 1996 Soc Neurosci Abstr 22: 1105.Fel1eman, DJ and Van Essen DC 1991 Cerebral Cortex I :1-46.Joshi SC , Miller MI , Christensen GE, Banerjee A, Coogan TA, and Grenander U. 1995 In: Vision Geometry IV,

eds . R.A. Melter, A.Y. Wu, F.L. Bookstein, and W.O. Green, vol. SPIE 2573 , pp . 278-289.

S41

ORAL SESSION: METHODS

Combining Bioelectric and Biomagnetic Data for Source ReconstructionM. Fuchs, M. Wagner, H.-A. Wischmann, A. Thei6en, Th. Kohler, R. Drenckhahn

Philips Research Hamburg, Rontgenstr. 24-26, 22335 Hamburg, Germany

Reconstructions combining bioelectric and biomagnetic data promise to benefit from the advantages of bothmodalities: EEG measurements can be carried out with an optimized electrode arrangement and exhibit nearly equalsensitivities for tangentially and radially oriented sources. MEG gradiometer systems have an increased sensitivityfor tangential superficial sources, leading to an improved SNR and a larger specificity for this class of generators.

MethodsIn order to combine both modalities in a unified framework, different problems have to be solved:I. The different measures have to be transformed to a common basis. This is done by referencing each sensor to its

individual noise statistics taken from signal free (e.g. pre-trigger) latencies.2. EEG data strongly depend on the head's conductivities (which are not well known), whereas MEG data are not

affected by them. We have thus chosen latencies where single, dominantly tangential dipoles are able to explainthe measured data very well (for both modalities) and matched the conductivities of the volume conductor model.

3. MEG reconstructions with realistic volume conductor models tend to overemphasize quasi-radial componentsdue to their very small gain (I), so dipole component regularization techniques have to be introduced.

Results and ConclusionsEvoked somato-sensory measurements with simultaneously recorded 31 electrodes EEG (SEP) and 31 channelsMEG (SEF) (Fig. 1) were analyzed with both modalities combined and compared to the corresponding singlemodality evaluations (2). In all cases a realistically shaped volume conductor model (BEM) has been used (1).Single moving dipole reconstructions representing the centers of the in this case overlapping cortical activations ofthe tangentially oriented N20- and the radially oriented P22-generators were overlayed onto the MR-data of thesubject and the segmented cortical surface (Fig. 2). The combined evaluations exhibit the best spatial resolution witha smooth transition between both dipole orientations, whereas the magnetic data alone contain information of thetangential source only and the electric data alone suffer from a smaller SNR and less spatial resolution due to volumeconductor effects and large inter-electrode distances.

? .....,Q." Q . ..•~ 0. QQ:

I'---;---- .-- --,.-.:..._=-

~A: Q. ~ -

j ~W =J

Fig.I: Butterfly-plots (-20..120 msec) of the measured31 SEP (upper row) and 31 SEF channels (lower row)with contour maps (right column) at a latency of21 msec post electric medianus nerve stimulation.

Fig.2: Single moving dipole reconstructions (18 ..24 msec)with an enlarged view of the right central sulcus (upperleft middle to [ower right corner). Upper row: SEP,lower row: SEF, right: combined SEP/SEF.

References1. Fuchs, M, Drenckhahn, R, Wischmann, HA, Wagner, M, Bioelectric and Biomagnetic Reconstructions with an

Improved Boundary Element Method, IEEE Trans. Biomed. Eng. 1996, submitted2. Buchner, H, Fuchs, M, Wischmann, HA, Dassel, 0, Ludwig, I, Knepper, A, Berg, P, Source Analysis of Median

Nerve and Finger Stimulated Somatosensory Evoked Potentials: Multichannel Simultaneous Recording ofElectric and Magnetic Fields Combined with 3D-MR Tomography, Brain Topography, 6: 299-310, 1994

S42

ORAL SESSION: METHODS

Transcranial Magnetic Stimulation During Positron EmissionTomography: ANew Method for Studying Connectivity of the

Human Cerebral Cortex

Tomas Paus, Robert Jecht , Christopher J. Thompson, Roch Comeau,Terry Peters, Alan C. Evans

Montreal Neurological Institute, McGill University, Montreal, Canada and t Department ofNeurology, 1st Medical Faculty, Charles University, Prague, Czech Republic.

IntroductionThe correlational approach to the study of functional connectivity suffers a major limitation in that the en­gagement of a subject in performing a task confounds the data being acquired; the observed "co-activations"may reflect relationships between different components of behavior rather than connectivity. Here we de­scribe a novel technique that allows an assessment of connectivity to be made directly, without requiringthe subject to engage in any specific behavior. The technique is based on the concurrent use of transcranialmagnetic stimulation (TMS) and positron emission tomography (PET). The key principle is that of mea­suring the effect of a focal TMS-induced electrical stimulation of one region on activity, indexed by changesin cerebral blood-flow (CBF), elsewhere in the brain. In the first TMS/PET study, we stimulated the leftfrontal eye-field (FEF) to reveal its connectivity.

MethodsSix subjects volunteered for the study after giving written informed consent. The study was approved by theResearch and Ethics Committee of the Montreal Neurological Institute and Hospital. A figure-eight TMScoil was positioned over the probabilistic location of the left FEF (i.e. X=-32, Y =-2, Z=46 [1]), and CBFwas measured in six 60-sec Jr)O_H~O scans acquired with the CTI/Siemens HR+ tomograph. During thescans, the subjects kept their eyes closed and white noise (80 dB SPL) was played through insert earphonesin order to mask the coil-generated clicks. Eye movements were recorded with electrooculography. It shouldbe pointed out, however, that we did not expect to evoke any eye movements in this experiment sinceseveral previous investigators failed to trigger eye movements by TMS of the frontal cortex. To allow fora correlational analysis of CBF data, different number of TMS pulse-trains was delivered in the six scans,namely 5, 10, 15, 20, 25 and 30 pulse-trains per scan. The order of scans was randomized.

The Cadwell High Speed Magnetic Stimulator and the Cadwell figure-eight coil (Corticoil) were used toproduce a focal stimulation of the cerebral cortex through the skull by rapid switching of a strong (~1.5

T) magnetic field in the coil. The duration of a single TMS pulse was 200 us: the pulses were delivered infive-pulse trains of 400 ms duration each (between-pulse interval: 100 ms; minimum between-train interval:1,500 ms). In each subject, the coil was positioned over the left FEF using frameless stereotaxy [2].

Results and ConclusionsA significant positive correlation between CBF and the number of pulse-trains was observed in the targetregion, i.e. the left FEF. Furthermore, positive co-variations were also observed in several areas of the visualcortex, namely in the left medial parieto-occipital cortex, and in the left and right superior parietal cortex.In addition, a positive correlation was found in the right supplementary eye-field located on the medial wallof the frontal lobe.

Our findings confirm that (1) TMS induces focal changes in brain activity which, in turn, lead to changes inregional CBF, and (2) such changes can be observed not only at the stimulation site but, most importantly,in regions presumably connected with this site.

References[1] T. Paus. Neuropsychologia, 34:475-483, 1996.

[2] T. Peters et al. IEEE Trans. Med. Imag., 15:121-128, 1996.

S43

ORAL SE SSION : METHODS

Conductivity Maps of White Matter Fiber Tracts usingMagnetic Resonance Diffusion Tensor Imaging

D. S. Tuch, V. J. Wedeen, A. M. Dale, and J. W. BelliveauMassachusetts General Hospital - NMR Center

Charlestown, Massachusetts, USA

IntroductionThe spatial map of t he effective diffusion tensor given by magneti c resonance diffusion t enso r imaging (DT! ) providesaddit ional insight into th e elect r ical conductivity tensor. The conduct ivity and diffusion t en sors share, for examplethe same eigenvectors due to the com mon geometry, but the connect ion between the tensor eigenvalues, however, is anop en qu estion (1) . We obtain here the relationship between the diffusion and electrical cond uc tivi ty t ensor eigen valuesfor a white matter fiber tract and use it to generate conducti vity maps of the region .

MethodsA set of axial diffusion tensor images was obtained by echo-planar MRI using a 128x64 collec t ion matrix and TE=1 23ms, TR=8 s (2, 3). The architecture of the fiber tract was approximated by a triangular array of infinite cylinders of ra­dius r = 3 Jtm and packing fraction f. The fibers were assumed to be solid dielectrics of negligible conductivity and theextracellular medium was taken to have conductivity 1.22 Slm (4) . The electrical conductivity tensor of the fiber tractwas derived by the Maxwell-Garnett effective medium approximation (5). The diffusion tensor was found by MonteCarlo calculation for the same fiber tract geometry with intracellular and extracellular diffu sion D, = 1O-5 cm 2 Is andD. = 2.5 x 1O-5cm 2 / s respectively, and membrane permeability P = 10-3 cmls (4). We then obt ain a relation be­tween the conductivity and diffusion tensor eigenvalues independent of any a priori assumption on the packing fraction .

ResultsThe effective medium approximation yielded a radial-to-transverse anisotropy ratio of 10.74 in the close-packed limitf =0.907. The derived relationship between the conductivity and diffusion tensor eigenvalues was used to constructan elect r ical con ductiv ity t ensor map from the DTI (Fig. labc) .

1.0

(e)

Figure 1: (a) Axial slice of xy-diffusion weighted image with (b) radial and (c) tangential conduct ivity (S/m) eigenvaluemaps of the ROJ. Note the difference between (b) and (c) due to conductivity anisotropy.

ConclusionThe relationship between the diffusion and electrical conductivity tensors was found for whit e matter fiber tracts ,a llowing for the generation of conductivity tensor maps from DTJ. An extension of the mo del to other brain region swill require knowledge of t he packing fraction and solution of th e diffusion and conductiv ity tensors in ter ms of thepolarization of the ensemble. Empirical verification will fur thermore be required to valida te the model. The conduc­tivity t ensor map has application to the electrolmagnetoencephalography forward and inverse problems which as amatter of convention have assumed the white matter fib er tracts to be of isotropic homogen eous conductivity.

References1. Basser, PJ, Matiello, J , LeBihan, D. Biophys. J . 1994 ,66: 259-267 .2. David , TL, Wedeen , VJ , Weisskoff, RM, and Rosen, BR. 12th Ann. Proc, Soc . Mag. Res. Med . 1993 , 289.3. Wedeen , VJ, Davis TL, Weisskoff, RM, Tootell , R , Rosen , BR, and Belliveau, JW. Human Brain Mapping. 1995,SI : 69.4. Geddes, LA and Baker, LE. Med. & BioI. Eng. 1967 , 5: 271-293 .5. Schwartz,L. Physica A. 1994, 207: 131-136.6. Gudbjartsson, Hand Patz S. IEEE Trans. Med. Imaging. 1995, 14: 636-642.

844

ORAL SESSION: METHODS

An Investigation of fMRI Resolution in the Visual CortexP. De Weerdj A. Karnit* S. Kastnert L.G. Ungerleidert and P. Jezzardt

[Laboratory of Brain and Cognition. NIMH, NIH, USA ; *Weizmann Institute. Israel

~'=~~~-.; (

<....~~-- :; ...,;:-/ =.:;- .=- =:i=:;;.-;- _~~~

.":.~ ~~~ ~~:-_.t'i)e --~ =~

-~~~--e:_

::=~"-::.a -~=~~

L ,.=~~

~=l:F~

b

IntroductionIn primate and non-primate species, it has been well documented that early visual areas in cortex receive aprecise retinotopic projection of the visual world. Neighboring points in the visual field should thereforestimulate neighboring points in the visual cortex in these early areas. In this tMRI study. we investigatedthe minimal distance between neighboring region s of visual stimulation that is required to reliablydissociate neighboring regions of activation in cortical area V I in human volunteers. We also comparedtheoretical values of the extent of cortical activation from a given stimulus (calculated from knowledge ofthe human conical magnification factor ( I)) with the extent of cortical activation measured experimentally.

MethodAll experiments were conducted using a 1.5 Tesla GE Signa Horizon EchoSpeed magnet equipped withrapidly switching whole body gradients (22 mT/m, 120 T/m/s) and a home written gradient echo EPI

sequence (64x64- 128x 128 matrix, FOV 140-160 mmcoronal , TE=40 rns, TR=4 s). The echo planar images werecompared with a coaligned high resolution anatomical scan ofthe same subject' s brain (3D-SPGR, 512x384x128,TE=5 ms, TR=24 ms, flip angle 45' ) to accurately extractthe calcarine sulcus. 30 s blocks of visual stimuli were rearprojected onto a screen, which subtended 15' visual angle(horizontally) and 12' visual angle (vertically), placed at thesubject's feet. The stimuli consisted of structured patches ofline elements, in which the constituent line elements changedorientation by 90' at a frequency of 2 Hz (e.g., see Fig. I ).The subject held fixation by performing a "T" and "L"discrimin ation task, whilst various patches of texture werepresented at different locations. and with different spatialextents, in a quadrant of the lower visual hemifield. Figure 1show s three examples of the stimuli presented. In the case ofExpt. A. resolution of VI in the polar direction(corresponding to different positions in the medial-lateraldirection of the calcarine sulcus) was assessed with a series ofwedge stimuli with incremented numbers of wedges (4 wedgesare shown in Fig. la). Presentation of only even numbered

Flg.I : Various visual stimuli presented wedges was compared with presentation of only odd numberedto either quadrant in the lower herni-field. wedges . Experiments were run with a total of 2, 4, 6 and 8

wedges. In Expt, B (Fig . Ib), a square patch of texture of incremented visual extent ( l ", 2' . 4', 6' and 8')was presented at an eccentricity of 7.5", and the extent of cortical activation was compared with theoreticalcalculations. Finally, in Expt . C, a measurement was made of the tMRI signal in V 1 related to the presenceor absence of texture of various spatial extents (Fig . lc), which were centered at 7.5" eccentricity in a larger(l2'x 10') patch of texture

Results and ConclusionsIn Expt. A we were unable to distinguish groups of voxels with different time courses if the visual field ina quadrant was divided into 4 or more wedges. indicating that BOLD tMRI signals in a traditionalexperiment (as opposed to the phase-fit resolution experiment of Engel et al . (3)) are unable to resolvewedges separated by less than approx. 22.5" of polar angle. In Expt. B, the extent of activation on cortexthat was observed experimentally exceeded the extent that is predicted from theoretical calculations based onthe cortical magnification factor in humans. Moreover, Expt. C revealed that pixels with a time coursewhich correlated with the presence and absence of the smaller square could not be detected unless it was6"x6' in extent, or greater. Though in the case of Expt. C the absence of a response could be in part due tosensory interaction of the larger surround patch with the smaller hole (2), it nevertheless further indicates alimited resolution of the fMRI signal in V'l . When projected onto a cortical flat-map, our results indicate aresolution (point spread function) for traditional tMRI difference experiments of approximately 5 mm oncortex. However, it may be possible to obtain better resolution using the phase fit approach (1,3), or athigher magnetic field strength using mapping signal approaches to retinotopy (e.g ., 4).

ReferencesI. Sereno, M. et al ., Science, 1995, 268:889. 2. Kastner et al., Vision Res. , 1997, in press.3. Engel et al., Nature, 1994, 369:525. 4. Malonek, D. & Grinvald, A., Science , 1996, 272 :551.

845

ORAL SESSION: METHODS

[1] and

TR Variation Compensated Cardiac Gating Combined with RetrospectiveCorrection of Respiratory Artifact

Tuong Huu Le and Xiaoping HuCenter for Magnetic Resonance Research, Minneapolis, Minnesota

INTRODUCTION: A fundamental limitation of cardiac gated {I} tMRI is that variation in heart rate introducesvariations in TR, leading to T [ -relaxation related signal fluctuations. The present study describes a generaltechnique for compensating the effect of variable TR and combines it with our previous retrospective scheme {2} tocorrect for both respiratory and cardiac induced artifacts.METHODS: Our technique is applicable to imaging sequences that acquire an image with a single RF excitation(e.g., EPI). Considering the following model:

-T(n)

M t (n) = Mt(1) + [Mt (n -l)cos(a) - M

t(l)]e T,

M t (n) - M t (1) - T(n)In =-- [2],

M t (n -1)cos(a) - Mt(l) T1where Mo == equilibrium magnetization, a= excitation angle, Mt(1) = Mosina, and T(n) = TR between the nth andthe (n-1)th pulse. If a:>1t/2, Eq.[I] reduces to Mt(n) = Mt(I){I-exp[-T(m/F] ]} {3}. Ifthe flip angle is not 1t/2 butknown, Eq. [1] can be linearized as in Eq. [2] to solve for lITl with least squares fitting. In the general case wherea is not known, both a and :Ii need to be obtained numerically due to the nonlinear nature ofEq.[I].

Two approaches were used to solve for a and Tj , The first approach was a brute-force one where a number ofT['s were calculated using Eq. [2] for a range of a's and the T] and the a with the best fit in the least squares sensewere chosen as the solution. The range of a was specified to be around the average value for the first pixel to becalculated and to be around the a of a neighboring pixel for subsequent pixels. The second approach we used wasthe Levenberg-Marquardt algorithm for the nonlinear optimization {4}. The minimization used initial estimates of1t/4 and 1.5s for a and Tj , respectively. The value of a of neighboring pixels was also used for initialization.

The retrospective correction of respiratory motion was done first on the phase of individual k-space points {2},followed by Tj compensation of individual voxels in the image space. Tl compensation was performed after thereduction of respiratory artifact to ensure that the respiration does not affect the modeling of Tj relaxation.Subsequent to Tl compensation, retrospective removal of any residual respiratory artifact is carried out forindividual image voxels.

MR!. Consecutive T2*-weighted multi-slice single-shot EP images (TE: 30 rns, FOV: 20x20 cm2, matrix size:64x64) were obtained at 4T from a phantom and from human subjects. Two sets of experiments (100 images/slice)were acquired, one with a constant TR (2 s) and one with gating (2 cardiac pulses of a volunteer). Tj-dependentsignal fluctuation was removed from the gated images. Visual stimulation was achieved with LED matrix (GrassInstruments, Quincy, MA) flashing at 8 Hz. Activation maps were generated with the student t-test (p<.001).RESULTS & DISCUSSION: Fig. 1 presents the standard deviation maps of the phantom images. A surface coilwas used to illustrate that the T I correction technique is not affected by B1 inhomogeneity since both the excitationangle and T1 were derived for individual voxels in the image.

(a) TI Compcsna tcd.(j ro i =0.43 4. (b)Cardiac Ga ted. (jro i =1.454 . (c) ConstantTR . (jroi = 0.41 5.

FMRI maps through a region ofthe LGN after (a) and before (b) Tj compensation are shown in Fig. 2. The tMRImap ofthe same slice from a study with a 2.0s-fixed TR (not shown) consists of LGN activation that is intermediatein spatial extent relative to Figs 2a&b. Two factors, (i) physiological fluctuation and (ii) variable-TR inducedfluctuation, contribute to the differences in the extent of LGN activation between Figs 2a&b. Our results indicatethat the combined approach presented here has the highest sensitivity. Supported by the NIH (RO1 MH55346).

1. Glover, G.H. & N.J. Pelc, Magn Reson Ann, pp. 299-333 (1988).2. Hu, X., et al., Magn Reson Med, 34:201-212 (1995).3. Guimares, A.R., et aI., Neurolmage, 3: Abstract 89 (1996).4. Levenberg, K., Quarterly Appl Mathematics, 2:164-168 (1944).

S46

ORAL SESSION: METHODS

6 - ARST

5 - "4-

3 -

2 -

0

Selective Averaging of Individual Trials Using fMRIA.M. Dale and R.L. Buckner

MGH-NMR Center and Harvard Medical School, Boston, USA

Introduction: A major limitation in conducting functional neuroimaging studies, particularly for cognitiveexperiments, has been the use of blocked task paradigms . A recent demonstration that tMRI can detect activationfrom individual trials spaced widely apart suggests that mixed trial designs are possible (I) . Here, using selectiveaveraging techniques similar to those used in ERP experiments, we demonstrate tMRI responses to single trialsspaced as little as 2s apart. These data provide further evidence that the tMRI response is linearly related to theneuronal response, greatly simplifying the analysis and interpretation of tMRl data (2) . Importantly, a linear systemallows for direct deconvolution of multiple overlapping trials . The ability to analyze single trial , or event-relatedsignals, provides for a class of experiments which cannot be conducted using blocked designs; trial types can berandomly intermixed and selective averaging based upon trial type and/or subject performance is possible.

Methods: Activation in visual cortex was studied using echo planar gradient echo imaging (BOLD) at 1.5T(Tke ls, TE=5Oms, 0.=90°, five 7mm thick slices perp. to the calcarine). In the first study (N=4), trials consisted offull-field checkerboard (8Hz counterphased) stimuli presented for Is. To test the linearity of the BOLD response toclosely-spaced trials, clusters of either one, two, or three trials (2s or 5s interstimulus interval), were presented in arandomized and counterbalanced order once every 20s. In the second study (N=2), Is hemifield stimuli were randomlypresented to the left or right visual field during each 240s run. The interstimulus interval was randomly jitteredbetween 3 and 7s or 8 and 12s. Selective averaging was used to separate out the two trial types. Statistical maps (t­statistic) were then generated by computing the difference between trial types and correlating this difference with thepredicted hemodynamic response function.

Results: (A) shows the average tMRI response from visual cortex using 36 averages per condition, time-locked tothe beginning of each cluster (consisting of I , 2, or 3 trial s each). By subtracting the time-course of clusterscontaining one trial from those containing two trials, and those with two trials from those with three trials , thefMRI signal for each trial can be estimated (B). The observed similarity between the estimated single-trial responsessupports the linear model, although a slight departure from linearity is observed in the response to the first eventrelative to subsequent events. (C) shows statistical difference maps from the second study based on 144 averages perhemifield . Clearly defined left and right hemifield activation is observed in the appropriate hemispheres (p<.OOOl).

8 - A PAW fMR SIC?NA L 8 DEOOM=lCSITION OF 93NAL7 -

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18TIME (SEq

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18TIME (SEC)

Condusions: For visual checkerboard activation, the tMRI BOLD signal adds in a roughly linear fashion acrosssuccessive trials even at very short (2s) intertrial intervals. Furthermore, using selective averaging techniques, it ispossible to obtain robust activation maps for rapidly presented randomly mixed trial types. These results suggest thatselective averaging and linear deconvolution methods may enable tMRI experimental designs identical to those usedin typical behavioral and ERP studies.

References: 1. Buckner, RL., Bandettini PA., et al . PNAS 1996,93:14878-14883.2. Boynton, GM ., Engel SA.,et aI. J. Neurosci. 1996, 16:4207-4221

S47

ORAL SESSION: METHODS

A neural network classifier for SPECT in Alzheimer's disease:Correlation with cognitive function.

S. Halkjeer (1), G. Waldemar (2), B. Lautrup (1), G.B. Paulson (2).CONNECT, the Niels Bohr Institute, University ofCopenhagen (1) and the Neurobiological

Research Unit, the Neuroscience Center, Rigshospitalet (2), Copenhagen, Denmark.

Introduction:In recent years artificial neural networks have proven to be a valuable supplement to conventional discriminantanalysis in medical pattern recognition tasks. The aim of the present study was to evaluate the response of a neuralnetwork classifier for SPECT perfusion images in patients with a clinical diagnosis of Alzheimer's disease andhealthy subjects. To make the classification task simple the network training was based on only 8 regional valuesfrom the SPECT image sets. The response of the network was correlated to the cognitive function as measured bythe Mini-Mental State Examination (MMSE) score, in order to see whether the continuous network output could beinterpreted as a measure of disease severity.

Methods:99mTc_HMPAO SPECT data sets from 25 patients with a diagnosis of probable Alzheimer's disease (mean age 70years [range 53-83 years]) and 25 healthy control subjects (mean age 70 years [range 53-83 yearsj) were includedin the analysis. A conventional region of interest (ROn based parametric analysis of these image sets was presentedpreviously (1). Eight large ROIs were selected for the present analysis: The left and right frontal, temporal, andparietal cortex, and the left and right hemisphere. The original set of 8 perfusion values representing each subjectwas transformed into a new set of 8 values consisting of sums and numerical differences between corresponding leftand right regions. A neural network was then trained on the binary classification problem based on these values.During training the network was pruned in order to discover the optimal network architecture. After training, acalculation of the saliencies of the network parameters ranked the lobar regions according to their importance in theclassification task. The continuous output of the network was compared to the corresponding MMSE scores.

Results:The classification problem was found to be linearly separable. The resulting ROC curve of the linear networkclassifier had a ROC area of 0.93. A study of the saliencies of the input variables showed that the response of thenetwork was largely based on four of the eight input variables. The correlation coefficient for the relation betweenthe response of the linear network classifier and the MMSE scores was -0.7 (p<O.OO1).

Conclusions:By using the method of pruning the classification task was found to be linearly separable. The ROC area of the linearnetwork classifier was comparable to that of more complex network classifiers found in similar analyses (2,3). Theconcept of parameter saliencies may provide important information about the topography of perfusion patterns inAlzheimer's disease. Although trained on a binary classification problem only, the significant correlation betweenMMSE scores and the corresponding continuous network output indicated, that the network output providesinformation about the disease severity. Furthermore, this finding indicated, that SPECT perfusion patterns reflectdisease severity, and that the relationship between MMSE scores and focal perfusion deficits is linear. Neuralnetwork classification is a non-observer dependent and consistent data analysis method which may be used as asupplement to conventional visual and parametric image analysis in SPECT.

References:1. Waldemar G, Bruhn P, Kristensen M, et aI. Heterogeneity of neocortical cerebral blood flow deficits in dementiaof the Alzheimer type: A 99mTc-HMPAO SPECT study. J Neurol Neurosurg Psychiatry 1994;57:285-295.2. Chan KH, Johnson KA, Becker JA, et aI. A neural network classifier for cerebral perfusion imaging. J Nucl Med1994;35:771-774.3. Page MPA, Howard RJ, O'Brien JT, et aI. Use of neural networks in brain SPECT to diagnose Alzheimer's disease.J Nucl Med 1996;37:195-200.

848

ORAL SESSION: METHODS

Detection of Brain Activity during Mental Rotation in a Single Trial by FMRIW. Richter, A. P. Georgopoulos", K. Ugurbil, and S.-G. Kim

Center f or Magnetic Resonance Research, University ofMinnesota, MinneapoLis, MN 55455{Brain Sciences Center, Veterans Affairs MedicaL Center, Minneapolis, MN 55417

I . Introduction Functi onal Magnetic Resonance Imaging (tM RI) is an extreme ly valuable method to map brainfunctio n. However, it suffers from a lack of sensitity as well as temporal resolution . The sensitivity disadvantagemay be overcome by ave raging, either ove r many trials or over many subjects, but ave ragi ng leads, by definition ,to a loss of information about individual trials or individual subjects. When cog nitive processes are mapped.indiv iduals may employ different strategies to perform a task, and eve n change their strategies whil e they arelearni ng. Hence it is extremely desirab le to measure cortica l ac tivity by fM RI in a single trial. Here we studied awell-known cognitive task , the mental rotation of three-d imensional objects. ' This task involves man y areas ofthe brain , and subjects ge nerally require times on the order of several seco nds to co mplete it. It has bee n studiedby tMRI by several groups.v' but always dur ing a "steady state condition" of the brai n, requiring co ntinuousrepetition of the task . We demonstrate that a single execution of a mental rotati on task can reprodu cibly bedetected by fMRI.

2. Methods Experiments were carried out with a whole body ima ging system with a head gradient insert. Threecontiguous coronal 10 mm thick slices were chosen, the most posterior of which contai ned the most posteriorpart of the parieto-oc cipital sulcus . Typically 408 singl e-shot blipped echo planar images were acquired (TE = 25ms, TR = 870 ms , matrix size = 64x64). Four volunteers (2 male, 2 female) were studied. The computer­generated paradigms were displayed on a rear-projection screen. Dur ing each experim ent, ni ne paradigms wereshown, appro ximately one every 35 seco nds . Each paradi gm consisted of a pa ir of three-d imensional objects[ada pted from ref. (I)] . The two objects show n were eit her identi ca l or mirror images of one another; the subjectschose between these two options and pressed one of two butt ons on a keypad accordingl y. Then the scree n wentblank unt il the display of the next paradig m. Two ex periments were performed ; in one, the objects were notrotated with res pec t to eac h other (rota tion angle = 0°). In the other experimen t, the rotat ion angle was 100°. Datawere ana lyzed by timecourse cross correlation. Each tirnecourse was correlated with forty reference functio ns wi thdifferent "on" widths and time shifts (nine "on" periods each). This ensured that all activated pixels were found,irrespective of temp oral shift s in neuronal activity or hemodynamic response, or widt h of response functi on.Pixels with a cross-co rrelation coefficient of at least 0 .5 were considered "ac tive".

3. Results The figure shows the average timecourse of all activated pixels in the par ietal lobe for one subject(100° ro tation angle). The display of the paradigm is schematically indicated by the sq uares. For each singleexecution of a task , the re is a corresponding peak in the timecour se. In order to verify that the activation is indeeddue to mental rota tio n, ac tive pixels in the par ietal and occ ipital lobe were co unted for both rotation ang les. At (Yrota tio n ang le, no men tal rotation takes place . In the table, the number of act ivated pixels in the parietal andoccipital lobe is given for each rotation angle and eac h subjec t. Despite large differences between subjects, thenumber of activated pixels is always considerably larger at 100° rotation angle than at 0° . Hence most act ivationthat is measured is inde ed due to the performance of me ntal rotation.

4. Conclusion Mental rotation of three-dimensional objec ts was manifest in the tMRI signal in a single trial.Hence differences between individual subjects may be assessed and compared to behavioral parameters, andlearning effects in the same subject may be investigated.

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

References1. Shepard, R.N. and Metzler, J., Science 1971,171 : 7012. Tagari s, G . et al. , NeuroReport 1996,7: 7733. Co he n M . S. et al. , Brain 1996,119: 89

Average timecourse in the parietal lobe (one subject)Number of activated pixels as a function of rotation angle

• • • • • • • • •

parietal lobe occipital lobe(Y 100° (Y 100"

subj ect I 34 199 14 103subject 2 7 45 4 6subjec t 3 2 184 0 246subject 4 6 74 0 52

JOO200100

-4~ ""

II

t lme (s)

S49

ORAL SESSION: METHODS

FMRI Studies of Face Memory using Random Stimulus SequencesV.P. Clark, J. Ma. Maisog, and J.V. Haxby

SFBI, LBC, NIMH, NIH Bethesda, MD USA

Background Most previous studies of human brain organization using functional magnetic resonance imaging(fMRl) have employed stimulus presentation method s in which trains of similar stimuli are presented in repeatedblocks. This method cannot be used to examine responses to unpredictable target stimuli. Moreo ver, thespeci ficity of functional data obtained using blocked experimental designs may also be compromised by thesubjects' expectancies regarding upcoming stimuli within blocks , and changes in the ir level of arousal andattentional state between blocks ( 1,2). Lastly, most electroencephalographic and magnetoencephalographicstudies have employed randomized interleaved sequences of multiple stimulus types. For comparison with thispre vious research, fMRI paradigms that use randomized sequences are needed. In order to overcome theseproblems, we have devi sed a new method that uses tMRI to identify the average functional responses to individualstimuli presented in randomized, interleaved sequence s. We have used this method in a study of face perception andmemory to obtain independent measures of responses to three different types of stimuli: scrambled faces, novelfaces, and a memorized target face.

Methods A GE Signa 1.5 Tesla MRI system was used to acquire whole-brain echo-planar MRI data with bloodoxygen level dependent (BOLD) contrast in seven subject s. Local cortical activity associated with the perceptionof a memorized target face, novel faces, and scrambled faces was examined by presenting stimuli (0.5 Hz, 100msec lSI) in pseudo-random sequences. Subjects were trained before scanning to make a speeded button pressresponse to each presentation of the target face . Data were analyzed using multiple regression with three regressorsof interest, each tracking the predicted response to one stimulus type. Stimulus sequences were developed suchthat the predicted BOLD responses to each stimulus type were uncorrelated (r < 0.05).

Results Activity was found for all stimuli in ventral posterior cortex near lower-order visual cortical areas thatrepresent simple visual features (Figure I). In contrast, the presentation of whole faces activated more anteriorlocations of occipitotemporal cortex, in higher-order visual areas thought to represent more complex features, suchas face identity. Detection of the memorized target face activated more lateral occipitotemporal cortex than didnovel faces, with additional activity found in frontal and parietal cortex.

Figure I.

Conclusions These results show that independent BOLD responses to different stimuli presented in randomized,interleaved sequences can be obtained using fMRI. The response to whole faces vs. scrambled faces agreed wellwith previous fMRl experiments using a blocked stimulus design, validating this new technique. In addition, therespon se to the memorized target face revealed region s of lateral inferior temporal, frontal and parietal cortex thatare involved in the recognition of memorized faces.

1. Haxby JV, Horwitz B, Ungerleider LG, Maisog J, Pietrini P & Grady CL. J. Neurosci . 1994, 14: 6336-6353.2. Clark VP, Keil K, Maisog J, Courtney S, Ungerleider LG & Haxby N . NeuroImage 1996,4: 1-15.

S50