Exp Brain Res (2008) 188:63–75

DOI 10.1007/s00221-008-1339-3

RESEARCH ARTICLE

Gaze inXuences Wnger movement-related and visual-related activation across the human brain

Patrick Bédard · Arul Thangavel · Jerome N. Sanes

Received: 5 December 2007 / Accepted: 28 February 2008 / Published online: 19 March 2008© Springer-Verlag 2008

Abstract The brain uses gaze orientation to organizemyriad spatial tasks including hand movements. However,the neural correlates of gaze signals and their interactionwith brain systems for arm movement control remain unre-solved. Many studies have shown that gaze orientationmodiWes neuronal spike discharge in monkeys and activa-tion in humans related to reaching and Wnger movements inparietal and frontal areas. To continue earlier studies thataddressed interaction of horizontal gaze and hand move-ments in humans (Baker et al. 1999), we assessed how hor-izontal and vertical gaze deviations modiWed Wnger-relatedactivation, hypothesizing that areas throughout the brainwould exhibit movement-related activation that dependedon gaze angle. The results indicated Wnger movement-related activation related to combinations of horizontal,vertical, and diagonal gaze deviations. We extended ourprior Wndings to observation of these gaze-dependenteVects in visual cortex, parietal cortex, motor, supplemen-tary motor area, putamen, and cerebellum. Most signiW-cantly, we found a modulation bias for increased activationtoward rightward, upper-right and vertically upward gazedeviations. Our results indicate that gaze modulation ofWnger movement-related regions in the human brain is spa-tially organized and could subserve sensorimotor transfor-mations.

Keywords Finger movement · Functional MRI · Gaze position · Human

Introduction

Humans commonly use their hands to reach, grasp, andmanipulate objects, often using visual guidance. To performthese movements, the brain processes the location and phys-ical properties of an object via visual information coded rel-ative to gaze orientation, that is, in a gaze-centered frame ofreference (Buneo and Andersen 2006). Psychophysics stud-ies have provided substantial evidence that gaze orientationinXuences accuracy of hand movements (Bock et al. 1986;Enright 1995; McIntyre et al. 1997; Desmurget et al. 1998;Henriques et al. 1998), thereby demonstrating the impor-tance of gaze signals for planning and controlling handmovements. These results suggest that hand movements areplanned in a gaze-centered frame of reference (McIntyreet al. 1997; Henriques et al. 1998; Buneo and Andersen2006). In addition, gaze orientation can inXuence identiWca-tion of a sound source (Lewald 1997) and spatial navigation(Hollands et al. 2002). Therefore, gaze orientation repre-sents a signiWcant input signal that the brain computes whenplanning hand movements as well as other tasks.

Despite the importance of gaze in controlling everydaybehavior, the precise mode that gaze orientation aVectsbrain processing still remains somewhat elusive. Neuralrecording studies with monkeys and neuroimaging workwith humans have revealed that gaze orientation modiWesneuronal spike counts and MRI signal in various parts ofthe brain. In monkey, neuronal spike counts are modulatedupon a reaching movement as a function of gaze orientationin the parietal cortex (MIP, area 5, V6A; Andersen andMountcastle 1983; Andersen et al. 1985; Batista et al.1999; Battaglia-Mayer et al. 2000; 2003; Buneo et al. 2002;Cisek and Kalaska 2002) and the ventral and dorsal part ofthe premotor cortex (PMv and PMd; Mushiake et al. 1997;Boussaoud et al. 1998; JouVrais and Boussaoud 1999;

P. Bédard · A. Thangavel · J. N. Sanes (&)Department of Neuroscience, Alpert Medical School of Brown University, Box GL-N, Providence, RI 02912, USAe-mail: Jerome_Sanes@brown.edu

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Cisek and Kalaska 2002) but not in the primary motorcortex (M1; Mushiake et al. 1997). Neurons in the visualcortex also exhibit gaze-related modulation of spiking uponvisual information processing (Trotter and Celebrini 1999;Rosenbluth and Allman 2002).

Human brain activation studies have also indicated thatgaze angle can modulate information processing in a vari-ety of brain areas involved in planning and preparing skele-tal movements (Baker et al. 1999; DeSouza et al. 2000;2002; Medendorp et al. 2003; Andersson et al. 2007).These gaze eVects occur for tasks that required gaze align-ment with Wnger pointing (DeSouza et al. 2000; Medendorpet al. 2003) and simply for arm position (Baker et al. 1999).Therefore, gaze eVects on movement-related activationoccur for dynamic pointing and for postural maintenance.

In the current work, we aimed to achieve a broaderunderstanding of the spatial organization of gaze eVectson brain representations for human voluntary movements,beyond the earlier descriptions of how horizontal gazemodulated hand movement-related activation (Baker et al.1999; DeSouza et al. 2000; Medendorp et al. 2003).Revealing how vertical gaze deviations inXuence Wnger-related activation in humans also has importance since thelower visual Weld seems over-represented in visual andparietal areas compared to the upper visual Weld (Gallettiet al. 1999; Dougherty et al. 2003). This over-representa-tion might mediate the observed lower visual Weld advan-tage for controlling visually-guided movements (Danckertand Goodale 2001; Khan and Lawrence 2005). Prior stud-ies focused upon frontal and parietal structures, althoughother brain structures, such as the cerebellum, have clearroles in oculomotor and arm motor control (Desmurgetet al. 2001; Robinson and Fuchs 2001; Miall and Reckess2002). Therefore, we undertook a more comprehensiveevaluation of gaze eVects on movement related activationin the entire human brain by asking participants to per-form a visually-cued Wnger-tapping task and to maintaingaze on various visible targets arranged vertically and hor-izontally.

We hypothesized that visual, parietal, and frontal motorareas would exhibit horizontal gaze eVects and that move-ment-related activation would increase as gaze deviatedtowards the eVector. We also expected that sub-corticalregions such as the cerebellum and basal ganglia wouldshow gaze eVects since these regions have involvement ingenerating hand movements and they have reciprocal con-nections with cerebral cortex. We also hypothesized thatdeviating gaze vertically would modulate movement-related activation; here we reasoned that since lower visualWeld has an over-representation from behavioral and func-tional imaging work, there would be an increase of activa-tion as gaze deviated downward in the visual, parietal, andfrontal motor areas.

Materials and methods

Participants

Fifteen healthy adults (aged 19–34 years; 10 female, 5male, 13 right-handed) recruited from the Brown Univer-sity community participated in this project. They had nohistory of neurological, sensory or motor disorder. All par-ticipants provided written informed consent according toestablished Institution Review Board guidelines for humanparticipation in experimental procedures at Brown Univer-sity and Memorial Hospital of Rhode Island (the site of theMR imaging). Participants received modest monetary com-pensation for their participation.

Tasks and apparatus

Participants performed a repetitive Wnger-tapping task,using the right index Wnger while statically directing gazeto one of nine visually deWned locations (Fig. 1a). The sim-plicity of the task likely did not induce any nuisance eVectsdue to two participants using their non-dominant indexWnger. After receiving task instructions, participants prac-ticed the procedures for a few minutes before becomingpositioned in the MRI in the standard supine body positionwith the right arm lying fully extended and pronated besidetheir right side (Fig. 1b). An MRI compatible game padequipped with push-buttons (Resonance Technology, Inc.,Northridge, CA) sensed the Wnger movements which wereregistered and stored in a Macintosh G3 Powerbook. Partic-ipants wore a set of headphones, for ear protection andcommunication with the experimenter, and a pair of MRIcompatible LCD-based goggles for delivery of visual stim-uli and eye movement monitoring via an embedded infraredcamera (Resonance Technology, Inc.; 800 £ 600 pixelsresolution; accuracy of §1 degree; Viewpoint software,Arrington Research, Scottsdale, AZ). A set of nine targets(circles, 10 mm diameter) in a 3 £ 3 array (deviation of 10°of visual angle) was presented to the participant (Fig. 1a,b). This arrangement has similarity to experimental designsemployed by others (e.g., Andersen and Mountcastle 1983;Boussaoud et al. 1998; Bremmer et al. 1999). All nine tar-gets appeared as white dots on a black background, andthey remained visible throughout the experiment. We usedPsychToolbox for Matlab 5.2 (Mathworks, Natick, MA,http://www.psychtoolbox.org/; Brainard 1997; Pelli 1997)running on a Macintosh Powerbook 3400c to generatevisual stimuli.

Each of six successive periods of acquiring functionalMRI data consisted of three sets of 16 trials each. For eachand every set of 16 trials, 18 sets of trials in total, partici-pants Wxed gaze upon one of the 9 targets as instructed bythe target having colors other than white for each trial, Wrst

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red, then yellow, then blinking green at 3 Hz (Fig. 1a). Theblinking green target signaled participants to emit threesynchronous taps using the right index Wnger. The Xashingsequence (red-yellow-blinking green) was repeated 16times for a particular target; then the same sequenceoccurred for another target until all nine targets had becomesampled, upon which all nine targets become sampled onceagain, thereby yielding two sets of 16 trials of functionalMRI data for each of the nine targets. The sequence of trialevents yielded functional MRI signals for 288 Wnger-move-ment events (9 targets £ 2 presentations £ 16 trials). After16 trials of gaze directed to a particular target, all targetsturned to yellow for 500 ms to indicate that the Xashingsequence would occur for a target at a diVerent location.Participants were instructed to maintain gaze Wxated on asingle target until the set of 16 trials Wnished. The presenta-tion order of the Wrst and second set of nine targets occurredaccording to a Latin-square design to eliminate potentialorder eVects and was randomized across participants. Eyeposition was monitored on-line and recorded via an infraredcamera mounted inside the goggles (sampling rate 30 Hz),and participants became informed if their gaze had movedaway from a particular target after each scan (i.e., three setsof 16 trials). Participants succeeded in maintaining gaze atthe requested location for the duration of each set of 16 tri-als such that no trials became rejected due to non-compli-ance with the gaze Wxation requirements.

Trials occurred with randomly presented trial-onset-asynchronies ranging from 3.84 to 7.68 s in 0.96 s incre-ments, so as to facilitate the subsequent event-related func-tional MRI data analysis procedures. Each trial had thefollowing time-course (x refers to one of the trial-onset-asynchronies): red target: 0.96 s + (x ¡ 1.96 s)/2; yellowtarget: (x ¡ 1.96 s)/2); green target Xashing, 1 s.

MRI procedures

We used a 1.5 T Symphony MRI Magnetom MR systemequipped with Quantum gradients (Siemens Medical Solu-tions, Erlangen, Germany) to acquire anatomical and func-tional MR images. Participants lay supine inside themagnet bore with the head resting inside a circularly polar-ized receive-only head coil used for radio frequency recep-tion; the body coil transmitted radio frequency signals.Head movements were reduced by cushioning and mildrestraint. After shimming the standing magnetic Weld, weacquired a high-resolution three-dimensional anatomicalimage consisting of 160 1 mm parasaggital slices (magneti-zation prepared rapid acquisition gradient echo sequence,MPRAGE; repetition time (TR) = 1,900 ms, echo time(TE) = 4.15 ms, inversion time = 20 ms, 1 mm isotropicvoxels, 256 mm Weld of view). We then acquired T2*-weighted gradient echo images using the blood oxygena-

Fig. 1 a Task schematic. Participants viewed nine targets and Wxed gazeat 1 for 16 consecutive trials. In each trial the target’s color changed fromred to yellow to green (left-middle-right panel for red-yellow-green,respectively) at which point the participant tapped three times with theright index Wnger. Trial-onset-asynchronies were 3.84, 4.8, 5.76, 6.72, or7.68 s (random presentation). b Experimental set-up. Participants wore apair of MRI compatible goggles and tapped with their right index Wnger.c Mapping of regression models for the horizontal (left), vertical (middle),and diagonal (right) dimensions. d Averages gaze positions for a subjectfor all trials as the target appeared green. See text for additional details

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tion level-dependent (BOLD) mechanism (Kwong et al.1992; Ogawa et al. 1992). Forty-eight slices were acquiredcovering the whole brain (TE = 38 ms, TR = 3.84 s, Weld ofview = 192 mm, image matrix = 64 £ 64, 3 mm slice thick-ness for 3 mm isotropic voxels). The MRI system acquiredthe slices in an ascending interleaved manner. Images wereacquired during 81 volumes (75 volumes for three partici-pants) in each of six periods of three 16-trials sets of (Wveperiods for one participant, see “Tasks and apparatus”above). The experimental procedures lasted 31.1 min andanother »9 min for the high-resolution T1-weighted MRimage.

MRI signal processing and analysis

Images were processed, analyzed and visualized usingAFNI (analysis of functional neuroimages; Medical Col-lege of Wisconsin; National Institute of Health: http://afni.nimh.nih.gov/afni, (Cox 1996; Cox and Hyde 1997)and FSL software packages (FMRIB software library, http://www.fmrib.ox.ac.uk/fsl/). The Wrst two volumes in eachscan were discarded from further consideration due to T1saturation eVects. The anatomical and functional datasetswere co-registered and normalized with FSL to the MNItemplate (Mazziotta et al. 1995) using linear (aYne) regis-tration (Jenkinson and Smith 2001). The BOLD dataset foreach participant was motion corrected using six motionparameters (x, y and z translations and roll, pitch and yawrotations), the linear trends were removed, and it was spa-tially smoothed with a 6 £ 6 £ 6 mm Gaussian kernelusing AFNI tools.

The occurrence of each tapping cue in each of the nineconditions (i.e., the nine target positions) was convolvedwith a gamma variate function (AFNI, waver tool; Cohen1997) to yield an impulse response function. We then usedthese nine reference functions and the six motion correctionparameters as inputs to a multiple regression analysis(AFNI, 3dDeconvolve tool) to estimate the � weight ofeach condition on a voxel-wise base. AFNI automaticallycomputes a baseline activation level with this model.Finally, we normalized the estimated � weights into per-centage change signal by dividing them by the mean signalof the entire time-series.

We Wrst determined those voxels that exhibited signiW-cant Wnger movement-related activation by testing the nullhypothesis that Wnger movement did not elicit activationusing a t test for each target separately and retaining voxelsthat passed a threshold of p · 0.001 for at least one target.We then corrected the resulting voxel-level analysis formultiple comparisons by setting a cluster threshold ofp · 0.05 corresponding to 12 adjacently clustered voxels.The cluster-level analysis used the Monte Carlo samplingprocedure (AFNI, AlphaSim tool) and yielded seven

clusters deemed to have Wnger movement-related activation(Fig. 2; Table 1).

Note that the two left-handed participants showed theexpected increased activation in the left hemisphere whentapping; this activation had similarly to that observed in theright-handed participants. As a check that inclusion of thesetwo individuals in the group of otherwise right-handed par-ticipants might have untowardly inXuenced the results, weconducted a subsidiary analysis without these participants.The results of this sub-analysis indicated the same clustersof activation for the group of right-handed participants andthe same gaze-dependent eVects on movement-related acti-vation. Therefore, we retained the two left-handed partici-pants in the data analyses reported here.

We then tested the null hypothesis that gaze position didnot modify Wnger movement-related activation in theseseven clusters by computing the slope of observed activa-tion across gaze conditions for each voxel within theseclusters for the horizontal, vertical, and diagonal compo-nents (tested independently). We set the regressors to iden-tify voxels showing increased activation as gaze deviatedrightward (horizontal) or downward (vertical), thoughopposite eVects would become detected with negativeslopes (AFNI, 3dRegAna tool). For the diagonal regression,we tested for increase of activation for gaze deviations fromthe upper left target towards the lower right one (UL-LR)

Fig. 2 Finger-related activation. Activation presented here resultsfrom data pooled across all targets. Note strong activation in classicallydeWned motor areas, such as contralateral M1, SMA, anterior cingulategyrus, and ipsilateral anterior cerebellum. See Table 1 for all activatedareas. CS central sulcus

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and from lower left target towards upper right one (LL-UR). In the horizontal dimension, we also used non-linearregression with weights of [1 2 2] for the left, center andright columns of targets to try to replicate the results ofBaker et al. (1999) who found a higher number of activatedvoxels for both straight ahead and rightward gaze devia-tions than leftward gaze. We then used t test across voxelsin each cluster to test whether the slopes diVered signiW-cantly from zero.

We also determined whether gaze position inXuencedvoxels that did not exhibit Wnger movement-related activa-tion. For this analysis, we created a masked dataset usingthose voxels identiWed in the previous analysis as havingWnger movement-related activation and ran linear regres-sion on the horizontal, vertical, and diagonal dimensionsseparately. In the horizontal dimension, we also used non-linear regression with weights of [1 2 2] for the left, centerand right columns of targets as in the previous analysis. Forthe horizontal and vertical regressions, we tested forincrease of activation as gaze deviated rightward and down-ward, respectively. For the diagonal regression, we testedfor increase of activation for gaze deviations from the upperleft target towards the lower right one (UL-LR) and fromlower left target towards upper right one (LL-UR).Figure 1c illustrates the mappings for the linear regressionsfor the horizontal, vertical and diagonal LL-UR regressionmodel to the targets. For all regressions, we tested also forthe opposite Wt to a model. We used a voxel threshold ofp = 0.001 and a cluster threshold of p = 0.05 correspondingto 11 adjacent voxels (smaller than the previous analysisbecause of the masking procedure).

We analyzed functional MRI data for 15 participants butbehavioral data for 14 participants since one behavioral data-set became corrupted. As noted, we monitored eye positionduring the MRI procedures to ascertain that gaze remainedWxed on a single target during each block of trials. Non-com-

pliance to the instructions occurred rarely; therefore, we hadno need to reject trial-data for any participant due to errantgaze positioning. Figure 1d illustrates gaze positions for eachof the nine targets for a single representative participant.Each dot represents the average of all samples that werewithin two standard deviations of the mean for a trial duringthe TAP event (1 s) and each ellipse represents the areacovering 95% of the average positions for each trial. Weeliminated eye-position data beyond two SD’s, since theytypically represented instability in the eye-tracking hardware.

We used the brain atlas of Duvernoy (1991), the cerebel-lum atlas of Schmahmann et al. (1999), and a navigableweb-based human brain atlas (http://www.msu.edu/»brains/brains/human/index.html) to localize activation tobrain areas and to assign Brodmann areas.

Results

Behavior

We addressed whether a particular gaze deviation aVectedbehavioral aspects of Wnger movements by computing thereaction time (RT) of Wnger movements (elapsed timebetween the green cue appearing and the Wrst tap, seeFig. 1a) by testing the null-hypothesis of no diVerence ofRT for each target, using a one-way ANOVA. This analysisrevealed no diVerence in RT across the nine targets,F8,117 = 0.35, with the mean (§SD) RT = 328 § 30 ms(averaged across all nine targets; range: 290–370 ms). Wealso considered whether participants, contrary to theinstructions, performed an unequal number of taps fordiVerent targets. The output of the one-way ANOVA failedto reject the null hypothesis that tap quantity did not diVeracross the nine gaze positions, with a mean number ofWnger taps per target of 3.05 § 0.05 (averaged across

Table 1 Cluster report for the Wnger-related activation

Cluster volume in �l with one voxel = 27 �l. Intensity represents the average activation across all targets. Coordinates represent the center of massof an activation cluster, with +x indicating left hemisphere. Percent of voxels shows proportion of voxels within a cluster with a positive slope forthe horizontal (left < center < right) and vertical dimensions (up < middle < low) with * indicating that the distribution of voxels is signiWcantlydiVerent than chance

Brain regions (BA) Volume Intensity Coordinates Percent of voxels

x y Z Horizontal Vertical

R Occipital cortex, lingual gyrus, Cuneus, SPL (18–19, 7) 7,857 ¡0.11 ¡9 77 14 73.5* 5.5*

L Primary motor cortex (4) 3,915 0.16 40 20 56 77.2* 48.9

R Cerebellum (CR-IV-V) 2,619 0.08 ¡12 55 ¡17 80.4* 22.7*

L Anterior cingulate gyrus (24) 1296 0.13 2 ¡1 54 87.5* 8.3*

R SPL (7) 945 ¡0.10 ¡25 63 58 100* 25.8*

L SMA (6) 405 0.06 12 5 46 86.7* 7.1*

R Putamen 324 0.06 ¡29 47 2 83.4 100*

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targets; F8,117 = 1.11). These results indicate that behaviorhad similarity across the various gaze locations.

Finger movement-dependent gaze eVects

We identiWed seven clusters that exhibited Wnger move-ment-related activation; their location appears in Fig. 2 andTable 1 provides additional details about these activationclusters. The largest of these Wnger movement related clus-ters appeared in occipital lobe and encompassed portions ofthe visual cortex, lingual gyrus (BA18, BA19), cuneusbilaterally, and right SPL (BA7); its location had consis-tency with prior work in our laboratory showing involve-ment of occipital cortical areas in visually paced tapping(Kim et al. 2005). We also found clusters in more classicalmotor regions, including the left M1 (BA4), right cerebel-lum (CR-IV-V), left ACC (BA24), right SPL (BA7), leftSMA (BA6), and right putamen.

Figure 3a depicts the percent signal change for eachcluster as a function of gaze positions in the horizontaldimension; the data revealed that all clusters exhibitedincreased activation as gaze deviated rightward. Our analy-ses did not reveal any cluster with the greatest movement-related activation when participants gazed leftward. Allseven clusters had slopes signiWcantly diVerent than zero(all p < 0.0005) as gaze deviated increasingly rightward,indicating signiWcant gaze eVects on Wnger movement-related activation. Note that for the clusters in SPL andvisual cortex the functional MRI signal was deactivated forall gaze positions; thus, gaze deviations toward the rightyielded less deactivation, in other words, a relative increasein activation as gaze position moved from the left to theright. The regression analysis using the non-linear [1 2 2]model also indicated that all clusters had slopes signiW-cantly diVerent than zero. However, we found that not all ofthe gaze-related patterns from individual voxels within anyparticular cluster exhibited a positive slope (Table 1). Toevaluate the distribution of gaze-related patterns typeswithin a cluster, we tabulated the percentage of voxels thatexhibited a gaze-related pattern with a positive slope andascertained whether this percentage occurred by chance.For all clusters, but the putamen, the percentage of positiveslopes diVered signiWcantly than what was expected bychance (X2 > 3.84 (df = 1), p < 0.05). In the putamen, acti-vation for 10/12 voxels exhibited a gaze-related positiveslope. The lack of signiWcance likely relates to power issueas 11/12 voxels with positive slope would have been sig-niWcantly diVerent than chance.

For vertical gaze, all but one of the clusters with move-ment-related activation exhibited slopes signiWcantly diVer-ent than zero. The clusters in the SMA, ACC, SPL,cerebellum, and visual cortex showed increased activationas gaze deviated upward, whereas the putamen had

increased activation as gaze deviated downward (allp < 0.002). The activation in M1 did not exhibit a verticalgaze eVect, i.e., slopes were not signiWcantly diVerent thanzero (p = 0.66). We also tabulated the percentage of voxelswithin each cluster that exhibited activation having positiveslope as gaze increasing deviated downward. This analysisrevealed that all, but M1, had more negative slopes thanwhat was expected by chance; the putamen had more posi-tive slopes than expected by chance (Table 1).

We found that all seven clusters with Wnger movement-related activation had slopes signiWcantly diVerent thanzero for the LL-UR model (all p < 0.005), and all clustersbut the one located in the putamen showed increased acti-vation for gaze deviating toward the upper-right; the puta-men exhibited increased activation for gaze deviatingtowards the lower left. For the UL-LR model all clustersbut the ACC and SMA (p > 0.01) had slopes signiWcantlydiVerent than zero and these showed increased of activationas gaze deviated towards the lower-right. Figure 3c illus-trates the Wnger movement-related activation for all gazepositions for the cerebellum, SPL, and putamen.

We also note that participants experienced asymmetricvisual input to the two hemispheres when they looked to theleft or to the right targets. Since the targets remained visiblethroughout the procedures, it is possible that some of theobserved activation patterns related to asymmetries invisual input, especially regarding lateralization of possibleactivation patterns. To address this potential confound, weexamined the spatial distribution of the positive and nega-tive slopes within the activation clusters relative to gazedeviating from left to right. We found that the clusterlocated in the region of the visual cortex exhibited a clearspatial dependence on visual input such that voxels in theleft hemisphere had negative activation slopes, that is, lessactivation as gaze deviated increasingly rightward, whereasvoxels in the right hemisphere had positive slopes, that is,more activation as gaze deviated increasingly rightward.No other activation cluster showed similar hemisphericeVects related to deviations of gaze angle. We found nospatial eVects for gaze in the vertical dimension.

Finger-movement independent gaze eVects

We next identiWed brain regions that exhibited systematicgaze-related modulation of activation independent ofWnger-movement activation. For the horizontal regression[1 2 3] model, we identiWed only a single cluster that exhib-ited increasing activation as gaze deviated from left toright; the cluster was located in the occipital cortex (104voxels; x = ¡13, y = 7, z = ¡1; max R2 = 0.24). The clusterin the occipital cortex found with the horizontal [1 2 3]model largely overlapped (81%; the remaining voxelsformed a small cluster of 10 voxels and the rest of the 9

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voxels were scattered; not shown) with a cluster in theoccipital gyrus/lingual gyrus (BA18) activated according tothe horizontal [1 2 2] model (Table 2). We also found 12voxels in the left MFG that exhibited increasing activation

as gaze deviated rightward. However, these voxels did notform a reliable and contiguous cluster since the activationof a single voxel in this region was slightly below(p = 0.0015) the rigorous statistical threshold (dark pink

Fig. 3 Gaze eVects of the Wnger movement-related activation for thehorizontal and vertical dimensions. a Activation for horizontal gazeshifts (pooled across vertical dimension). Movement-related activationincreases as gaze deviates towards the right for all clusters. b Activa-tion related to vertical gaze shifts (pooled across horizontal dimen-sion). Movement-related activation increased as gaze deviated upwardfor every cluster but the putamen in which activation increased as gazedeviated downward and the primary motor cortex with did not exhibit

vertical gaze eVects. c Finger-movement-related activation of all gazepositions for the cerebellum, SPL, and putamen. d Slopes of individualvoxels in the visual cortex cluster. Slopes show a spatial organizationwith negative slopes (more activation for leftward than rightward gazedeviation) appearing in the left hemisphere and positive slopes (moreactivation for rightward than for leftward gaze deviations) in the righthemisphere

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label in axial slices in Fig. 4a). We found four clusters withan activation pattern that conformed to the [1 2 2] horizon-tal model (Table 2, Fig. 4a). We found four activation clus-ters for the [1 2 2] model with two clusters located in anexpanse of right visual cortex (Fig. 4a, red label; on thecoronal view they are separated by the dashed line) involv-ing BA17, BA18, and BA19, the lingual and fusiformgyrus, and the right cuneus (most superior cluster). The

analysis also revealed a cluster in the left pre-frontal cortex(BA46) and one in the right medial frontal gyrus (MFG,BA8; axial slices). Figure 4a also illustrates the locations ofthese clusters and corresponding overlap with those clustersshowing activation conforming to the horizontal [1 2 3]model (red and yellow labels, respectively).

Deviations in vertical gaze yielded systematic variationin activation independent of Wnger movement for 11 clus-ters, 6 that exhibited increased activation as gaze deviatedincreasingly downward and 5 clusters that showed moreactivation as gaze deviated increasingly upward (in Fig. 4b,red and blue labels, respectively, Table 3). From those Wveclusters with upward gaze eVects, we found three adjacentclusters in the occipital cortex with one cluster located inthe occipital gyrus extending superiorly to the pre-cuneusand SPL (BA18, 7; inferior saggital image) and two clus-ters in the left cuneus (BA18; most superior saggitalimage); they showed increasing activation as gaze shiftedfrom the lower to the upper targets. We found two otherclusters with this eVect in the left IFG (BA10; not shown)and parahippocampal gyrus (37; axial image). The six acti-vated clusters best related to downward gaze appeared inthe parahippocampal formation (BA37; axial image) bilaterally

Table 2 Cluster report for the horizontal regression analysis: [1 2 2]model

All clusters showed increase of Wnger-related activation as gaze devi-ates rightward. R2 correspond to the amount (maximum) of explainedvariance (%)

Brain regions (BA) Volume R2 Coordinates

X y z

R Occipital gyrus, lingual gyrus (18)

2,646 0.22 ¡13 72 0

L Pre-frontal cortex (46) 513 0.13 43 ¡44 22

R Cuneus (18) 486 0.16 ¡10 79 18

R MFG (8) 351 0.12 ¡22 ¡38 35

Fig. 4 Horizontal, vertical, and diagonal gaze eVects. a Horizontalgaze eVects: brain responses principally for horizontal gaze shiftsshowing activation in the frontal gyrus bilaterally and occipital cortex(see Table 2 for all activated areas). Numbers refer to areas discussedin text. b Vertical gaze eVects: activation related to vertical gaze shiftsshowing labeling in the occipital cortex, parahippocampal gyrus andorbito-frontal cortex bilaterally (see Table 3 for all activated areas). cDiagonal gaze eVects : activation related to two diagonal regression

models, lower-left to upper-right (LL-UR) and upper-left to lower-right (UL-LR). For the LL-UR regression, areas with gaze eVects in-cluded a continuous cluster covering parts of the visual cortex, thesuperior parietal area and the cuneus, the cerebellum. For the UL-LRregression, gaze eVects occurred in the right lingual gyrus, left superiortemporal gyrus, and orbito-frontal gyrus bilaterally. Complete detailsin Tables 2, 3, and 4

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and in the anterior orbito-frontal gyrus bilaterally (BA11;axial image) and medially (BA11; saggital image) and rightfusiform gyrus (BA37; not shown).

We also found activation that tracked linear gaze shiftsalong the diagonal of the target array. Application of theLL-UR regression model (Fig. 4c; Table 4) revealed sevenclusters with two of these clusters exhibiting increased acti-vation as gaze deviated progressively from the lower-lefttoward the upper-right portions of the visual workspace(Fig. 4c, red label). We found a large activation cluster pos-teriorly and principally in the right hemisphere thatinvolved the lingual gyrus, the cuneus, and the visual cortex(BA17, BA18, and BA19) and extended superiorly to theright SPL (BA7). There was also a cluster in the left cere-bellum (CR-I) that showed the same eVect. Clusters thatexhibited increasing activation as gaze deviated from theupper-right toward the lower-left of the target array

(Fig. 4c, blue label) occurred bilaterally in the orbito-fron-tal gyrus (BA11; note that we found two clusters in eachhemisphere) and the left parahippocampal gyrus (BA37).Finally, the UL-LR regression revealed four clusters (greenlabels) located in the orbito-frontal gyrus bilaterally(BA11), left superior temporal gyrus (BA38; not shown),and right lingual gyrus (BA18).

Discussion

The current Wndings replicate previous Wndings that staticgaze orientation inXuences Wnger movement-related brainactivation in humans (Baker et al. 1999; DeSouza et al.2000) and neural spiking of cortical areas in monkeys(Andersen and Mountcastle 1983; Andersen et al. 1985;Batista et al. 1999; Battaglia-Mayer et al. 2000; 2003;

Table 3 Cluster report for the vertical regression analysis: [1 2 3] model

Brain regions (BA) Volume R2 Coordinates

X y z

R Occipital gyrus (18–19), SPL (7) 5,184 0.25* ¡4 83 25

L Anterior orbito-frontal cortex (11) 2,754 0.20 30 ¡57 ¡12

R Anterior orbito-frontal cortex (11) 2,133 0.18 ¡29 ¡55 ¡17

L Parahippocampal gyrus/ lingual gyrus (18) 1,539 0.18 27 46 ¡11

L IFG (10) 432 0.21* 28 ¡30 ¡26

L Cuneus (18) 405 0.16* 10 86 31

L Anterior orbito-frontal cortex (11) 351 0.18 1 ¡30 ¡27

R fusiform gyrus (37) 351 0.14 ¡36 37 ¡22

R Parahippocampal gyrus/hippocampus 351 0.14 ¡29 43 ¡7

L Cuneus (18) 324 0.13* 4 93 11

R Parahippocampal gyrus 297 0.12* ¡35 39 ¡13

R2 with an * refers an increase of Wnger-related activation as gaze deviates upward whereas those without refers to an increase of Wnger-related activation as gaze deviates downward

Table 4 Cluster report for the LL-UR and UL-LR diagonal regressions analysis

Brain regions (BA) Volume R2 Coordinates

X y z

LL-UR

R Occipital gyrus, cuneus, SPL (17,18,19,7)

6,615 0.22 ¡10 78 30

L Orbito-frontal cortex (11) 756 0.12* 47 ¡33 ¡15

L Cerebellum (CR-I) 513 0.15 24 86 ¡23

L Orbito-frontal cortex (11) 486 0.15* 31 ¡55 ¡16

L Parahippocampal gyrus (37) 459 0.11* 28 47 ¡7

R Orbito-frontal cortex (11) 351 0.16* ¡39 ¡30 ¡20

R Orbito-frontal cortex (11) 324 0.12* ¡36 ¡57 ¡17

UL-LR

R Lingual gyrus (18) 1,053 0.16 ¡15 71 ¡3

L Orbito-frontal gyrus (11) 351 0.11 22 ¡55 ¡17

L Superior temporal gyrus (38) 324 0.12* 26 ¡4 ¡38

R Orbito-frontal gyrus (11) 324 0.11 ¡15 ¡55 ¡18

R2 for the LL-UR regression with an * refers an increase of Wnger-related activation as gaze deviates left and downward whereas those without refers to an increase of Wnger-related acti-vation as gaze deviates right and upward. R2 for the UL-LR regression with an * refers an in-crease of Wnger-related activa-tion as gaze deviates left and upward whereas those without refers to an increase of Wnger-re-lated activation as gaze deviates right and downward

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72 Exp Brain Res (2008) 188:63–75

Buneo et al. 2002; Cisek and Kalaska 2002). We replicatethese gaze eVects in frontal and parietal areas and for theWrst time in the cerebellum and putamen. We also show thatthese gaze eVects have an orderly spatial organization muchlike that described for neural activity in monkeys (Bous-saoud et al. 1998; Bremmer et al. 1998). Finally, we showthat gaze orientation also has a global inXuence on activa-tion independently of Wnger movement, perhaps an atten-tional eVect, in a host of cortical and sub-cortical regionsacross the entire brain. These results suggest that gaze rep-resents an essential signal computed by the brain and that itunderlies a basic organizational principle for conveyingstatic and dynamic properties of visual input to wide sectorsof the brain. Nevertheless, the lateralization of the visualinputs for the gaze left and gaze right conditions alonecould have been a factor in some of the observed resultsand may for some areas prevent a clear diVerentiationbetween modulatory eVects related to visual input or gaze.

Gaze eVects on Wnger movement

The current Wndings provide support for widespread modu-latory eVects of gaze position on brain processing (e.g.,Trotter and Celebrini 1999; Buneo et al. 2002) and in par-ticular interactions between the ocular motor and skeletalmotor systems (Baker et al. 1999; Batista et al. 1999; DeS-ouza et al. 2000; Buneo et al. 2002; Cisek and Kalaska2002). We found static gaze eVects in M1, ACC, and SMA,thereby extending to some frontal motor areas prior obser-vations of gaze eVects in humans that had been mostly lim-ited to the parietal cortex (DeSouza et al. 2000; Medendorpet al. 2003). We also show for the Wrst time in humans thatmaintaining gaze in diVerent positions aVects Wnger move-ment-related activation in the putamen and cerebellum.While we show that gaze modulated movement-related pro-cessing in M1 (Baker et al. 1999), other groups have notfound this eVect (e.g., Mushiake et al. 1997; DeSouza et al.2000); the discrepancies may relate to diVerences in thetasks used across experiments, with gaze position modulat-ing tapping-related activation (Baker et al. 1999 and currentresults) but not neural processes related to reaching (Mush-iake et al. 1997; DeSouza et al. 2000).

We found that gaze held in diVerent positions had wide-spread inXuences in the cerebellum and putamen by modu-lating Wnger movement-related activation, likely havingrelationship to the presumed role of these areas in formingvoluntary motor commands. The cerebellum has reciprocalconnections with the parietal cortex (Middleton and Strick1998; Glickstein 2003) and participates in eye-hand coordi-nation and regulation of ongoing movements (Desmurgetet al. 2001; Robinson and Fuchs 2001; Miall and Reckess2002). The cerebellum also sends projections to the puta-men (Hoshi et al. 2005) which is connected to SMA and

M1 via the basal ganglia thalamocortical circuits (Alexan-der et al. 1986). The cerebellum and putamen along withparietal and frontal motor areas likely participate in gener-ating hand movements and our results show that thesestructures likely incorporate gaze signals as a common ref-erence frame. While our work does not directly addresshow these regions integrate gaze and reaching referenceframes, it nevertheless suggests interactions between brainsystems controlling gaze and skeletal movements.

Although previous studies have demonstrated that gazeorientation modulates human brain processing (e.g., Bakeret al. 1999; DeSouza et al. 2000; Medendorp et al. 2003),the current results indicate that these gaze eVects follow aspatial organization with a general preference for rightwardand upward gaze deviation, at least for Wnger-tapping. Thevertical and diagonal gaze modulation of Wnger movement-related activation may have particular functional signiW-cance. Prior work has demonstrated an over-representationof the lower visual Weld in visual and parietal areas (Gallettiet al. 1999; Dougherty et al. 2003), perhaps indicatingasymmetries for visual processing in the vertical dimension.This vertical asymmetrical eVect resonates with psycho-physical studies showing an advantage in performing goal-directed movements in the lower visual Weld (Danckert andGoodale 2001; Khan and Lawrence 2005; but see Binstedand Heath 2005). Our results demonstrating coding of verti-cal visual space in motor areas, such as SMA, cerebellum,putamen, and also parietal and visual brain regions providesa physiological substrate for the observations of Danckertand Goodale (2001) and Khan and Lawrence (2005).

The current Wndings of gaze modulation in visual, parie-tal and frontal cortical areas and the cerebellum have com-patibility with results indicating that these areas use a gaze-centered frame of reference to code visual information(Trotter and Celebrini 1999; DeSouza et al. 2002; Rosenb-luth and Allman 2002) and plan movements (Baker et al.1999; Batista et al. 1999; DeSouza et al. 2000; Buneo et al.2002; Cisek and Kalaska 2002). Spatial congruencebetween the angle of gaze, visual targets and the physicallocation of the arm—as we found here—seem to combineto yield enhanced activation in the human brain across avariety of structures. However, this remains speculativesince we have not tested the full range of hand and gazepositions. Note that one could have anticipated strongergaze eVects had the spatial congruence between gaze andhand been higher, that is had participants looked directlytowards their hand. There is however evidence that per-forming goal-directed movements with simple sensorimo-tor transformations yields more MRI signal thanmovements with complex sensorimotor transformations(Gorbet et al. 2004). Our task focused more on spatialalignment between gaze and hand in the same hemispacewhich probably reduced the strength of gaze eVects.

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The observations of modulated activation in the rightparietal cortex might seem surprising since one might haveexpected activation occurring predominantly in the lefthemisphere, contralateral to the right hand movements.However, this region, especially in the right hemisphere ofhumans, has a prominent role in spatial attention and infor-mation processing (Perenin and Vighetto 1988); a featureof the current task. Also, it is well recognized that the ipsi-lateral hemisphere is critically involved in hand movements(Davare et al. 2007; Kawashima et al. 1998; Schaefer et al.2007). Moreover, we observed that changes in gaze posi-tion modulated movement-relation changes in activation ina large portion of the visual cortex, a region not commonlyconsidered a “motor” structure (but see Kim et al. 2005).However, AstaWev et al. (2004) recently showed enhancedoccipital activation for movements performed toward acovertly attended peripheral visual target.

These Wndings might have relation to our showing gazeeVects in occipital regions upon visually triggered handmovements. Nevertheless, we do acknowledge that activa-tion observed in the visual cortex may have been driven byvisual processing alone since we also found gaze eVects inthis region in the Wnger-independent gaze eVects analysis.Furthermore, we also found this region had sensitivity tolateralization of visual inputs, a feature not present in otherareas, certainly not as would be predicted by a strict segre-gation of visual input from the two hemi-Welds. Therefore,gaze eVects in visual cortex may be driven more by lateral-ization of visual inputs rather than by gaze eVects onWnger-movement activation. We also did not Wnd activa-tion in traditional ocular motor regions such as the parie-tal, frontal or supplementary eye Welds (Krauzlis 2005),but consider that our task did not have saccades but gazeWxation.

Pure gaze eVects

Consistent with previous observations (Trotter and Cele-brini 1999; DeSouza et al. 2002; Rosenbluth and Allman2002; Deutschländer et al. 2005; Andersson et al. 2007), wefound that gaze modulated visual information processingactivation independent of Wnger movement in occipital,frontal, and parietal cortex and parahippocampal region.Contrary to previous publications (Deutschländer et al.2005; Andersson et al. 2007), we found a clear spatial orga-nization of gaze eVects that generally showed preferencefor rightward and upward gaze deviations. This spatialorganization paralleled the one observed on Wnger move-ments and suggest a tight coupling between the visual andmotor systems that could subserve and initiate visuo-motorintegration. Gaze eVects in the parahippocampal gyrus maynot have been expected but consider that others havedescribed gaze-dependent visual processing (Sato and

Nakamura 2003; Deutschländer et al. 2005) as well asWnger movement-related activation (Kertzman et al. 1997;Kim et al. 2005). These gaze eVects may relate strictly tovisual processing but attention, a feature of our task, mayhave enhanced the gaze eVects as observed in posteriorparietal cortex of monkeys (Andersen and Mountcastle1983). The eVect of attention on gaze eVects upon process-ing visual information and/or computing hand movementshas not been studied yet in humans.

Gaze-related gain Welds

The spatial organization of the gaze eVects we found hereresembles the results of Baker et al. (1999) and thosedescribing how gaze shifts by monkeys in two-dimensionalspace inXuence spiking (e.g., Andersen and Mountcastle1983; Boussaoud et al. 1998; Bremmer et al. 1998; Buneoet al. 2002); the relationship between spiking and gazeposition has been coined as gaze gain Welds (Andersen andMountcastle 1983). The gaze eVects observed here couldrelate to the gaze gain Weld mechanism observed in mon-keys. This gain Weld mechanism oVers an explanation howvisual information about a target location becomes trans-formed from a retinal to a head/body centered frame of ref-erence (Salinas and Sejnowski 2001). Additionally, gainWelds have roles in other visual tasks such as object recog-nition and spatial navigation (Salinas and Thier 2000; Sali-nas and Sejnowski 2001) and are ubiquitous in the monkeybrain. In human, no such eVect had been described yet,though our data suggest that these mechanisms occur acrossseveral neocortical and subcortical regions.

Acknowledgements This work was funded by the National Insti-tutes of Health (R01-EY01541 to J.N.S.) and the Ittleson Foundation(to J.N.S and John P. Donoghue). Portions of this work representedpartial fulWllment of the Senior Honors project for Mr. Thangavel.

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