cerebral hemispheric specialization for spatial attention: spatial distribution of search-related...

Neuropsychologia 41 (2003) 1396–1409

Cerebral hemispheric specialization for spatial attention:spatial distribution of search-related eye fixations in the

absence of neglect

Mark Mapstonea,c,1, Sandra Weintrauba,b,c,∗, Caralynn Nowinskib,Gülüstu Kaptanoglub, Darren R. Gitelmanb,c, M.-Marsel Mesulama,b,c

a Department of Psychiatry and Behavioral Sciences, Northwestern University Feinberg School of Medicine, Chicago, IL, USAb Department of Neurology, Northwestern University Feinberg School of Medicine, Chicago, IL, USA

c Cognitive Neurology and Alzheimer’s Disease Center, Northwestern University Feinberg School of Medicine, Chicago, IL, USA

Received 20 September 2001; received in revised form 9 January 2003; accepted 9 January 2003

Abstract

The “specialization” of the right hemisphere for spatial attention is widely accepted but poorly understood. While several theories havebeen supported by studies of patients with acute hemispatial neglect, generalizability beyond this population remains unclear. In this study,we compared the predictions of two attention models [Brain 119 (1996) 841; Trans. Am. Neurol. Assoc. 95 (1970) 143] when applied todata obtained from subjects with unilateral right- or left-cerebral lesions, but without clinical evidence of neglect during a visual search task.Both Left Lesion and Right Lesion subjects detected fewer targets in the contralesional hemispace. However, the Right Lesion subjects alsomade fewer visual fixations and longer saccades in the contralesional hemispace, suggesting a fundamental alteration in the architectureof visual search. The spatial distribution of fixations made by Right Lesion subjects more closely fits the prediction of a “salience” modelthan of the strict interpretation of a linear “gradient” model. These data support the long-standing notion of right hemisphere dominancefor spatial attention, especially for the top–down processes entailed in self-directed visual search, and extend this to lesion patients withoutclinically evident neglect. A theoretical model based on the salience of extrapersonal space appears useful for understanding alterations ofattentional allocation, particularly after recovery from stroke.© 2003 Elsevier Science Ltd. All rights reserved.

Keywords:Cerebral dominance; Visual search; Eye movements; Neuropsychology

1. Introduction

The dramatic manifestations of the hemispatial inattention(neglect) syndrome have stimulated vigorous investigationinto the behavioral and neural mechanisms of spatial atten-tion. One central question focuses on the nature of hemi-spheric specialization for this important behavioral domain.Early studies of patients with focal cerebrovascular lesionssuggested that contralateral hemispatial neglect is more fre-quent and severe following right-sided lesions than follow-ing unilateral left-cerebral damage (Bisiach, Cornacchia,Sterzi, & Vallar, 1984; Fullerton, McSherry, & Stout, 1986;

∗ Corresponding author at: Cognitive Neurology and Alzheimer’s Dis-ease Center, Northwestern University Feinberg School of Medicine, 320East Superior, Searle 11-467, Chicago, IL, 60611, USA.Tel.: +1-312-908-9023; fax:+1-312-908-8789.

E-mail address:[email protected] (S. Weintraub).1 Present address: Department of Neurology, University of Rochester

Medical Center, Rochester, NY.

Mosidze, Mkheidze, & Makashvili, 1994; Weintraub &Mesulam, 1987). This conclusion was reiterated in a re-cent review that revisited studies directly comparing theoccurrence of unilateral spatial neglect following right- orleft-sided unilateral cerebral lesions (Bowen, McKenna, &Tallis, 1999). Results of recent functional neuroimagingstudies in young, non-brain damaged individuals furtherhave suggested that the right cerebral hemisphere may berelatively more important than the left in modulating di-rected spatial attention (Coull & Nobre, 1998; Nobre, Coull,& Frith, 1999).

According to one model of right cerebral dominance fordirected spatial attention, neural units in the right cerebralhemisphere modulate attention within both the contralat-eral and ipsilateral hemispaces, while neural units in theleft are only directed at the contralesional right hemispace(Mesulam, 1981, 1985, 1990, 1998, 1999). Several clinicalobservations support this model. First, the study of patientsundergoing the intracarotid sodium amytal procedure prior

0028-3932/03/$ – see front matter © 2003 Elsevier Science Ltd. All rights reserved.doi:10.1016/S0028-3932(03)00043-5

M. Mapstone et al. / Neuropsychologia 41 (2003) 1396–1409 1397

to surgical intervention for epilepsy has shown that anes-thetization of the right cerebral hemisphere results in markedcontralateral hemispatial neglect while injection of the lefthemisphere does not produce the same effect (Spiers et al.,1990). Second, it has been demonstrated that right-sided le-sions that cause contralesional neglect are associated witha milder degree of inattention within the ipsilesional righthemispace (Weintraub & Mesulam, 1987). Finally, func-tional imaging studies also have provided support for thismodel by showing greater activation of right hemispheric re-gions during performance of naturalistic tasks during whichattention is equally allocated to the left and right hemispaces(Gitelman et al., 1996; Nobre et al., 1997).

A number of models addressing the control of spatial at-tention have been proposed to account for neglect behav-ior. An early “gradient” model (Kinsbourne, 1970a, 1970b,1987) was proposed to characterize the shift of attentionto the ipsilesional space. This model is based on the no-tion that the cerebral hemispheres direct attention toward thecontralateral visual hemispace in an increasing linear gra-dient. Furthermore, it hypothesizes that moment-to-momentshifts of attention can be influenced by the nature and lo-cation of external stimuli. Experiments in normal individ-uals have demonstrated that such a gradient exists withineach hemispace as well, and that under certain circum-stances such as orientation conflict, a rightward bias of at-tention can be demonstrated (Reuter-Lorenz, Kinsbourne,& Moscovitch, 1990). In the simplest interpretation of thismodel, the distribution of attention following a right cere-bral lesion adopts a linear gradient from a nadir in theleftmost side of space to its peak in the rightmost side ofspace.

More recently, studying the phenomenon of line bisectionin patients with hemispatial neglect,Anderson (1996)pro-posed a different theoretical model to account for the spatialdistribution of attention. This model hypothesizes that thespatial distribution of attention can be predicted by determin-ing the salience of each point within the extrapersonal space.According to Anderson, the salience of a point in space is“ . . . a function of its spatial location along the linear di-mension of left to right and is something akin to the weightor attraction a point has as a result of a subject’s attention”(Anderson, 1996, p. 843). According to this model, eachcerebral hemisphere contributes to attentional processingover the extrapersonal space in a bell-shaped “salience”curve. The right hemisphere curve normally is broad andencompasses the entire extrapersonal space, while the lefthemisphere curve is narrower and is centered in the righthemispace. When these curves are summed, they provide abimodal distribution of the total salience of horizontal space.Following a right hemisphere lesion, salience is shifted to-ward the ipsilesional side of space whereas relatively littlechange occurs after a left hemisphere lesion. Both the gra-dient and salience models depict an ipsilesional shift of at-tention following right hemisphere damage but the shape ofthe predicted distribution differs considerably.

Although eye movements are often used to study un-derlying attentional processes, the relationship betweenocculo-motor programming and attention is complex. Mosteye movements produce overt shifts of attention to thelocation of the saccadic target, however attention can beshifted covertly without eye movements (Shepard, Findlay,& Hockey, 1986). Numerous studies have explored thisrelationship and in general, provide evidence that networksinvolved in shifts of attention and eye movement generationoverlap substantially (e.g.Gitelman et al., 1996; Moore& Fallah, 2001; Sheliga, Riggio, Craighero, & Rizzolatti,1995). This appears to be especially true when both the ter-mination of the saccade and the focus of attention are in thesame location or are the same object (Deubel & Scheider,1996).

There is recent evidence suggesting that eye movementsare altered in hemispatial neglect in a way that implies ashift of egocentric space to the ipsilesional side (e.g.Barton,Behrmann, & Black, 1998; Chedru, Leblanc, & Lhermitte,1973; Ishiai, Koyama, Seki, & Nakayama, 1998; Karnath &Fetter, 1995). Barton et al. (1998)analyzed the spatial distri-bution of eye movements during the performance of a line bi-section task by patients with hemispatial neglect. Alterationsin the distribution were attributed to a “re-centering” of at-tention slightly to the right of the subject’s midline and werecited as support for the gradient model. This re-centering hasbeen characterized both as a shift in the egocentric frame ofreference to the ipsilesional side of space (Karnath & Fetter,1995) and also as an intensification of a rightward gradientcovering the global work space (Behrmann, Watt, Black, &Barton, 1997).

In another recent study byKarnath and Fetter (1995),neglect patients were asked to search a dark room fora non-existent target amid an array of distractors. Eyemovements recorded during search revealed that explo-ration of space was shifted to the right of the objectivemid-sagittal plane. However, when the eye movement datawere analyzed with the subjects’ self-reported mid-sagittalplane, the eye movements were distributed symmetricallyaround a rightward-shifted subjective mid-sagittal plane.The authors suggest that the essential component in hemis-patial neglect is a systematic ipsilesional error in thecomputation of the egocentric coordinates of spatial ref-erence.

One paradoxical limitation of neuropsychological investi-gations in the study of hemispheric specialization for spatialattention is the use of subjects with clinical neglect, who,by definition, fail to perform the relevant task in the ne-glected hemispace. This prevents a direct comparison of theputatively differential attentional strategies linked to eachhemisphere. In this investigation, we compared the impactof unilateral lesions on visual search strategies of patientswithout neglect who displayed accurate target detection inboth hemispaces. We also used sensitive eye tracking mea-surements to reveal more complex hemispheric asymmetriesin the neural encoding of search behaviors.

1398 M. Mapstone et al. / Neuropsychologia 41 (2003) 1396–1409

2. Methods

2.1. Subjects

All subjects in the current experiment were selected froma larger group (n = 106) participating in a study of visualattention at the Cognitive Neurology and Alzheimer’s Dis-ease Center at Northwestern University Feinberg Schoolof Medicine. Subjects were drawn from the NorthwesternMemorial Hospital Neurology Service, the RehabilitationInstitute of Chicago, the control subject registry at theBuehler Center on Aging at Northwestern University Fein-berg School of Medicine, and the subject pool of healthyolder control participants in the Northwestern Alzheimer’sDisease Center. The Institutional Review Board of North-western University approved the study.

2.2. Inclusion and exclusion criteria

A total of 40 stroke subjects with single unilateral strokeswere initially identified from the larger subject group. Thesesubjects were then screened for the following inclusioncriteria: (1) absence of hemianopia on confrontation test-ing at the time of experiment; (2) absence of clinicallysalient hemispatial inattention on traditional bedside tasksof neglect (e.g. line bisection, visual extinction, manualexploration, and pencil and paper cancellation test); and (3)absence of verbal comprehension deficits (e.g. aphasia) thatmight interfere with understanding task instructions. A totalof 11 patients with right-sided lesions and 12 with left-sidedlesions met criteria. All stroke patients were tested at least2 months after stroke, and in many instances, much later.Subject demographics appear inTable 1.

A total of 19 community-dwelling, neurologically normalsubjects of approximately the same age (range from 31 to 74years) and level of education (range from 10 to 20 years) asthe stroke subjects were also identified. All control subjectswere administered research neurological examinations anda research MRI or CT brain scan to rule out abnormalities.

Patients underwent a full clinical neurological evaluationand MRI or CT brain scans to confirm the presence and lo-cation of the lesion. The size of the lesion was determinedfrom analysis of research MRI scans in 20 subjects. Threesubjects (two Left Lesion and one Right Lesion) had clini-cal imaging studies and did not wish to undergo a researchMRI scan. Two subjects in each lesion group had only sagit-

Table 1Subject demographics and neuropsychological test data

Group N (M/F) Mean Age (years) Mean education (years) ANART EIQ BDAE

Left Lesion 12 (6/6) 58.9 (10.9) 14.3 (3.2) 114.8 (12.2) 10.5 (2.3)Right Lesion 11 (7/4) 57.3 (11.3) 14.0 (2.4) 118.4 (10.2) 11.3 (0.9)Control 19 (7/12) 55.5 (12.4) 15.8 (2.7) 122.7 (7.6) 11.2 (0.7)

ANART EIQ: American National Adult Reading Test, estimated full scale IQ; BDAE: Complex Ideational Subtest score from the Boston DiagnosticAphasia Examination (maximum score= 12); numbers in parentheses are the standard deviations, with the exception of column 1.

tal images that were analyzed on a Macintosh computer us-ing the Scion Image program, as modified from NIH Im-age for the Macintosh by Scion Corporation and availableon the internet athttp://www.scioncorp.com. In Scion Im-age, the lesion volume was calculated by measuring the areaof the lesion as it appears on consecutive slices and thenmultiplying by the slice thickness. All the remaining sub-jects had axial images and lesion size was analyzed in thesesubjects using the Stereo Investigator analysis program (Mi-croBrightField, Colchester, VT). Stereo Investigator uses theCavalieri method to estimate lesion size from axial slicessampled every 10 mm. In both programs, total brain volumewas estimated by measurements taken every 10 mm. Thepercentage of total brain volume occupied by lesion and theinterval from stroke to test for each stroke subject can befound inTable 2.

The two lesion groups did not differ with respect to per-centage of whole brain volume occupied by the lesion. How-ever, the Left Lesion group had a significantly longer inter-val from stroke to test (P < 0.01) (Left Lesion mean= 51.3months, S.D. = 40.5; Right Lesion mean= 12.6 months,S.D. = 12.8). This can be attributed in large part to the pres-ence of two subjects in this group who were tested nearly 9years after stroke (Table 2).

2.3. Procedure

Subjects were tested at the Cognitive Neurology Lab-oratory at Northwestern University Feinberg School ofMedicine. The experimental protocol was explained toall subjects in advance and signed consent was obtained.Subjects underwent neuropsychological testing and wereadministered clinical tests of neglect and the experimentalsearch task.

2.4. Neuropsychological and clinical neglect measures

A version of the American National Adult ReadingTest (ANART) (Schwartz & Saffran, 1987) and the Com-plex Ideational Material Subtest of the Boston DiagnosticAphasia Examination (Goodglass & Kaplan, 1983) wereadministered as measures of estimated premorbid generalintelligence and auditory language comprehension, respec-tively.

Subjects were tested for evidence of clinical neglect withfour tasks. The first was a test of visual extinction using

http://www.scioncorp.com


Table 2Characteristics of subjects with strokes

Subject Months since stroke Lesion volumea Lesion Site

Left Lesion group1 56 n/a L central sulcus region and precentral and post-central gyri2 17 0.80b L external capsule, lateral basal ganglia and thalamus3 39 0.80b L basal ganglia4 4 1.08c L posterior thalamus and medial temporal lobe5 2 0.12c L inferior frontal gyrus6 103 1.00b L caudate nucleus and putamen7 36 1.00b Mid-L frontal lobe and middle and inferior frontal gyri8 20 1.10b L inferior frontal gyrus and internal capsule9 51 3.40b L frontal and parietal lobes and insular cortex

10 119 n/a L inferior frontoparietal region11 111 21.10b L MCA distribution12 57 5.60b L MCA distribution to temporal, posterior frontal and anterior parietal lobes

Right Lesion group1 24 12.10b R MCA distribution to frontal, temporal and parietal lobes2 7 1.30b R lateral basal ganglia, insular cortex and body of caudate nucleus3 5 1.66c R MCA distribution to insular cortex, basal ganglia and internal capsule4 9 1.50b R insular cortex and lateral basal ganglia5 3 0.60b R thalamus, basal ganglia, putamen and head of caudate nucleus6 14 7.00c R frontal lobe and basal ganglia7 27 2.10b R parietal lobe8 1 0.20b R internal capsule9 41 0.10b R thalamus

10 6 0.80b R external capsule11 2 n/a R posterior parietal lobe

a Lesion volume is expressed as percentage of total brain volume.b Lesion size estimated by Stereo Investigator.c Lesion size estimated by NIH Image.

routine clinical methods of bilateral simultaneous stimula-tion. There were a total of 18 counterbalanced trials (6 leftstimulation only, 6 right only, and 6 bilateral). Neglect wasdefined as present if the subject made 30% more errors onbilateral trials than on unilateral trials. The second was aline bisection task in which subjects were asked to placea mark bisecting a 26 cm horizontal line presented on an8.5 in. × 11 in. sheet of paper. The average magnitude (inmm) and direction (left, right) of the deviation of the markfrom true center was calculated over four trials for each sub-ject and compared to the mean deviation of the normal con-trol group. Neglect was defined as greater than 2.5 standarddeviations from true center.

Exploratory neglect was tested by blindfolding subjectsand asking them to search by palpation with the preferredhand (unless hemiplegic) for 20 Velcro targets arranged ina non-linear fashion on a 62 cm× 46 cm Plexiglas board.Neglect was deemed present if 30% more targets were un-detected in one hemispace than the other. Finally, visualtarget cancellation was measured with a paper-and-penciltest in which subjects were required to locate 60 targets (30in each hemispace) within an array of over 300 non-lineardistractors (Weintraub, 2000; Weintraub & Mesulam,1985). Neglect was judged present on this test if 30%fewer targets were detected in one hemispace than in theother.

2.5. Experimental computerized visual search task

Subjects were seated 40 in. in front of a 21-in.,high-resolution display monitor subtending an angle of 23◦horizontally and 17◦ vertically. The subject’s eye positionwas sampled during the experimental task by an ISCAN®

RK-426PC (ISCAN, Burlington, MA) Pupil/Corneal Re-flection Tracking System at a rate of 60 Hz. The positionof the eye was automatically recorded in two-dimensionalspace and saved to a Macintosh computer for analysis usingILAB © (Gitelman, 2002), custom-designed software oper-ating in the MATLAB® software environment (Mathworks,Natick, MA). All subjects in this study had reliable eyeposition data defined as the presence of valid eye positioncoordinates in at least 75% of each subject’s sample. Veryfew subjects had more than 10% missing data. Missing eyedata was usually due to blinking during a trial.

The experiment began with a standardized nine-point cali-bration procedure. Subjects maintained gaze on a central fix-ation point in the center of the display monitor. The centralfixation point disappeared and was replaced by a non-lineararray of 80 stimuli (20 per visual quadrant, consisting of 1target number and 79 letter distractors). On each of 40 tri-als, one of four target numbers (2, 4, 6 or 7) appeared atone of the test locations (10 per visual quadrant). The tar-get numbers were selected on the basis of pilot testing to


determine which numbers were most easily discriminatedfrom the distracter letters. Trial order was randomized sothat a target could not appear in the same quadrant on morethan three consecutive trials.

Subjects were asked to search for “a number” within theletter distractors and to press a response key centered on atable in front of them. Subjects were not told which numberswould serve as targets. Subjects were also required to callout the number after pressing the response key to verify ac-curacy of response. Most stroke subjects used the preferredhand to respond. However, six Left Lesion subjects had sig-nificant right hemiplegia at the time of test and thus used thenon-preferred left hand to respond. In order to minimize anybias introduced by using the non-preferred hand to respond,six Control subjects were also tested using the non-preferredhand (left in all cases). The target and distracter stimuli re-mained on the monitor until the subject responded or until10 s had elapsed.

2.6. Data analysis

Because we were interested in examining spatial asym-metries in visual search we operationally defined two visualhemispaces (i.e. two adjacent bins each 320 horizontal pix-els wide and 480 pixels high) in the 640× 480 pixel videodisplay. This was done after data collection and the hemis-pace designation was not visible to the subjects during thesearch task. From the eye movement data collected duringthe search task we extracted five dependent measures foranalysis and computed left and right hemispace values foreach dependent measure described below.

Accuracy of target detectionwas defined as a correct ver-bal response in addition to a button press within the 10-stime limit for each trial and was expressed as a percentageof the 40 trials. Thetotal area coveredduring search, wasdefined as the number of display monitor pixels covered bythe eye during all 40 trials, regardless of whether or not thetarget was found. The ISCAN system represents point ofgaze as a single pixel in the display monitor. This does notimply that the system is able to provide one pixel spatialresolution. Nor does this imply that subject gaze was lim-ited to this single pixel. Passing over a single pixel twice ina trial resulted in that pixel being counted twice. Thetotalnumber of eye fixationsmade during search across all 40trials constituted a third measure. An eye fixation was de-fined as stable eye position within any 6 pixel horizontal by4 pixel vertical area on the display for at least 100 ms (Zihl& Hebel, 1997). For most subjects, the first fixation of eachtrial was usually of very long duration (often three timeslonger than the average fixation duration for that subject).This initial fixation was thought to reflect a delay in initiat-ing active search following disappearance of the central fix-ation point and was excluded from analysis.Mean durationof eye fixationsfor each subject was also computed. Finally,we computed themean distance of saccadesmade by eachsubject. A saccade was defined as a continuous eye move-

ment between two successive fixations. Saccadic distancewas measured in screen pixels.

2.7. Magnitude of search asymmetry

In order to facilitate between-group comparisons of searchasymmetry, we computed an asymmetry composite for eachof the five dependent measures. We used the following for-mula to derive these measures for the Left Lesion group:

(left hemispace− right hemispace)

(left hemispace+ right hemispace)

For the Right Lesion group, the asymmetry measures werecomputed using the following formula:

(right hemispace− left hemispace)

(left hemispace+ right hemispace)

These formulae were based on the a priori assumption thatsubjects with stroke would have larger values in the ipsile-sional hemispace and were used to maximize the likelihoodof positive values for the comparison of absolute magnitudesof asymmetry.

A single mixed within- and between-subjects multivariateanalyses of variance (MANOVA) compared the three sub-ject groups on the five variables. The within-subjects factorwas visual hemispace (left or right) and the between-subjectsfactor was group (Control, Left Lesion, Right Lesion). Sig-nificant effects and interactions were explored using pairedt-tests with Bonferonni adjustment of alpha levels. Statisti-cal significance was thusP < 0.01.

A single multivariate analysis of variance (MANOVA)was used to compare the three groups on magnitude of searchasymmetry derived as above for accuracy, area covered, totalnumber of eye fixations, mean fixation duration, and meansaccade distance. The between-subjects factor was group(Control, Left Lesion, Right Lesion). Post hoc comparisonswere run using the Bonferonni procedure.

2.8. Mapping spatial distribution of eye fixations withinthe global work space

Linear and non-linear regression methods were used tocompare the obtained distribution of eye fixations with pre-dicted distributions based on the gradient and salience mod-els. In addition, the distribution of fixations within the globalwork space for the Right Lesion group was fit to the saliencemodel equation by best-fit equation modeling using the pa-rameters specified byAnderson (1996).

The distribution of eye fixations across the workspace dur-ing search was used as a measure of the spatial distributionof attention to evaluate the predictions of the two models.The display monitor, subtending approximately 23◦ of visualangle, was operationally partitioned into 23 separate verti-cal bins, each 1◦ of visual angle. Data from all 40 trials ofthe experimental task were used, regardless of accuracy of


Fig. 1. Predictions of the gradient and salience models for the spatial distribution of attention in Normal and Right Lesion subjects. Each bar represents∼1◦ on the display monitor which subtends a total of 23◦ of visual angle. The distribution of eye fixations predicted by the gradient model (A) follows alinear increase from left to right. The predicted distributions of eye fixations based on the salience model for Control (B) and Right Lesion (C) subjectsare based on the sums of two bell-shaped salience curves and were determined using the algorithm and parameters proposed byAnderson (1996). Themethod for determining the numbers of fixations expected at each bin for each of the models is described in detail in the text.

detection, to calculate the average number of eye fixationswithin each bin for the Control and Right Lesion groups.The raw number of fixations in each bin was converted intopercentages of total fixations for direct comparison to eachother and to the model predictions. The distributions pre-dicted by the gradient and salience models (Fig. 1A and C)were compared to the obtained distributions for the RightLesion and Control groups only (Fig. 2). The Control groupdata were included to test the prediction of the saliencemodel for a normal distribution of attention and to provide

a reference point with which to compare the Right Lesiondata. The Left Lesion distribution was not modeled becausethis group did not demonstrate a significant asymmetry onthis measure and because performance on this measure wasalmost identical to that of the Control group.

The distribution of eye fixations following a right hemi-sphere lesion as predicted by the gradient model was ob-tained by fitting a straight line to the Right Lesion groupdata obtained in this experiment. We desired only to im-pose a linear fit to the data and not constrain the model


Fig. 2. Obtained eye fixation distributions for Normal Control and Right Lesion groups. Both Control (A) and Right Lesion (B) distributions are tri-modalwith the largest proportion of fixations occurring in the middle third of the defined workspace. The distribution of the Right Lesion group is shifted tothe right of center.

with regard to the starting or ending point of the line. Thus,they-intercept was not specified. This fitting resulted in theequationy = 0.1523x + 2.5209. The predicted number offixations for each of the 23 bins was derived from this equa-tion and the root-mean-squared (RMS) difference betweenthe model and the data obtained from the Right Lesion groupwas calculated. The RMS difference is a method for evalu-ating regression models and represents the average distancefrom the model to each data point. It is calculated by squar-ing the differences between the data and the model at eachpoint then taking the square root of the average of thesesquared residuals. A lower RMS value indicates a better fitbetween the model and the data.

The predicted distribution of fixations for a non-brain-injured individual and for a patient with a right hemispherelesion according to the salience model was computedusing the algorithm and parameter values described byAnderson (1996). According to this model, three parame-ters define each of two bell-shaped distributions providedby each cerebral hemisphere. The six parameters definethe breadth, height, and location of the two curves on thehorizontal plane (seeTable 3). The relevant predictionsof the salience model were compared to the Control andRight Lesion group distributions obtained in the presentstudy and the RMS difference was calculated for both com-parisons.


Table 3Evaluation of gradient and salience models

Model Formula and parameter values RMS of residuals

Gradient (Right Lesion) y = 0.1523x + 2.5209 1.90Salience (Normal Control) y = 100 arctan((x − 750)/100)0.6+ 250 arctan((x − 475)/250)0.6

+ 100 arctan((−x + 750)/100)0.6+ 250 arctan((−x + 475)/250)0.61.90

Salience (Right Lesion) y = 100 arctan((x − 750)/100)0.6+ 75 arctan((x − 480)/75)0.6+ 100 arctan((−x + 750)/100)0.6+ 75 arctan((−x + 480)/75)0.6

1.75

Salience best-fit starting values (Right Lesion) y = 87 arctan((x − 780)/87)5+ 70 arctan((x−470)/70)6.7+ 87 arctan((−x + 780)/87)5+ 70 arctan((−x + 470)/70)6.7

na

Salience best fit (Right Lesion) y = 97.8 arctan((x − 842.4)/97.8)5.2+ 181.6 arctan((x −532.8)/181.6)6.78+ 97.8 arctan((−x + 842.4)/97.8)5.2+ 181.6 arctan((−x + 532.8)/181.6)6.78

0.99

Formula variables:x = location (bin) on horizontal axis (1–23),y = predicted number of fixations atx. Salience algorithm (Anderson, 1996): salience=S.D.L arctan((XR −ML )/S.D.L )SFL + S.D.R arctan((XR −MR)/S.D.R)SFR + S.D.L arctan((−XL +ML )/S.D.L )SFL + S.D.R arctan((−XL +MR)/S.D.R)SFR.In this formula,X represents any point along the horizontal dimension,M is the point on the horizontal axis under the peak of each curve, S.D. is thestandard deviation, or breadth of each curve, and SF is a scaling factor for the height of each curve. The L and R subscripts are used to denote thecontributions from the left and right attentional systems, respectively.

In a final analysis, the salience model algorithm was usedto provide the best fit for the fixation distribution of the RightLesion group obtained in this experiment. Algorithm startingvalues for this best-fit analysis can be found inTable 3.

3. Results

3.1. Neuropsychological and neglect screening measures

All subjects had estimated premorbid verbal IQ’s withinthe above-average to superior range and both lesion groupshad normal language comprehension (seeTable 1). Noneof the subjects demonstrated neglect on any of the clinicalneglect screening measures.

3.2. Computerized visual search task

Both MANOVA’s produced significant omnibusFstatistics atP < 0.01 each. The following sections de-scribe the univariate tests for each of the five dependentmeasures.

3.2.1. Accuracy of target detectionThe three groups differed with respect to the accuracy of

target detection in the two hemispaces (F(2, 39) = 25.21,P < 0.001). Both the Right and Left Lesion groups detectedsignificantly fewer targets in the contralesional hemispace(P < 0.01 andP < 0.001, respectively), while control sub-jects did not differ in this regard. The three groups differedin the magnitude of this asymmetry (F(10, 70) = 3.56,P <

0.001) with the Right Lesion group demonstrating greaterasymmetry compared to the Control group (P < 0.001), butnot when compared to the Left Lesion group (P = 0.09).The Left Lesion group did not differ from the Control groupin asymmetry of target detection.Fig. 3shows the accuracyfor the three groups by hemispace.

3.2.2. Area covered during searchThe three groups differed with respect to the area searched

in the two hemispaces (F(2, 39) = 11.39, P < 0.001). Al-though both Right and Left Lesion groups covered less areawhile searching the contralesional space, these differences(P = 0.02 each) failed to reach statistical significance withadjustedP-value criterion of 0.01. Interestingly, the Controlgroup also showed a nearly significant bias toward search-ing more area in the left than the right hemispace. The threegroups did not differ in the magnitude of the asymmetry de-scribed above (Fig. 3).

3.2.3. Total eye fixationsThe groups differed with respect to the total number of

eye fixations made in the two hemispaces during search(F(2, 39) = 9.45, P < 0.001). This effect was supportedprimarily by the Right Lesion group who made signifi-cantly fewer fixations in the contralesional compared tothe ipsilesional hemispace (P < 0.01). The Left Lesionand Control groups did not show significant differencesas a function of hemispace on this measure. Accordingly,the magnitude of the Right Lesion group’s asymmetryon this measure was greater than both the Left Lesiongroup (P < 0.01) and the Control group (P < 0.001)(Fig. 3).

3.2.4. Mean fixation durationThe three groups did not differ in the average duration of

fixations made in the two hemispaces, nor did they differ inthe magnitude of the asymmetry on this measure.

3.2.5. Mean saccade distanceThe three groups did not differ significantly in the average

length of saccades made during search of the two hemis-paces. However, the Right Lesion group did make signifi-cantly longer saccades in the left hemispace compared to theright (P < 0.001) and this asymmetry was greater than that


Fig. 3. Performance on dependent measures; Control, Left Lesion, and Right Lesion group performance with respect to accuracy of target detection, areacovered, total number of fixations, mean fixation duration, and mean saccade distance during search for the targets (A, B, C, D, and E respectively).Significant within-group hemispheric asymmetries (P < 0.01) are indicated by asterisks.

of the other two groups who essentially showed no asym-metry at all (P < 0.01 each) (Fig. 3).

3.2.6. Spatial distribution of eye fixationsThe distributions of eye fixations across the horizontal

plane for all groups are best characterized as trimodal, with a

major percentage occurring in the central region (Fig. 2). TheRight Lesion group’s obtained distribution was shifted to theright of midline and, consistent with the eye fixation asym-metry results, most fixations occurred in the right hemispace.Correspondence of the gradient model to the obtained datawas lowest in the central region and at the rightmost edge of


Fig. 4. Evaluation of model predictions to obtained distributions. The distribution of eye fixations in the Right Lesion group is compared with thepredicted distributions from the gradient and salience models. The salience model resulted in a lower root-mean-squared (RMS) residual value, whichimplies that it is a better fit than the gradient model with the actual data.

Fig. 5. Salience model for Right Lesion using best fit parameters; depiction of the best fit of the salience model to the Right Lesion group data. Startingparameter estimates and RMS residual value can be found inTable 3.


the visual workspace. The root mean square difference forthis comparison was 1.90 (Fig. 4A). The salience model’sprediction of the Right Lesion group’s distribution was bet-ter with a RMS value of 1.75 (Fig. 4B). The distribution offixations made by the Left Lesion group was nearly identicalto that made by the Control group. Indeed, the percentageof fixations made by the Left Lesion group in the majorityof the 23 bins did not differ from the Control group by sepa-rate Mann–WhitneyU-tests. This is expected given the lackof group differences in the eye-movement-dependent behav-ioral measures (especially in the number of fixations made).Because the Left Lesion and Control groups did not differ inthis regard and because the gradient and salience models donot make explicit predictions about alterations in attentionfollowing left-cerebral lesions, we chose to evaluate only theRight Lesion and Control group’s distributions with the twomodels. The distribution of fixations for the Control groupwas adequately described by the salience model’s prediction.The RMS difference for this comparison was 1.90. Finally,the best-fit estimate of the six-parameter model proposed bythe salience theory produced a RMS value of 0.988 (Fig. 5).The parameter values of the salience model and the best fitfor the current data can be found inTable 3.

In summary, this study demonstrates that:

(1) Contralesional deficits in accuracy of target detectionare present following either left or right cerebral lesions,but contralesional deficits in the number of eye fixationsand the average length of saccades occur only in subjectswith right cerebral lesions.

(2) Right unilateral cerebral lesions alter the architecture ofvisuomotor search in the contralesional hemispace, evenin the absence of clinically observable neglect.

(3) Differences in the programming of fixations may con-stitute a major mechanism of hemispheric asymmetry inspatial attention.

(4) The salience modelAnderson (1996)provides a bet-ter characterization of the distribution of attention fol-lowing right-sided damage without hemispatial neglectthan does a simple gradient model (Kinsbourne, 1970a,1970b, 1987).

4. Discussion

The present study sought to explore attentional asymme-tries reflected in visual search following unilateral strokesthat did not produce clinically observable neglect. Controlsubjects explored slightly more area in the left visual hemis-pace when compared to the right. However, this did notreach statistical significance. This finding may reflect theimpact of the organizational structure imposed by readingthe English language. Several early studies (e.g.Kugelmass,Lieblich, & Ehrlich, 1972) have demonstrated a bias in theinitiation of perceptual search based on the direction fromwhich text in the native language is read (left to right in En-

glish readers, right to left in Hebrew, etc.). The linguisticnature of our stimuli may have reinforced the adoption ofthis organizational search strategy.

The Left Lesion group demonstrated significant asymme-try in target detection with fewer targets detected in the con-tralesional right visual hemispace than the left. This patternclosely resembled that seen in the Control group and did notdiffer in magnitude from the Control group. On the othermeasures, the Left Lesion group did not show significantasymmetries. In general, the pattern of performance seen inthe Left Lesion group was the same as the Control group’s(i.e. L > R), but usually of slightly greater magnitude. Thus,the Left Lesion group’s performance appears to be a mildexaggeration of the Control group’s pattern.

One possible reason for this mild exaggeration ofsearch-related asymmetry may be the use of linguistic stim-uli in the search task. Although all Left Lesion subjectsperformed within normal limits on a test of language com-prehension, it is possible that the lesions could have alsointerfered with the ability to rapidly process the linguistictargets in this task. This, coupled with mild disruption ofthe left attentional network may have resulted in an iso-lated contralesional deficit in target detection. The use ofnon-linguistic stimuli in future experiments would be use-ful in determining the roles of linguistic and attentionalprocesses in explaining this result.

The Right Lesion group also demonstrated a significantasymmetry in target detection. However the pattern wasopposite (i.e. L< R) that of the Control and Left Le-sion groups. This finding underscores the notion that visualsearch performance in the Right Lesion group is qualita-tively different from the pattern seen in normal control sub-jects and Left Lesion subjects.

In addition to an asymmetry in target detection, the RightLesion group made fewer visual fixations and longer sac-cades while searching the left visual hemispace. These de-pendent measures may more directly tap the fundamentalcomponents of the attentional network than target detectionaccuracy, which may require additional cognitive networkssuch as language.

For the purposes of this study, we defined a saccade as acontinuous eye movement between two fixations. Thus, thenumber of fixations and the number of saccades are highlycorrelated. Theoretically, this fact does not constrain thelength of any individual saccade. However, in our subjectsthe average length of saccades was also highly correlatedwith the number of fixations in both the left (r2 = −0.54,P = 0.000) and right (r2 = −0.63, P = 0.000) hemis-paces. Thus, fewer fixations resulted in longer saccades andalthough fixations and saccade length were treated as inde-pendent measures, they are highly interdependent and mayrely on a common process. The reason for longer saccades(or fewer fixations) is unclear and deserves further study.

In contrast to the isolated asymmetry in target detectionseen in the Left Lesion group, the asymmetries seen in theRight Lesion group suggest an elementary disruption of the


architecture of visual search revealed by eye movement mea-sures. Furthermore, these results suggest that the fundamen-tal components of search revealed by eye movement mon-itoring largely are supported by right cerebral hemispherestructures.

The finding of significant contralesional hemifield asym-metries in the Right Lesion group is in contrast to the re-sults of early work on the activation-orienting model. Forexample,Reuter-Lorenz et al. (1990)reported data suggest-ing that hemisphere-specific attentional resources of normalsubjects can be manipulated by presentation of stimuli in thecontralateral visual hemifield. In their study, young normalsubjects viewed tachistoscopically-presented bisected linesof varying length in several locations in the right and leftvisual hemifields. Subjects judged the accuracy of the bisec-tion point. The results showed that bisection judgments wereaffected depending on which cerebral hemisphere was ac-tivated by contralateral stimulation. The authors interpretedthis as strong evidence for the activation-orienting hypothe-sis which would appear to be evidenceagainsta right hemi-sphere dominance for spatial attention.

In attempting to reconcile these findings with the findingsreported in this paper, it is clear that differences in tasksmust be considered. The task used by Reuter-Lorenz et al. isbased on externally generated stimulation which may utilizemore automatic or perceptually driven processes. In fact, theauthors touch on this point briefly in their paper. The visualsearch task used in the present study, in contrast, ostensiblyrequires a great deal of internally generated, top–down, cog-nitive processing to construct an effective search strategy.Under this condition, there is a clear preference for a dis-tribution of attention that is best described by the Saliencemodel proposed by Anderson. Indeed, Anderson’s modelwas originally proposed to account for line bisection behav-ior in subjects, whereas in the Reuter-Lorenz study the linespresented to subjects were already bisected.

Our results also suggest that although traditional testsof neglect may have many advantages for assessing acutepatients or those with marked visual neglect, they are notsensitive enough to detect subtle alterations of visual atten-tion that remain after the acute phase of stroke. The fail-ure of traditional bedside pencil and paper tasks to regis-ter mild deficits in spatial attention may ultimately result inan under-representation of the true frequency of hemispatialinattention in the population of patients with stroke.

With regard to the spatial distribution of visual fixationsmade during visual search, all groups demonstrated a tri-modal distribution with peaks of fixations centered in the leftand right hemispaces and in the center of the visual space.For all three groups, the largest percentage of fixations oc-curred in the center of the defined workspace. The first fixa-tion of each trial was excluded from the analysis to accountfor fixations resulting from latency in disengaging from thepre-trial central fixation point. In a recent study using thesame visual search task to study the impact of aging andAlzheimer’s disease on attention (Rosler et al., 2000), young

normal subjects made several small fixations around the cen-ter of the global workspace in the first several seconds priorto making subsequent larger saccades. This observation sug-gests that these subjects may have been “planning a strategy”before initiating a visual search. This preparation might con-sist of an immediate deployment of covert attention allowingfor an initial scan of the global workspace (or portions ofit) (Greenwood, Parasuraman, & Alexander, 1997; Treisman& Gelade, 1980; Zelinsky, Rao, Hayhoe, & Ballard, 1997).This initial scan may have been used to identify likely areasfor deployment of focal attention and more detailed search.This notion is similar to a recent model (Guided Search 2.0)proposed byWolfe (1994)who suggests that, in the presenceof similar appearing distractors, search is generally initiatedin “parallel”, and then proceeds in “serial” fashion. The re-mainder of the eye movements made by all subjects in thisstudy strongly suggests the use of a serial search strategyand this is consistent with eye movement data reported byother investigators (e.g.Williams, Reingold, Moscovitch, &Behrmann, 1997).

The most notable finding in this analysis is the patternof fixations produced by the Right Lesion group in the ab-sence of clinical neglect. This pattern is best characterizedby an ipsilesional remapping of the “significant work space”(Mesulam, 2000) and is consistent with the results of severalstudies on patients with neglect by Karnath and colleagueswho conclude that the salient behavioral manifestation isan ipsilesional shift in the egocentric frame of reference(Karnath & Fetter, 1995; Karnath, Niemeier, & Dichgans,1998).

On visual inspection, the Right Lesion group’s patternof fixation distribution was not a linear gradient, but ap-peared to be a skewed variant of a normal distribution thathad been translated across the horizontal plane. We choseto implement only the fundamental principle of the gradientmodel, namely that the distribution of attention in the globalworkspace follows a linear gradient from left to right. Wedid not attempt to restrain the model further by setting ay-intercept in the linear fit to the data. While we acknowledgethat there are complexities in both the initial conceptualiza-tion of the gradient model (Kinsbourne, 1970a,b) and in thesubsequent work on unilateral neglect that are not addressedin this rather limited conceptualization, nonetheless, we be-lieve that the basic premise of the linear gradient notion wasnot supported in this population of patients with unilaterallesions and no clinically observable neglect. Variations onthe experimental paradigm used in the present study couldbe used to explore the more subtle predictions of the gra-dient model by varying hemispace of stimulus presentationand the nature of the stimulus (verbal versus non-verbal)(Reuter-Lorenz, Kinsbourne, & Moscovitch, 1990).

The distribution appeared to be most similar to the predic-tion made by the salience model (Anderson, 1996). Whendirectly compared to the distribution of fixations producedby the Right Lesion group, the salience model resulted ina smaller root-mean-squared value than the gradient model


and was therefore determined to better describe the actualdata obtained in this experiment.

The fixation distribution of the Right Lesion group in thecurrent study is in partial agreement with those ofBehrmannet al. (1997), who studied eye movements while nine patientswith neglect performed a visual search task. The subjectsin the Behrmann study demonstrated a distinctive pattern offixations across the global workspace consisting of an in-creasing linear gradient from left to right (Behrmann et al.,1997). However, the neglect subjects demonstrated one im-portant deviation from a perfect linear gradient: a distinctdrop-off in the rightmost edge of space. With this drop-off,the data do not fully support one of the most important pre-dictions of the gradient theory, namely, that the maximumweight of attention occurs in the rightmost space.

Finally, the parameter values obtained from the best fit ofthe salience model to the actual data produced by the RightLesion group in this study should be useful to drive futureresearch on the characterization of the spatial distribution ofattention following unilateral lesions.

Acknowledgements

This research was supported by grant NS20285 (M.-M.Mesulam, PI) from the National Institute of NeurologicDisorders and Stroke, and, in part, by grants AG14068from the National Institute on Aging (S. Weintraub, PI) andH133B980 (E. Roth, PI) from the Department of Educationto the Rehabilitation Institute of Chicago. The authors thankAlissa Hays and Kathleen Schelble for technical assistance,and Marc Dublin for statistical assistance.

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