Evidence of a divided-attention advantage in autism

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Evidence of a divided-attention advantage inautismM. D. Rutherford a , Eric D. Richards b , Vanessa Moldes a & Allison B.Sekuler aa Department of Psychology, Neuroscience & Behaviour , McMasterUniversity , Hamilton, Ontario, Canadab University of Prince Edward Island , 550 University Avenue,Charlottetown, Prince Edward Island, CanadaPublished online: 15 Feb 2011.

To cite this article: M. D. Rutherford , Eric D. Richards , Vanessa Moldes & Allison B. Sekuler (2007)Evidence of a divided-attention advantage in autism, Cognitive Neuropsychology, 24:5, 505-515, DOI:10.1080/02643290701508224

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Evidence of a divided-attention advantage in autism

M. D. RutherfordDepartment of Psychology, Neuroscience & Behaviour, McMaster University, Hamilton, Ontario, Canada

Eric D. RichardsUniversity of Prince Edward Island, 550 University Avenue, Charlottetown, Prince Edward Island, Canada

Vanessa Moldes and Allison B. SekulerDepartment of Psychology, Neuroscience & Behaviour, McMaster University, Hamilton, Ontario, Canada

People with autism spectrum disorders appear to have some specific advantages in visual processing,including an advantage in visual search tasks. However, executive function theory predicts deficitsin tasks that require divided attention, and there is evidence that people with autism have difficultybroadening their attention (Mann & Walker, 2003). We wanted to know how robust the knownattentional advantage is. Would people with autism have difficulty dividing attention betweencentral and peripheral tasks, as is required in the Useful Field of View task, or would they show anadvantage due to strengths in visual search? Observers identified central letters and localized peripheraltargets under both focused- and divided-attention conditions. Participants were 20 adults withhigh-functioning autism and Asperger’s syndrome and 20 adults matched to the experimental groupon education, age, and IQ. Contrary to some predictions, individuals with autism tended to showrelatively smaller divided-attention costs than did matched adults. These results stand in stark contrastto the predictions of some prevalent theories of visual and cognitive processing in autism.

Autism is a developmental disorder characterizedby deficits in three primary areas: (a) social cogni-tion, (b) delays in communication and language,and (c) idiosyncratic, repetitive behaviours, andinterests. There is no consensus on the psychologi-cal causes of autism or autism spectrum disorders(ASD), but several researchers have proposed thatthe core and causal psychological deficits inautism are lower level differences in sensory andperceptual processes (Dakin & Frith, 2005;Happe & Frith, 2006; Mottron, Dawson,Soulieres, Hubert, & Burack, 2006). Indeed, anumber of studies have shown enhanced

performance of individuals with ASD on a rangeof perceptual tasks. For example, individuals withASD show a perceptual bias toward local detailrather than global meaning. Shah and Frith(1983) compared a group of children with autismto mental-age-matched typical control childrenand chronological-age-matched children withdevelopmental delays. The group with autismshowed an advantage in finding an embeddedfigure in a meaningful larger image, on theChildren’s Embedded Figures Test, compared toboth matched groups (Shah & Frith, 1983).Similarly, a later comparison of adults with

Correspondence should be addressed to M. D. Rutherford, Department of Psychology, Neuroscience & Behaviour, McMaster

University, 1280 Main Street West, Hamilton, ON, L8S 4K1, Canada (E-mail: [email protected])

# 2007 Psychology Press, an imprint of the Taylor & Francis Group, an Informa business 505http://www.psypress.com/cogneuropsychology DOI:10.1080/02643290701508224

COGNITIVE NEUROPSYCHOLOGY, 2007, 24 (5), 505–515

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autism, adults with Asperger’s syndrome, and acontrol group, found that both clinical groupswere faster than the control group on the standardEmbedded Figures Test: Individuals with autismshowed superior performance in identifyingshapes within the designs than did the controlgroup (Jolliffe & Baron-Cohen, 1997). Superiorperformance of observers with autism also hasbeen shown with tasks such as visual search(O’Riordan, Plaisted, Driver, & Baron-Cohen,2001; Plaisted, O’Riordan, & Baron-Cohen,1998) and discrimination of novel visual stimuli(Plaisted et al., 1998). In a classic visual searchtask, participants are asked to find a unique targetitem that differs from distractors on one or moredimension. In one study, children with ASD andmatched controls were tested on several visualsearch tasks. The children with autism showedsuperior performance, whether the target was tobe identified by a single feature or a conjunctionof features (O’Riordan et al., 2001).

When do individuals with ASD show percep-tual benefits, and when do they show perceptualcosts? Some researchers have proposed that theattentional or neural demands involved inperforming simple perceptual tasks may be a keypredictor of whether benefits or deficits in per-formance are seen with observers with autism(Bertone & Faubert, 2006; Dakin & Frith,2005). For example, Bertone and colleagues(Bertone, Mottron, Jelenic, & Faubert, 2003,2005) show that individuals with ASD performas well or better than matched control individualson first-order motion and orientation discrimi-nation tasks, but are relatively impaired onsecond-order versions of those tasks (thought torequire additional or more complex neural proces-sing). Several studies also have shown that obser-vers with autism are significantly impaired,compared to normal observers, when tasksrequire some level of dynamic attentionalcontrol. For example, Rinehart and colleaguesfound that observers with autism respondedmore slowly when a global target followed a localtarget, but not when a local target followed aglobal target (Rinehart, Bradshaw, Moss,Brereton, & Walker, 2001). In other words, the

group with autism had relative difficulty whenasked to expand their attention dynamically fromone trial to the next from the smaller digits tothe larger digits. In another study, Mann andWalker (2003) asked participants to judge whichof two bisecting line segments was longer: thehorizontal or the vertical. The bisecting linescould be either both relatively large or both rela-tively small, and this overall size varied from trialto trial. Compared to typical individuals, individ-uals with autism were worse at large stimuli afterseeing small stimuli, although the groups did notdiffer for small–small, large–large, or large–small trial pairs. These authors concluded thatpeople with autism spectrum disorders have defi-cits in rapidly expanding visual attention afterattention already had been set more locally.

In the current study, the methodologicalapproach is the Useful Field of View (UFOV)paradigm, used to assess the ability of observerswith ASD and matched control observers todivide their attention. The Useful Field of Viewis defined as the region of the visual field fromwhich an observer can extract information in oneglance. In the UFOV paradigm, participantsperform two tasks: central-letter identificationand peripheral-target localization, under eitherfocused- or divided-attention conditions. Infocused-attention conditions each task is per-formed individually, whereas in divided-attentionconditions both tasks are performed concurrently.Assessments of observers’ UFOV involve themeasurement of observers’ performance on a per-ipheral-target localization task. When this task isperformed concurrently with an attention-demanding central task, such as central-letteridentification, there are significant divided-atten-tion costs (Ikeda & Takeuchi, 1975; Leibowitz& Appelle, 1969; Richards, Bennett, & Sekuler,2006; A. B. Sekuler, Bennett, & Mamelak, 2000;R. Sekuler & Ball, 1986; Williams, 1982).UFOV performance and general intelligence arenot known to be related, but there is evidence ofvariability in the UFOV across the population.For example, older subjects consistently haveshown larger deficits in their UFOVs thanyounger subjects, as indexed by peripheral-task

506 COGNITIVE NEUROPSYCHOLOGY, 2007, 24 (5)

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performance in divided-attention conditions(Ball, Beard, Roenker, Miller, & Griggs, 1988;Ball, Owsley, & Beard, 1990; Richards et al.,2006; R. Sekuler & Ball, 1986; A. B. Sekuleret al., 2000) although this age-related deficit canbe reduced with training (Ball et al., 1988; Ballet al., 2002; Ball, Cissell, Edwards, Roenker, &Wadley, 2003; Richards et al., 2006; R. Sekuler& Ball, 1986). Little is known about the neuralbasis of UFOV performance, but one studysuggests that a unilateral lesion to visual cortexcan result in a bilateral reduction of the usefulfield of view (Rizzo & Robin, 1996).

The goals of the current study are two-fold:first, to test whether differences in performanceon the UFOV task exist between individualswith ASD and matched control individuals; and,second, to determine whether the visual searchadvantage found previously (e.g., O’Riordanet al., 2001) would be found when observersneeded to simultaneously divide their attentionbetween two visual tasks.

Method

ParticipantsA total of 40 volunteers participated in the exper-iment. The ASD group consisted of 20 adults (18male) with autism spectrum disorders and amatched control group consisted of 20 adults (18male) without any developmental disorders (seeTable 1). Participants in the autism group wererecruited via referral from a clinical specialist treat-ing autism spectrum disorders. All participants inthe ASD group had previously received clinicaldiagnoses of autism or Asperger’s syndrome

before entering the study, and one of the authors(M.D.R.) confirmed their diagnoses via two criteria:(a) Autism Diagnostic Interview (ADI-R; Lord,Rutter, & LeCouteur, 1994) and (b) the AutismDiagnostic Observation Schedule (ADOS-G;Lord et al., 2000). They were free from otherknown medical conditions. Participants in thecontrol group were recruited from the community(that is, they were not university students) througha newspaper advertisement. Participants from thetwo groups were matched for age, sex, educationlevel, and IQ; all groups had comparable visualacuity and contrast sensitivity. Table 1 showsgender ratios and the mean IQ scores, age, closeand far acuity, and contrast sensitivity for eachgroup. Visual acuity for each participant is indecimal units, while contrast sensitivity wasmeasured using the Pelli–Robson contrastsensitivity chart (Pelli, Robson, & Wilkins, 1988).

All participants were given the Wechsler AdultIntelligence Scale (WAIS), which yields verbal,performance, and full-scale IQ scores (Wechsler,1997). All participants scored above 80 on bothverbal and performance scales. Mean full-scaleIQ score was 102.8 (SD ¼ 15.2) for the controlgroup and 103.4 (SD ¼ 18.2) for the ASD group.

Stimuli and apparatusVisual stimuli were presented on a 2200 MultisyncFE2111SB monitor (refresh rate ¼ 85 Hz), andresponses were recorded via a keyboard. AnApple G4 computer recorded responses and con-trolled stimulus presentation. Figure 1 presents aschematic illustration of each task. Centraltargets were single white letters (0.7 � 1.0degrees of visual angle; luminance ¼ 54.5 cd/m2)

Table 1. Demographic information for participants in Experiment 1

Group

No. of

participants

Gender

Mean age

Contrast

sensitivity Near acuity Far acuity IQM F

Control 20 18 2 25 (11) 1.94 (0.10) 1.31 (0.29) 1.24 (0.33) 102.8 (15.2)

Autism spectrum 20 18 2 19 (2) 1.95 (0.05) 1.31 (0.33) 1.21 (0.44) 103.4 (18.2)

Note: Standard deviations in parentheses.

COGNITIVE NEUROPSYCHOLOGY, 2007, 24 (5) 507

DIVIDED-ATTENTION ADVANTAGE IN AUTISM

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presented at the centre of the screen on a greybackground (luminance ¼ 29.5 cd/m2). Centraltargets were chosen randomly from a pool offour possible letters (E, F, H, and L) and were fol-lowed by a checkerboard pattern mask (seeFigure 1a). Peripheral targets were single whitespots (diameter ¼ 1.4 degrees; luminace ¼

54.5 cd/m2) presented at 4, 8, 12, 16, or 20degrees in the periphery on the grey background,within an array of 20 white circular outlines(each slightly larger in diameter than the periph-eral target: diameter ¼ 1.6 degrees; luminance ¼

54.5 cd/m2). Checkerboard masks (identical tothose used for the central task) appeared in all 20circles following the presentation of the peripheraltarget.

ProcedureAn experimental session began with the assess-ment of observers’ near and far acuities, assessmentof contrast sensitivity (Pelli–Robson ContrastSensitivity Chart; Pelli et al., 1988), and the com-pletion of a health questionnaire. Participants thenwere provided with verbal instructions and visualillustrations of each task before beginning theexperiment. All participants were tested binocu-larly from a distance of approximately 50 cm in adimly lit room. Each testing session was completedin one day and lasted approximately two hours.

The experimental procedure is illustrated inFigure 1. Participants first completed one blockof practice trials followed by three blocks ofexperimental trials. The practice block contained12 trials and consisted of 4 trials of each tasktype (focused-central, focused-peripheral, anddivided-attention), with stimuli presented for800 ms in each case. Practice trial conditionswere sampled randomly, without replacementfrom all possible experimental conditions, foreach task type. Each experimental block contained80 trials. The first experimental block consistedof focused-central trials, the second focused-peripheral trials, and the third divided-attentiontrials. Participants were instructed to maximizetheir accuracy and to take a break at the end ofeach block. The computer program also promptedparticipants to take a rest break half way through

each block. On divided-attention trials, partici-pants were instructed to ensure that they got thecentral task correct first and then do their beston the peripheral task.

Focused-central task. Each trial of the focused-central task comprised four events: ready signal,target, mask, and response. To begin each trialthe word “READY”, which served as the fixationpoint, appeared in the centre of the screen andremained visible until the participant pressed thespace key. After a 1,000-ms blank interstimulusinterval, a letter target then was presented at thecentre of the screen for 60 ms. The four possibleletters (E, F, H, L) were sampled randomlywithout replacement on every trial, and after theletter pool was exhausted, all letters were replaced,and sampling continued. Following the offset ofthe central target, a checkerboard mask was pre-sented for 1,000 ms at fixation. All four possiblecentral targets then were presented in a rowcentred on fixation, with E and F to the left of fix-ation and H and L to the right. The letter choicesremained on the screen until the participantresponded. Participants’ instructions indicatedthat they were to press the key labelled “1” if thepresented letter was E, “2” if it was F, “3” if itwas H, and “4” if it was L. Response keys labelled“1”, “2”, “3”, and “4” corresponded to keys “z”,“x”,“.”, and “/”, respectively, on a standardQWERTY keyboard. This ordering of responsekeys provided a simple mapping to the spatialorder of possible targets on the screen. Auditoryfeedback was provided in the form of a high(correct) or low (incorrect) beep.

Focused-peripheral task. Each trial of the focused-peripheral task began with the presentation of theword “READY” at the centre of the screen. Afterparticipants pressed the space key, placeholdersindicating the 20 possible peripheral locationswere presented and remained in view for the dur-ation of a trial. One second later, the peripheraltarget was presented for approximately 60 ms.The 20 possible peripheral locations weresampled randomly without replacement on everytrial, and after the pool of locations was exhausted,


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Figure 1. Schematic illustration of sequence of events used in Experiment 1 focused-attention central task trials (Panel A), focused-attention

peripheral task trials (Panel B), and divided-attention trials (Panel C). In all cases, each trial began with the presentation of the word

“READY” at the centre of the screen, and participants pressed the space key to start the trial.



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all locations were replaced, and sampling contin-ued. Following the offset of the peripheral target,checkerboard masks were presented at every poss-ible peripheral location for 1,000 ms. Placeholdersthen were presented for all possible peripherallocations with each radial spoke labelled “1”, “2”,“3”, or “4” and remained on the screen until the par-ticipant responded. Participants were instructed topress the key labelled “1” if the peripheral targetappeared anywhere in Spoke 1, “2” if it was inSpoke 2, “3” if it was in Spoke 3, and “4” if it wasin Spoke 4. No feedback was provided for this task.

Divided-attention task. On divided-attentiontrials, “READY” appeared at the centre of thescreen until the observer pressed the space key.Placeholders for all possible peripheral locationsthen were presented and remained on the screenfor the duration of a trial. One second later, thecentral and peripheral targets were presented sim-ultaneously for 60 ms. Following the offset of bothtargets, checkerboard masks were presented for1,000 ms at fixation and at every peripherallocation. The response screen for the central taskthen was presented, and a response was madeand recorded. The response screen for the periph-eral task then was presented, and a response wasmade and recorded. Auditory feedback was pro-vided only for central-task performance.Crossing each of the four possible letters witheach of the 20 possible peripheral locationscreated 80 central-peripheral target combinationsfor divided-attention trials. These conditionswere sampled randomly without replacement onevery trial.

Design and analysisA 2 (group: ASD vs. control) � 2 (attention con-dition: focused vs. divided) � 2 (task type: centralvs. peripheral) � 5 (target eccentricity: 4, 8, 12, 16,or 208) mixed design was used. Group was a

between-subjects variable, whereas attention con-dition, task type, and target eccentricity werewithin-subjects variables. Performance on eachtask type was assessed in separate analyses. For allanalyses the proportion of errors in each taskserved as the dependent variable, with an errorbeing defined as incorrect letter identification forthe central task and incorrect radial localization forthe peripheral task. Radial localization error ratescorrespond to the proportion of times that a partici-pant misidentified the radial direction of the periph-eral target.1 Proportions of errors were transformedby the inverse sine of their square root to normalizethe variance of our measure (Zar, 1974) and toenable comparisons with results from previousresearch (A. B. Sekuler et al., 2000). As both taskswere four alternative forced choice, chanceperformance corresponds to an error rate of .75,which is equivalent to 1.05 on our normalized scale.

Results

Central-task performanceFigure 2a shows central- and peripheral-task per-formance as a function of attention conditionand group, while untransformed error rates arepresented in Table 2. To assess central-task per-formance a 2 (attention condition) � 2 (group)analysis of variance (ANOVA) was conducted onthe transformed data. The main effect of attentioncondition, F(1, 38) ¼ 4.40, MSE ¼ 0.02, p , .05,was significant; as shown in Figure 2a, participantsmade more identification errors in divided- than infocused-attention conditions. No significant groupeffect (F , 1.8, p . .19) was found, and the inter-action between attention condition and group (F,

1) did not reach significance.

Peripheral-task performanceTo assess peripheral-task performance a 2 (attentioncondition) � 2 (group) � 5 (target eccentricity)

1 Previous research with typically developed younger and older observers found similar patterns of results regardless of whether

the error rate was based on absolute localization errors, eccentricity localization errors, or radial localization errors (Sekuler et al.,

2000). We chose to use radial errors here to minimize the response options and equate the guessing rate for central and peripheral

tasks. The use of radial errors also ensures that differences in peripheral performance are not due to differences in visual acuity

(Leibowitz & Appelle, 1969; Post & Leibowitz, 1980)


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ANOVA was conducted. A significant main effectof attention condition, F(1, 38) ¼ 17.51, MSE ¼

0.12, p , .001, and a marginally significant inter-action between attention condition and group were

found, F(1, 38) ¼ 3.48, MSE ¼ 0.12, p ¼ .07).Participants made more errors in divided- thanfocused-attention conditions, and this effectwas sig-nificant for the control group, F(1, 19) ¼ 16.52,MSE ¼ 0.13, p , .001, and not for the ASDgroup, F(1, 19) ¼ 3.01, MSE ¼ 0.10, p ¼ .10,when each of these groups’ peripheral-task resultswere analysed individually with a 2 (attention con-dition) � 5 (eccentricity of target) ANOVA.

Figure 3 presents the peripheral-task resultsreplotted as a function of attention condition,group, and eccentricity of the peripheral target.As can be clearly seen in Figure 3, a significantmain effect of eccentricity, F(4, 152) ¼ 11.48,MSE ¼ 0.02, p , .001, was also found. Moreerrors were made with increasing eccentricity ofperipheral targets, and this effect was significant

Figure 2. (A) Experiment 1 error rates (arcsine of the square root of the proportion of errors) in central-letter identification and peripheral-target

localization tasks are shown as a function of attention condition and group. Error bars indicate + 1 standard error of the mean. (B) Attentional

costs for central and peripheral tasks are shown as a function of testing group. Costs were calculated by subtracting the transformed errors rates in the

focused-attention condition from the transformed error rates in the divided-attention condition. Error bars indicate + 1 standard error of the mean.

Table 2. Proportion of errors in central-letter identification and

peripheral-target localization tasks as a function of attention

condition and group

Central task Peripheral task

Group

Focused

attention

Divided

attention

Focused

attention

Divided

attention

Control .06 (.11) .07 (.08) .22 (.25) .38 (.25)

ASD .08 (.09) .13 (.16) .27 (.25) .33 (.26)

Note: Standard deviations in parentheses. ASD ¼ autism

spectrum disorders.



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for both groups of observers. Post hoc analysis ofperipheral-task performance, using Fisher’s leastsignificant difference (LSD), revealed the follow-ing pattern of significant eccentricity differences.Performance with targets presented at the twoleast eccentric positions (4 and 8 degrees) differedfrom performance with targets presented at thethree most eccentric positions (12, 16, and 20degrees). Performance with targets presented at12 degrees of eccentricity differed marginallyfrom targets presented at 20 degrees of eccentricity(p ¼ .06). None of the other comparisons wassignificant. No significant group effect or othersignificant higher order interactions were found(Attention � Eccentricity; Eccentricity � Group;Attention � Eccentricity � Group; Fs , 1.45,p . .22). In general, the eccentricity of peripheraltargets affected ASD and control groups equallyin both focused- and divided-attention conditions.

As can be seen in Figure 2a, overall error ratesin peripheral-task performance ranged fromapproximately .40 to approximately .60 across allgroups (see Figure 2b for attentional costs).Although previous research has found that periph-eral error rates of older adults (aged 60 years oldand older) can approach chance levels (e.g.,Sekuler et al., 2000), performance of the groupsassessed in the current experiment did notapproach chance levels (1.05 on this scale). Thus,our finding of significantly larger effects of divid-ing attention on peripheral-task performance ofour control than for our ASD group was not dueto a ceiling effect in our ASD group’s performance.

Inspection of Figure 2a (also see Figure 3) alsoindicates that the ASD group may have performedless well in the focused-attention condition thandid the control group, and that this may have con-tributed to the interaction between attention

Figure 3. Experiment 1 peripheral-target errors (arcsine of the square root of the proportion of errors) are shown as a function of attention

condition, testing group, and eccentricity of the peripheral target.


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condition and group. Thus, this baseline differencein peripheral-task performance may have contrib-uted to the larger effect of dividing attention onthe control group than on the ASD group. Toassess whether this was the case, a post hoc analysiswas performed comparing focused-peripheral taskperformance between each group and a compari-son of divided-attention peripheral task perform-ance between groups. No significant differenceswere found between ASD and control groups’focused-attention performance (F , 1) andbetween each groups divided-attention perform-ance (F , 1). This indicates that basic groupdifferences in peripheral-task performance withineach of these attention conditions are not thesource of the Attention Condition�Group inter-action. It is the difference between the focused-and divided-attention conditions across groups(i.e., attention costs) that is causing this two-wayinteraction, supporting our assertion that dividedattention has larger effects on our control groupthan on our ASD group.

DISCUSSION

Our primary interest in this study was to testwhether people with autism would show a costof divided attention in a task that created compe-tition between central and peripheral attention,and whether this cost was enough to interferewith an expected visual search-type advantage.Contrary to predictions related to task complexity(Bertone et al., 2005) limited attentional abilities(Burack, 1994), and evidence of an autism specificdeficits in attention shifting (Courchesne,Townsend, Akshoomoff, & Saitoh, 1994;Rinehart et al., 2001) participants with autismshowed a significantly smaller cost of dividedattention on the peripheral-localization task thandid matched controls. It appears that people withautism are better able to divide attention in theUFOV task than can control individuals.

Our findings also contrast with past empiricalfindings from Mann and Walker (2003), whichsuggest that people with autism spectrum dis-orders have deficits in expanding visual attention.

Our results seem incompatible with this con-clusion, because our participants did not show adeficit in our peripheral task in the divided-attention condition, relative to the control group.Our participants were able to use information inthe foveal area and then in the periphery whenthe information was presented simultaneously.For the same reasons, our results also contrastwith those of Rinehart et al. (2001), who foundthat observers with autism responded moreslowly when a global target followed a localtarget, but not when a local target followed aglobal target in a hierarchical letter detectiontask. However, notice that the UFOV task doesnot vary the attentional set across trials. We didnot ask participants to expand their attentionalfocus from trial to trial, so our results may beincompatible with the results of these two previousexperiments.

Although this result is surprising in the contextof some previous theoretical approaches, it is poss-ible to interpret our results in terms of a visualsearch paradigm. The peripheral-task componentof the UFOV task is essentially a visual searchtask, in that observers have to find a filled targetamong unfilled distractors. Past research showsan advantage in autism in visual search tasks(O’Riordan et al., 2001). The fact that we do notfind evidence for individuals with ASD perform-ing better on the peripheral task than controlsunder a focused-attention condition suggests thatthere are some limits to the extent of a generalvisual search advantage for individuals withASD. However, the relatively superior perform-ance of individuals with ASD on our peripheraltask in the divided-attention condition is consist-ent with a visual search advantage. Our resultssuggest that this advantage is strong enough towithstand a divided-attention manipulation.

Similarly, observers were not required to inte-grate information across the visual display. It ispossible that visual integration, an early step inthe process of extracting meaning from a visualdisplay, is the process that people with autismhave difficulty with. In the UFOV display thereis no need to integrate information across differentparts of the visual field, so a deficit in this ability



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would not change performance on this particulartask. The deficit seen in autism has been character-ized as seeing intricate detail at the expense of per-ceiving global meaning. Our stimulus did not offerany globally meaningful information, just visuallyeccentric information. This difference in stimulimay account for the difference in results. Thesimple notion that individuals with autism necess-arily overfocus on a small target (e.g., the centralletter) is not supported by our results.

There has been some interest recently inexplaining the social and especially perceptualanomalies in autism in terms of abnormal neuralprocessing. Although some authors have suggestedthat deficits in the perception of motion indicate aprocessing problem in the magnocellular pathways(Milne et al., 2002; Pellicano, Gibson, Maybery,Durkin, & Badcock, 2005), recent work byBertone and colleagues suggests that these beha-vioural differences can be entirely explained bythe complexity of the stimuli used in the exper-iments (Bertone & Faubert, 2006; Bertone et al.,2003, 2005). They operationalize complexity bycomparing first-order (luminance defined) andsecond-order (texture defined) motion and findthat contrary to previous reports, people withautism have no difficulty perceiving motion, aslong as the motion is first-order motion. Peoplewith autism do show difficulties with second-order motion, which the authors argue is morecomplex. Others have also suggested that com-plexity of the stimuli account for differences invisual processing in autism (Minshew &Goldstein, 1993; Minshew, Goldstein, & Seigel,1995, 1997). Our findings are surprising in lightof this view as well, since the divided-attentiontrials are, if anything, more complex than eitherthe central or peripheral tasks.

Our primary interest in this study was a test ofwhether people with autism would show a cost ofdivided attention in a task that created compe-tition between central and peripheral attention,and whether this cost was enough to interferewith an expected visual-search-type advantage.Contrary to the predictions of some prominenttheories, participants with autism showed a sig-nificantly smaller cost of divided attention than

did matched controls. This finding may beexplained in terms of the fact that the stimulilacked global meaning, or in terms of low-levelperceptual differences between the groups.

Manuscript received 29 September 2005

Revised manuscript received 8 June 2007

Revised manuscript accepted 12 June 2007

First published online 14 July 2007

REFERENCES

Ball, K., Beard, B. L., Roenker, D. L., Miller, R. L., &Griggs, D. S. (1988). Age and visual search:Expanding the useful field of view. Journal of the

Optical Society of America A, 5, 2210–2219.Ball, K., Berch, D. B., Helmers, K. F., Jobe, J. B.,

Leveck, M. D., Marsiske, M., et al. (2002). Effectsof cognitive training interventions with olderadults. A randomized controlled trial. Journal of the

American Medical Association, 288, 2271–2281.Ball, K., Cissell, G. M., Edwards, J. D., Roenker, D. L.,

& Wadley, V. G. (2003). Speed-of-processing anddriving simulator training result in improveddriving performance. Human Factors, 45, 218–233.

Ball, K., Owsley, C., & Beard, B. (1990). Clinical visualperimetry underestimates peripheral field problemsin older adults. Clinical Vision Sciences, 5, 113–125.

Bertone, A., & Faubert, J. (2006). Demonstrations ofdecreased sensitivity to complex motion informationnot enough to propose an autism-specific neuraletiology. Journal of Autism and Developmental

Disorders, 36, 55–64.Bertone, A., Mottron, L., Jelenic, P., & Faubert, J.

(2003). Motion perception in autism: A “complex”issue. Journal of Cognitive Neuroscience, 15, 218–225.

Bertone, A., Mottron, L., Jelenic, P., & Faubert, J.(2005). Enhanced and diminished visuo-spatialinformation processing in autism depends onstimulus complexity. Brain, 128, 2430–2441.

Burack, J. A. (1994). Selective attention deficits inpersons with autism: Preliminary evidence of an inef-ficient attentional lens. Journal of Abnormal

Psychology, 103, 535–543.Courchesne, E., Townsend, J., Akshoomoff, N. A., &

Saitoh, O. (1994). Impairment in shifting attentionin autistic and cerebellar patients. Behavioral

Neuroscience, 108, 848–865.


RUTHERFORD ET AL.

Dow

nloa

ded

by [

Uni

vers

ity o

f So

uthe

rn Q

ueen

slan

d] a

t 03:

45 0

5 O

ctob

er 2

014

Dakin, S., & Frith, U. (2005). Vagaries of visual percep-tion in autism. Neuron, 48, 497–507.

Happe, F., & Frith, U. (2006). The weak central coher-ence account: Detail-focused cognitive style inautism spectrum disorders. Journal of Autism and

Developmental Disorders, 36, 5–25.Ikeda, M., & Takeuchi, T. (1975). Influence of foveal

load on the functional visual field. Perception and

Psychophysics, 18, 255–260.Jolliffe, T., & Baron-Cohen, S. (1997). Are people with

autism and Asperger syndrome faster than normal onthe Embedded Figures Test? Journal of Child

Psychology and Psychiatry, 38, 527–534.Leibowitz, H. W., & Appelle, S. (1969). The effect of a

central task on luminance thresholds for peripherallypresented stimuli. Human Factors, 11, 387–392.

Lord, C., Risi, S., Lambrecht, L., Cook, E. H.,Leventhal, B. L., DiLavore, P. C., et al. (2000).The Autism Diagnostic Observation Schedule–Generic: A standard measure of social and communi-cation deficits associated with the spectrum ofautism. Journal of Autism and Developmental

Disorders, 30, 205–223.Lord, C., Rutter, M., & LeCouteur, A. (1994). Autism

Diagnostic Interview–Revised: A revised version ofa diagnostic interview for caregivers of individualswith possible pervasive developmental disorders.Journal of Autism and Developmental Disorders, 24,659–685.

Mann, T. A., &Walker, P. (2003). Autism and a deficitin broadening the spread of visual attention. Journal

of Child Psychology and Psychiatry and Allied

Disciplines, 44, 274–284.Milne, E., Swettenham, J., Hansen, P., Campbell, R.,

Jeffries,H.,&Plaisted, K. (2002).Highmotion coher-ence thresholds in children with autism. Journal of

Child Psychology and Psychiatry, 40, 255–263.Minshew, N., & Goldstein, G. (1993). Is autism an

amnesic disorder? Evidence from the CaliforniaVerbal Learning Test. Neuropsychology, 7, 209–216.

Minshew, N. J., Goldstein, G., & Seigel, D. J. (1995).Speech and language in high-functioning autisticindividuals. Neuropsychology, 9, 261.

Minshew, N. J., Goldstein, G., & Seigel, D. J. (1997).Neuropsychological functioning in autism: Profileof a complex information processing disorder.Journal of the International Neuropsychological Society,3, 303–316.

Mottron, L., Dawson, M., Soulieres, I., Hubert, B., &Burack, J. (2006). Enhanced perceptual functioningin autism: An update, and eight principles of autistic

functioning. Journal of Autism and Developmental

Disorders, 36, 27–43.O’Riordan, M. A., Plaisted, K. C., Driver, J., & Baron-

Cohen, S. (2001). Superior visual search in autism.Journal of Experimental Psychology: Human Perception

and Performance, 27, 719–730.Pelli, D. G., Robson, J. G., &Wilkins, A. J. (1988). The

design of a new letter chart for measuring contrastsensitivity. Clinical Vision Sciences, 2, 187–199.

Pellicano, E., Gibson, L., Maybery, M., Durkin, K., &Badcock, D. R. (2005). Abnormal global processingalong the dorsal visual pathway in autism: A possiblemechanism for weak visuospatial coherence?Neuropsychologia, 43, 1044–1053.

Plaisted, K., O’Riordan, M., & Baron-Cohen, S.(1998). Enhanced visual search for a conjunctivetarget in autism: A research note. Journal of Child

Psychology and Psychiatry and Allied Disciplines, 39,777–783.

Post, R. B., & Leibowitz, H. W. (1980). Independenceof radial localization from refractive error. Journal of

the Optical Society of America, 70, 1377–1379.Richards, E., Bennett, P. J., & Sekuler, A. B. (in press).

Aging, learning and the useful field of view. Vision

Research.Rinehart, N. J., Bradshaw, J. L., Moss, S. A.,

Brereton, A. V., & Walker, P. (2001). A deficitin shifting attention present in high-functioningautism but not Asperger’s disorder. Autism, 5,67–80.

Rizzo, M., & Robin, D. A. (1996). Bilateral effects ofunilateral visual cortex lesions in humans. Brain,119, 951–963.

Sekuler, A. B., Bennett, P. J., & Mamelak, M. (2000).Effects of aging on the useful field of view.Experimental Aging Research, 26, 103–120.

Sekuler, R., & Ball, K. (1986). Visual localization: Ageand practice. Journal of the Optical Society of America

A, 3, 864–867.Shah, A., & Frith, U. (1983). An islet of ability in autis-

tic children: A research note. Journal of Child

Psychology and Psychiatry and Allied Disciplines, 24,613–620.

Wechsler, D. (1997). Wechsler Adult Intelligence Scale

(3rd ed.). San Antonio, TX: PsychologicalCorporation Harcourt Brace & Company.

Williams, L. J. (1982). Cognitive load and thefunctional field of view. Human Factors, 24,683–692.

Zar, J. H. (1974). Biostatistical analysis. EnglewoodCliffs, NJ: Prentice Hall.



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Evidence of a divided-attention advantage in autism