working memory in children with autism and with moderate learning difficulties

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0021-9630(95)00169^-7

J. Child Psyehol. Psyehiat. Vol. 37, No. 6, pp. 673-686, 19%€> 1996 Association for Child Psychology and Psydiiatry

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Working Memory in Children with Autism and with Moderate LearningDifficulties

James Russell and Christopher JarroldDepartment of Experimental Psychology,

Cambridge University, U.K.

Lucy HenryDepartment of Psychology, Reading University, U.K.

We asked whether children with autism are specifically impaired on tests of workingmemory. Experiment 1 showed that children with autism were at least as likely as normalchildren to employ articulatory rehearsal (criterion: evincing the "word length effect")and that they had superior spans to that of children with moderate learning difficulties. InExperiment 2, participants were given "capacity tasks" in order to examine groupdifferences in the capacity of the central executive of working memory. The performanceof the children with autism was inferior to that of the normally developing group andsimilar to that of the children with moderate learning difficulties.

Copyright © 1996 Association for Child Psychology and Psychiatry.

Keywords: Autism, executive functions, working memory, mental handicap

Abbreviations: ID/ED, the Intra-dimensional/Extradimensional task; TOH, the Tower ofHanoi task; TOL, the Tower of London task; VMA, verbal mental age; WCST, theWisconsin Card Sorting Task

It is now well established that children with autism arespecifically impaired on tests of executive functioning.Such tests require on-line planning, shifting of atten-tional set and the inhibition of incorrect responses thatare "prepotent" because salient features of the environ-ment call them out or because past learning has madethem difficult to abandon. In different ways, such testsrequire top-down, goal-directed processing; and themental operations necessary for completing them areassumed to be those carried forward by the pre-frontalcortex (Shallice, 1988).

Individuals with autism perform poorly compared tocontrols matched for verbal mental age on the Tower ofHanoi (TOH) planning task, a task that requires thegeneration and the holding in mind of future moves(Ozonoff, Pennington & Rogers, 1991) and on its(derivative the Tower of London (TOL) task (Hughes,Russell & Robbins, 1994). Their difficulties withsecond-order "theory of mind" tasks (e.g. "A thinksthat B thinks that X"; Happe, 1994; Ozonoff et al, 1991)may also be executive in nature insofar as they requirethe on-line, strategic manipulation of data (see Tager-Flusberg & Sullivan, 1994 for a study in support of thisview). They perform poorly on the Wisconsin CardSorting Task (WCST) that requires a shifting of responsecategory (Ozonoff et al, 1991) and on the intra-dimensional/extra-dimensional (ID/ED) shift task requir-

Requests for reprints to: James Russell, Department ofExperimental Psychology, Cambridge University, DowningStreet, Cambridge CB2 3EB, U.K.

ing a similar kind of shift (Hughes et al, 1994). Theirdifficulties with inhibiting prepotent responses areevident in their performance on tasks requiring subjectsto ignore a goal object and to refer instead to an adjacent,empty location (the "windows task": Russell, Mauthner,Sharpe & Tidswell, 1991; Hughes & Russell, 1993) or toignore a goal object and make a seemingly arbitraryresponse (the "box task": Hughes & Russell, 1993).Their difficulties with appearance-reality judgementsabout trick objects (Baron-Cohen, 1989) also yield to anexplanation in terms of prepotency.

The reason why specific impairments in "mental-ising" (e.g. Baron-Cohen, Tager-Flusberg & Cohen,1993) and in executive control co-exist in autism is notclear. Some have argued that "theory of mind"impairments are sui generis and can be regardedseparately from executive problems (Leslie & Thaiss,1992); while others have argued that social (Pennington,1994) and mentalising (Russell, 1995, 1996) impair-ments may be caused by early executive impairments.But whatever the relationship between these twoimpairments, it is important to determine whichcomponents of the executive system are impaired inthe disorder.

The principal aim of the present investigation was toask whether working memory is one of the componentsof the executive system impaired in autism. The reasonfor doing this is that all of the executive tasks describedabove depend upon the adequate functioning of theworking memory system. In every case, an arbitrary rulehas to be held in mind (e.g., sort by colour; point to theempty box) while the influence of a prepotent response

673

674 J. RUSSELL et al.

has to be resisted (e.g., abandon sorting by shape; do notpoint to the box containing the sweet). Indeed it couldturn out to be the case that learning-engendered orenvironment-based prepotency have relatively minorroles to play and that these only have their effects bydefault—^because the working memory system is soinefficient. This point has been thoroughly made byPennington (1994), and similar claims have been madeby Kimberg and Farah (1992) who support theirargument by a computer simulation. Likewise, Roberts,Hager and Heron (1994) argue that many "frontal" tasksinvolve an interaction between the strength of theincorrect prepotent response and the efficiency ofworking memory, and succeed in demonstrating thatwhile such tasks may vary in their surface form the sameunderlying demands are present. Finally, a factor-analytic study by Daigneault, Braun and Whitaker(1992) with a group of normal adults showed that awide range of frontal tasks load heavily on "representa-tional memory", a finding which they interpret assupporting Goldman-Rakic's (1987) view that theprimary function of the prefrontal cortex is that of"representational memory". So it is reasonable toconclude that tasks that simultaneously involve bothinhibition and working memory typically tap pre-frontalfunctioning (see Diamond, 1991; Gerstadt, Hong &Diamond, 1994).

We approached the question of whether children withautism have a specific impairment in working memoryby adopting the theoretical framework of Baddeley andHitch (1974) in which it is assumed that memory tasksvary in the degree to which they recruit the "centralexecutive". In that model, a distinction is drawn betweenthe processing carried out in this central executive andthat carried out by the subsidiary or "slave" systems*.The central executive (discussed in Baddeley, 1986) is asystem of limited capacity that performs mental opera-tions while data are being temporarily held off-line in theslave systems so as to ensure that they do not take upcentral processing space. One of these slave systems isthe "articulatory loop", a system that refreshes verbalinformation by articulatory rehearsal and whose capacityis limited by the speed at which this articulation can beperformed (Baddeley, Thomson & Buchanan, 1975).

Immediate verbal memory tasks primarily involve theoperations of the articulatory loop, on this model On the

*There are also models that treat working memory as a unitarysystem in which storage and processing compete for acommon, developmentally invariant space. Case (Case et al ,1982), for example, claims that the working memory systemcontains a single processing space in which data are stored andin which mental operations are performed and that there is atrade-off between these two such that the greater the efficiencyof the operations the greater the amount of space available forstoring data. This is supposed to account for the fact that short-term memory improves with age. But while this model isclearly different to that of Baddeley and Hitch, it shares with itthe assumption that the amount of data that can be held inmind during the performance of capacity tasks can provide ameasure of the efficiency of mental operations. Indeed Case(1992) has more recently argued that capacity tasks (tasks thatrequire simultaneous processing and memory) index thedevelopment of the pre-frontal cortices.

other hand, tasks which involve the simultaneousperformance of some central process (e.g., counting)and the storage of information on the loop (e.g., a seriesof totals) test the efficiency and capacity of the centralexecutive in addition to that of the articulatory loop. Wewill refer to such tasks as "capacity tasks". If it is thecase that the operation of the articulatory loop inimmediate recall makes relatively modest demands uponthe central executive of working memory whileperformance on capacity tasks informs us about theefficiency of the central executive then we shouldpredict that if children with autism are specificallyimpaired in working memory {qua an essentiallyexecutive system) they will not be impaired in the firstcase and that they will be impaired in the second case.

Before describing the studies, we will review briefiywhat is currently known about the performance ofindividuals with autism on the kinds of memory taskrelevant to the present issues. First, a classic study byHermelin and O'Connor (1970) showed that immediatememory is unimpaired in autism; although it is aseparate question, of course, whether these subjectsachieved adequate immediate memory via the articu-latory loop. Second, two studies have shown thatsubjects with autism have deficits in free recall togetherwith unimpaired cued recall (Boucher & Warrington,1976; Tager-Flusberg, 1991). When coupled with thefact that a further study by Boucher showed a lowerprimacy effect in subjects with autism than in matchedcontrols (Boucher, 1981), the possibility emerges thatpersons with autism may be impaired in the moreeffortful and strategic memory functions. Minshew andGoldstein (1993) have, however, recently reported afailure to unearth a specific free-recall deficit in a groupof individuals with autism tested on the CaliforniaVerbal Learning Test.

Bennetto, Pennington and Rogers (in press) perfonneda study more directly relevant to our present concerns.They asked whether persons with autism are impaired onthe kinds of memory tasks on which individuals withlesions to the pre-frontal cortices are impaired (Shima-mura, Janowsky & Squire, 1991 for a review) and to thisend gave the following tasks to a group of adults andadolescents with autism but with IQs within the normalrange: working memory capacity tasks, free recall,source memory and memory for temporal order. Forpurposes of comparison, the participants also competedtasks which were assumed to load only lightly onexecutive operations—cued recall, recognition memory,and new learning ability. Bennetto et al. report that theirgroup of autistic subjects was impaired on the first,broadly "frontal" set of memory tasks relative tocontrols matched for IQ, but that they were not impairedon the second set of tasks, and used this finding insupport of their view that one of the core deficits inautism is "a general deficit in working memory". Indeedthey arg,ue that such a deficit may underlie the kind ofdifficulties which persons with autism experience inunderstanding the social world.

In the light of these data the prediction can reasonablybe made that children with autism will show no evidenceof dysfunctions of the articulatory loop but will beimpaired on capacity tasks—insofar as these are heavily

WORKING MEMORY IN AUTISM 675

dependent upon an adequate central executive. If thisprediction is fulfilled it will be further evidence for theBennetto et al. claim that autism is characterised by ageneral deficit in working memory. Our first experimentconcerned the articulatory loop and our second con-cerned performance on capacity tasks.

Table 1Participant Details for Experiment 1

Group

NCA(months)VMA(months)

MeanSDMeanSD

Autism

33148.6135.4375.2114.22

MLD

33129.7923.2674.8214.20

Normal

3375.3314.32

Experiment One

Baddeley and Hitch (1974) proposed that the capacityof the articulatory loop is limited by the speed withwhich verbal material can be rehearsed, with memorytraces decaying within 1-2 seconds unless refreshed byrehearsal In support of this idea, it has been possible toshow that memory span is related to the time it takesindividuals to vocalise the materials to be remembered(Standing, Bond, Smith & Isely, 1980). Moreover, bothadults (Baddeley & Hitch, 1974) and children (Hulme,Thomson, Muir & Lawrence, 1984) show the "wordlength effect" i.e., they can remember fewer words thattake a long time to articulate (e.g., "helicopter") thanwords which can be spoken quickly (e.g., "cat")*. In ourfirst experiment we asked whether children with autismdemonstrate a word length effect comparable to that ofnormally developing children and comparable to thatshown by children with moderate learning difficulties(MLD children) matched for verbal mental age. The twoclinical groups were matched on verbal mental age onlybecause matching for nonverbal mental age is insuffi-ciently stringent, given that the nonverbal mental ages ofchildren with autism are typically higher than theirverbal mental ages. Matching for nonverbal mental agewould therefore have been inappropriate.

The presentation of the words in this experiment wasauditory, with either spoken or nonverbal (by pointing)recall being required. We varied the mode of output inthis way in order to determine the degree to which theword length effect was, for any group, a function of howlong it took to articulate the words when reporting them.If a group of subjects or an individual subject is taking aparticularly long time to speak the words then thememory trace of words in the output buffer will havemore opportunity to decay. For this reason, it might besaid that using nonverbal output gives us a "purer"measure of the word length effect—one uncontaminatedby articulation time at recall

*Although there is some controversy as to whether the wordlength effect is indeed an index of rehearsal (Henry, 1991;Henry & Millar, 1991, 1993), this is not of immediaterelevance to the current study; our focus is on immediate recallas a task which makes on modest demands on the centralexecutive in working memory.

Method

Participants. We tested three groups of participants,with 33 children in each: children with autism, childrenwith moderate learning difficulties (MLD) and normallydeveloping children. Participant details are give in Table1. Each child with autism was matched with a child withMLD on the basis of verbal mental age as assessed bythe long form of the British Picture Vocabulary Scale(Dunn, Dunn, Whetton & Pintilie, 1982) and with anage-appropriate normally developing child.

The children with autism were selected on the basis ofshowing the characteristic symptoms of the disorder,namely severe problems in socialisation, impoverishedlanguage use, and impaired communicative ability(DSM III-R; APA, 1987). All children were attendingschools or special units for children with autism. Thechildren with MLD were drawn from schools inCambridge for children with a variety of learningdifficulties. The normally developing children wereattending Infant and Primary schools in Cambridge.

Design. Each child in each group received verbalshort-term memory tasks with both short (single-syllable) and long (three-syllable) words. In addition,each child had either to recall the words by speakingthem aloud or by pointing to the relevant pictures(henceforth: "verbal" versus "nonverbal" recall). Achild received either the verbal recall condition first orthe nonverbal recall condition first. Speed of wordarticulation was assessed in all participants. There were,therefore, two within-subjects variables (word length,and order of recall task), in addition to the between-subjects variable of group (three groups).

Materials. The short-term memory tasks were pre-sented on a Macintosh computer using a HyperCardprogram devised by Cox, Hulme and Brown (1992),enabling automatic control of presentation rate as well asother aspects of presentation and of data logging.Nonverbal recall was assessed using two picture boards,one for each word length, which displayed line drawingsof the nine objects corresponding to the nine words ineach set. These were approximately 10 cm by 7 cm insize, and were displayed in a 3 x 3 array. The wordswere all high-frequency concrete nouns. The nine shortwords were: bee, bone, cup, gate, lamp, nail, pig, shoe,tent. The nine long words were: bananas, bicycle,caterpillar, elephant, grandmother, newspaper, police-man, radio, telephone. These two sets were matched for


Table 2Mean Spans and Speech Rates for Experiment 1

Group

Autism

MLD

Normal

MeanSDMeanSDMeanSD

Verbal

Short Ws

3.520.913.080.723.990.87

recall

Long Ws

3.170.582.650.693.410.90

Spans

Non-verbal

Short Ws

3.650.853.000.803.821.07

recall

Long Ws

2.960.582.730.653.360.78

Speech rates(words/second)

Short Ws

2.770.832.400.582.660.73

Long Ws

1.590.331.400.291.500.24

word frequency as presented in Carroll, Davies andRichman (1971) grade 3 counts.

Procedure. Participants were tested in two sessions ofaround 10 minutes duration. Each session began with atest of articulation speed, in which children were askedto repeat word pairs drawn from the two sets of wordsused in the experiment. Articulation rate for short wordswas assessed in the first session, and long wordarticulation rate was measured in the second session.For each set of words five word pairs were selected (soone of the nine words was repeated once), and childrenhad to repeat each pair five times. These sessions wereaudio-recorded for subsequent timing with a stopwatch.

Following the measurement of articulation rate, spanfor short and long words was assessed. The words were"spoken" by the computer within a 1-second period, andonce the computer had finished presenting the list theexperimenter signalled that the child should recall thewords. Initially only one word was presented, afterwhich the number of presented words increased in astep-wise manner. Three trials were given at each listlength, and the two lengths of words were presentedseparately, with the short words coming first. Listlengths were increased until the child failed at leasttwo of the three trials. On any trial the computer

programme randomly selected the required number ofwords from the pool of nine being used. FollowingHenry (1991), span was taken to be equal to the longestlist length at which a child had been correct on two orthree of the three trials, while a further half point wascredited if the child was correct on one of the three trialsat the next list length.

In the verbal recall condition children had to repeatimmediately the words they had heard in the correctorder. In the nonverbal recall condition they immediatelyhad to point, in the correct order, to the appropriatepictures on a response board that contained all ninepictures. In the latter case, the pictures were covereduntil the list had been presented to ensure that thechildren did not encode a spatial sequence before recall.In both conditions the children were told to recall thewords in the order in which they had been presented.These two conditions were spread between the twosessions, with half of the children receiving verbal recallfirst, and the other half beginning with nonverbal recall.Within each condition, half of the children were giventhe short words first and the other half were given thelong words first.

Mag. ofWordLengthEffect

Verbal Non-VerbalRecall Condition

Figure 1. The absolute magnitive of the word length effect shown by each group in eachrecall condition. * Children with autism show a significantly greater word length under non-verbal than under verbal recall (p = .02). ^Children with autism show a greater non-verbal

word length effect than children with MLD (p < .05).


Results

Mean spans and articulation speeds for each of thethree groups are given in Table 2.

A three-way analysis of variance (ANOVA) wasperfonned on the data shown in Table 2, with thebetween-subjects variables of group (3) and the within-subjects variables of word length (2) and recall condition(2). The main effect of group was significant: F(2,96) = 10.72, p < .001. This was due to the fact thatchildren with MLD had significantly lower spans thanthose of the other two groups {p < .05 on Newman-Keuls test; all subsequent post-hoc comparison of meanswill be by Newman-Keuls). The spans of children withautism and of the mainstream children did not differsignificantly. There was also a significant main effect ofword length [F(l, 96) = 100.70, p < .001] but nosignificant interaction between this factor and group:F(2, 96) = 1.52; p = .22. The main effect of recallcondition was not significant: F(l, 96) = 0.91, p = .34.

There was a significant three-way interaction betweengroup, condition, and word length: F{2, 96) = 3.69,p = .03). Post-hoc analysis of simple effects showed thatthis was due to a significant group by word lengthinteraction for nonverbal recall [F{2, 90) = 3.12, p = .05]but not for verbal recall {F{2, 90) = 1.44, p = .24). Undernonverbal recall conditions the children with autismshowed a significantly larger word length effect than thechildren with MLD {p < .05). Further, the word length bycondition interaction was significant for the childrenwith autism [F(l, 90) = 5.82, p = .02], but not for theother two groups [MLD: F(l, 90) = 1.10, /? = .30;mainstream: F{1, 90) = 0.70, p = .40]. Inspection ofTable 2 shows that this is due to a greater word lengtheffect under nonverbal than under verbal recall forchildren with autism. Figure 1 summarises the pattern ofdata just described.

A second analysis examined whether the groupdifferences in span might be accounted for in terms ofdifferences in the average speech rates of the groups. Tothis end, an analysis of covariance (ANCOVA) wasperformed, which employed measures of articulationrate as covariates against span scores. As articulationrate was assumed not to vary with recall condition, spansfor short and for long words were averaged across verbaland nonverbal recall. The ANCOVA analysis thereforehad the between-subjects variable of group (3), and thewithin-subjects variable of word length (average forshort words, average for long words) with the twocovariates of articulation rate for short words andarticulation rate for long words.

It should be noted that ANCOVA is subject toassumptions which can complicate the interpretation ofthe findings and that the situation is particularlyproblematic for a mixed analysis of this kind (Tabach-nick, 1989, pp. 338-339). Two separate regressions werefitted to the data, one for within-subject effects and onefor between-subject effects, with normality of distribu-tion, homogeneity of variance and homogeneity ofregression being assumed across all cells. Preliminaryanalysis suggested that these latter assumptions were notall met in all cases and that, accordingly, the results ofthis analysis should be interpreted with some caution.

Further, the within-subjects regression fitted by theanalysis was nonsignificant [F(l, 94) < 0.01, p = .96]indicating that differences in an individual's span acrossdifferent word lengths were not reliably predicted bydifferences in their speech rates for short and longwords. The lack of a significant regression invalidatesany further examination of the effect of word length orof group by word length interactions. The between-subject regression fitted via this analysis was, bycontrast, significant [F(l, 94) = 4.34, p = 0.04], indicat-ing that differences in average speech rates did predictdifferences in average spans across individuals.

After speech rate had been covaried out of theanalysis, the main effect of group remained highlysignificant [F(2, 94) = 9.76, p < .01], and comparison ofadjusted means with observed means showed thatcovariance, though significant, made little absolutedifference to the span scores. This resulted in thefollowing means: children with autism—original = 3.37,adjusted = 3.33; children with MLD—original = 2.86,adjusted = 2.91; mainstream children—original = 3.64,adjusted = 3.64.

In summary, this analysis of covariance shows thatspans are predicted by speech rates to some extent, butthat group differences in spans cannot be explained bygroup differences in speech rates. As noted, it alsoindicates that the word length effect at an individuallevel cannot be explained in terms of differences inspeech rates for short and long words. One possiblereason for the discrepancy between this latter finding andthe fact that spans are broadly predicted by speech rate isthat some of the groups were not employing thearticulatory loop in a normal fashion. In support of thissuggestion, individual speech rates correlate withaverage span across both recall conditions for themainstream children {r = .51, N = 33, p< .01 for shortwords; r = .41, N = 33, p = .02 for long words) but notfor children with autism and children with MLD (rranges from - .30 to +.08, N = 33, p^ .34). Never-theless, all these groups show significant word lengtheffects; so the articulatory loop does appear to befunctioning "normally" at least on that criterion.

Before passing on, we need to address the possibilitythat the reason we found no significant conelationsbetween individual spans and individual rates in theclinical groups is that our rate measures were insensitive.This is unlikely to have been the case because thecorrelations within children between rate for short andlong words were strong in the clinical groups andcomparable to those for normally developing children:children with autism—r = .53, N=33,p< .01; childrenwith MLD—r = .46, N = 33,p< .01; normally develop-ing children—r = .62, N = 33,p< .01.

Finally, it can be noted that VMA scores in the twoclinical groups were related to the mean (i.e., across longand short words) spans; although this relationship wasclearer in the MLD children. In the children with autism,VMA correlated with span when assessed nonverbally(r = .38, N=33,p- .03) but not when assessed verbally(r = .23, iV= 33; p = .21). In the MLD children, VMAcorrelated with both nonverbal (r = .49, N - 33;p = .004) and verbal (r = .48, N^'iTt, p = .004) spans.


ITiese correlations were not significantly higher in thelatter groups than in the former.

Discussion

The finding of primary interest from this experimentis that the word length effect in children with autism is atleast as substantial as that shown by normally developingchildren. This is especially clear when nonverbal ratherthan verbal recall was required. This result is consistentwith the articulatory loop being unimpaired in autism.Moreover, when we compare span across the threeexperimental groups we see that it is the children withMLD who are impaired relative to the other two groupsrather than the children with autism.

What makes it difficult to conclude firmly that "thearticulatory loop is unimpaired in autism" is the factthat, while both clinical groups demonstrated a wordlength effect, in neither case were significant correla-tions found between span and articulation rate for thechildren in these groups. For the normally developingchildren, by contrast, such correlations were found bothfor the long and for the short words. So if we make theexistence of such conelations a necessary condition forsaying that a group of subjects is "employing thearticulatory loop" a question-mark must remain over thetwo clinical groups. We can conclude, however, thatthere is no evidence that children with autism arespecifically impaired in their employment of thearticulatory loop because the lack of a clear relationshipbetween articulation rate and span in the children withautism is mirrored in the data for the MLD children.

Before discussing further features of the data we needto note that our data from MLD children are differentfrom those which Hulme and Mackenzie (1992) reportfor children with severe (rather than moderate) learningdifficulties and for children with Down's Syndrome. Thespans of these children were not reliably affected byword length. Hulme and Mackenzie conclude from thisfact that these children were not rehearsing and supporttheir claim with a training study. / / we take demonstra-tion of the word length effect to indicate rehearsal (seecaveat in footnote 2), our MLD subjects would be said tohave been rehearsing. This raises the possibility thatrehearsal is only found above a certain level of generalintelligence.

We now turn to the question of why the size of theword length effect was larger with nonverbal than withverbal output in the children with autism but not in theother two groups. Indeed in the nonautistic children thesize of the effect was (nonsignificantly) smaller in thenonverbal condition. It can be seen (Table 2) that in thechildren with autism the mean span for short words wasslightly increased with nonverbal output while the meanspan for long words was clearly decreased. How mightone account for this? In the first place, as we arguedearlier, nonverbal output can be said to give a purermeasure of the word length effect because verbal outputis contaminated by how long it takes a subject to say thewords at recall. Perhaps data from nonverbal output aresimply more reliable. In the second place, it is possiblethat when a subject has both to remember words andpoint to pictures at the same time an element of response

competition is being introduced, with the result that thelonger acoustic traces are, the more vulnerable theybecome to disruption through having to perform aconcurrent motor act. We have, however, no reason tobelieve that children with autism are particularlysusceptible to such effects.

We will discuss the reasons why the spans of theMLD children were lower than those of the children withautism after the data have been reported from Experi-ment 2. It will be seen that these differences are bestregarded in the light of the data on capacity tasks.

Experiment Two

Having demonstrated in our first experiment thatchildren with autism appear to utilise the articulatoryloop in a way that is not substantially different to theway it is utilised by normally developing children andthat their spans are superior to those of MLD children,we tested our prediction that they are specificallyimpaired on capacity tasks. These are tasks whichrequire the concurrent storage of information and theperformance of a relevant cognitive task. In contrast to"dual" tasks in which the subject simultaneouslyperforms two unrelated tasks (e.g., a motor and a verbaltask; see Baddeley, 1986 for discussion), in capacitytasks the processing task (e.g., counting) is related to thestorage task (e.g., recalling the totals).

In a developmental context, at least three kinds ofcapacity tasks have been employed to date. Because weused all three in Experiment Two we will describe thembefore reviewing the relevant data. In the first place.Case and his colleagues devised a task in which subjectshave to count dots on a series of cards whileremembering the totals of the cards previously counted.Using this task. Case, Kurland and Goldberg (1982)showed that in children between 6 and 12 years of agethere was a correlation between the child's counting span(i.e., the highest number of totals recalled) and the rate atwhich the stimuli were being counted. Older childrenrecall more totals, they argued, because of their greaterprocessing efficiency. They fiirther claimed that thishypothesis was confirmed by the fact that when adults'counting speeds were artificially lowered by havingthem count with nonsense words their recall totals weresimilar to those of 6-year-old children.

A second kind of capacity task is one owing toDaneman and Carpenter (1980). In this, the individualmust read and understand a series of sentences—a truthjudgement has to be made about each—^while at thesame time remembering the final word of each, withspan being measured in terms of the greatest number ofwords recalled. Finally, there is the odd-man-out taskemployed by Hitch and McAuley (1991) in whichparticipants see a series of three dots on a card, identifythe odd one out and remember its position from trial totrial

Using a modification of the Daneman and Carpentertask in addition to Case's counting task, Siegel and Ryan(1989) were able to demonstrate that reading-disabledchildren were impaired on both tasks, that arithmetic-disabled children were impaired on the counting taskonly and that younger children with attention deficit


Table 3Participant Details for Experiment 2

Group

CA(months)VMA(months)

MeanSDMeanSD

Autism

22149.6833.8583.0917.92

MLD

22133.6824.5882.9119.40

Normal

2282.145.95

83.1418.15

disorder were impaired on the Daneman and Carpentertask. Furthermore, Yuill, Oakhill and Parkin (1989)found that children with reading comprehension diffi-culties were impaired relative to normal children in theirability to recall the final digits of a series of three digits,while Hitch and McAuley (1991) found that arithmetic-disabled children were impaired on both Case's countingtask and the odd-man-out task.

While these relationships between impaired capacitytask performance and specific disorders of skill areintriguing they must be interpreted with caution. AsHitch and McAuley (1991) point out with reference totheir own data, younger children or children withlearning difficulties may be impaired on capacity taskssimply by virtue of the fact that they are slower atperforming the component processes (e.g., slower atcounting and finding the odd one out), thus affordingmore time for the memory trace of the running totals todecay. A recent study by Towse and Hitch (1995) withchildren of 6 and 11 years makes this point with someforce. For this reason we recorded the time ourparticipants took to perform the operations and covariedthese times out of the subsequent analyses. In addition tothis we also employed two levels of difficulty for thefocal tasks (e.g., an easy versus a difficult counting task).We did this for the following reason. It is reasonable tosuppose that subjects with relatively small workingmemory capacities will be affected more by increasingthe difficulty of the focal task than will other subjects.We can ask, therefore, whether children with autism aremore affected by task difficulty than the children in thetwo comparison groups.

Our first task was a version of Case's counting task,with the difficulty of the counting operations beingmanipulated in the following manner. In the easy taskthe dots on the card were arranged in the canonical formof the kind used on dice, while in the difficult task thearrangement was random and there were distracterstimuli. Our second task was similar to Hitch andMcAuley's odd-man-out task, with the difficult versionbeing one in which children had to identify which dothad a pattern different from the other two and the easyversion being one in which they had to record in whichposition of three a single black dot had appeared. Ourthird task had a similar structure to that of Daneman andCarpenter's sentence processing task. Because we feltthat such a task would over-tax the semantic abilities ofthe participants with autism, given their well-documen-ted difficulties with meaning and relevance (Frith, 1989),we devised a task in which simple sums rather than

sentences were presented to the children (e.g.,"2 + 3 = ?"). In the difficult version of the task theanswer had to be supplied by the child and in the easyversion the answer was provided (e.g., 2 + 3 = 5).

Method

Participants. Groups of children with autism, childrenwith MLD and normally developing children were againassessed. A similar population of children with autismwas employed to that in the previous experiment, andinclusion criteria were the same as those used pre-viously. However, because the present set of tasks wasmore demanding, some of the less able children wereexcluded. For this reason, group sizes were smaller thanin Experiment 1, consisting of 22 children each. Thistime, all children, including normally developingchildren were matched individually for verbal mentalage as measured by the BPVS. Participant details aregiven in Table 3.

Design. All children received both simple andcomplex versions of the three tasks—counting task,odd-man-out task, and sums task.

Materials. All three tasks were presented using aHyperCard programme on a Macintosh computer. Forthe counting and sums tasks the stimuli were displayedon "cards" represented by white rectangles measuring15 cm by 8 cm. In the counting tasks the target itemswere black dots 1.5 cm in diameter, and for the complexcounting task the distracter stimuli used were unfilledsquares of 1.3 cm width. In the sums task the stimuliwere presented in 18 point font. For the two versions ofthe odd-man-out task the screen displayed a number ofblack rectangles equal in number to the list length beingpresented and arranged in a left-to-right series. Each ofthese rectangles contained three white squares in whichthe target stimuli appeared. In the simple version of thetask this was a black dot which appeared in one of thethree squares. In the complex version dots of the samesize appeared in each of the squares. Two of these hadthe same pattern. See Fig. 2.

Procedure and tasks. Children were tested in twosessions, each of approximately 15-20 minutes in length.In the first session, the simple version of each of thethree tasks was presented along with a measure of thetime it took to perform the component operations of each(e.g., counting). In the second session the complexversions of the tasks were given together with a measureof the time it took to perform these componentoperations.

In the counting task children had to count the numberof black dots seen on each card and keep a tally of thenumbers. For both simple and complex versions, thenumber of dots ranged from 3 to 6. In the simple versionthe dots were presented in the canonical form used ondice. In the complex version the dots were spread in arandom pattern and distracters were included. Thesewere unfilled squares, and twice as many squares wereused as dots in each case.

In the simple version of the odd-man-out task thechild had to identify the position of a black dot whichappeared in one of three possible positions by pointing.In the complex version all three positions were filled.


Figure 2. The appearance of the computer screen during the complex odd-man-out task,showing item 2 of a list length of four.

and the child had to locate the dot whose pattern differedfrom that of the other two by pointing at it.

The sums task required children to recall the answersto a number of simple additions. In the simple versionthe answer to each sum was provided, e.g., "2 + 3 = 5",with the child having to read out the appropriate number.In the complex version the children had to work out theanswer for themselves, e.g., "2 + 3 = ?". The answersnever exceeded 7. All possible sums with totals between2 and 7 were used, and these were distributed randomlythroughout the task.

The three tasks were presented in a similar way. Ineach, children were given three trials at each list length,beginning at list length 1. List lengths then increaseduntil a child was incorrect on two or more of the threetrials at any length. As described in the Materialssection, the stimuli for the counting and the sums taskswere presented on a series of "cards". Each cardremained on the screen until the child had respondedcorrectly by saying how many dots were shown. Theexperimenter then clicked the mouse, the card disap-peared, and after a delay of 1 second the next card wasshown. Upon completion of the list a tone signalled thatthe child should recall all the items in the list. In the odd-man-out tasks the stimuli were presented sequentially ina number of rectangles. Thus, when the child hadidentified the position of the dot (simple version) or thatof the odd dot (complex version) in one of the threewhite squares in the first rectangle, these dots disap-peared and new stimuli appeared in the next rectangle. Inthis way, the stimuli moved across the screen with thechild responding to one of three possible locations ineach of n rectangles, where n is the list length of the trialFigure 2 presents an example of how the screen mightappear for the second item of a complex trial at a listlength of four. At the end of the trial a tone indicated thatthe child should recall, by pointing, the position in each

rectangle in which the target stimuli had appeared. Thecomputer recorded the total time elapsed over each trialfrom the onset of the first item to the disappearance ofthe last, excluding the time taken for the child to recallthe items.

In order to obtain a measure of how long it tookchildren to complete the focal tasks the following stepswere taken. For the simple and complex versions of theodd-man-out task and for the simple version of the sumstasks, the mean time to work out the appropriate answeror position at a list length of 1 was taken as the measureof processing speed. (To measure the speed of proces-sing in longer list lengths would have meant confound-ing processing speed with storage demands.) However,for the other tasks, processing speeds were necessarilydependent on the particular stimuli seen. For example, inthe complex version of the counting task children wouldbe expected to take longer to count six dots than threedots. Similarly, one would expect a sum like "5 + 2 = ?"to take longer to complete than one like "1 + 1 = ?". Forthis reason, separate tests of processing speeds werepresented for each computation, again as part of theHyperCard programme. Children were told that theywould not have to remember the answers they gave, butsimply that they had to count the dots, or work out thesums, as quickly as possible. For the test of countingspeed, three of each of the possible stimuli werepresented in a random order (three, four, five and sixdots), first in simple and then in complex form. Themeasure of processing speed for each version was takento be the mean time to count the dots, averaged over alltrials. Similarly, for the sums task, three examples ofsums totalling 2, 3, 4, 5, 6 and 7 were presented in arandom order, and the time to work out the answers wasaveraged over all trials.

Following the procedure adopted in Experiment 1,children's spans were taken as the longest list length at


Table 4Mean Spans and Processing Times for Experiment 2

Counting task

Odd-man-out task

Sums task

Simple

Complex

Simple

Complex

Simple

Complex

MeanSDMeanSDMeanSDMeanSDMeanSDMeanSD

Autism

2.861.062.861.133.551.022.860.923.201.222.31*1.39

Spans

MLD

3.200.922.680.703.500.833.000.643.090.732.14*1.00

Normal

4.410.753.550.654.180.553.680.664.180.823.231.14

Processing

Autism

1.771.162.581.001.300.402.500.942.291.194.02*2.36

times

MLD

1.350.722.751.101.450.522.630.791.430.365.44*3.60

(seconds)

Normal

0.930.212.410.661.200.222.470.641.360.393.621.91

= 18, see text.

which they had been correct on at least two of the threetrials. A further half point was added if they were correcton one of the three trials at the next list length (cf.,Henry, 1991).

Results

Mean spans and processing times are given in Table 4.The complex version of the sums task proved toodifficult for four of the children with autism, and for fourof the children with MLD; no data were recorded inthese cases.

An initial set of analyses compared mean span scoresacross the three groups. Three separate two-factorAnovas were performed, one for each task, each withthe between-subjects variable of group (3) and thewithin-subjects variable of task complexity (2). Themain effect of group was significant for each of the threetasks [F(2, 63) = 13.31, p < .001, counting task; F(2,63) = 7.43, p < .01, odd-man-out task; F(2, 55) = 6.92,p < .01, sums task], and in every case was due to thesuperior spans of the normally developing childrencompared to those of the other two groups of children(p < .05; Newman-Keuls tests). The main effect ofcomplexity was also significant in each analysis [F(l,63) = 23.79, p<.001 for the counting task; F(l,63) = 40.49, p < .001 for the odd-man-out task; F(l,

55) = 59.19, p < .001 for the sums task], due to lowerspans on the complex version of each task. The group bycomplexity interaction was not significant for the odd-man-out task [F(2, 63) = 0.47, p = .63] or for the sumstask [F(2,55) = 0.20, p - .82], but was significant for thecounting task [F(2, 63) = 7.03, p < .01]. In this case,post-hoc analysis of simple effects revealed that thechildren with autism showed no complexity effect [F(l,63) < 0.01, p > .99], while the other two groups showedthe expected effect of complexity [F(l, 63) = 10.15,p < .01, children with MLD; F(l, 63) = 27.69, p < .001,normal children]; see Table 5. (Note that this is counterto our prediction, which was that children with autismwould be more affected by complexity than children inthe comparison groups.)

As in Experiment 1, a second set of analyses wasconducted in order to find out whether the variations inspan scores observed above could be explained in termsof differences in time taken to perform the focal tasks ofcounting, odd-man-out identification and adding up. Tothis end, three separate Ancova analyses were per-formed, one for each task. Each took the same form asthe Anovas described above (i.e., with a between-subjects factor of group and a within-subjects factor ofcomplexity), except that in each case, an individual'sprocessing time for the simple version of a task was thecovariate for their simple span, and their processing time

Table 5Effects of Covarying Out Processing Times on Group by Complexity Analyses (F Values are Given for Effects and Interactions,Mean Square Values are Given for Error Terms)

Source

GroupComplexityGroup X ComplexityBetween-S errorWithin-S error

Counting

Anova

13.31***23.79***7.03**1.280.30

task

Ancova

10.29**2.704.95*0.810.29

Odd-man-out

Anova

7.43**40.49***

0.470.980.26

task

Ancova

6.79**16.16***0.460.930.26

Sums

Anova

6.92**59.19***

0.201.710.54

task

Ancova

4.36*15.00***0.171.090.50

*p<.05; **p<.01; ***p < .001.


for the complex version was the covariate for theircomplex span score. Once again, a preliminary analysisof the data revealed that the assumptions underlyingthese Ancovas (and in particular heterogeneity ofregression) were not met in all cases, and so the resultsshould be interpreted with caution. As in Experiment 1,within-subject and between-subject effects could beconsidered separately in these mixed Ancovas, and thepresence of a significant regression for either of thesesets of effects was accepted as a partial validation for themodel

The between-subject regression was significant foreach Ancova [F(l, 62) = 37.73, p < .001 for the countingtask; F(l, 62) = 4.55, p = .04 for the odd-man-out task;F(l, 54) = 32.70, p < .001 for the sums task] indicatingthat individuals' average processing times predictedspan to a significant extent. Nevertheless, despite this"control" for differences in processing times, groupdifferences in span remained significant in each case[F(2, 62) = 10.29, p<.001 for counting task; F(2,62) = 6.79, p<.01 for odd-man-out task; F(2,54) = 4.36, p = .02 for sums task].

Within-subjects regressions were not significant forthe counting task [F(l, 62) = 2.17, p = .15] or the odd-man-out task [F(l, 62) = 0.58, p = .45], but weresignificant for the sums task [F(l, 54) = 5.85, p = .02],showing that in the case of the sums task alonedifferences in an individual's simple and complex spanscores were related to differences in their processingspeed across the two conditions. Again, despite apredictive relationship, covariance made no essentialdifference to the pattern of within-subject effects for thesums task; the main effect of complexity remainedsignificant [F(l, 54) = 15.00, p < .001] and the group-by-complexity interaction remained nonsignificant [F(2,54) = 0.17,/? = .85].

Discussion

In contrast to Experiment 1 in which the children withautism performed similarly to the normally developingchildren and where the children with MLD were the leastsuccessful, we found in this experiment that the childrenwith autism were performing in a similar way to thechildren with MLD. There is, accordingly, nothing inthese data to suggest that autism is associated withspecific impairments in the central executive of workingmemory system, at least as measured by tasks thatrequire concurrent storage and processing. The fact thatthe children with autism were no more affected byincreasing the complexity of the focal task than were theother two groups of children reinforces this conclusion.

We need, first of all, to give some account of why theperformance of the children with autism was superior tothat of the MLD children in Experiment 1 and similar tothat of the normal children, whereas it was similar to thatof MLD children and lower than that of normallydeveloping children in Experiment 2. The first thoughtwould be that performance on capacity tasks is a bettermarker for general mental handicap than is performanceon immediate memory tasks. Perhaps any group ofindividuals with mental handicap would be impaired onthem. Indeed, there is good evidence, as we have seen.

that children with a variety of learning disabilitiesperform poorly on tests of working memory capacity(Hitch & McAuley, 1991; Siegel & Ryan, 1989;Swanson, 1993a, b; Yuill, Oakhill & Parkin, 1989).Recall that although there had been some significantconelations between VMAs and spans in Experiment1—an experiment on immediate memory—the spans ofthe children with autism were significantly higher thanthose of the MLD children despite the fact that the twogroups had been matched for VMA. In this experimenton the other hand—an experiment on working memory—the two groups had similar spans, reflecting theirmatched VMAs. Given these data, one might proposethat when a test requires working memory capacity wewill generally find that verbal mental age is unambigu-ously related to span, whereas when it taxes immediatememory the relationship is weaker. This explanationbears upon a thesis recently put forward by Anderson(1992) about the relation between intelligence, develop-mental rate, and speed of processing. One of Anderson'sclaims is that IQ is essentially a measure of processingefficiency. / / one can assume that capacity tasks aremore accurate measures of processing efficiency than areimmediate memory tasks then we can explain why bothof our clinical groups performed less well than thenormally developing children and at roughly the samelevel as each other: their IQs were much lower than thatof the normal children and similar to each other.

The question remains, however, why the children withautism performed better than the MLD children (i.e., hadlarger spans) in the immediate memory task used inExperiment 1. This result is not surprising because roterecall (in contrast to processing efficiency) is sometimesreported to be one of the "islets of ability" in autism(Frith, 1989). It is reasonable to propose that a high levelof articulatory rehearsal may be responsible for thissuperior functioning. That is to say, children with autismwho are mentally handicapped may be more likely thanare mentally handicapped children without autism toemploy articulatory rehearsal; and indeed they maysometimes be more likely to do so than normallydeveloping children.

Finally, why did we find that the children with autism,unlike the two groups of comparison children, showedno effect of stimulus complexity on the counting tasks?It is clear from Fig. 2 that these children took just as longto count the dots on the simple arrays as they took tocount the complex arrays. Remember that the config-urations in the simple tasks were canonical (e.g., cardswith five stimuli had four dots at each corner of a"square" and one dead centre as on dice), and that wasexpected to increase the likelihood that children wouldcompute the number immediately rather than bycounting each dot in turn. However, observation of theway in which many of these children went about thattask suggested that they were not using this cue tonumerosity; they would frequently count the dots with asmuch deliberation when they were arranged canonicallyas when they were not. Although the suggestion isentirely post hoc, this tendency can be explained in termsof a kind of processing found in autism that is normallymanifested as an "islet of ability", namely, supra-normalperformance on tasks such as the Embedded Figures Test


(Shah & Frith, 1983) and on the Block Design test (Shah& Frith, 1993). These are tests that require wholes to beseen as made up of discrete parts, something whichrequires the subject to suppress a natural tendency toprocess patterns holistically rather than analytically—toapply what Frith (1989) refers to as "central coherence".Accordingly, in the simple version of the counting taskin which the stimuli were arranged canonically thechildren with autism may have been failing to see thenumbers "as a whole", being forced, therefore, to counteach dot in turn. However, it is also possible that theabsence of the distracter stimuli in the simple task alsohad a role to play; so a further study would need to berun in which no distracter stimuli are present on eithertask.

General Discussion

These two experiments broadly demonstrate thatchildren with autism utilise the articulatory loop in asimilar way to normally developing children, that theyhave superior immediate memory spans to MLDchildren, and that they are not specifically impaired(i.e., relative to MLD children) on tasks that are taken tomeasure working memory capacity. In the first case theyshowed normal performance and in the second case theyperformed similarly to the MLD children. The first resultwas as predicted, but the second runs counter to ourprediction and to the data of Bennetto et al. (in press).

We will tackle two questions in this GeneralDiscussion. First, we need to consider the discrepancybetween our data and those of Bennetto et al Second—and at greater length—^we need to return to questionsraised in the Introduction about the locus of difficulty inexecutive tasks when they are being performed bypersons with autism.

The most obvious respect in which the Bennetto studydiffered from the present one was in terms of theparticipant populations. While the participants in ourstudy were children and adolescents all of whom werementally handicapped, the participants in Bennetto etal.'s study were adolescents and adults who were notmentally handicapped; their average age was around 16and their mean fiill-scale IQ was around 90. Theircontrol group was comprised of a set of individuals with"nonautistic learning disorders", that included dyslexia,borderline intellectual functioning and ADHD. Thismeans that their autistic subjects were more or less"uncontaminated" by the presence of general mentalhandicap, and so in this sense their investigation wasmore sensitive than ours: their participants represented"purer" cases of autism. However, because our studywas less sensitive than theirs it was accordingly moreconservative. That is to say, if a deficit within autism isto be regarded as a core deficit then it is reasonable toexpect that it will reveal itself in autistic subjects whoare mentally handicapped when they are being comparedagainst nonautistic mentally handicapped subjects. Thisis clearly the case in "theory of mind" tasks (Baron-Cohen, Tager-Flusberg & Cohen, 1993), where therelevant comparisons are with mentally handicappedsubjects without autism. For this reason, the manifestdifferences between mentally handicapped persons with

autism and those without autism cannot readily beexplained in terms of differences in the working memorycapacity if these do not show up in a study of the presentkind. Given that the large majority of children withautism are also mentally handicapped, the explanatorypower of a theory that regards working memory as a coredeficit is limited by this fact. This does, however, leaveintact Bennetto et al.'s claim that persons with autismhave memory impairments similar to those of patientswith frontal lobe lesions; indeed we have recentlyreported data consistent with Bennetto et al.'s claim thatindividuals with autism are specifically impaired on"source" memory (Russell & Jarrold, 1995). As Benettoet al. note, such memory impairments may contributetowards an explanation of the social difficultiesexperienced by individuals with autism.

To say this is not, however, to explain why Bennettoet al.'s subjects were impaired on working memorytasks. Perhaps the answer lies in the fact that the group inrelation to which they were impaired was a group ofindividuals without significant mental handicap. Nowour subjects too were impaired when set against a groupof individuals without significant mental handicap, thatis, normally developing children. It was against childrenwith MLD that our subjects were unimpaired. Thisleaves open the possibility that deficiencies in workingmemory may accompany many kinds of neurologicalimpairment; for while Bennetto et al.'s subjects had IQswithin the normal range they also had significantneurological impairments which rendered them autistic.On this view, our children with autism and with MLDboth had less efficient working memories than those ofnormally developing children because both groups hadsignificant neurological impairments.

We now turn to the question of what our negativefindings tell us about the locus of difficulty in autisticpersons' performance on executive tasks. In theIntroduction we reviewed evidence for the view thatexecutive tasks require both adequate working memoryand the ability to inhibit prepotent, incorrect responses.It would be naive to believe that these two exhaust therequirements for adequate executive functioning but theyobviously play a major role. Our study was motivated bythe need to know which of these two components is moreresponsible for autistic persons' deficits on executivetasks; and what our data clearly suggest is that theimportant deficit is not working memory capacity, giventhat our second experiment taxed working memorywithout taxing the ability to inhibit prepotent responses.We will now discuss this result with reference to deficitswhich persons with autism demonstrate on tests ofplanning ability. There are two reasons for concentratingon planning tasks: (1) these tasks are among the bestdiscriminators between participants with autism andtheir controls, and (2) we know a little about the role ofworking memory capacity in normal adults' performanceon them. First, we need to expand on these two claims.

Three studies to date have shown clear planningimpairments in individuals with autism and none havefailed to find a deficit. [By contrast, two studies havefailed to show specific impairments on the WCST inparticipants with autism—Minshew, Goldstein, Muenz8L Payton (1992) and Schneider & Asarnow (1987);


see Pennington & Ozonoff, for a review of executivefunction deficits in developmental psychopathology).]As we mentioned earlier, Ozonoff, Pennington andRogers (1991) demonstrated that high-ftinctioning in-dividuals with autism are impaired on the Tower ofHanoi (TOH) task; Hughes, Russell and Robbins (1994)found that lower-functioning and moderately high-functioning individuals with autism are impaired on acomputerised version of similar task called the "Towerof London" (TOL). Moreover, Ozonoff and McEvoy(1994) followed the Ozonoff et al. sample longtitudin-ally and showed that the TOH deficits were not onlystable over a two-and-a-half year period but thatperformance showed a tendency to decline.

Both TOH and TOL require participants to moveitems from a starting configuration (discs on sticks, or"balls" in "socks") to a target configuration, with thedifficulty of the task being graded in terms of theminimum number of moves that have to be madebetween the two configurations. The working-memoryrequirements here are obvious: holding in mind asequence of moves. The requirement for inhibiting aprepotent response is less obvious but it is certainlypresent. The subject must in some cases inhibit a movedirectly to the stick on which he or she wants the ball toend up (a goal move), move the ball elsewhere, andremove a ball from that stick which may later have to bereturned to it (both sub-goal moves). Detour actions, asDiamond (1991) points out in relation to reaching ininfancy, necessarily require inhibition of a directresponse. In support of this analysis, a recent study byGoel and Grafman (1995) demonstrated that theperformance on the TOH by patients with frontal lesionsis best explained in terms of their inability to resolvegoal-subgoal conflicts, with the goal-directed movebeing the prepotent one.

It is worth mentioning in addition that the Ozonoff etal. study employed a wide range of measures on which tocompare experimental and control groups—executivetasks, theory of mind tasks, and tasks which wereneither. Their data showed that performance on the TOHtask was best able to discriminate between the groupsand best able to predict group membership, withperformance on TOH classifying 80% of the subjectsconectly; while first-order theory of mind, (nonworking)memory, emotion perception, and spatial abilitiespredicted group membership at no better than chancelevel We are, then, well justified in regarding TOH andTOL tasks as tapping executive dysfunctions in autism atleast as well as any other task, if not better.

The next question to ask is whether the locus ofdifficulty on planning tasks resides in the workingmemory requirement or in some other cognitiverequirement. Adequate working memory capacity isobviously necessary for adequate on-line planning, butthe question is whether task difficulty is predictable interms of concurrent working memory load. In order toask this question with reference to persons with autism itis worth considering first how it should be answered withreference to normal adults.

A recent study by Ward and Allport (1996) suggeststhat the working memory load may, in fact, make arelatively insignificant contribution to task difficulty in

normal adults. Taking as their dependent measuresplanning time before making the first move and thenumber of errors of execution. Ward and Allport gaugedthe role of concurrent working memory load by reducingworking memory demands in two ways. In one conditionthe subjects were told to move the discs during theplanning phase (obviating the need for holding in mindthe cunent configuration while planning); and in anothercondition, in addition to this, the computer executed theplanned moves after a button was pressed—alsoobviating the need for holding in mind the completemovement history. They found that reducing workingmemory load in these ways had a negligible effect onperformance while "move choice equivocation" (mean-ing the number of competing, alternative moves at eachstep) had a substantial effect on performance (also seeAtwood, Masson & Poison, 1980). Broadly speaking.Ward and Allport found that the more conflict thatexisted between potential but equally appropriate movesthe harder the task, with "conflict" meaning a situationwhere one potential move satisfies one subgoal at theexpense of a second and when that second alternativemove satisfies the second subgoal at the expense of thefirst.

Combining Ward and Allport's data with the results ofExperiment 2 inspires the suggestion that the reason whypersons with autism perform poorly on planning tasks isnot that they have working memories of limited capacity.This is because the main locus of difficulty on TOL isnot working memory load (Ward and Allport) andbecause mentally handicapped persons with autism donot appear to be specifically impaired on workingmemory (our data). Moreover, if it turns out thatindividuals with autism find relatively easy planningtasks difficult for essentially the same reasons thatnormal subjects find difficult planning tasks to bedifficult then we will have gained important informationabout the nature of the executive dysfunctions in autism.We will have demonstrated that planning is hard forindividuals with autism because it requires choicesbetween equally weighted alternatives.

It may, however, turn out that what Ward and Allportcall "move-choice equivocation" is not the maindeterminant of task difficulty for the autistic person;for while this is related to prepotency (detour movementscan often be achieved in a number of equivalent ways) itis not the same notion as prepotency. As we mentionedearlier, Goel and Grafman (1995) have recently arguedthat frontal patients' difficulty with TOH is bestexplained in terms of goal-subgoal conflicts—^prepo-tency rather than move-choice equivocation (a goal-based choice is the prepotent and incorrect choice). Inordinary language, we need to find out whether it ischoosing or inhibiting that persons with autism findmore difficult.

Acknowledgements—This research was made possible by agrant from the Wellcome Trust to the first author. We aregrateful to the headteachers, staff, and pupils of the followingschools for their kind cooperation and support: DoucecroftSchool, Colchester; Lady Adrian School, Cambridge; PriorySchool, Cambridge; Rosehill School, Nottingham; St Luke'sSchool, Cambridge; Walnuts School, Milton Keynes; War-


grave House School, Newton-Le-Willows; Whitefield School,Walthamstow. We would also like to thank Charles Hulme forpermission to use the HyperCard program in Experiment 1 andfor his initial advice.

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Accepted manuscript received 21 November 1995

working memory in children with autism and with moderate learning difficulties

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