asperger syndrome and autism neurocognitive perspectives

7/27/2019 Asperger Syndrome and Autism Neurocognitive Perspectives

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Asperger's Syndrome and Autism: Neurocognitive AspectsPETER SZATMARI, M.D., LAWRENCE TUFF, PH.D., M. ALLEN J. FINLAYSON, PH.D., ANDGIAMPIERRO BARTOLUCCI, M.D.

Abstract. The objectives of this study were to see: (1) whether children with Asperger's Syndrome (AS)have similar neurocognitive deficits compared to nonretarded, or high.functioning autistic (HFA) children; and (2)whether the essential cognitive deficit among these children is in language or abstract problem solving . Subjectswith AS, HFA, and a control group of socially impaired child psychiatric outpatient controls (OPe) were comparedon a battery of neuropsychological tests . The results indicated that the AS and HFA groups differed little but thatlarge differences from the OPC were observed on all tests. When the AS and HFA with FSIQ above 85 werecompared to the OPC, outstanding deficits on motor coordination, language comprehension, and facial recognitionwere observed. Finally, some evidence is presented to suggest that the pattern of deficits of AS and HFA subjectsvaried by developmental level. The implications of these results for a neurological theory of autism are discussed.J. Am. Acad. ChildAdolesc. Psychiatry, 1990,29, 1:130-136. Key Words: autism, Asperger's syndrome, cognitive

The term Asperger's Syndrome (AS) has appeared withincreasing frequency in published reports, case studies, andcommentaries over the past several years (Wing and Gould,1979; Wolff and Barlow, 1979; Wolff and Chick, 1980;Wing, 1981; Burgoine and Wing, 1983; Gillberg, 1985;Mawson et al., 1985; Schopler, 1985; Nagy and Szatmari,1986; Tantum, 1988). The disorder, first described by Asperger in 1944 (Asperger, 1944), is characterized by socialisolation and odd or eccentric behavior in childhood. Thesechildren are often described by their parents as affectionateduring infancy but show extreme social isolation from theirpeers. They are socially clumsy and engage in essentiallyone-sided social interactions. While their speech is not noticeably deviant, children with AS have difficulty with thepragmatics of communication (i.e. , problems in initiatingand sustaining a conversation). They often show a paucityof gestures and facial expression or have difficulty judging"social distance." Frequently, they develop intense interests in often obscure subjects (i.e., floor plans to buildings ,sharks, washingmachines, etc.), but sometimes these preoccupations can be difficult to differentiate from more normalinterests (i.e. , wrestling, horror movies, sport statistics). Inviewof the subtlety and mildness of many of the symptoms,children with AS are often given other diagnoses and, upto fairly recently, were rarely considered to have a form ofpervasive developmental disorder (PDD).Although these children have also been associated withother diagnostic labels (i.e. , atypical, pseudo-neuroticschizophrenic, autistic psychopathy , borderline, schizotypal, and schizoid), there is emerging agreement on the essential clinical features of the syndrome (Nagy and Szat-AcceptedMay 12, 1989.Dr. Szatmari is Associate Professor, Dr. Tuffis Assistant Professor,Dr. Finlayson is Professor and Dr. Bartolucci is Pro fessor, Depart-ment of Psychiatry. McMaster University. Hamilton. Ontario.The authors wish to thank the staffof the West End Creche for theirhelp in data collection.This research was supported by a grant from the Medical ResearchCouncil of Canada .0890-8567/90/290I-0130$2.0010 1990by theAmerican Academyof Child and Adolescent Psychiatry .

mari, 1986). These include social isolation and abnormalinteractionswithpeers , impairments in verbal andnonverbalcommunication, and early developmental delays (Szatmariet al., 1989). While published case reports (Burgoine andWing, 1983; Gillberg , 1985,; Mawson et al. , 1985;Volkmaret al. , 1985) suggest AS may be considered a mild variantof autism, it is clear that children with the disorder differfrom the majority of autistic children who are without communicative language, are mentally retarded, and have a poorprognosis. It is less clear whether subjects with AS aredistinguishable from high-functioning (HFA) or nonretardedautistic children. Recent reports (Wing, 1981; Szatmari etal., 1990) do suggest that the two groups can be discriminated on the basis of their clinical features (particularlysocial responsiveness, imaginative play , bizarre preoccupations) and outcome, although these differences probablyreflect severity rather than a different etiology. Whether ASand HFA are distinguishable neurocognitively, however,has not been directly addressed.The diagnostic validity of a psychiatric disorder such asAS can be strengthened if a specific deficit, or pattern ofdeficits, is evident on psychological tests. Although theauthors were not able to identify any papers on AS, two.studies were found that examined the neurocognitive profiles of children with " nonautistic" forms of PDD (a groupthat includes children with AS).Wolff and Barlow (1979)compared schizoid (i.e. , AS-like children), high-functioning autistic, and controls on a variety of tests and concludedthat those with schizoid disorders had similar deficits inlanguage and visual association to autistic children but lessperseverative responses. Pomeroy and Friedman (1987), onthe other hand, compared 15 boys (4 to 13 years of age)diagnosed as either "atypical" or "childhood onset" PDD,with psychiatric outpatient controls on the Kaufman Assessment Battery (Kaufman et al. , 1983). Significant differences between the groups were found only among the" holistic" processing (visual-perceptual) subtests rather thanthe verbal subtests, suggesting a pattern quite different thanthat seen in autism. These two studies, then, have producedsomewhat contradictory findings.Much more work has been done on neurocognitive pro-

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ASPERGER'S SYNDROME AND AUTISM

mari et aI. , 1989). The AS sample consisted of28 children,five females and 23 males: one child did not complete thetesting protocol. The average age was 14 years with a rangefrom 8 to 18 years. Previous chart diagnoses for the ASgroup included, among others, hyperactivity, anxiety disorders, learning disability, schizoid disorder, borderlineschizophrenia , obsessive-compulsive disorder, and adjustment reaction. All children had consistently proved to beserious diagnostic puzzles to previous clinicians . No AS 'child had ever been diagnosed as autistic.Since high-functioning autistic (HFA) children are quiterare, they had to be recruited from two sources. The autisticservice at our Centre had a small number (N = 5) of nonretarded autistic children on its caseload. These childrenhave been independently diagnosed by two physicians (apediatrician and child psychiatrist) as autistic according toDSM-III criteria . All these children were enrolled in thestudy. The second source of HFA children was from theWest End Creche (WEC) in Toronto, a center specializingin the treatment of autistic children since 1950. The chartsof all children who had been seen at the Creche were reviewed. Any child who received a diagnosis of autism,childhood schizophrenia or childhood psychosis was identified (these diagnoses were used interchangeably at theWEC over the years). The diagnostic criteria for these threediagnoses were identical and included: (1) qualitative impairments in social relationships, (2) deficits in communicative abilities, and (3) various abnormal behaviors (suchas stereotypies or insistence on sameness) . Any child withthis diagnosis whose most recent IQ test score was above65 (usually according to the Stanford-Binet) was included.Children without an IQ score were also included to avoidmissing any nonretarded autistic children . The authors wereable to identify 84 children who met these criteria. Theparents of 41 children were traced and agreed to participatein this study. On subsequent testing, the diagnosis of autismwas confirmed in 20 subjects who had an IQ score over 70.The autistic sample then, consisted of 25 individuals (fivefrom Chedoke, 20 from WEC). The average age was 23years but ranged from 7 to 32 years. Seventeen (17) HFAstudentscompleted the neuropsychological protocol; the othereight were either unavailable (i.e., out of town) or else didnot wish to participate in this component of the project.A second comparison group consisted of children with avariety of peer problems. A consecutive series of childrenreferred to the child and adolescent psychiatric outpatientteams presenting with some type of social impairment noted

TABLE 1. Sample Characteristicsiles of autistic children. Until recently, the main conclusionhas been that these children show relative deficits on testsof language, particularly comprehension, and relative.strengths on visual-perceptual tasks. This finding has beenextended to include other left-hemisphere tasks and, as aresult, a left-hemisphere dysfunction hypothesis has beenproposed for autism (Hoffman and Prior , 1982; Dawson,1983). More recently, Rumsey and Hamburger (1988) haveshown, in a sample of 10 nonretarded autistic males (18 to39 years of age), outstanding deficits on tests measuringabstract problem solving. Using the Wisconsin Card SortingTest (WCST) and subtests from the Stanford-Binet , the autistic men obtained very poor scores compared to 'normalvolunteers. No outstanding deficits were noted on eitherlanguage or visual-perceptual tests, nor were there lateralized sensory or motor weaknesses . Rumsey and Hamburger's (1988) results support a dysfunction in frontal-subcortical systems rather than a left-hemispheredeficit. Finally,Fein et al. (1985) argue that there are distinct subtypes ofneurocognitive profiles among autistic children and havereported an elegant cluster analysis to support their hypothesis.There appear, then, to be two outstanding issues withrespect to neuro-cognitive impairments in PDD children: (1)do children with AS have a different cognitive profile fromautistic children , and (2) is the core cognitive deficit inlanguage or problem solving? The present study was designed to address these issues by comparing AS and autisticchildren and a consecutive series of cases referred to amental health outpatient clinic for a variety of social problems. The latter comparison group was chosen to determineif the neurocognitive correlates of AS are different fromthose found in socially impaired children who are not PDD(Rourke, 1982). I f no differences are found on this comparison, these cognitive deficits cannot be used to explainthe essential nature of the PDD syndrome. The subjects forthis study were part of a larger project designed to investigate the diagnostic validity of ASas a disorder distinctfrom autism. Previous reports document comparisons acrossearly history and outcome (Szatmari et aI., 1990), perception of social information (Szatmari et aI. , submitted), andlinguistic functioning (Fine et aI., 1989).

MethodSampleChild psychiatrists and developmental pediatricians working at a children's mental health center were sent descriptions of odd and eccentric children and were asked to referany such child between the ages of 8 and 18 (Table 1). Astandard assessment by the senior author (P. S.) was carriedout to determine whether or not the child had AS. Thisassessment, which was unstructured, included intensive interviews with the parents and child and discussions with thechild's teacher . The inclusion criteria for AS, adapted fromWing (1981), stipulated that a child show all of: (1) isolatedbehavior; (2) impaired social interaction; (3) one of oddspeech, impaired nonverbal communication, or bizarrepreoccupations; and (4) onset prior to 6 years of age (Szat-

Asperger'sSyndrome

N 26Age (yr) 14.3Range (8- 18)Sex (F/M) 5121Mean IQ 86.6aHFA > AS = OPC.b OPC > AS = HFA.

Autistic1722.8(7-32)4/1382.2

OutpatientControl3613.7a(7- 18)6/30101.5b

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SZATMARI ET AL.TABLE 2. Clinical Differences between AS and HFA

Group (%)Asperger's AutisticVariable (N = 27) (N = 24) p Value

Social impairmentsLack of social responsive-ness to mother 25 72 0.000Enjoys other adults 80 34 0.004Shows gaze avoidance 36 50 0.48Shares interests with par-ents 68 33 0.03Affectionate baby 67 33 0.04Complete lack of interest inpeers 38 72 0.02Language and communication

Babbled less than siblings 24 65 0.009Echolalia/pronoun reversal 37 75 0.007Repetitive speech 22 48 0.04Seldom starts a conversa-tion 59 65 0.88Lack of imaginative play 12 48 0.02Range of interestsStereotypies 48 86 0.003Rituals 13 25 0.46Insistence on routines 30 50 0.23Bizarre preoccupations 37 86 0.000

on the intake referral sheet were eligible for inclusion. Thiscould include comments such as "being a loner," "shysaway from other children," "social withdrawal," "fightswith friends," etc. These children had the usual psychiatricdisorders of childhood and adolescence with the added provision that there was a problem in getting along with otherchildren of the same age, for whatever reason. The childrenalso had to be age- (within 2 years) and sex-matched to theAS group and could not have a history of brain damage(such as epilepsy or head injury). The authors were able toenroll 42 such children as out-patient controls (OPC), 34males and eight females; 36 of these completed the neuropsychological testing. The average age was 14, rangingfrom seven to 17. Twenty-five (25) of the 36 OPC weregiven a psychiatric diagnosis on the parent version of theDiagnostic Interview for Children and Adolescents (Reichet al., 1982). The largest group (10) were those with bothattention deficit disorder with hyperactivity (ADDH) andconduct disorder (CD). An additional three children hadADDH alone; four had CD alone; five had a pure anxietydisorder; and the final three had both CD and an anxietydisorder. The age, sex, and IQ characteristics of the AS,autistic, and control subjects who completed the testing areshown in Table 1. One-way analysis of variance indicatedsignificant effects for age and FSIQwith the autistic subjectsolder than the AS and control subjects (p < 0.05). Controlshad significantly higher IQs than either AS or autistic subjects (p < 0.05).Before testing, the subject's mother was interviewed bya research assistant, blind to diagnosis, using a structuredinterview. This instrument contains questions about early132

history and behaviors seen in PDD. Details on the intervieware available elsewhere, as well as results on clinical comparisons between the AS and HFA subjects (Szatmari et al.,1990). For purposes of illustration, data from a number ofquestions that reflect DSM-III criteria are reported here todemonstrate differences between the AS and HFA groupson early history (see Table 2). It is clear that the HFAsubjects demonstrated greater impairment on all measuresof social responsiveness except gaze avoidance. Similarly,the groups were different on all language and communication measures except one item reflecting pragmatics (i.e.,"seldom starts a conversation"). On the other hand, thegroups had similar rates of "rituals" and "insistence onroutines." Rates of "stereotypies" and "bizarre preoccupation" were strikingly different. These results support thenotion that while AS can be considered a type of PDD,there are significant clinical differences between AS andHFA on clinical presentation.Measures

Neurocognitive tests were selected to sample a wide rangeof abilities and included several tests previously reported tomeasure deficits in autistic children. Accordingly, subjectswere assessed on measures of: (1) intelligence (i.e.,WISC-R and WAIS-R) (Wechsler, 1974, 1981); (2) schoolachievement, (i.e. , WRAT-R) (Jastak and Jastak, 1984);(3 ) auditory comprehension and memory, (i.e., Children'sToken Test) (Di Simoni, 1977); (4) verbal problem solving,(i.e., Children's Word Finding T e s t ~ W F T ) (Pajurkovaet al., 1976); (5) facial recognition (i.e ., Benton Test ofFacial Recogni tion-BTFR) (Benton et al., 1983); (6)graphomotor construction (i.e., Developmental Test of Visual Motor Integration-DTVMI) .(Beery, 1982); (7) cognitive flexibility (i.e., WisconsinCard SortingTest-WCST)(Heaton, 1981);and (8) manualspeed and dexterity (GroovedPegboard Test) (Knights and Norwood, 1979). All tests were administered according to the standardinstructions prescribed in the published manuals or reports.Testing sessions lasted approximately 31/ 2 hours and wereusually completed in a single sitting. Raw scores were converted to standard scores using published age norms. In thecase of several tests, normative information was not available for older children or adults (i.e., CWFT, DTVMI). In .these instances, standard scores for the DTVMI were therefore based on 13- to 14-year norms. Because the performanceof older children on the CWFT approaches adult levels,this was not considered to be a problem. Total scores wereused for all tests except the WRAT-R and WCST. On theWRAT-R, the reading and math subtests were used, whileon the WCST, the number of correct categories achieved,the total number of errors, and the percentage of perseverative errors committed were used.Analysis

First, a one-way analysis of variance was carried out onall tests to see whether mean scores differed between thethree groups. A discriminant function analysis was thenperformed to see which measures differentiated the AS andHFA groups. An analysis of covariance could not be per-J .Am.Acad.Child Adolesc.Psychiatry,29:1 ,Jan. 1990


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TABLE 3. Group Task Performance (Total Sample)Asperger's Autistic ope p ValueeN = 26) eN = 17) (N = 36) ANOVA

VIQ 85.8 84.5 101.6 0.000"Information 7.93 7.66 9.52 0.024"Similarities 8.50 6.76 10.48 0.00()bArithmetic 7.66 7.72 10.12 0.011"Vocabulary 8.14 7.75 10.24 0.002"Comprehension 6.31 6.88 11.35 0.000"Digit Span 8.41 8.59 9.37 0.53Q AS = HFA.b = OPC > AS > HFA .c Nonsignificant.

formed on the test battery since the assumption of parallellines was violated for several of the variables (Le. , therelationship between IQ and several tests varied by group).To deal with this problem, the ANOVAs were rerun onlyin PDD and ope subjects with FSIQ above 85. To controlfor the effects of multiple testing, a discriminant functionanalysis was then carried out to see which variables distinguished the PDD and ope groups. Finally, to see whetherPDD children were heterogeneous in terms of neurocognitive impairment, the PDD children were divided into thosewith FSIQ above and below 85. Their score on each testwas subtracted from their own IQ scores to get an idea ofcognitive deficits relative to IQ. These discrepancy scoresamong the low- and high-IQ PDD subjects were comparedto see whether the cognitive profile of PDD children variesby IQ.

ResultsThe mean scores obtained by the AS, autistic, and controlgroups on all of the neurocognitive measures are shown inTables 3 and 4. Table 3 provides information on the Wechsler subtests. The groups differed on all subtests, except fordigit span. Appropriate post-hoc tests indicated that (otherthan for similarities) the out-patient controls performed better than the AS and autistic groups (who were not different

from each other). In terms of level of performance, the ASand HFA groups showed significant impairments on bothverbal and performance subtests and were quite similar toeach other.Table 4 summarizes the neuropsychological and achievement test results. Looking first at the absolute WRAT-Rscores, there were no differences between the groups. If ,however, one calculates a discrepancy score between thestandard score on reading and arithmetic, minus their FSIQ,significant differences emerge. Both the AS and the autisticgroups were reading roughly 10 points above their IQ,whereas on arithmetic, the control group was performingroughly 10 points below their IQ. On the Token Test , Peg-l .Am.Acad.ChildAdolesc.Psychiatry, 29:1 . Jan . 1990

ASPERGER'S SYNDROME AND AUTISMTABLE 4. Group Task Performance (Total Sample)

p ValueAsperger's Autistic OPC for(N = 26) (N = 17) eN = 36) ANOVA

WRATReading 98.8 105.5 101.4 0.63'Arithmetic 85.1 86.8 88.8 0.27'Read-FSIQ 9.1 10.6 0.6 0.000"Math-FSIQ -1.8 1.4 -8.7 0.000"Token Test 40.3 43.9 53.1 0.002"CWFT 31.4 34.2 41.3 0.016'Pegs-dominant 27.1 29.6 49.4 0.000"Pegs-nondominant 25.9 41.0 46.3 OOOldDTVMI 34.7 32.6 42.5 0.006-BTFR 37.3 39.1 45.2 0.023'WSCT

% Perseverative error 33.6 24.4 44.8 0.003bCategories 40.2 34.7 4 i6 0.006-Errors 42.0 33.8 45.4 0.006bNote: Except for standard scores on the WRAT, all other scoresaretransformed to T-scores with a mean of 50 and SD of 10." OPC> AS = HFA.b OPC > HFA.' OPC > AS.dHFA = OPC > AS., Nonsignificant.

board (dominant), and the DTVMI, both PDD subtypesperformed worse than the ope (but not different from eachother). On the eWFT, Pegboard (nondominant), and theBTFR, only the ope and AS groups were different. Finally ,on the 3 subjects ofthe weST, the autistic group was worsethan ope. In general, one or the other of the PDD subtypeswas significantly different from the ope on all tests , although whether the AS or HFA group obtained lower scoresvaried.It was apparent, on these univariate analyses, that therewere small differences between the two PDD subtypes. Adiscriminant function analysis, specifically comparing ASand HFA subjects, was carried out to explore this in moredetail (not shown). Four variables discriminated the twogroups: (1) Pegboard performance with the nondominanthand; (2) percent perseverative errors from the WeST; (3)Pegboard performance with the dominant hand; and (4) thenumber of errors committed on the WeST. The HFA didnot show the expected dominant hand advantage, in contrastto the AS group, and did worse on the WeST subtests.However, the multivariate Wilks was barely significant (p= 0.048) and the classification matrix indicated that onlytwo-thirds of each group were correctly classified. Thus,while somedifferencesexist between AS and HFA, it seemedappropriate to combine these groups into one category (PDDsubjects) for further analyses.The next issue investigated was whether PDD and opesubjects differed on their test results , taking account of thelarge differences in IQ between the groups. The comparisonwas carried out only on those subjects with FSIQ above 85,since an analysis of covariance could not be run (see Analysis) . There were now 22 PDD children with FSIQ above

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SZATMARI ET AL.TABLE 5. PDD"vs. OPC (Only in those with FSIQ >85) TABLE 6. Discriminant Function Analysis (PDD vs. OPC)Neuropsychological TestsPDD'

(N = 22) OPC(N = 36) p Value Step . No . Variables Wilks p Value

85 (14 AS and 8 HFA). These were compared to the 36OPC with similar FSIQ. Table 5 shows these results (tofacilitate comparison with later tables, all tests are nowreported as T-scores with a mean of 50 and a standarddeviation of 10). The first point to note is that there wereno significant differences between these groups on eitherverbal, performance, or FSIQ. The WISC-R subtests thatsignificantly differentiated the groups were comprehension,picture completion, picture arrangement, and object assembly. Thus, deficits in both higher-order verbal and performance skills were apparent. On the neuropsychological tests,significant differences were found on the BTFR, Pegboard,and the discrepancy between academic achievement and IQ.It appears that PDD children , with IQ above 85, show outstanding deficits in motor coordination, higher-order nonverbal problem solving, and language comprehension, buthave excellent reading recognition skills. Tests of acquiredknowledge (i.e., Information, Arithmetic, Vocabulary), immediate attention and memory (Digit Span), and concretematch-to-sample tasks (Block Design , Coding, DTVMI),were performed at levels indistinguishable from OPC.When the significant variables (i.e . , Comprehension, Picture Completion, Picture Arrangement, Object Assembly,BTFR, Pegs) were entered into a discriminant function analysis (Tables 6 and 7), four measures significantly differ-

PDD = Asperger's Syndrome (n(n = 8)

b NS = nonsignificant.14) and Autistic subjects

entiated the groups: (1) Pegboard performance, both dominant and (2) nondominant; (3) comprehension from theWISC-R; and (4) the BTFR (see Table 6). The classificationmatrix correctly classified 82% of the children (73% of thePDD group and 88% of the out-patient controls) and theWilks Lambda was highly significant (p = 0.002) (Table7). This suggests that the pattern of neuropsychologicaldeficits is quite specific to PDD children with FSIQ above85, but that some PDD children (6 of 22) are free of thispattern .The issue of subtypes of cognitive profiles among PDDchildren was investigated by noting the extent to which thepattern of deficits differed according to the IQ of the subject.The PDD sample was , therefore, divided into two groups ;low IQ (i .e . , IQ between 70 and 85), and high IQ (i.e. , IQabove 86). Each child's T-score (on each test) was subtractedfrom his/her own FSIQ T-score . This discrepancy scoreprovided an estimate of the child's cognitive profile, relativeto his/her own IQ. The discrepancy scores of the high andlow IQ PDD groups were then compared using a simple t-test. Table 8 presents the results from this analysis. Individual verbal subtests were slightly better than FSIQ forboth low-IQ and high-IQ groups (i.e., the scores were negative), but discrepancy scores for these two groups were notdifferent from each other. On the performance subtest scores,however, the pattern was quite different. For the high IQPDD group these subtests (except for block design) wererelative deficits, whereas they were relative strengths forthe low IQ group. The discrepancy scores were significantlydifferent for object assembly, picture arrangement, and picture completion. Similarly, on the BTFR and the DTVMI,the high-IQ subtests performed quite badly, relative to IQ.In contrast , for the low-IQ group, there was little discrepancy from their own IQ. There was also a trend (p = 0.06)for the high-IQ group to have better verbal than performanceIQ scores than the low-IQ group. It appears, then , thatamong high-IQ PDD subjects, relative cognitive deficitsexist in both verbal and nonverbal tasks that measure higherorder abstract processes. As IQ decreases, relative deficitsin verbal skills become apparent and tests of visual-perceptual ability are a strength .

ConclusionThe main objectives of this study were to see: (1) whetherAS and HFA had different neurocognitive profiles; and (2)whether the essential deficit among PDD children is foundin language or abstract problem solving. The univariateanalyses demonstrated that the AS and HFA groups were

0.00030.00010.00010.0002

0.782880.701540.672950.65803

Pegs-DominantComprehensionPegs -NondominantBTFR .

1234Note: FSIQ > 85.

NSbNSNSNSNSNSNS0.0003NS0.040.04NS0.02NS0.04NS0.0020.04NSNSNSNSNS0.09NS0.0020.01

51.751.551.648.751.850.951.455.348.349.553.252.853.547.445.242.549.446.344.848.445.753.141.352.443.20.6-8.7

48.647.148.749.448.951.350.044.752.844.548.252.947.645.138.739.931.436.139.644.843.351.842.457.146.18.5- 2.4

VIQPIQFSIQInformationSimilaritiesArithmeticVocabularyComprehensionDigit SpanPicture CompletionPicture ArrangementBlock DesignObject AssemblyCodingBTFRDTVMIPegs-dominantPegs-nondominantWCST-% Perseverative errorsWCST-CategoriesWCST-no. of errorsToken TestCWFTReadingMathRead-FSIQMath-FSIQ

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TABLE 7. Discriminant Function Analysis (PDD vs OPC):Classification MatrixCases Classified into Group

Actual Group % Correct AS OPCPDD 73 16 6OPC 88 4 30Totals 82 20 36Note: FSIQ > 85.

impaired on all tests, relative to the OPC, but were notreally different from each other. The differences with theOPC were quite robust and indicate that some measurableneurocognitive impairment is almost always found in PDDchildren. Few statistically significant differences werefound between the HFA and AS groups. These differenceswere relatively small and probably reflect severity ratherthan a separate etiology. Why the AS group should do sopoorly with their nondominant hand is unclear. This couldrepresent a measurement problem or greater evidence ofmixeddominance among younger subjects. Other tests commonly thought to be associated with right-hemisphere function did not differentiate these two groups, so the notionthat AS is a disorder of the nondominant hemisphere is notsupported by these data. On the basis of these results, theauthors feel it isjustified to combine the AS andHFA groupsinto a more general PDD category.As a way of investigating the core cognitive deficit ofPDD children, the AS and HFA groups were combined andcompared to the OPC. The authors expected to find deficitsin language and no differences on the performance subtestsand other measures of visual-perceptual function; this didnot tum out to be the case. Instead, measures of languagecomprehension, motor coordination, andnonverbal problemsolving (i.e., Picture Completion, Picture Arrangement,ObjectAssembly, and Facial Recognition) significantly differed between the groups, and the resulting classificationmatrix indicated that this pattern is both sensitive and specific to PDD children but not unique.Previous studies reporting deficits in language andstrengths in visual-perceptual function were done on lowerfunctioning, or younger, PDD children. The authors wondered about the extent to which their findings could beexplained by the developmental level of the child. Many ofthe tests from the present battery assess differed cognitiveabilities at different developmental levels. Performance subtests from the Wechsler Scales, for instance, require moreindependent problem solving and less simple perceptualmatching at older age levels and/or higher IQ. Indeed, theresults on pattern differences by IQ subtype (Table 8) indicated that many of these performance subtests were deficits only for the PDD children with FSIQ above 85 (i.e.,at higher developmental levels). Thus, the pattern of neurocognitive deficit appears to vary by IQ. Among low-IQPDD children, the typical pattern of low verbal/high performance scores is evident. Among high-IQ PDD probands,the pattern is more complex and suggests selective impairments in' higher-order problem solving, irrespective ofl.Am.Acad. ChildAdolesc.Psychiatry, 29:1 ,Jan. 1990

ASPERGER'S SYNDROME AND AUTISMTABLE 8. Pattern Difference by PDD IQ Subtype

PDDIQ


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SZATMARI ET AL.DSM-llI-R criteria of autistic disorder and PDD-not-otherwise-specified, but the results were substantially the same.Second, there was considerable disparity between the groupsin age and IQ. This was necessary because the intent wasto collect as large a sample size as possible, but it has meantthat not all tests were equally sensitive across all age groups,nor do they necessarily assess similar cognitive abilities. Infuture studies, it would be worthwhile to test more specifichypotheses which better matched samples of more clearlydefined PDD probands. The authors also think it would beimportant to see how the cognitive deficits of PDD childrendiffer from those seen in learning disabled groups. Thiswould control for the presence of cognitive impairments.One of the other implications of the present results is theusefulness of including AS subjects when studying the pervasive developmental disorders. AS children are not all thatuncommon and are of normal IQ. Thus, including themavoids two of the major difficulties in studying autism (i.e.,small numbers and the complicating effect of mental retardation). Many investigators have commented on the importance of using PDD individuals of normal IQ for biological and cognitive studies. Since nonretarded autisticchildren are quite rare, this can be difficult. The presentresults support the inclusion of AS as a very mild form ofPDD where the cognitive profiles are virtually identical toautism, suggesting similar deficits in brain organization.

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asperger syndrome and autism neurocognitive perspectives

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