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Mesial temporal lobe and memory function inautism spectrum disorder: An exploration ofvolumetric findingsHaley G. Trontela, Tyler C. Duffielda, Erin D. Biglerabcd, Tracy J. Abildskova, AlysonFroehlichc, Molly B.D. Priggeg, Brittany G. Traverse, Jeffrey S. Andersonf, BrandonA. Zielinskig, Andrew L. Alexanderehi, Nicholas Langejk & Janet E. Lainhartei

a Department of Psychology, Brigham Young University, Provo, UT, USAb Neuroscience Center, Brigham Young University, Provo, UT, USAc Department of Psychiatry, University of Utah, Salt Lake City, UT, USAd The Brain Institute of Utah, University of Utah, Salt Lake City, UT, USAe Waisman Laboratory for Brain Imaging and Behavior, University of Wisconsin,Madison, WI, USAf Department of Radiology, University of Utah, Salt Lake City, UT, USAg Department of Pediatrics and Neurology, School of Medicine, University of Utah,Salt Lake City, UT, USAh Department of Medical Physics, University of Wisconsin, Madison, WI, USAi Department of Psychiatry, University of Wisconsin, Madison, WI, USAj Departments of Psychiatry and Biostatistics, Harvard University, Boston, MA, USAk Neurostatistics Laboratory, McLean Hospital, Belmont, MA, USAPublished online: 09 Mar 2015.

To cite this article: Haley G. Trontel, Tyler C. Duffield, Erin D. Bigler, Tracy J. Abildskov, Alyson Froehlich,Molly B.D. Prigge, Brittany G. Travers, Jeffrey S. Anderson, Brandon A. Zielinski, Andrew L. Alexander, NicholasLange & Janet E. Lainhart (2015) Mesial temporal lobe and memory function in autism spectrum disorder: Anexploration of volumetric findings, Journal of Clinical and Experimental Neuropsychology, 37:2, 178-192, DOI:10.1080/13803395.2014.997677

To link to this article: http://dx.doi.org/10.1080/13803395.2014.997677

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Mesial temporal lobe and memory function in autismspectrum disorder: An exploration of volumetric findings

Haley G. Trontel1, Tyler C. Duffield1, Erin D. Bigler1,2,3,4, Tracy J. Abildskov1,Alyson Froehlich3, Molly B.D. Prigge7, Brittany G. Travers5, Jeffrey S. Anderson6,Brandon A. Zielinski7, Andrew L. Alexander5,8,9, Nicholas Lange10,11,and Janet E. Lainhart5,9

1Department of Psychology, Brigham Young University, Provo, UT, USA2Neuroscience Center, Brigham Young University, Provo, UT, USA3Department of Psychiatry, University of Utah, Salt Lake City, UT, USA4The Brain Institute of Utah, University of Utah, Salt Lake City, UT, USA5Waisman Laboratory for Brain Imaging and Behavior, University of Wisconsin, Madison, WI, USA6Department of Radiology, University of Utah, Salt Lake City, UT, USA7Department of Pediatrics and Neurology, School of Medicine, University of Utah, Salt Lake City, UT,USA8Department of Medical Physics, University of Wisconsin, Madison, WI, USA9Department of Psychiatry, University of Wisconsin, Madison, WI, USA10Departments of Psychiatry and Biostatistics, Harvard University, Boston, MA, USA11Neurostatistics Laboratory, McLean Hospital, Belmont, MA, USA

(Received 28 January 2014; accepted 8 December 2014)

Studies have shown that individuals with autism spectrum disorder (ASD) tend to perform significantly belowtypical developing individuals on standardized measures of memory, even when not significantly different onmeasures of IQ. The current study sought to examine within ASD whether anatomical correlates of memoryperformance differed between those with average-to-above-average IQ (AIQ group) and those with low-averageto borderline ability (LIQ group) as well as in relations to typically developing comparisons (TDC). Usingautomated volumetric analyses, we examined regional volume of classic memory areas including the hippocam-pus, parahippocampal gyrus, entorhinal cortex, and amygdala in an all-male sample AIQ (n = 38) and LIQ (n =18) individuals with ASD along with 30 typically developing comparisons (TDC). Memory performance wasassessed using the Test of Memory and Learning (TOMAL) compared among the groups and then correlated withregional brain volumes. Analyses revealed group differences on almost all facets of memory and learning asassessed by the various subtests of the TOMAL. The three groups did not differ on any region of interest (ROI)memory-related brain volumes. However, significant size–memory function interactions were observed. Negative

The authors report no conflicts of interest. The content is solely the responsibility of the authors and does not necessarily representthe official views of the National Institute of Mental Health, the National Institute of Child Health & Development, or the NationalInstitutes of Health. We thank former members of the Utah Autism Collaborative Program of Excellence for their assistance during theearly stages of this project. We sincerely thank the children, adolescents, and adults with autism and the individuals with typicaldevelopment, who participated in this study, and their families. Although E. D. Bigler is the co-author of the Test of Memory andLearning (TOMAL), he receives no royalties and reports no conflict of interest. The assistance of Jo Ann Petrie with manuscriptpreparation is gratefully acknowledged.

The project described was supported by the National Institute of Mental Health [grant number RO1 MH080826 (J.E.L., E.D.B., A.L.A., N.L.)], [grant number RO1 MH084795 (J.E.L., P.T.F., N.L.)], [grant number KO8 MH092697 (J.S.A.)]; the Eunice KennedyShriver National Institute of Child Health and Human Development [grant number T32 HD07489 (B.G.T.)], [grant number P30HD003352-45 (Waisman Center Core Grant)]; The Hartwell Foundation (B.G.T.); and the Primary Children’s Foundation EarlyCareer Development Award (B.A.Z.). Support from the Poelman Foundation to Brigham Young University for autism research isgratefully acknowledged.

Address correspondence to: Erin D. Bigler, Department of Psychology & Neuroscience Center, 1001 SWKT, Brigham YoungUniversity, Provo, UT 84602, USA (E-mail: erin_bigler@byu.edu).

Journal of Clinical and Experimental Neuropsychology, 2015

Vol. 37, No. 2, 178–192, http://dx.doi.org/10.1080/13803395.2014.997677

© 2015 Taylor & Francis

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correlations were found between the volume of the amygdala and composite, verbal, and delayed memory indicesfor the LIQ ASD group, indicating larger volume related to poorer performance. Implications for general memoryfunctioning and dysfunctional neural connectivity in ASD are discussed.

Keywords: Memory; Autism spectrum disorders; Neurodevelopmental disorders; Magnetic resonance imaging.

Lower performance on memory tasks, particularlyepisodic memory, has been consistently observed inautism spectrum disorders (ASD) when comparedwith typically developing individuals (BenShalom, 2003; Boucher & Bowler, 2008; Hill &Frith, 2003; Narzisi, Muratori, Calderoni, Fabbro,& Urgesi, 2013; Russell, Jarrold, & Henry, 1996;Southwick et al., 2011). Yet, areas of preservedmem-ory processing have also been found (e.g., Assouline,Foley Nicpon, & Dockery, 2012; Boucher &Lewis, 1989; Boucher & Warrington, 1976; O’Shea,Fein, Cillessen, Klin, & Schultz, 2005) includingexceptional memory skills (Bennett &Heaton, 2012; Mottron, Belleville, Stip, &Morasse, 1998). Southwick et al. (2011) used a com-prehensive test battery, the Test of Memory andLearning (TOMAL; Reynolds & Bigler, 1994), tobroadly assess memory performance in ASD andfound that the individuals with ASD performed sig-nificantly below age- and education-matched typi-cally developing comparisons (TDC), 5–19 years ofage, across all domains of memory function.

The Southwick et al. (2011) study did not examinewhether there were any neuroanatomical differencesbetween the ASD and TDC groups. Is part of theexplanation for differences in memory related to anysize–function differences between the ASD and TDCgroups? Since well-known mesial temporal lobestructures participate in memory, could a differencein their size relate tomemory function? Size–functionrelations tend to be positive, and their evolutionarybasis is well documented in the mammalian brain(Koscik & Tranel, 2012). Volume of a given structureor region of interest (ROI) has been a traditionalmeasure of size where developmentally, neuroima-ging-based volumetric methods have long been usedas a proxy of brain health and growth (Brown &Jernigan, 2012; Stiles & Jernigan, 2010), includingvolumetric analyses of developing mesial temporallobe structures critical for memory like the hippo-campus (Hu, Pruessner, Coupe, & Collins, 2013).Nonetheless, the issues are complex because withaberrant development other regions may be recruitedto participate in a given function associated withmore typical development. For example,Brunnemann et al. (2013) found smaller hippocam-pal volume in preterm children with uncomplicatedneonatal courses (<34 weeks of gestation, birth

weight <2000 g) than in controls (7–11 years).However, only in the controls did hippocampalvolume positively relate to episodic memory functionbased on neuropsychological testing (see alsoOmizzolo et al., 2013). Whether impaired memoryfunctioning in ASD compared with TDC is asso-ciated with any gross volumetric differences inbrain regions known to participate in memory is thefocus of the current investigation.

Neuroanatomy and memory functioning

Key anatomical regions associated with memoryand underlying neural networks have been wellestablished and investigated for decades, includingcritical mesial temporal lobe structures like theparahippocampal, entorhinal, and perirhinal cor-tices and the hippocampus (Aggleton et al., 2010;Clark & Boutros, 1999; Miller, Li, &Desimone, 1991). The amygdala, a subcorticalmesial temporal lobe structure, also plays animportant role, particularly in learning contingen-cies between internal and external cues of emotion(Aggleton, 1993; Aggleton et al., 2010; Clark &Boutros, 1999) including social stimuli, processingof which may be more aberrant in autism (Barnea-Goraly et al., 2013; Green et al., 2013). All of theaforementioned brain structures critical for mem-ory have some overlap with networks importantfor social–emotional processing and therein maybe an important relation between ASD andimpaired memory performance (Boucher, Mayes,& Bigham, 2012).

Cognitive deficits across the autism spectrum

Higher frequency of intellectual disability is asso-ciated with ASD when compared to typically devel-oping individuals (Charman et al., 2011).Additionally, even when individuals with ASDwithout intellectual disability are demographicallymatched to neurotypical comparisons, individualswith ASD generally score significantly lower onmeasures of IQ (Jou, Frazier, Keshavan, Minshew,& Hardan, 2013). Intellectual ability constitutes animportant issue in the study of memory functioningin those with ASD because of the important relation

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between memory and IQ (see Lezak, Howieson,Bigler, & Tranel, 2012). However, in a study bySouthwick et al. (2011), even when statistically com-parable on IQ, individuals with ASD displayed sig-nificantly lower memory performance across mostdomains than did TDC.Since IQ also relates to brain morphology (Eliez,

Blasey, Freund, Hastie, & Reiss, 2001; Freitaget al., 2009; Haier, Jung, Yeo, Head, & Alkire,2004; Lange, Froimowitz, Bigler, & Lainhart,2010; Reiss, Abrams, Singer, Ross, & Denckla,1996), examination of neuroanatomical correlatesof memory performance would require controllingin some fashion for intellectual level of the partici-pants being examined. The need to control for IQwould also apply to brain structures associatedwith memory, where lower IQ may be uniquelyassociated with morphology differences. Boucheret al. (2012) provided an extensive review of mem-ory in ASD and discussed the potential differencesin memory function that may occur along thedimension of general cognitive ability as well asbrain regions associated with memory that maydiffer in ASD. Operationally, they differentiatedASD in terms of level of functioning, with highfunctioning defined as “individuals with ASD andintellectual and linguistic abilities within the nor-mal range, regardless of whether language wasinitially delayed” (Boucher et al., 2012, p. 460).In their schema, individuals with verbal IQ scoresof 85 and above would be categorized as highfunctioning. Boucher et al. discussed lower func-tioning autism with several qualifiers dependingon borderline or below intellectual ability scoresand degree of language impairment. By categoriz-ing along the dimension of intellectual ability,Boucher et al. showed differences in memory per-formance associated with ASD.For example, Boucher et al. (2012) summarized

a number of studies contrasting high-functioningversus lower functioning ASD groups on norm-referenced memory tasks. Unimpaired nondeclara-tive memory in the high-functioning ASD groups(14/15 findings), as well as intact declarative mem-ory when tested by recognition (29/35 findings),was observed. However, with free-recall para-digms, the declarative memory of high-functioningindividuals with ASD was often, yet inconsistently,found to be impaired (21/42 findings).Additionally, in the lower functioning ASDgroups, declarative memory was impaired regard-less of whether assessed by recognition (10/14 find-ings) or by free recall (11/18 findings). Both groupsgenerally had intact cued recall (15/18 findings forhigh-functioning and 11/12 findings for lower func-tioning individuals). Studies on source memory

were mixed, with both impaired and unimpairedfindings for both higher (3/5 impaired findings)and lower functioning groups (3/5 impaired find-ings). The Boucher et al. review documented thevariability in memory performance associated withASD along with the importance of examiningmemory function across the dimension of intellec-tual ability.

Working memory in ASD

The Boucher et al. (2012) review also highlightedparticular features of memory function that maybe central to ASD. For example, working memorymay be particularly interesting in relation to ASDinasmuch as Barendse et al. (2013) argued thatworking memory deficits are central to symptomsof ASD. Working memory operates during proces-sing of complex information and executive func-tions, including during social cognition andinterpersonal interactions, all areas of impairmentin ASD (Barendse et al., 2013). Boucheret al. (2012) showed mixed results with workingmemory, with some investigations finding impair-ment in both higher and lower functioning groups(11/26 and 8/15 impaired findings, respectively).The Boucher et al. review found relatively intactperformance for both groups during working mem-ory tasks that simply keep basic information onlinefor further processing. However, some studiesfound that on tasks that require executive controlin order to manipulate and process the onlineinformation (e.g., digits backward), individualswith ASD exhibited greater deficits with workingmemory, regardless of level of intellectual ability.

Size–function relations in memoryimpairments in ASD

Similar to Barendse et al. (2013), Minshew andGoldstein (1998) have suggested that the patternof memory performance observed in ASD relatesto disordered information processing of complexinformation, leaving simple information processingintact. In other words, individuals with autismhave greater impairment on tasks that requireorganization, integration, or a high processingload than individuals with neurotypical develop-ment (Minshew & Goldstein, 1998). From thisperspective, the impairment in information proces-sing in ASD may reflect neural disconnectivity of a“generalized dysfunction of the association cortex,with sparing of the primary sensory and motorcortex” (Minshew & Williams, 2007, p. 946).Boucher et al. (2012) noted that impaired

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information processing in autism is consistent withmodels that view autism as a disconnection syn-drome, which would affect memory functioning(Belmonte et al., 2004; Courchesne, 2004;Rippon, Brock, Brown, & Boucher, 2007).Indeed, Casanova and Trippe (2009) andCasanova (2007) have shown that increases in cor-tical gray matter may relate to aberrant increasedwhite matter projections necessary to maintain theconnectivity of the increased number of corticalcells in the brain in ASD. Lewis, Theilmann,Townsend, and Evans (2013) argue that largerintracranial size in ASD is associated with dimin-ished network efficiency. The size–function rela-tionships posited by these investigators suggeststhat it may be possible to use volumetric measure-ments as a proxy for assessing brain connectivity.

Current study

The current investigation is an extension of thestudy by Southwick et al. (2011) and explores theanatomical correlates of TOMAL-assessed mem-ory function in ASD as well as potential relationswhen the ASD sample is differentiated into func-tional groups based on level of measured intellec-tual ability. In a technical sense, because of the IQexclusion rules for participants in the current inves-tigation, the lower functioning schema operationa-lized by Boucher et al. (2012) could not be appliedto this group of ASD in whom TOMAL testinghad been performed. Accordingly, for the currentinvestigation, the dimension of intellectual abilitywas divided into two groups, one of average-to-above-average IQ (AIQ), defined as verbal IQ(VIQ) ≥85, and the other with low-average to bor-derline IQ (LIQ), defined as VIQ ≤84.

Memory performance was examined broadlyusing the TOMAL (Reynolds & Bigler, 1994) com-paring AIQ and LIQ ASD groups to TDC parti-cipants. Age, education, and head circumferencewere not significantly different at the p < .05 levelbetween the groups. To examine region of interest(ROI) volumes of traditional areas associated withmemory function based on magnetic resonanceimaging (MRI) findings, the automatedFreeSurfer (Dale, Fischl, & Sereno, 1999) methodwas used to compute volumes of mesial temporallobe structures associated with memory includingoverall temporal lobe along with mesial temporallobe volumes including volumes of the hippocam-pus, parahippocampal gyrus, entorhinal cortex,and amygdala. Much of this investigation wasfocused on descriptive findings of potentialTOMAL differences between AIQ and LIQ

functioning individuals with ASD and sought to(a) distinguish memory performance of ASD bothwithin the disorder by differentiating AIQ andLIQ, and from TDC participants, (b) exploreROI findings in relation to memory in both ASDAIQ and LIQ groups and TDC participants, and(c) examine the relations of memory impairment tovolumetric differences in classic memory ROIs ofthe temporal lobe in ASD. It was hypothesizedthat TOMAL scores would be significantly higherfor TDC subjects than for the AIQ ASD group,and that within ASD, scores for AIQ would besignificantly higher than LIQ. We also hypothe-sized that ROI volume relations by TOMAL mem-ory index performance would be different betweenthe ASD and TDC groups.

METHOD

Ascertainment

Subjects were recruited predominantly from com-munity sources, including parent support groups,youth groups, and schools, and from clinic socialskills groups. The participants in this study are asubset of individuals in a longitudinal investigationof late brain development from three years of agethrough early adulthood, with the initial findings ofTOMAL performance previously reported bySouthwick et al. (2011). The subset for this investi-gation was selected from the larger sample based onage (5–19 years of age) within the reference normsof the TOMAL, having complete TOMAL datafrom the time of initial assessment and completeneuroimaging data. Additionally, MRI studies hadto have been completed within a few months ofwhen TOMAL testing was performed to beincluded in the current investigation (M = 2.1, SD= 0.26). All facets of this investigation were under-taken with the understanding and written consentand assent of each subject or legal guardian, withthe approval of the University of Utah and BrighamYoung University Institutional Review Boards,where testing was performed, and in compliancewith national legislation and the Code of EthicalPrinciples for Medical Research Involving HumanSubjects of the World Medical Association.

Participant groups

All participants were males, 5–19 years of age, andwere part of the Time 1 phase of the longitudinalstudy. The ASD group had a total of 56 subjects (38AIQ, 18 LIQ) and the TDC group a total of 31subjects with complete neuropsychological and

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neuroimaging datasets. Subjects were selected fromthe larger neuroimaging study if they met the fol-lowing criteria: male; between age 5–19 years; com-plete neuroimaging and neuropsychologicaldatasets. Forty-seven participants were excludedfrom the larger dataset due to missing or incompleteIQ data; eight were excluded for missing or incom-plete imaging data; 24 were excluded for missing orincomplete TOMAL data. Subject characteristicsare summarized in Table 1.

Idiopathic autism sample

Autism was diagnosed rigorously. For individualsin the autism group, the subject’s mother was

interviewed using the Autism DiagnosticInterview–Revised (ADI–R; Lord, Rutter, & LeCouteur, 1994), a semistructured, investigator-based interview with good reliability and validity.Subjects with autism were also directly assessedusing the Autism Diagnostic ObservationSchedule–Generic (ADOS–G; Lord et al., 2000) asemistructured play and interview session designedto elicit social, communication, and stereotypedrepetitive behaviors characteristic of autism. Allsubjects in the autism group met ADI–R, ADOS–G, and the Diagnostic and Statistical Manual ofMental Disorders–Fourth Edition (DSM–IV;American Psychiatric Association, 1994) criteriafor autistic disorder (see Table 2 for greater

TABLE 1Subject characteristics

Characteristic

TDCn = 31

AIQn = 38

LIQn = 18

F pMean SD Range Mean SD Range Mean SD Range

Age in years 12.0 4.2 5.3–19.4 10.4 4.1 5.7–18.4 2.9 .06

Head cir (cm) 55.4 2.2 51.8–60.5 55.8 2.7 50.7–60.5 54.5 1.8 51.5–57.9 1.8 .17

TICV (cm3) 1679.0 178.6 1400.0–2170.0 1674.4 164.0 1270.0–2060.0 1667.9 148.5 1380.0–2010.0 0.03 .98

Handed 64.8 45.7 –80 to 100 73.2 45.9 –100 to 100 49.0 68.5 –93.3 to 100 1.4 .26

Education (years) 5.6 3.7 1–12 6.8 3.7 1–14 4.6 3.4 1–12 2.5 .09

FIQ 116.3 14.9 93–152 106.7 12.0 85–137 79.9 8.5 61–99 46.0a,b,c .00

PIQ 116.5 15.6 90–155 107.2 12.1 83–131 92.3 18.7 66–138 14.7a,b,c .00

VIQ 112.2 14.9 87–140 106.8 14.8 85–145 71.8 7.4 55–83 54.8b,c .00

Note. FIQ = full scale IQ; PIQ = performance IQ; VIQ = verbal IQ; TDC = typical developing comparisons; AIQ = average-to-above-average IQ; LIQ = low-average to borderline IQ; cir = circumference; TICV = total intracranial volume.

aTDC is significantly greater than AIQ at p < .05; bTDC is significantly greater than LIQ at p < .05; c AIQ is significantly greaterthan LIQ at p < .05 .

TABLE 2Characterization of the autism and control sample

Test

LIQ AIQ TDC

n Mean (SD) Range n Mean (SD) Range n Mean (SD) Range

ADOS S+C Module 1 2 14 (1.4) 13–15 1 18 (—) — 0 — —

ADOS S+C Module 2 6 18.7 (3.3) 15–23 4 17.3 (4.6) 12–22 1 2 (—) —

ADOS S+C Module 3 9 15.7 (2.1) 14–19 26 13.6 (3.6) 7–20 18 1.4 (1.4) 0–4

ADOS S+C Module 4 1 18 (—) — 7 15.4 (4.5) 8–20 10 1.1 (1.5) 1.5

ADI-R Soc 18 20.2 (6.3) 8–29 35 18.8 (5.6) 6–28

ADI-R Com 18 16.8 (4.9) 8–25 35 15.8 (4.2) 8–24

ADI-R RSB 18 7.4 (2.4) 2–11 35 6.7 (2.3) 0–10

Note. ADOS S+C = Autism Diagnostic Observation Schedule: Social and Communication Total; ADI–R Soc = Autism DiagnosticInterview, Revised: Reciprocal Social Interactions; ADI–R Com = Autism Diagnostic Interview, Revised: Language/Communication;ADI–R RSB = Autism Diagnostic Interview, Revised: Restricted, Repetitive, and Stereotyped Behaviors and Interests; TDC = typicaldeveloping comparisons; AIQ = average-to-above-average IQ; LIQ = low-average to borderline IQ. The ADOS consists of fourmodules, and the individual being evaluated is given just one module, depending on expressive language level and chronological age.Each module has different cutoff scores, and as such they should not be considered equivalent. Three AIQ participants were notadministered the ADI–R. Two comparison participants had incomplete ADOS data, which is not reported above.

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characterization of the autism sample). History,physical exam, fragile X gene testing, and karyo-type, performed on all subjects, excluded medicalcauses of autism. Eighteen subjects in the autismsample were on prescribed medications (9 subjectswere on selective serotonin reuptake inhibitors, 2subjects were on tricyclic antidepressants, 4 sub-jects were on stimulant medications, 2 subjectswere on antipsychotic medications, 1 subject wason a proton pump inhibitor). No subjects had ahistory of seizures, severe head injury, bipolar dis-order, schizophrenia, or drug or alcohol abuse atthe time of participation. While their primary diag-nosis was autism, within the autism sample severalhad secondary comorbid diagnoses as follows:Seven subjects were diagnosed with anxiety disor-ders, three subjects were diagnosed with depres-sion, and five were diagnosed with attentiondeficit hyperactivity disorder. Using the verbal IQmetric (see Boucher et al., 2012), the ASD groupwas divided into two groups, an average (VIQ ≥85)to above-average IQ (AIQ) group and a low (VIQ≤84) intellectual (LIQ) group.

Typically developing sample

Typically developing comparison (TDC) subjectshad no developmental, neurological, or clinicalhistory of major developmental, learning, cogni-tive, neurological, or neuropsychiatric disorders,with the exception of one subject with a historyof seizure. One subject was prescribed an antihis-tamine medication. Comparison subjects likewisecompleted an assessment with the ADOS–G andwere assessed rigorously for ASD to ensure thatnone met any criterion, including no first-degreerelative with autism. Level of intellectual function-ing was not stratified in the comparison subjects.

IQ

Different versions of intellectual tests were usedover the 10 years of subject accrual to the parentproject. IQ findings are reported (for descriptivepurposes) that included summary measures fromone of the following: Wechsler Intelligence Scalefor Children–Third Edition (WISC–III; Wechsler,1991); Wechsler Adult Intelligence Scale–ThirdEdition (WAIS–III; Wechsler, 1997); WechslerAbbreviated Scale of Intelligence (WASI;Wechsler, 1999; VIQ and performance IQ, PIQ,indexes), or Differential Ability Scales (DAS;Elliott, 1993). IQ was not used as a covariatesince IQ was used as an independent selectionvariable for AIQ and LIQ designation.

Handedness and head circumference

Handedness was measured using the EdinburghHandedness Inventory (Oldfield, 1971). A scoreof +100 signifies complete right-handedness, and–100 indicates complete left-handedness. Standardoccipitofrontal head circumference was obtainedon all participants as previously described (seeBigler et al., 2003). Head circumference was initi-ally done at the time of recruitment as a quickproxy for brain volume (Tate, Bigler, McMahon,& Lainhart, 2007) and because of the role of headsize as a factor in autism and the importance ofreporting head circumference values in autismresearch (Lainhart & Lange, 2011). However, amore precise measure of brain volume (total intra-cranial volume, TICV) was controlled for duringanalysis.

Memory

Memory was assessed using the TOMAL (Reynolds& Bigler, 1994). Details of this memory battery inautism have been previously published in Trontelet al. (2013) and Southwick et al. (2011). Theupdated TOMAL had not been released at thetime that this sample was tested. Briefly, theTOMAL samples various domains of memory inchildren and adolescents, ages 5 years 0 monthsthrough 19 years 11 months. The TOMAL is com-posed of a core battery of 10 subtests, including fiveverbal and five nonverbal, as well as supplementarysubtests (three verbal, one nonverbal). FourTOMAL subtests assess retrieval both immediatelyupon stimulus presentation and following a 30-minfilled delay. Among the 10 core subtests, Memoryfor Stories involves immediate and delayed freerecall of short verbal narratives; Word SelectiveReminding is a verbal list-learning task thatincludes a delayed free recall condition; ObjectRecall requires immediate verbal recall of pairedverbal–visual stimuli; Digits Forward involves repe-tition of a number series; and Paired Recall involveslearning verbal paired associates. Among the fivecore nonverbal subtests, Facial Memory presentsarrays of pictured faces that must be recognizedand selected among distractors immediately andfollowing a delay; Visual Selective Reminding is atest of spatial learning with a delayed recall condi-tion; Abstract Visual Memory involves immediaterecognition and discrimination of abstract geo-metric figures; in Visual Sequential Memory a setof abstract figures must be recalled sequentially;and Memory for Location is a spatial recall task.Supplementary subtests consist of three additional

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auditory span and working memory tasks, DigitsBackward, Letters Forward, Letters Backward, andManual Imitation, which involve serial repetition ofbasic hand gestures. The TOMAL has been shownto have high reliability using standard methods forestimating the internal consistency of the subtestsand composites (Reynolds & Bigler, 1994). TheTOMAL assesses declarative memory for novelinformation that was encountered within a specificcontext. Thus, in the present study these results arebroadly described as measures of episodic memoryfunctioning.

Neuroimaging

Volumetric studies were based on magnetic reso-nance images acquired on a Siemens Trio 3.0-Teslascanner at theUniversity ofUtah. At time point 1, an8-channel, receive-only radio frequency (RF) headcoil was used to acquire sagittal 3D magnetizationprepared rapid gradient echo (MPRAGE) spin lat-tice relaxation time (T1)-weighted images (inversiontime = 1100 ms, echo time = 2.93 ms, repetition time= 1800 ms, flip angle = 12°, field of view = 56 mm,slice thickness = 1.0 mm, 160 slices). No subjects inthe current study underwent sedation for scanning.No complications were encountered in the scanningprocess. Additional neuroimaging details previouslyhave been published (see Prigge, Bigler, et al., 2013;Prigge, Lange, et al., 2013).

Volumetric image analysis

All analyses were performed with FreeSurfer imageanalysis suite, Version 5.1 (Dale et al., 1999). Theestablished FreeSurfer image pipeline was followedwherein individual Digital Imaging andCommunications in Medicine (DICOM) imagefiles were conformed and saved in native MGZ for-mat. All analyses were performed on identical nodesat the Fulton Supercomputing Lab at BrighamYoung University. Skull striping, normalization,segmentation and classification were all performedas part of the normal FreeSurfer pipeline. TheFreeSurfer Query, Design, Estimate, Contrast(QDEC) function was used for quality inspectionof the classified images. Within the QDEC functiona ROImay be identified plotting all volumes for thatROI across all participants. This method permitsidentification of outliers where the segmentation/classification can then undergo visual inspection.All participant scans were visually inspected in thismanner before being included in the study. Nooperator-controlled editing was performed.

Volume calculations of the following FreeSurferidentified ROIs were selected: amygdala and hip-pocampal, parahippocampal gyrus, entorhinal cor-tex along total temporal lobe, or medial temporallobe volume (summed volumes of amygdala, hip-pocampal, parahippocampal, entorhinal cortex)with total intracranial volume (TICV). TICV wasused as a covariate.

Statistical analysis

Given the descriptive nature of this investigation,group means were calculated and compared for aut-ism and comparison subjects for ROIs using multi-variate analysis of variance (MANOVA), andp values were Bonferroni corrected for multiplicity.TOMAL composite, index, and subtest scores werecompared using MANOVA. TOMAL scores werethen correlated with neuroanatomically definedROIs controlling for TICV and age for each group.

RESULTS

Sample characteristics

As shown in Table 1, no significant differences atthe p < .05 level were found between groups ondemographic variables (age, head circumference,TICV, handedness index, or education). However,there was a significant group difference for IQ,which was expected. Post hoc comparisons usingBonferroni correction revealed that all three groupswere significantly different on PIQ, F(83, 2) = 14.74,p < .001, and FIQ, F(83, 2) = 45.96, p < .001, withthe TDC group having the highest scores, followedby the AIQ and then LIQ. However, VIQ was notsignificantly different for the TDC group whencompared with AIQ but VIQ for both TDC andAIQ was significantly higher when compared withLIQ (both p < .001).

Memory performance

Results for TOMAL composite, index, and subtestscores are reported in Table 3. Post hoc analysesrevealed that all three groups were significantly dif-ferent from one another on the Composite, Verbal,Nonverbal, and Delayed Memory indices of theTOMAL (p < .01), with TDCs having the highestscores, AIQ having the next highest, and LIQ havingthe lowest scores. This pattern was also true for themajority of the subtests, including Memory forStories, Object Recall, Digits Forward, VisualSequential Memory, and Memories for Stories

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Delayed (p < .01). The TDC and AIQ groups per-formed significantly better than LIQ while not differ-ing from each other for Paired Recall, LettersForward, Memory for Location, and WordSelective Reminding Delayed. No differences werefound between AIQ and LIQ, while performance forboth was significantly worse than TDC, for DigitsBackward, Letters Backward, Facial Memory,Abstract Visual Memory, and Facial MemoryDelayed. Visual Selective Reminding was signifi-cantly different only between the TDC and LIQgroups (p < .01), with the LIQ group performingsignificantly worse. No significant differences werefound between any of the three groups on ManualImitation and Visual Selective Reminding Delayed.Table 4 shows the relationship between IQ andTOMAL performance for each group.

Effect sizes for individual contrasts (TDC vs. AIQ,TDC vs. LIQ, AIQ vs. LIQ) were calculated for theComposite Memory Index and Verbal Memory

Index, as the overall effect size of the MANOVAfor these indices was greater than or equal to amoderate effect (Cohen’s d > 0.5). The effectsbetween the individual groups for the CompositeMemory Index were quite large. The effect size forthe Composite Memory Index between TCD andAIQ was d = 1.39, d = 3.52 between TDC andLIQ, and d = 1.48 between AIQ and LIQ.Similarly, the effect between the individual groupson the Verbal Memory Index was d = 1.20 betweenTDC andAIQ, d = 3.27 between TDC and LIQ, andd = 1.61 between AIQ and LIQ.

Volumetric differences in memory ROIs

Volumetric findings are summarized in Table 5.MANOVAs comparing the two ASD groups withTDC controlling for age and TICV revealed no sig-nificant volume differences in the left, right, or total

TABLE 3Results of Test of Memory and Learning

Index/subtest

TDCn = 31

AIQn = 38

LIQn = 18

F p η2pMean SD Mean SD Mean SD

Composite Memory Index 107.8 9.6 90.8 14.6 70.8 12.3 35.90 .000a,b,c .51

Verbal Memory Index 105.1 11.5 89.2 15.6 66.1 13.2 33.97 .000a,b,c .50

Memory for Stories 11.7 3.2 8.3 3.4 4.4 2.5 23.58 .000a,b,c .41

Word Selective Reminding 11.3 2.3 9.7 4.5 4.9 3.4 14.24 .000b,c .29

Object Recall 9.4 2.7 7.1 3.5 4.4 3.3 11.32 .000a,b,c .25

Digits Forward 9.7 3.4 7.4 3.5 4.6 2.5 12.22 .000a,b,c .26

Paired Recall 11.4 2.5 9.8 2.6 6.9 3.8 11.12 .000b,c .24

Letters Forward 9.0 3.0 7.5 3.1 4.4 2.6 11.81 .000b,c .26

Digits Backward 10.7 2.4 8.4 2.8 6.9 2.7 11.76 .000a,b .25

Letters Backward 10.5 2.3 8.3 2.7 6.2 3.3 12.91 .000a,b .27

Nonverbal Memory Index 109.4 11.6 93.0 15.2 77.9 13.2 21.35 .000a,b,c .38

Facial Memory 10.4 2.6 7.8 2.3 6.6 2.6 13.06 .000a,b .27

Visual Selective Reminding 10.0 2.7 8.2 3.2 6.6 3.2 6.25 .003b .15

Abstract Visual Memory 12.7 2.7 9.8 3.0 8.2 3.5 12.27 .000a,b .26

Visual Sequential Memory 11.3 2.7 9.1 2.5 6.9 2.4 14.43 .000a,b,c .29

Memory for Location 11.9 3.6 9.8 4.5 6.6 4.0 8.04 .001b,c .19

Manual Imitation 12.0 2.9 10.7 2.7 10.5 3.2 1.84 .163 .05

Delayed Recall Index 102.5 9.3 91.5 10.9 78.4 11.7 21.87 .000a,b,c .39

Memory for Stories 11.3 3.5 8.1 3.3 4.7 2.9 18.65 .000a,b,c .35

Facial Memory 9.9 2.2 8.0 2.7 6.7 3.5 6.68 .002a,b .16

Word Selective Reminding 10.0 2.5 9.8 2.3 7.2 2.9 6.19 .003b,c .15

Visual Selective Reminding 10.1 1.6 9.1 2.1 8.6 2.0 3.27 .040 .09

Note. TDC = typical developing comparisons; AIQ = average-to-above-average IQ; LIQ = low-average to borderline IQ. WordSelective Reminding was not normally distributed and did not pass tests of normality; however, an identity transformation was optimal.Word Selective Reminding Delayed did meet the assumption of normality. η2p = partial eta squared is an estimate of the effect varianceand error variance that is attributable to the effect.

ap < .01 for TDC and AIQ; bp < .01 for TDC and LIQ; cp < .01 for AIQ and LIQ.

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entorhinal cortex, parahippocampal gyrus, hippo-campus, or amygdala (p > .05). Additionally, nogroup differences were found for total temporallobe, total mesial temporal lobe (sum of parahippo-campal, entorhinal, hippocampus, and amygdala),total gray matter, or total brain volume (p > .05).

Relation between ROI volume and TOMALperformance

As shown in Table 6, ASD individuals’ perfor-mance on the Composite Memory Index, VerbalMemory Index, and Nonverbal Memory Index of

the TOMAL was negatively correlated only withthe amygdala in the LIQ group, indicating thatlarger amygdala volume related to lower memoryperformance for that group. Additionally, totalgray matter volume was negatively correlatedwith the Verbal Memory Index for both AIQ andLIQ, but not for TDC, indicating that greater graymatter volumes were related to lower verbal mem-ory performance in the ASD groups. None of theother classic memory ROIs was correlated withTOMAL performance on the Composite MemoryIndex, Verbal Memory Index, Nonverbal MemoryIndex, or Delayed Recall Index for the threegroups.

TABLE 5Comparisons of structure volume by group controlling for TICV and age

Region of interestTDC

Mean (SD)AIQ

Mean (SD)LIQ

Mean (SD) F p

Temporal lobe 134.8 (13.6) 132.8 (13.1) 132.8 (14.8) 0.95 .39

Left 67.2 (7.5) 66.3 (6.9) 66.1 (7.7) 0.71 .49

Right 67.5 (6.4) 66.5 (6.7) 66.8 (7.6) 1.05 .36

Entorhinal 4.3 (1.1) 4.0 (0.8) 4.1 (0.6) 1.18 .31

Left 2.3 (0.6) 2.1 (0.4) 2.2 (0.4) 1.65 .20

Right 2.1 (0.6) 1.9 (0.5) 2.0 (0.4) 0.36 .70

Parahippocampal 4.9 (0.8) 4.9 (0.8) 4.9 (0.5) 0.02 .98

Left 2.6 (0.4) 2.6 (0.5) 2.5 (0.3) 0.55 .58

Right 2.3 (0.5) 2.3 (0.4) 2.4 (0.4) 0.36 .70

Hippocampus 8.9 (1.0) 9.3 (1.2) 9.1 (1.2) 1.29 .28

Left 4.4 (0.7) 4.7 (0.6) 4.5 (0.7) 2.40 .10

Right 4.6 (0.5) 4.6 (0.7) 4.6 (0.6) 0.29 .75

Amygdala 3.4 (0.4) 3.6 (0.6) 3.5 (0.4) 1.33 .27

Left 1.7 (0.2) 1.8 (0.3) 1.8 (0.2) 1.79 .17

Right 1.7 (0.2) 1.8 (0.3) 1.7 (0.2) 0.97 .38

Mesial temporal lobe 21.59 (2.6) 21.7 (2.6) 21.6 (1.8) 0.10 .90

Total GM 596.5 (53.8) 587.0 (63.4) 613.0 (71.9) 0.09 .92

Total brain 1345.7 (123.9) 1338.0 (130.1) 1332.7 (115.2) 0.92 .40

Note. GM = gray matter; TDC = typical developing comparisons; AIQ = average-to-above-average IQ; LIQ = low-average toborderline IQ; TICV = total intracranial volume. Volumes are in cm3.

TABLE 4Correlations between IQ and TOMAL performance

Index score

Performance IQ Verbal IQ Full Scale IQ

TDC AIQ LIQ TDC AIQ LIQ TDC AIQ LIQ

Verbal Memory Index .13 .57** –.04 .36 .56** .66** .26 .66** .09

Nonverbal Memory Index .57** .63** .60* .45* .21 .06 .60** .49** .50

Delayed Memory Index –.06 .38* –.16 .18 .26 .50 .07 .37* .35

Composite Memory Index .47* .67** .35 .52** .43* .38 .55** .64** –.12

Note. TOMAL = Test of Memory and Learning; TDC = typically developing comparisons; AIQ = average-to-above-average IQautism; LIQ = low-average to borderline IQ autism.

*p < .05. **p < .01.

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DISCUSSION

Memory performance differences

This investigation revealed, consistent with ourhypotheses, that individuals with ASD in the AIQor LIQ group performed significantly worse onmemory tasks than did their TDC counterparts.Furthermore, AIQ and LIQ groups differed inmemory performance as expected; AIQ performedsignificantly better than LIQ. Interestingly, in com-parison to the TOMAL normative standard, theAIQ group performed within one standard devia-tion (average) on all four memory index scores,while the LIQ group performed one standarddeviation below (low average) on the composite,nonverbal, and delayed recall indices but two stan-dard deviations (impaired) below on the verbalmemory index. This suggests that verbal intellec-tual abilities likely have the greatest influence onverbal-based memory impairments. These findingsare consistent with previous literature implicatingmemory impairments as part of the ASD cognitivephenotype (Ben Shalom, 2003; Boucher &Bowler, 2008) and suggest that memory perfor-mance is related to level of intellectual ability.Additionally, the relationship between IQ andmemory performance for each group may suggestthat despite the overall lower TOMAL perfor-mance in the AIQ ASD group, their relation withintellectual ability is similar to TDC, whereas withLIQ an even greater level of impaired memoryfunction is present.

Overall, the ASD AIQ and LIQ groups appearto perform more similarly to one another on

nonverbal tasks (with the exception of visualsequential memory and memory for location).However, for verbal memory tasks that do notplace prominent demands on working memoryand for delayed memory tasks (with the exceptionof facial memory), AIQ appears to perform signif-icantly better than LIQ individuals. Given that theLIQ group is defined by lower levels of VIQ, andASD is associated with language deficits (DePape,Hall, Tillmann, & Trainor, 2012), the memoryimpairments in the LIQ group likely reflect a nega-tive interaction on linguistic and mnestic deficitsfrom the core language deficits that are part ofASD (see Tyson et al., 2013). How level of generalcognitive ability in ASD relates to memory perfor-mance requires further study.

Working memory

In the current investigation, the AIQ group per-formed similarly to TDC on a verbal workingmemory task (e.g., letters forward), which is con-sistent with research by Rumsey andHamburger (1988) and Minshew andGoldstein (1993) who failed to find any memorydeficits in higher functioning individuals with aut-ism. However, as the task becomes more complex(i.e., recitation of numbers/letters backwards), AIQand LIQ groups appear to perform more similarly(e.g., digits and letters backward). This is consis-tent with Barendse et al.’s (2013) review of theworking memory literature in ASD, which foundgreater deficits in working memory with heavierdemands, and with Boucher et al.’s (2012) review,

TABLE 6Correlations between brain volumes and TOMAL performance controlling for TICV

Region of interest

Composite MemoryIndex

Verbal MemoryIndex

Nonverbal MemoryIndex

Delayed RecallIndex

TDC AIQ LIQ TDC AIQ LIQ TDC AIQ LIQ TDC AIQ LIQ

Temporal lobe –.01 –.17 –.25 .07 –.26 –.34 –.09 –.05 –.13 .05 –.13 –.15

Entorhinal –.11 –.12 –.06 –.06 –.10 –.12 –.11 –.13 –.02 –.03 –.08 –.14

Parahippocampal –.17 –.01 –.18 –.10 .09 –.12 –.16 –.11 –.18 –.15 .08 –.11

Hippocampal .08 –.07 –.20 .04 –.07 –.08 .10 –.05 –.27 .09 –.16 .14

Amygdala –.12 .26 –.69** –.17 .28 –.59* –.02 .18 –.60* .05 .33 –.44

Mesial temporal lobe –.09 .01 –.39 –.07 .05 –.29 –.06 –.06 –.39 –.01 .03 –.13

Total gray matter .28 –.27 –.37 .32 –.37* –.51* .11 –.11 –.17 .16 –.23 –.43

Total brain .26 –.07 .06 .24 –.10 –.07 .18 –.03 .15 .29 –.15 .02

Note. TDC = typical developing comparisons; AIQ = average-to-above-average IQ; LIQ = low-average to borderline IQ; TICV =total intracranial volume. Only the correlation between the amygdala and the composite memory index for the LIQ group remainedsignificant after the Bonferroni correction.

*p < .05. **p < .01, controlling for age and TICV.

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which found that tasks that require executive con-trol in order to manipulate and process the onlineinformation (e.g., digits backward) were more dif-ficult for individuals with ASD. Likewise, a diffi-culty with processing of complex information inASD is consistent with the disconnection modelposited by Minshew and Williams (2007).

Intact memory performance in ASD

Two subtests revealed no impairments in ASD parti-cipants regardless of whether AIQ or LIQ were com-pared with TDC: manual imitation (a sequentialmotor memory task) and visual selective remindingdelayed (recall of visual information previouslylearned over trials). While motor proficiency is acommonly reported deficit in ASD (Duffieldet al., 2013; Minshew, Goldstein, & Siegel, 1997),the current study suggests that memory for a motorsequence (with nomeasure ofmotor fluency) remainsintact in ASD. Additionally, intact performance ondelayed visual selective reminding in both groups isconsistent with the task support hypothesis (Bowler,Gardiner, & Berthollier, 2004; Bowler, Matthews, &Gardiner, 1997), which posits that the absence ofadequate “supports” during testing explains the def-icits seen on recall tasks. The importance of supportshas been found to be particularly true for multipletrial learning (Bowler, Gaigg, & Gardiner, 2008;Bowler, Limoges, & Mottron, 2009).

Heterogeneity in ASD

In the newest version of the Diagnostic andStatistical Manual–5th Edition (DSM–5; AmericanPsychiatric Association, 2013), individuals meet cri-teria for a diagnosis of ASD if they demonstratecharacteristics in two core areas (communicationand social deficits and fixed or repetitive behaviors).The criteria reflect an attempt to acknowledge thespectrum of abilities and deficits in the disorder. Thecurrent memory performance findings underscore adimensional model approach to autism and reflectthe vast differences in memory across the spectrum,not simply between TDC and ASD. TOMALComposite Memory Index ranged from profoundlyimpaired to superior (41 to 124) for ASD, while theTDC group ranged from low average to superior(81 to 126). Clearly, much greater variability existswithin the ASD group for memory performance(see Table 3). Likewise, full-scale IQ (FSIQ) inASD ranged from 61–137, while TDC FSIQ scoresranged from 93–152. This neurocognitive heteroge-neity emphasizes the complexity of the neurobiolo-gical underpinnings of autism. Further, the lowest

functioning participants in the ASD group wereexcluded from this study, so it is unknown howsubstantial the memory impairment is or howbroad the within-group differences may be that arenot reliably captured with only two severity levels ofcomparison for ASD (i.e., AIQ versus LIQ).

No structural volumetric differences in mesialtemporal lobe structures

There were no gross volumetric differencesbetween the ASD and TDC groups in mesial tem-poral lobe structures typically thought to beinvolved in memory processes. The finding of“normal” ROI structural volumes in ASD in thecurrent study is consistent with several volumetricstudies (Bigler et al., 2003; Piven, Bailey, Ranson,& Arndt, 1998; Saitoh, Courchesne, Egaas,Lincoln, & Shreibman, 1995) that have not foundunique differences in gross temporal lobe morphol-ogy in ASD. Since memory differences in bothAIQ and LIQ ASD were shown compared toTDC individuals, the absence of gross morpholo-gical differences implies that memory function inASD is likely due to disrupted neural connectivitywithin memory networks rather than the absolutesize of mesial temporal lobe structures.

Relation of memory performance and ROI

Contrary to our hypotheses, hippocampal, para-hippocampal gyral, and entorhinal cortex volumeswere not significantly related to memory perfor-mance for any of the groups. However, for theLIQ group only, memory performance was nega-tively correlated with amygdala volume. In otherwords, larger amygdala volumes in the LIQ func-tioning ASD group were related to poorer memoryperformance in our sample. Although this relation-ship did not withstand correction for family-wiseerror, this finding is interesting given research sug-gesting that learning and memory processes maybe specifically linked to the amygdala in autism(Howard et al., 2000; O’Keefe & Nadel, 1978).

The relation between larger amygdala and poorermemory possibly relates to the overgrowth hypoth-esis of neural development in ASD where largervolume is associated with less efficient networks(Amaral, Geschwind, & Dawson, 2011). Casanovaand Trippe (2009) and Casanova (2007) have shownthat increases in cortical gray matter may relate toaberrant increased white matter projections neces-sary to maintain the connectivity of the increasednumber of cortical cells in the autistic brain. Thissuggests that an increased number of white matter

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connections in autism may not result in greater andmore efficient functional connectivity, but ratherless efficient networks.

Limitations

The two autism groups were differentiated using acutoff of one standard deviation below averageverbal intelligence. Although this differentiationproved fruitful in delineating memory differencesbetween the groups, it was arbitrary and not neces-sarily a clinically derived criterion for differentiat-ing within autism. More clinically meaningfulphenotypes may allow better delineation of cogni-tive factors associated with impaired memory func-tion in ASD. Small (LIQ = 18) and modest (AIQ =38; TDC = 31) group sizes limited power to detectmeaningful differences in important demographicvariables. The LIQ group had, on average,younger participants with fewer years of educationthan the other two groups (approximately 3 yearsdifference), which might suggest that memory per-formance was related to age and education in theseindividuals with ASD. Head circumference alsofavored the TCD group, although total brainvolume did not. It could be that these variablescontribute to group differences given sufficientsample sizes as direct or indirect predictors.Although all children were in educational pro-grams, it was impossible to control for the kindsand types of educational experiences that hadoccurred. Likewise, there were potential differencesin the kinds of supportive therapies and interven-tions received by participants. There are alsopotential age, education, and family interactionvariables that could influence memory function asmeasured by the TOMAL that could not be con-trolled in this study. Accordingly, given the limitedpower of group cell sizes, caution is recommendedin the generalizability of these findings.Replication with larger sample sizes matched onidentified key variables related to memory perfor-mance will be critical for future research to con-firm present findings. Further, participants whowere not amenable to testing due to behavioraland/or cognitive factors (low-functioning partici-pants) were not included in the current study,which may also limit generalizability of the find-ings to the autism spectrum as a whole.

The inability to find consistent volumetric differ-ences correlated with memory function in ASDmay suggest that the neuropathology of ASD isnot expressed at the level of gross morphologywithin these structures. It may be that more refinedmeasures that assess neural connectivity and

networks such as functional MRI (fMRI) and dif-fusion tensor imaging (DTI) will better clarify theneurobiological basis of memory impairment inautism. A review of the literature on memory inASD by Goh and Peterson (2012) reveals that thebulk of the existing research in this involves struc-tural imaging rather than functional imaging, sothere is an absence of such research to address theneural connectivity of memory in ASD. Futurestudies investigating the structure and functionalneuroimaging of neural pathways in memoryregions may provide insight regarding abnormal-ities that contribute to memory and learningimpairments in this population. It should benoted that automated image analysis methodsused in this investigation have limitations, and itremains possible that more refined structural imageanalysis methods may prove successful in definingbrain structure–function relations in memory andASD (Hanson et al., 2012).

CONCLUSION

Generally, lower performance on measures ofintellectual functioning was associated with worseTOMAL performance in ASD and when com-pared to TDC. The AIQ group performed simi-larly to TDC on less complex verbal workingmemory tasks. AIQ and LIQ ASD groups appearto perform more similarly on nonverbal tasks andmore complex verbal working memory tasks.However, for verbal memory tasks that do notrequire working memory and for delayed memorytasks (with the exception of facial memory), AIQperformed significantly better than LIQ ASD (i.e.,greater within-group variability) and more similarto TDC.Although amygdala volume was found to be

negatively related to general memory performancein LIQ, and total gray matter volume was found tobe negatively related to verbal memory perfor-mance for both ASD groups, these relations werenot robust enough to withstand correction for mul-tiple comparisons and were unlikely to represent amajor explanation for poor memory performancein ASD.

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