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Copyright 2008 by the American Psychological Association Intact Implicit Learning of Spatial Context and Temporal Sequences in Catholic University of America and Georgetown University William D. Gaillard and Chandan J. Vaidya Children’s National Medical Center and Georgetown University Autism spectrum disorder (ASD) is defined by atypicalities in domains that are posited to rely on implicitlearning processes such as social communication, language, and motor behavior. The authors examined 2forms of implicit learning in 14 children with high-functioning ASD (10 of whom were diagnosed withAsperger’s syndrome) and 14 control children, learning of spatial context known to be mediated by themedial temporal lobes (using the contextual cueing task) and of sequences known to be mediated byfrontal–striatal and frontal– cerebellar circuits (using the alternating serial reaction time task). Both formsof learning were unimpaired in ASD. Spatial contextual implicit learning was spared in ASD despiteslower visual search of spatial displays. The present findings provide evidence for the integrity oflearning processes dependent on integration of spatial and sequential contextual information in high-functioning children with ASD.
Keywords: frontostriatal circuits, medial temporal lobes, spatial attention, sequence learning, develop-mental disorders The ability to learn environmental regularities (e.g., where or when In the present study, we examined implicit contextual learning in two events may occur) implicitly, without intention or conscious aware- domains: In the spatial domain, repeated experience with invariant ness, is posited to support linguistic and motor skill acquisition (Per- spatial relationships provides predictive cues that guide visual atten- ruchet & Pacton, 2006) and social intuition (Lieberman, 2000).
tion during visual search tasks (e.g., contextual cueing [CC] task; Impairments in these domains characterize children with autism spec- Chun, 2000). In the perceptual–motor domain, repeated experience trum disorder (ASD) in whom difficulties with social communication with invariant sequential structure of stimuli forms the basis for accompany repetitive behaviors and restricted interests. Implicit learn- predicting subsequent responses to contiguous (e.g., serial reaction ing of contextual information guides perception of social cues and time [SRT] task; Nissen & Bullemer, 1987) or noncontiguous (e.g., predicts actions and, therefore, may mediate atypical cognition in alternating SRT [ASRT] task; Howard & Howard, 1997) stimuli.
ASD. However, investigation of the integrity of learning processes Learning is implicit because participants cannot recollect or recognize has not figured centrally in models of cognitive dysfunction in ASD.
the learned spatial context or sequential information. Knowledge ofthese two forms of implicit learning in ASD is necessary for con-straining knowledge about the status of cognition in the disorder.
Examining two forms of implicit learning in ASD provides the Kelly Anne Barnes and Darlene V. Howard, Department of Psychology, opportunity to probe the functional integrity of learning mecha- Georgetown University. James H. Howard Jr., Department of Psychology, nisms shown to be dissociable in adults. Whether functional spe- Catholic University of America; Department of Neurology, Georgetown cialization of memory systems is complete by late childhood is not University. Lisa Gilotty and Lauren Kenworthy, Department of Neurology, fully known. Nevertheless, forms of learning that have been dis- Children’s National Medical Center. William D. Gaillard, Department of sociated in adults provide a heuristic for systematic examination of Neurology, Children’s National Medical Center; Department of Neurol-ogy, Georgetown University. Chandan J. Vaidya, Department of Psychol- memory systems in childhood (see also Berl, Vaidya, & Gaillard, ogy, Georgetown University; Department of Neurology, Children’s Na- 2006). Spatial contextual learning is hypothesized to involve the medial temporal lobes (i.e., the hippocampus and entorhinal, Funding support came from Georgetown University, National Alliance perirhinal, and parahippocampal cortices) because learning was for Autism Research, National Institute of Mental Health Grants MH reduced in patients with extensive medial temporal lobe lesions 065395, NIA R37AG15450, and the Frederick and Elizabeth Singer Foun- (Chun & Phelps, 1999). Although hippocampal lesions did not dation. We thank Jennifer Foss-Feig and Margaret Benner for assistance disrupt learning on the CC task (Manns & Squire, 2001) hip- with data collection, and Sunbin Song and Marvin Chun for providing the pocampal involvement was observed using functional brain imag- ASRT and CC tasks, respectively. Lisa Gilotty is now with the National ing during CC performance in healthy adults (Greene, Gross, Institute of Mental Health, the National Institutes of Health.
Elsinger, & Rao, 2007). Furthermore, activations also involve Correspondence concerning this article should be addressed to Kelly Anne Barnes, Department of Psychology, 306L White Gravenor, George- lateral–frontal and temporal cortices projecting to the medial tem- town University, Washington, DC 20057. E-mail: [email protected] poral lobe. Thus, although the role of the hippocampus remains to be elucidated, other medial temporal lobe regions and their cortical uration repeats on some trials and is novel on others. Context- projections appear to be important for spatial contextual learning.
dependent learning is indexed by faster responding on trials with In contrast to spatial contextual learning, sequence learning is repeated than novel distractor configurations. On the ASRT task, hypothesized to involve striatal circuitry because it is impaired in participants respond to the location of a visual stimulus by pressing people with Huntington’s and Parkinson’s disease (Willingham, a corresponding key. Unbeknownst to participants, the stimulus 1997), which are characterized by degeneration of basal ganglia location varies in a fixed sequence involving alternate trials (i.e., structures. Functional brain imaging studies also show involve- item n predicts item n ϩ 2 on these trials); randomly determined ment of the cerebellum and regions projecting to the striatum such stimulus locations alternate with sequence trials. Context-depen- as prefrontal and motor cortices in adults on the ASRT and SRT dent learning is indexed by faster responding on sequential than on tasks (Fletcher et al., 2005; Rauch, Whalen, et al., 1997; Willing- random trials. The ASRT rather than SRT task was used for two ham, Salidis, & Gabrieli, 2002) and in children on the SRT task reasons. First, the ASRT task is more resistant to the development (Thomas et al., 2004). Double dissociations in elderly participants of conscious awareness of underlying sequential structure and use further suggest that implicit spatial contextual and sequence learn- of explicit memory strategies during performance. Therefore, dif- ing are separable. Specifically, Negash et al. (2007) reported ferences in explicit memory abilities are less likely to influence reduced CC but not ASRT learning in individuals with mild sequence learning. Second, the ASRT task is more sensitive to cognitive impairment, a condition characterized by medial–tem- ongoing learning because performance on sequential and random poral lobe pathology, compared with age-matched controls. In trials is assessed continuously during learning rather than after contrast, reduced ASRT but not CC learning was reported in learning has occurred. Thus, factors affecting expression of learn- healthy aging (Howard, Howard, Dennis, Yankovich, & Vaidya, ing, such as fatigue, are minimized for ASRT than they are for 2004), a period characterized by reductions in striatal, cerebellar, and prefrontal volumes with relative sparing of the medial–tem-poral lobes (Raz et al., 2005). Thus, brain imaging and neuropsy- chological findings suggest that medial temporal and frontostria- tal– cerebellar circuits mediate learning of spatial context andsequential structure, respectively.
Fourteen children with ASD (13 boys) ages 8 to 14 years with Cognitive strengths and weaknesses observed in ASD lead to IQ within the normal range were recruited from Children’s Na- distinct hypotheses about the status of implicit learning. A strength tional Medical Center (see Table 1). Ten children with ASD had a observed in ASD is a tendency toward superior processing of local diagnosis of Asperger’s syndrome; of the 4 remaining children information. Relative to controls, participants with ASD are faster with ASD, 2 had a diagnosis of high-functioning autism and 2 had at detecting targets embedded in complex visual figures (Jolliffe & a diagnosis of pervasive developmental disorder—not otherwise Baron-Cohen, 1997) and give fewer context-appropriate pronun- specified. Fourteen control children (13 boys) ages 7 to 14 years ciations of homographs (Happe´, 1997). The source of this bias, with IQ within the normal range were recruited from the Wash- whether due to impaired (Happe´, 1999) or unaffected (Mottron, ington, DC, area through advertisements. The groups matched for Burack, Iarocci, Belleville, & Enns, 2003; Plaisted, Saksida, Al- sex, age (ASD: M ϭ 11.57 years, SD ϭ 1.65; controls: M ϭ 11.00 cantara, & Weisblatt, 2003) global information processing, years, SD ϭ 1.80; p ϭ .39), and IQ (ASD: M ϭ 110.43, remains unresolved. Nevertheless, those findings suggest that con- SD ϭ 12.59; controls: M ϭ 116.29, SD ϭ 13.79; p ϭ .25). All textual information weakly modulates visual–perceptual and lin- parents or guardians provided informed consent; children provided guistic processing in ASD. Such a bias could reduce contextual informed assent and were paid for participation.
encoding, thereby reducing learning dependent on invariant con- Children were diagnosed with ASD by clinicians using criteria textual information in ASD, regardless of stimulus domain. Thus, in the Diagnostic and Statistical Manual of Mental Disorders (4th this view hypothesizes reduced learning on both sequence learning ed., text revision; DSM–IV–TR; American Psychiatric Association, and contextual cueing tasks. Consistent with this prediction, se- 2000); diagnosis was confirmed by expert opinion of clinicians quence learning on the SRT task was reduced in children with specializing in ASD (LK, LG; see Table 1). The Childhood As- ASD (Mostofsky, Goldberg, Landa, & Denckla, 2000). Alterna- perger Syndrome Test (CAST) (Scott, Baron-Cohen, Bolton, & tively, intact learning on both sequence learning and contextual Brayne, 2002) was used to objectively screen for ASD symptoms cueing tasks may be hypothesized in light of one of the core (cutoff ϭ 15); all participants with ASD were above the ASD symptoms of ASD, the need for sameness and regularity. The cutoff (see Table 1). In addition, a portion of children with ASD preference for repetition in ASD may promote acquisition of who had clinical evaluations at Children’s National Medical Cen- invariant contextual information, leading to spared or superior ter received the Autism Diagnostic Interview—Revised (ADI–R) learning of spatial and sequential relationships. Thus, there are and the Autism Diagnostic Observation Schedule (ADOS; Lord reasonable arguments to hypothesize both impaired and intact et al., 2000; Lord, Rutter, & Le Couteur, 1994). Seven children contextual learning in ASD. The present study tested these hy- received both ADI–R and ADOS, 3 children ADOS only, 1 child potheses by examining both learning of spatial context and se- ADI–R only, and 3 children neither ADI–R nor ADOS. All ADOS quential information in the same children with ASD and matched Social Domain summary scores (M ϭ 8.60, range ϭ 4 –13, cut- off ϭ 4) and all but one of the ADOS Communication Domain We examined implicit learning of spatial context using the CC summary scores (M ϭ 3.60, range ϭ 1– 8, cutoff ϭ 2) were above task and of sequences using the ASRT task in children with ASD the ASD cutoff. Restricted and Repetitive Behavioral Domain and age-, sex-, and IQ-matched controls. On the CC task, partic- summary scores were consistent with Lord et al.’s (2000) scores ipants search for a target among distractors whose spatial config- (M ϭ 3.00, range ϭ 2– 4, no cutoff). ADI scores were above the Table 1Demographics of Participants With Autism Spectrum Disorder FSIQ ϭ Full-scale IQ determined by Wechsler Intelligence Scale for Children (3rd ed.) or Wechsler Abbreviated Scale of Intelligence; CAST ϭ Childhood Asperger Syndrome Rating Scale Score (autism spectrum disorder [ASD] diagnosis suggested by scores higher than 15). M ϭ male; F ϭ female.
Diagnosis: ASP ϭ Asperger syndrome; HFA ϭ high-functioning autism; PDD ϭ pervasive developmental disorder—not otherwise specified. All childrenwith a diagnosis of ASP had normal onset of language and normal adaptive functioning. Contextual cueing (CC) learning ϭ faster reaction times to repeatedthan to novel configurations in the last epoch. Alternating serial reaction time (ASRT) learning ϭ faster reaction times to pattern than to random trials inthe last epoch. S3’s CAST score was 1 point below cutoff, but this participant met criteria for ASD on the Autism Diagnostic Interview—Revised or theAutism Diagnostic Observation Schedule.
autism cutoff (Reciprocal Social Interaction: M ϭ 21.12, range ϭ from the screen’s center and screen half (left/right); no targets 18 –25, cutoff ϭ 10; Communication: M ϭ 19.25, range ϭ 14 –24, appeared in the four center or corner cells. Every element was cutoff ϭ 8; Restricted and Repetitive Behaviors: M ϭ 8.62, randomly repositioned by Ϯ2 pixels along each axis to avoid range ϭ 5–12, cutoff ϭ 3). Exclusion criteria included other colinearity. Each block consisted of 24 trials: 12 unique configu- neurological disorders (e.g., epilepsy), IQ Ͻ 85, or use of antipsy- rations of distractors (novel) and 12 configurations of distractors chotic medications. Medications could not be withdrawn in 10 that repeated across the experiment (repeated). Target location, but children with ASD who participated on antidepressants (9), stim- ulants (3), nonstimulants (i.e., Strattera; 1), or valproic acid (1); 4 Stimuli were presented via Matlab with instruc- Control children were screened for ASD using the CAST (Scott tions to locate the T as quickly and accurately as possible. Fol- et al., 2002) and psychiatric conditions (e.g., attention problems) lowing 24 practice trials, participants completed 30 blocks of 24 using the Child Behavior Checklist (Achenbach, 1991). Children trials each. Trials were randomized within blocks. Blocks were completed the subtests of the Woodcock–Johnson III Diagnostic grouped into 6 epochs of 5 blocks (e.g., Blocks 1–5 made up Reading Battery to screen for reading disorder. No control partic- Epoch 1). On each trial, a fixation dot appeared for 1 s, followed ipants had any neurological or psychiatric conditions, including by a stimulus, which remained until a response was made. If no ASD. Unpaired t tests confirmed that symptoms on the CAST were response was made within 6 s, the trial timed out following an higher in ASD than those in control participants (ASD: M ϭ 19.71, error tone. Feedback tones were high pitched for correct responses SD ϭ 4.20; controls: M ϭ 5.00, SD ϭ 3.19), t(26) ϭ 10.45, p Ͻ and low pitched for errors. Following the task, 24 configurations (12 novel, 12 repeated) were presented for recognition memory;participants pressed a key for familiar configurations.
used with group (ASD vs. control) as a between-subjects factor and configuration (repeated vs. novel) and epoch (1– 6) as within- used with group (ASD vs. control) as a between-subjects factor and trial type (pattern vs. random) and epoch (1–5) as within- Each trial consisted of a 12-element stimulus array of a single target and 11 distractors presented in white on a gray background Each trial began with three empty circles displayed horizontally (Figure 1, upper portion). The target was a horizontal T rotated left across a screen (Figure 1, lower portion), mapped to a keyboard key or right by 90°, to which subjects responded by pressing a key- (M and the adjoining symbol keys Ͻ and Ͼ). On each trial, one circle board key (Z for left, “/” for right). The distractors were Ls filled in and remained filled until participants pressed the correct key.
randomly rotated by 0°, 90°, 180°, or 270°. Arrays were generated The circles remained empty for 120 ms between trials. One of two by randomly placing the 12 items into cells of an invisible grid (6 patterns was randomly assigned to each participant (either A-r-B-r-C rows ϫ 8 columns). Target location was balanced for distance or A-r-C-r-B-r, where A, B, and C denote the left, central, and right Trials with reaction times (RTs) that were 3 or more standard deviations from the mean were excluded. The percentage of ex-cluded trials did not differ between groups (CC–ASD: M ϭ 1.00%,SD ϭ 0.73, control: M ϭ 0.81%, SD ϭ 0.54, p ϭ .45, d ϭ 0.30;ASRT–ASD: M ϭ 1.15%, SD ϭ 0.49, control: M ϭ 1.27%,SD ϭ 0.63; p ϭ .56, d ϭ 0.21). Based on past research using theCC task (Chun & Jiang, 1998), trials without a response within 6 swere excluded (total trials: ASD ϭ 11; controls ϭ 5). Cohen’s dand ␩ 2 effect sizes are reported for t tests and analyses of variance Percentage of correct responses (accuracy) and mean RTs for correct trials were computed for each participant and were ana-lyzed in Group (ASD vs. control) ϫ Configuration (repeated vs.
novel) ϫ Epoch (1– 6) repeated measures ANOVAs (see Figure 2).
Analysis of accuracy revealed no significant main effects or inter-actions, except a trend for higher accuracy for repeated than novelconfigurations (main effect of configuration), F(1, 26) ϭ 3.89, p ϭ.06, ␩ 2 ϭ .13 (other ps Ͼ .26, ␩ 2 Ͻ .05). Overall accuracy was high (ASD: M ϭ 97.58%, SD ϭ 1.88; control: M ϭ 97.03%,SD ϭ 2.31).
Analysis of RTs revealed that responses were slower in ASD than in control children (main effect of group), F(1, 26) ϭ 5.20, Schematics of computer displays for the contextual cueing p Ͻ .03, ␩ 2 ϭ .17. Participants exhibited learning of visual search (CC; upper portion) and alternating serial reaction time (ASRT; lower skill because responses were faster with practice (main effect of portion) tasks. The arrow in CC task display indicates the target’s location.
epoch), F(5, 130) ϭ 43.57, p Ͻ .0001, ␩ 2 ϭ .63. Although overall For both tasks, the black keys indicate the correct response.
responses were faster to repeated than to novel configurations(main effect of configuration), F(1, 26) ϭ 17.95, p Ͻ .0001, ␩ 2 ϭ .41, children exhibited context-dependent learning because the positions and r denotes a random element, constrained so that all benefits of repetition increased with practice (Configuration ϫ locations appeared with equal frequency). The three-position long Epoch interaction), F(5, 130) ϭ 3.25, p ϭ .008, ␩ 2 ϭ .11.
pattern repeated throughout the experiment.
Magnitude of learning did not differ between groups (Group ϫ Stimuli were presented via E-Prime with instruc- Epoch ϫ Configuration interaction, p ϭ .95, ␩ 2 ϭ .01). No other tions to press the key that matched the filled-in circle’s location (M interactions reached significance (all ps Ͼ .14, ␩ 2 Ͻ .06).
and the adjoining symbol keys Ͻ and Ͼ on a keyboard). Partici- In light of slower visual search in ASD relative to control pants completed 20 blocks of 60 trials each. Blocks were grouped children, we determined whether differences in magnitude of into 5 epochs of 4 blocks (e.g., Blocks 1– 4 made up Epoch 1).
learning were apparent on a measure that equated speed by ex- Each block began with 8 practice trials and ended with feedback pressing learning as a proportion of one’s baseline speed (i.e., encouraging speed and accuracy. Conscious awareness for learnedsequences is commonly tested subjectively with questions such as“Did you notice any regularity in the way the stimulus moved?”We did not include such a test because metacognitive immaturity in childhood often results in unreliable introspective reports(Kuhn, 2000).
Participants performed the CC and ASRT tasks within a single session in counterbalanced order. Both tasks were self-paced.
Participants took short breaks between blocks, approximately ev- ery 60 s on the CC task and every 90 s on the ASRT task. Includingbreaks, total time on the CC task ranged from 30 to 45 min and total time on the ASRT task ranged from 20 to 25 min. For bothtasks, children were instructed to rest their hands over the relevant Mean response time (in seconds) on the contextual cueing (CC) response keys during the experiment. The experimenter confirmed task as a function of epoch and type of configuration for autism spectrum that this was done throughout the task.
novel – repeated/novel, calculated per epoch). Proportional learn- other interactions reached significance (all ps Ͼ .26, ␩ 2 Ͻ .05).
ing scores computed for each participant were analyzed in a We examined the three-way interaction for effects of group (with Group ϫ Epoch ANOVA. The main effect of group and the Epoch ϫ Trial Type ANOVAs for each group) and epoch (with Group ϫ Epoch interaction were not significant ( ps Ͼ .43, ␩ 2 Ͻ Group ϫ Trial Type ANOVAs for each epoch). Each group .02), indicating that measures of proportional learning did not exhibited sequence learning because the Epoch ϫ Trial Type differ between ASD and control children. Thus, the absence of interaction reached significance: ASD, F(4, 52) ϭ 2.60, p Ͻ .05, group differences in learning was not an artifact of speed differ- ␩ 2 ϭ .17; control, F(4, 52) ϭ 3.60, p ϭ .01, ␩ 2 ϭ .22. Sequence ences because group differences were not observed after equating learning marginally differed between groups in Epoch 5 (Group ϫ Trial Type interaction), F(1, 26) ϭ 3.84, p ϭ .06, ␩ 2 ϭ .13, but For the recognition memory test, dЈ scores [z (%hits) – z (%false not in Epochs 1– 4 (all ps Ͼ .11, ␩ 2 Ͻ .10). Planned comparisons alarms)] were computed for each participant. One-sample t tests indicated that the difference between pattern and random trials was indicated that dЈscores did not differ from chance in ASD larger in ASD than control participants in Epoch 5, t(26) ϭ 1.96, (M ϭ 0.75, SD ϭ 1.50, p ϭ .11) and control (M ϭ 0.28, p ϭ .06, d ϭ 0.74 (other epochs ps Ͼ .11, d Ͻ 0.63). Thus, ASD SD ϭ 1.41, p ϭ .54) children. Furthermore, an unpaired t test but not control children continued to show learning into the last indicated that dЈscores did not differ between groups ( p ϭ .44, d ϭ 0.32). Thus, participants were unable to consciously recognize It is possible that group differences in magnitude of learning emerged because the ASD group’s response speed appeared toimprove to a greater extent than did controls’ response speed. We therefore determined whether differences in magnitude of learningwere apparent on a measure that equated speed by expressing Percentage of correct responses (accuracy) and mean RTs for learning as a proportion of one’s baseline speed (i.e., random – correct trials were computed for each participant and were analyzed in pattern/random, calculated per epoch). Proportional learning Group (ASD vs. control) ϫ Trial Type (pattern vs. random) ϫ Epoch scores computed for each participant were analyzed in a Group ϫ (1–5) repeated measures ANOVAs (see Figure 3). Accuracy did Epoch ANOVA. Overall measures of proportional learning did not not differ between ASD (M ϭ 92.25%, SD ϭ 3.48) and control differ between ASD and control children (main effect of group), (M ϭ 93.37%, SD ϭ 3.08) participants (main effect of group, p ϭ p ϭ .41, ␩ 2 ϭ .03. Group differences in learning were suggested .38, ␩ 2 ϭ .03). Participants were more accurate on pattern than by a significant Group ϫ Epoch interaction, F(4, 104) ϭ 2.47, p Ͻ random trials (main effect of trial type), F(1, 26) ϭ 36.40, p Ͻ .05, ␩ 2 ϭ .09. We examined this interaction to determine whether .0001, ␩ 2 ϭ .58, and accuracy increased with practice (main each group demonstrated learning (with one-way ANOVAs for effect of epoch), F(4, 104) ϭ 2.42, p Ͻ .05, ␩ 2 ϭ .09. No each group) and whether magnitude of learning differed between interactions reached significance (all ps Ͼ .17, ␩ 2 Ͻ .06).
the two groups (with unpaired t tests for each epoch). Each group Overall RTs did not differ between groups (main effect of exhibited sequence learning because the main effect of epoch was group, p ϭ .90, ␩ 2 ϭ .001). Participants exhibited perceptual– significant: ASD, F(4, 52) ϭ 3.07, p ϭ .02, ␩ motor skill learning because responses were faster with practice F(4, 52) ϭ 3.28, p ϭ .02, ␩ 2 ϭ .20. Unpaired t tests revealed that (main effect of epoch), F(4, 104) ϭ 6.59, p Ͻ .0001, ␩ 2 ϭ .20.
proportional magnitude of learning was larger in ASD than control Although overall responses were faster to pattern than random children in Epoch 5, t(26) ϭ 1.99, p ϭ .06, d ϭ 0.75 (all other trials (main effect of trial type), F(1, 26) ϭ 32.13, p Ͻ .0001, ps Ͼ .17, d Ͻ 0.54). Thus, group differences in learning persisted ␩ 2 ϭ .55, children exhibited sequence learning because the ben- after controlling for baseline differences in response speed.
efits of repetition increased with practice (Trial Type ϫ Epochinteraction), F(4, 104) ϭ 3.72, p ϭ .007, ␩ 2 ϭ .13. Group differences in learning were suggested by a Group ϫ Epoch ϫ Trial Type interaction, F(4, 104) ϭ 2.53, p Ͻ .05, ␩ 2 ϭ .09. No Two forms of implicit learning, for spatial context and percep- tual–motor sequences, did not differ between high-functioningchildren with ASD and controls. For spatial contextual learning,learning on the CC task did not differ between groups, despite slower visual search performance in ASD relative to control chil- dren. For sequential learning, whereas baseline ASRT perfor- mance did not differ between the groups, expression of learning was more prolonged in ASD than control children. Recognition memory for spatial configurations did not differ between groups, and therefore, differences in explicit memory ability are unlikely to account for the observed findings on the CC task. Explicit memory for sequences on the ASRT task was not tested.
In a disorder characterized by impaired functioning in multiple behavioral domains, spared learning abilities have important im- plications for future research and treatment. Nonetheless, accept-ing the null hypothesis requires caution, and we consider several Mean response time (in milliseconds) on the alternating serial reaction time (ASRT) task as a function of epoch and type of trial for alternative explanations: First, it is possible that our measures autism spectrum disorder (ASD) and control groups.
lacked sensitivity to detect group differences in learning. However, previous studies have found reduced magnitude of learning on the Despite no group differences in implicit spatial contextual learn- ASRT task in healthy aging (Howard & Howard, 1997; Howard ing, the ASD group’s performance differed from that of controls in et al., 2004) and dyslexia (Howard, Howard, Japikse, & Eden, two ways. First, overall response speed on the CC task was slower 2006) and on the CC task in childhood (Vaidya, Huger, Howard, in children with ASD than it was in controls, a finding that is & Howard, 2007) and mild cognitive impairment (Negash et al., inconsistent with reports of superior visual search in ASD 2007), suggesting that these tasks are sensitive to group differences (O’Riordan, Plaisted, Driver, & Baron-Cohen, 2001; Plaisted, in learning. Second, the small sample size could result in reduced O’Riordan, & Baron-Cohen, 1998). Superior visual search in ASD statistical power, thereby reducing our ability to detect group has been posited to arise from weak central coherence (Happe´ differences in learning. Effect size for a group difference in total 1999) or a preference for visual details (O’Riordan et al., 2001).
magnitude of learning (sum of the difference between trial types However, past studies have noted that superiority in ASD may not across epochs) was moderate for the ASRT task (d ϭ 0.43) and extend to all visual search tasks (Kenworthy et al., 2005; Klein- small for the CC task (d ϭ 0.16); the larger effect size for the hans, Akshoomoff, & Delis, 2005). Our finding of slower visual ASRT task reflects greater rather than reduced learning in ASD search in ASD is consistent with at least one previous study relative to control children. The power to detect these effect sizes examining visual search for a target letter (T or F) surrounded by is low (ASRT: .17–.25; CC task: .06 –.08). More than 70 subjects similar distractors (letters that were halfway between Ts and Fs; would be needed for group differences of the obtained effect sizes Edgin & Pennington, 2005). The present CC task also required to be significant at ␣ ϭ .05 with power ϭ .80. Third, similar ASRT searching for a target (T) among similar distractors (L). In the learning in the two groups may result from differential explicit present task, targets were rotated and the response required an awareness for sequential information between the two groups. In orientation judgment for the long arm of the T (left/right). This past studies using a variety of recognition measures, adult partic- added perceptual demand may have made visual search more ipants did not develop explicit awareness on the CC and ASRT effortful, enhancing the task’s sensitivity to group differences.
tasks (Chun & Jiang, 2003; Song, Howard, & Howard, 2007).
Thus, slower performance on tasks requiring visual search in ASD Although CC recognition was at chance in the present study, the may be more apparent under certain experimental conditions.
influence of explicit awareness on the ASRT task cannot be Slower visual search in children with ASD was not due to general conclusively ruled out because it was not measured. Fourth, there motor impairments because baseline response speed on the ASRT were children in the ASD group who did not demonstrate learning task did not differ between groups. Task selectivity of performance in the last epoch (see Table 1), suggesting that there may be some differences suggests that slower visual search in ASD reflects children with ASD who showed impaired implicit learning. How- atypical properties of spatial attention, possibly mediated by ocu- ever, lack of implicit learning on the last epoch at the individual lomotor dysfunction (Sweeney, Takarae, Macmillan, Luna, & level is not unusual because it was apparent in some control Minshew, 2004) rather than perceptual–motor dysfunction. How- children (ASRT task: 5/14; CC task: 1/14).
ever, motivation levels could have also differed across tasks.
While considering our observation of lack of group differences, Second, learning on the ASRT task did not differ between the it is important to note that several characteristics of our sample groups but its expression was more prolonged in ASD than in control constrain interpretation and generalization of the present findings.
children. Studies with adults indicate that the expression of sequence First, IQ was matched across groups, and therefore, the present learning in performance can be dissociated from the acquisition of findings are limited to intellectually high-functioning children with sequence knowledge. For example, participants’ response latencies ASD. Second, the present findings are limited to Asperger’s syn- were modulated by task characteristics (e.g., stimulus context) and drome, the diagnosis for 10 of the 14 children with ASD. It is also performance demands (e.g., inclusion of a secondary task), even important to note that ADOS and ADI scores were unavailable though the structural knowledge of sequences they gained was un- on 3 children with ASD. Third, the present findings extend pri- changed (Jimenez, Vaquero, & Lupianez, 2006; Willingham, Green- marily to boys with ASD because only 1 girl was included in the berg, & Thomas, 1997). It is possible that prolonged expression of ASD sample. Fourth, only 2 children with ASD were left-handed.
sequence learning in ASD reflects cognitive inflexibility that is known Although hand assignment for the tasks was not changed for these to characterize the ASD phenotype (Hill, 2004). Cognitive inflexibil- participants, exclusion of their data from analyses did not influence ity may promote expression of learning pertaining to invariant stim- the results. Fifth, psychotropic medications that could not be ulus-response contingencies, due to an inability to discard the adopted withheld during testing in some children could have influenced task set. Indeed, the tendency for more expression of sequence learn- learning. Four of these children were on medications for attention ing was observed in another psychiatric condition that is characterized problems that are most likely to influence learning. However, by stereotypical behaviors and cognitive inflexibility, obsessive– com- magnitude of learning did not differ between children medicated pulsive disorder. Patients with obsessive– compulsive disorder for attention problems, unmedicated children with ASD, and con- showed numerically, albeit not statistically, greater SRT improvement trols on either task (unpaired t tests, all ps Ͼ .31). Furthermore, relative to controls (Rauch, Savage, et al., 1997). The small sample magnitude of learning for these children was within 95% confi- size in the present study precludes examination of the relation be- dence intervals for mean magnitude of learning in control children tween magnitude of sequence learning and cognitive inflexibility in for each task. Sixth, differences in fatigue did not appear to ASD. However, this hypothesis can be tested in future studies.
influence the results because both groups responded faster as Unimpaired learning of a complex sequential structure (i.e., epochs progressed. Faster performance, particularly on random involving second-order regularity) in children with ASD is sur- and novel trials, is inconsistent with fatigued performance. Thus, prising in light of impaired learning of a simpler sequential struc- the present findings most directly extend to right-handed, intellec- ture on the SRT task (i.e., containing zero-order regularity where tually high-functioning boys diagnosed with Asperger’s syndrome.
some positions occur more frequently than others; Mostofsky et al., 2000). Two factors could have contributed to these differ- learning in childhood ASD provides a basis for investigating the ences: First, characteristics of performance differed between the nature of frontal–striatal– cerebellar involvement that characterizes groups in the study by Mostofsky et al. (2000). Overall response speed was slower in ASD than in control children, perhaps because In sum, the present findings indicate that two dissociable forms of motor impairments that are common in ASD. Thus, nonmne- of learning, of spatial context and perceptual–motor sequences, monic aspects of SRT performance may have reduced the expres- were intact in ASD children with a diagnosis of Asperger’s syn- sion of learning in Mostofsky et al.’s ASD participants. Second, drome. If the present findings are replicated in future studies, they ASD is characterized by highly heterogeneous symptom expres- could be harnessed for treatment purposes. Future research could sion. Perhaps differences in findings between the studies simply study interventions that encourage children to focus on the degree reflect distinct cohorts of children with ASD. Our sample consisted to which social cues and contextual information co-occur and how primarily of children diagnosed with Asperger’s syndrome (10/ that relates to the status of implicit learning. Furthermore, findings 14), whereas participants in the study by Mostofsky et al. were from the ASRT task suggest that ASD may promote longer ex- diagnosed with high-functioning autism. Among the 4 non-As- pression of learning based on invariant sequential information.
perger’s children in the present study, learning was not below the Functional imaging studies of sequence learning are required to 95% confidence interval in any child for the ASRT task but was elucidate the neural basis of the current findings. The ASRT task below the 95% confidence interval in 2 children (1 with high- is an optimal probe for those studies because it taps a well- functioning autism, 1 with pervasive developmental disorder—not operationalized learning mechanism that is rooted in frontal–stria- otherwise specified) for the CC task. Thus, future studies that compare ASD cohorts are needed to clarify the extent of sparing orimpairment in implicit learning.
These results provide new knowledge about the functional in- tegrity of neural systems that subserve implicit learning in ASD.
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