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Contextual priors do not modulate action prediction in children with autism.

ABSTRACT: Bayesian accounts of autism suggest that this disorder may be rooted in an impaired ability to estimate the probability of future events, possibly owing to reduced priors. Here, we tested this hypothesis within the action domain in children with and without autism using a behavioural paradigm comprising a familiarization and a testing phase. During familiarization, children observed videos depicting a child model performing actions in diverse contexts. Crucially, within this phase, we implicitly biased action-context associations in terms of their probability of co-occurrence. During testing, children observed the same videos but drastically shortened (i.e. reduced amount of kinematics information) and were asked to infer action unfolding. Since during the testing phase movement kinematics became ambiguous, we expected children's responses to be biased to contextual priors, thus compensating for perceptual uncertainty. While this probabilistic effect was present in controls, no such modulation was observed in autistic children, overall suggesting an impairment in using contextual priors when predicting other peoples' actions in uncertain environments.

SUBMITTER: Amoruso L

PROVIDER: S-EPMC6710602 | biostudies-literature | 2019 Aug

REPOSITORIES: biostudies-literature

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Contextual priors do not modulate action prediction in children with autism.

Amoruso Lucia L Narzisi Antonio A Pinzino Martina M Finisguerra Alessandra A Billeci Lucia L Calderoni Sara S Fabbro Franco F Muratori Filippo F Volzone Anna A Urgesi Cosimo C

Proceedings. Biological sciences 20190814 1908

Bayesian accounts of autism suggest that this disorder may be rooted in an impaired ability to estimate the probability of future events, possibly owing to reduced priors. Here, we tested this hypothesis within the action domain in children with and without autism using a behavioural paradigm comprising a familiarization and a testing phase. During familiarization, children observed videos depicting a child model performing actions in diverse contexts. Crucially, within this phase, we implicitly ...[more]

PMID: 31409253

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Project description:ImportanceAutism spectrum disorder (ASD) affects 1 in 88 children and is characterized by a complex phenotype, including social, communicative, and sensorimotor deficits. Autism spectrum disorder has been linked with atypical connectivity across multiple brain systems, yet the nature of these differences in young children with the disorder is not well understood.ObjectivesTo examine connectivity of large-scale brain networks and determine whether specific networks can distinguish children with ASD from typically developing (TD) children and predict symptom severity in children with ASD.Design, setting, and participantsCase-control study performed at Stanford University School of Medicine of 20 children 7 to 12 years old with ASD and 20 age-, sex-, and IQ-matched TD children.Main outcomes and measuresBetween-group differences in intrinsic functional connectivity of large-scale brain networks, performance of a classifier built to discriminate children with ASD from TD children based on specific brain networks, and correlations between brain networks and core symptoms of ASD.ResultsWe observed stronger functional connectivity within several large-scale brain networks in children with ASD compared with TD children. This hyperconnectivity in ASD encompassed salience, default mode, frontotemporal, motor, and visual networks. This hyperconnectivity result was replicated in an independent cohort obtained from publicly available databases. Using maps of each individual's salience network, children with ASD could be discriminated from TD children with a classification accuracy of 78%, with 75% sensitivity and 80% specificity. The salience network showed the highest classification accuracy among all networks examined, and the blood oxygen-level dependent signal in this network predicted restricted and repetitive behavior scores. The classifier discriminated ASD from TD in the independent sample with 83% accuracy, 67% sensitivity, and 100% specificity.Conclusions and relevanceSalience network hyperconnectivity may be a distinguishing feature in children with ASD. Quantification of brain network connectivity is a step toward developing biomarkers for objectively identifying children with ASD.

Dataset Information

Contextual priors do not modulate action prediction in children with autism.

Publications

Contextual priors do not modulate action prediction in children with autism.

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