Archival Report
Neurocognitive Mechanisms of Social Inferences in Typical and Autistic Adolescents

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Abstract

Background

Many of our efforts in social interactions are dedicated to learning about others. Adolescents with autism have core deficits in social learning, but a mechanistic understanding of these deficits and how they relate to neural development is lacking. The present study aimed to specify how adolescents with and without autism represent and acquire social knowledge and how these processes are implemented in neural activity.

Methods

Typically developing adolescents (n = 26) and adolescents with autism spectrum disorder (ASD) (n = 20) rated in the magnetic resonance scanner how much 3 peers liked a variety of items and received trial-by-trial feedback about the peers’ actual preference ratings. In a separate study, we established the preferences of a new sample of adolescents (N = 99), used to examine population preference structures. Using computational models, we tested whether participants in the magnetic resonance study relied on preference structures during learning and how model predictions were implemented in brain activity.

Results

Typically developing adolescents relied on average population preferences and prediction error updating. Importantly, prediction error updating was scaled by the similarity between items. In contrast, preferences of adolescents with ASD were best described by a No-Learning model that relied only on the participant’s own preferences for each item. Model predictions were encoded in neural activity. Typically developing adolescents encoded prediction errors in the putamen, and adolescents with ASD showed greater encoding of own preferences in the angular gyrus.

Conclusions

We specified how adolescents represent and update social knowledge during learning. Our findings indicate that adolescents with ASD rely only on their own preferences when making social inferences.

Section snippets

Methods and Materials

The study consisted of 2 assessments, an online preference survey in a large sample of adolescents (N = 99; 55 female; age, mean ± SD = 15.7 ± 1.4 years; age range = 11–18 years) to establish preferences of the adolescent population, and a functional magnetic resonance imaging (fMRI) experiment in a separate group of TD adolescents (n = 26; 11 female; age, mean ± SD = 13.7 ± 2.5 years; age range = 9–18 years) and adolescents with ASD (n = 20; 12 female; age, mean ± SD = 14.8 ± 2.8 years; age

Differences in Social Inferences Between Typical and Autistic Adolescents

We tested group differences in task performance with 2 different metrics: unsigned model-free PEs (the numerical differences between estimates and feedback) and open-answer descriptions of preference profiles. Average accuracy, i.e., average absolute model-free Pes, did not differentiate between TD adolescents and adolescents with ASD. Median model-free PEs were on average equally high (median for TD = 2.49; median for ASD = 2.49; H-test on median PEs: χ245 = 0.07, p = .790) and reduced over

Discussion

This study investigated how adolescents with and without autism build knowledge representations of their peers. We tested whether adolescents rely on preexisting social knowledge to make preference inferences and how their knowledge is updated during learning about a specific peer. Based on preference profiles from an independent sample of adolescents, we devised computational models that combine knowledge about peers at varying levels of complexity with PE updating. TD adolescents relied on a

Acknowledgments and Disclosures

This research was supported by the Hilibrand Fellowship for Autism Research at the Yale Child Study Center.

We thank Koen Frolichs for assisting us with data analysis.

This article was published as a preprint on bioRxiv: https://doi.org/10.1101/850552.

DL is a cofounder of Neurogazer. The other authors report no biomedical financial interests or potential conflicts of interest.

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