Alexithymic and autistic traits : relevance for comorbid depression and social phobia in adults with and without autism spectrum disorder

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was supported by the Max Planck Society via a grant for an Independent Max Planck Research Group awarded to L.S. L.A. was funded via the Else-Kröner-Fresenius-Stiftung (EKFS) as part of a joint residency/PhD program in translational psychiatry at the LMU Munich and the Max Planck Institute of Psychiatry.Peer reviewedPublisher PD

Aberrant computational mechanisms of social learning and decision-making in schizophrenia and borderline personality disorder

This repository entails the processed data to the manuscript "Aberrant computational mechanisms of social learning and decision-making in schizophrenia and borderline personality disorder" as well as the computational modeling code

Social Bayes: Using Bayesian Modeling to Study Autistic Trait–Related Differences in Social Cognition

Background: The autistic spectrum is characterized by profound impairments of social interaction. The exact subpersonal processes, however, that underlie the observable lack of social reciprocity are still a matter of substantial controversy. Recently, it has been suggested that the autistic spectrum might be characterized by alterations of the brain's inference about the causes of socially relevant sensory signals. Methods: We used a novel reward-based learning task that required integration of nonsocial and social cues in conjunction with computational modeling. Thirty-six healthy subjects were selected based on their score on the Autism-Spectrum Quotient (AQ), and AQ scores were assessed for correlations with cue-related model parameters and task scores. Results: Individual differences in AQ scores were significantly correlated with participants' total task scores, with high AQ scorers performing more poorly in the task (r = -.39, 95% confidence interval = -0.68 to -0.13). Computational modeling of the behavioral data unmasked a learning deficit in high AQ scorers, namely, the failure to integrate social context to adapt one's belief precision-the precision afforded to prior beliefs about changing states in the world-particularly in relation to the nonsocial cue. Conclusions: More pronounced autistic traits in a group of healthy control subjects were related to lower scores associated with misintegration of the social cue. Computational modeling further demonstrated that these trait-related performance differences are not explained by an inability to process the social stimuli and their causes, but rather by the extent to which participants consider social information to infer the nonsocial cue. Keywords: Autistic traits; Bayesian modeling; Computational psychiatry; Reward-based learning; Social cognition; Social gaze

Social Bayes: Using Bayesian Modeling to Study Autistic Trait-Related Differences in Social Cognition

BACKGROUND: The autistic spectrum is characterized by profound impairments of social interaction. The exact subpersonal processes, however, that underlie the observable lack of social reciprocity are still a matter of substantial controversy. Recently, it has been suggested that the autistic spectrum might be characterized by alterations of the brain's inference about the causes of socially relevant sensory signals. METHODS: We used a novel reward-based learning task that required integration of nonsocial and social cues in conjunction with computational modeling. Thirty-six healthy subjects were selected based on their score on the Autism-Spectrum Quotient (AQ), and AQ scores were assessed for correlations with cue-related model parameters and task scores. RESULTS: Individual differences in AQ scores were significantly correlated with participants' total task scores, with high AQ scorers performing more poorly in the task (r = -.39, 95% confidence interval = -0.68 to -0.13). Computational modeling of the behavioral data unmasked a learning deficit in high AQ scorers, namely, the failure to integrate social context to adapt one's belief precision -the precision afforded to prior beliefs about changing states in the world-particularly in relation to the nonsocial cue. CONCLUSIONS: More pronounced autistic traits in a group of healthy control subjects were related to lower scores associated with misintegration of the social cue. Computational modeling further demonstrated that these trait-related performance differences are not explained by an inability to process the social stimuli and their causes, but rather by the extent to which participants consider social information to infer the nonsocial cue