Autistic traits, but not schizotypy, predict increased weighting of sensory information in Bayesian visual integration.

ABSTRACT: Recent theories propose that schizophrenia/schizotypy and autistic spectrum disorder are related to impairments in Bayesian inference that is, how the brain integrates sensory information (likelihoods) with prior knowledge. However existing accounts fail to clarify: (i) how proposed theories differ in accounts of ASD vs. schizophrenia and (ii) whether the impairments result from weaker priors or enhanced likelihoods. Here, we directly address these issues by characterizing how 91 healthy participants, scored for autistic and schizotypal traits, implicitly learned and combined priors with sensory information. This was accomplished through a visual statistical learning paradigm designed to quantitatively assess variations in individuals' likelihoods and priors. The acquisition of the priors

SUBMITTER: Karvelis P 

PROVIDER: S-EPMC5966274 | biostudies-literature | 2018 May

REPOSITORIES: biostudies-literature