Probabilistic Learning of Cue-Outcome Associations is not Influenced by Autistic Traits

J Autism Dev Disord. 2023 Oct;53(10):4047-4059. doi: 10.1007/s10803-022-05690-0. Epub 2022 Aug 11.

Abstract

According to Bayesian/predictive coding models of autism, autistic individuals may have difficulties learning probabilistic cue-outcome associations, but empirical evidence has been mixed. The target cues used in previous studies were often straightforward and might not reflect real-life learning of such associations which requires learners to infer which cue(s) among many to track. Across two experiments, we compared adult learners with varying levels of autistic traits on their ability to infer the correct cue to learn probabilistic cue-outcome associations when explicitly instructed to do so or when exposed implicitly. We found no evidence for the effect of autistic traits on probabilistic learning accuracy, contrary to the predictions of Bayesian/predictive coding models. Implications for the current Bayesian/predictive coding models are discussed.

Keywords: Autistic traits; Bayesian; Prediction; Predictive coding; Probabilistic; Statistical learning.

MeSH terms

  • Adult
  • Autism Spectrum Disorder*
  • Autistic Disorder*
  • Bayes Theorem
  • Cues
  • Humans
  • Learning