title: When the world becomes 'too real': a Bayesian explanation of autistic perception.
abstract: Perceptual experience is influenced both by incoming sensory information and prior knowledge about the world, a concept recently formalised within Bayesian decision theory. We propose that Bayesian models can be applied to autism - a neurodevelopmental condition with atypicalities in sensation and perception - to pinpoint fundamental differences in perceptual mechanisms. We suggest specifically that attenuated Bayesian priors - 'hypo-priors' - may be responsible for the unique perceptual experience of autistic people, leading to a tendency to perceive the world more accurately rather than modulated by prior experience. In this account, we consider how hypo-priors might explain key features of autism - the broad range of sensory and other non-social atypicalities--in addition to the phenomenological differences in autistic perception.
authors.affiliation: Centre for Research in Autism and Education, Institute of Education, University of London, London, UK. l.pellicano@ioe.ac.uk
authors.forename: Elizabeth
authors.initials: E
authors.lastname: Pellicano
authors.forename: David
authors.initials: D
authors.lastname: Burr
mesh_terms: D000223:Adaptation, Psychological; D001321:Autistic Disorder / Q000503:physiopathology* / Q000523:psychology; D001499:Bayes Theorem; D006801:Humans; D008606:Mental Processes; D008960:Models, Psychological; D010465:Perception / Q000502:physiology*