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.