When the world becomes too real: a Bayesian explanation of autistic perception

When the world becomes too real: a Bayesian explanation of autistic perception

| Elizabeth Pellicano & David Burr
The article by Elizabeth Pellicano and David Burr explores the application of Bayesian decision theory to understand the perceptual differences in autism. They propose that attenuated Bayesian priors, or hypo-priors, may explain the unique perceptual experiences of individuals with autism, leading to a more accurate but less biased perception of the world. The authors suggest that hypo-priors result in a tendency to perceive the world more accurately rather than being modulated by prior experiences. They argue that these hypo-priors could account for the broad range of sensory and non-social atypicalities in autism, such as hypersensitivity, hyposensitivity, and sensory seeking behaviors. The article also discusses how hypo-priors might explain other key features of autism, including the desire for sameness and the sense of being overwhelmed by sensory information. The Bayesian framework is seen as a powerful tool for studying the underlying mechanisms of autistic perception and for developing testable hypotheses about the functional atypicalities in autism.The article by Elizabeth Pellicano and David Burr explores the application of Bayesian decision theory to understand the perceptual differences in autism. They propose that attenuated Bayesian priors, or hypo-priors, may explain the unique perceptual experiences of individuals with autism, leading to a more accurate but less biased perception of the world. The authors suggest that hypo-priors result in a tendency to perceive the world more accurately rather than being modulated by prior experiences. They argue that these hypo-priors could account for the broad range of sensory and non-social atypicalities in autism, such as hypersensitivity, hyposensitivity, and sensory seeking behaviors. The article also discusses how hypo-priors might explain other key features of autism, including the desire for sameness and the sense of being overwhelmed by sensory information. The Bayesian framework is seen as a powerful tool for studying the underlying mechanisms of autistic perception and for developing testable hypotheses about the functional atypicalities in autism.
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