Suboptimal but intact integration of Bayesian components during perceptual decision-making in autism

Area of Science:

• Neuroscience
• Cognitive Science
• Psychology

Background:

• Autism is characterized by altered sensory perception, potentially due to imbalanced integration of sensory information and prior knowledge in Bayesian inference.
• Current hypotheses link altered sensory processing in autism to Bayesian perception and predictive coding models.
• Empirical evidence is limited and conflicting, with prior studies failing to isolate the roles of priors and sensory uncertainty.

Purpose of the Study:

• To quantitatively assess the independent and combined contributions of priors and sensory uncertainty to perceptual decision-making in autistic and non-autistic individuals.
• To investigate whether autistic individuals exhibit altered Bayesian inference during a perceptual task.

Main Methods:

• A quantitative assessment of perceptual decision-making was conducted in 126 autistic and non-autistic individuals.
• Participants completed an orientation categorization task to evaluate the integration of priors and sensory uncertainty.
• Bayesian inference components were independently and interdependently analyzed in decision behavior.

Main Results:

• Autistic individuals integrated prior knowledge and sensory uncertainty into their decision-making, indistinguishably from non-autistic individuals.
• Both groups exhibited suboptimal adjustments in their decision criteria.
• The findings challenge the common view of imbalanced prior integration in autism.

Conclusions:

• Autistic individuals demonstrate intact Bayesian inference during perceptual decision-making.
• The results challenge the notion that Bayesian computations are fundamentally altered in autism.
• Further research is needed to explore potential alterations in implicit prior learning or specific decision-making contexts.