Disentangling "Bayesian brain" theories of autism spectrum disorder

Background: Bayesian theories of perception have provided a variety of alternative mechanistic explanations for autistic symptoms, including (1) overprecise sensations, (2) imprecise priors, (3) inflexible priors, and (4) altered hierarchical learning. Here, we designed a set of experiments to systematically test predictions from each of the four hypotheses in individuals with autism spectrum disorder (ASD). Methods: Two versions of a two-alternative forced-choice (2AFC) random dot motion task were developed to disentangle the influence of sensory inputs and prior expectations and test implications of the four Bayesian hypotheses. Behavioural data were obtained from participants with autism spectrum disorder (N=47) and a control group (N=50). Analyses used mixed effects models and a drift diffusion model. Results: Contrary to the sensory overprecision hypothesis, individuals with ASD did not differ from controls in performance or parameter estimates during the perceptual 2AFC task. When adding cues to the task, individuals with ASD profited less from this prior information than controls, as predicted by the imprecise prior hypothesis. However, individuals with ASD were still able to update their initial priors, contradicting the inflexible prior hypothesis. Finally, in line with the hierarchical learning hypothesis, volatility differentially modulated expectation effects, exerting a significantly smaller effect in the ASD group compared to the control group. Conclusion: Our findings support two mutually compatible alterations of perception in ASD (imprecise priors and, to a lesser degree, altered hierarchical learning). By contrast, they are not compatible with the notions of sensory overprecision and inflexible priors.