Atypical sensory perception in autism from the perspective of Bayesian framework
Autism spectrum disorder(ASD)is a complex neurodevelopmental condition characterized by social impairments and restricted and repetitive behaviours and interests.Moreover,individuals with ASD often exhibit atypical perceptual features(i.e.,hypersensitivity or hyposensitivity to stimuli).Previous perceptual models such as enhanced perceptual functioning(EPF)and weak central coherence(WCC)offer only partial explanations for differences between individuals with ASD and typically developing(TD)individuals.A novel approach to understanding these differences is the Bayesian framework,which conceptualizes perceptual processes through the lens of Bayesian computational modelling and predictive coding theory.This framework offers insight into how prediction errors(i.e.,bottom-up sensory input)and priors(i.e.,top-down cognitive processes)jointly influence perception in individuals with ASD in various ways.In this paper,we conducted a comprehensive review of prominent Bayesian models of ASD and delved into the intricate explanations provided by these models for both social and nonsocial symptoms of ASD.To evaluate the validity of these models,we also scrutinized a wide range of empirical evidence derived from behavioural and neuroimaging studies.We identified several notable Bayesian models in the literature,two of the most prominent being the"hypo-prior hypothesis"and the"high,inflexible precision of prediction errors in autism theory"(HIPPEA).Empirical studies have examined these theories at different levels of cognitive processing,ranging from higher-level social cognitive functions to sensory perception across multiple modalities,with varying designs and methodological details.Overall,these studies have provided equivocal support for Bayesian theories.While some studies have suggested that individuals with ASD have a lower weighting of prior expectations than TD individuals,other studies have reported inconsistent or even contrasting findings.Similarly,some studies have reported that individuals with ASD exhibit a decreased ability to adapt prediction error signals to varying contexts,whereas other studies have suggested that the neural coding of prediction errors remains intact in ASD.Furthermore,in some studies,behavioural findings were at odds with neuroimaging findings.These mixed outcomes may be attributed to participant heterogeneity,different learning timescales in the task,different presentation probabilities of stimuli material,and variations in how priors were operationalized.In addition,few empirical studies have made comparisons between different Bayesian theories of ASD or between Bayesian theories and traditional perceptual models,and most previous studies have struggled to distinguish between different types of priors.Although Bayesian theories of ASD are promising and may help us better understand atypical sensory perception in individuals with ASD,they face challenges on the empirical front.For example,there is a lack of comparisons between multiple theories within the same study,and there is a relative scarcity of current neuroscience research.At the theoretical level,following the proposal of the"hypo-priors"hypothesis in 2012,scholars have conducted further studies to develop the hypothesis and provide empirical validation.While the empirical findings have been heterogeneous,this hypothesis has the potential to enhance our comprehension of altered sensory perception in ASD individuals.Ongoing research endeavours will provide substantial empirical data,with ample opportunities to refine the hypothesis and investigatory approach.Subsequent research initiatives should include a comparative analysis of theoretical frameworks within Bayesian theories and expand the integration of neuroimaging studies.In summary,Bayesian theories have demonstrated practical utility and are supported by considerable evidence,thereby contributing to an enriched understanding of atypical sensory perception in individuals with ASD.Nevertheless,Bayesian theories remain an evolving concept,necessitating extensive future research to accommodate updates and refinements.
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