Assessing the predictive coding accounts of autism spectrum disorders

ended

Autism Spectrum Disorder (ASD) affects more than seven million individuals in the European Union. Yet, this neurodevelopmental disorder remains poorly accounted for. ASD is defined by persistent deficits in social interactions and communication, and by restricted interests and repetitive patterns of behaviors. Recent predictive coding theories offer potential accounts of ASD. The predictive coding framework assumes that the brain constantly generates predictions about its environment. These predictions, or priors, are integrated with sensory information to produce a percept, and their relative contributions depend on their precisions. A suboptimal balance of prior and sensory precisions could be at the core of ASD. Theories suggest low prior precision, high sensory precision and/or inflexible ratio of precisions in ASD. Empirical evidences are scarce, and this proposal aims at testing these theories. I aim at characterizing the behavioral and neural mechanisms underlying the estimation of prior (WP1) and sensory (WP2) precisions in ASD. In WP1, participants will perform a visual task designed to elicit the implicit learning of a prior with a high or low precision (quantifiable with computational models). The neural correlates of prior precision estimation will be investigated with functional and structural MRI, DTI, and magnetic resonance spectroscopy. In WP2, participants will be passively exposed to fast periodic visual stimulations. Using a sweep paradigm with visual stimuli changing in magnitude of low-level features, we will determine their perception thresholds from the EEG data. Sensory precision will be estimated from both EEG and behavioral measurements of perception thresholds. In WP3, I will integrate the results of WP1 and WP2 together to suggest a refined theory of ASD and I will relate these findings to the symptoms of ASD. Altogether, I aim to contribute to a better understanding of the mechanisms underlying the heterogeneous symptomatology of ASD.