In the first work package focused on priors, we conducted two behavioral studies and one neuroimaging experiment. First, we developed and tested two visual tasks to better understand how autistic individuals learn and adjust priors (both implicitly and explicitly). These studies showed that autistic individuals could learn priors, but had difficulties to adjust them according to the context. We also found that autistic participants were biased by their priors, contrary to the hypothesis suggesting hypo-priors in ASD. These behavioral experiments enabled us to develop a neuroimaging experiment where we used functional Magnetic Resonance Imaging (fMRI) to characterize the brain regions that were activated when signaling priors or prediction errors (i.e. mismatch between priors and sensory inputs). We were able to precisely identify these regions in an analysis relying on computational models. We observed a few group differences in some regions that were involved in signaling priors and prediction errors, which might explain why autistic individuals could have enhanced sensations of surprise. We also used another non-invasive neuroimaging method, called Magnetic Resonance Spectroscopy (MRS), to measure the concentrations of two neurotransmitters in a brain region that encodes priors. We observed that individuals who had a higher ratio in the neurotransmitters of interest had more difficulties to make predictions. As the autistic group had an excess of one of these neurotransmitters in this region, it might contribute to their difficulties to learn predictions in certain contexts. In total, these three experiments included 163 participants with or without ASD.
In a second work package focused on sensory precision, we conducted experiments assessing visual sensitivity and responsiveness at the self-reported, behavioral and neural levels. Participants were 49 adults with and without ASD. As expected, at the self-reported level, questionnaires indicated more atypical sensory sensitivity, more hypersensitivity and responsiveness in ASD. At the behavioral level, autistic participants were more sensitive and responsive to certain simple visual stimuli than controls. At the neural level, we acquired data using electroencephalography (EEG), combined with a method to implicitly determine the threshold from which the brain starts responding to a visual stimulus. The analysis of the EEG is not finished yet, but should contribute to better understand the neural mechanisms related to the hypersensitivity encountered in ASD.
Finally, in a last work package focused on the integration of the results mentioned above with the symptoms of ASD, we investigated whether atypical predictive processes could be related to the high intolerance of uncertainty experience by autistic individuals, and how it was related to the symptoms of ASD. Among other results, individuals who were not much influenced by priors reported a more atypical sensory sensitivity. Unexpectedly, the ability to learn predictions was not related to the self-reported intolerance of uncertainty. Using online questionnaires involving 426 adults with and without ASD, we also explored how intolerance of uncertainty was related to autistic traits, social difficulties, repetitive behaviors, sensory sensitivity, anxiety and sleep problems. All these results will be integrated together to suggest a refined predictive coding theory of ASD.
These results have been exploited and disseminated as scientific articles in peer-reviewed journals (3 articles are already published and 3 are in preparation), oral presentations as invited speaker (7) and poster presentations in international conferences (3).
