Perceptual inference and learning in autism : a behavioral and neurophysiological approach

Abstract : How we perceive our environment relies both on sensory information and on our priors or expectations. Within the Baysian framework, these priors capture the underlying statistical regularities of our environment and allow inferring sensation causes. Recently, Bayesian brain theories suggested that autistic symptoms could arise from an atypical weighting of sensory information and priors. Autism spectrum disorders (ASD) is characterized defined by difficulties in social interactions, by restricted and repetitive patterns of behaviors, and by an atypical sensory perception.This thesis aims at characterizing perceptual inference and learning in ASD, and studies sensory sensitivity and prior learning. This was investigated using behavioral tasks, computational models, questionnaires, functional magnetic resonance imaging and magnetic resonance spectroscopy in adults with or without ASD. Sensory profiles in people with high autism spectrum quotients were first refined, using a questionnaire that we validated in French. The study of perceptual learning strategies then revealed that subjects with ASD were less inclined to spontaneously use a learning style enabling generalization. The implicit learning of priors was explored and showed that subjects with ASD were able to build up a prior but had difficulties adjusting it in changing contexts. Finally, the investigation of the neurophysiological correlates and molecular underpinnings of a similar task showed that perceptual decisions biased by priors relied on a distinct neural network in ASD, and was not related to the same modulation by the glutamate/GABA ratio.The overall results shed light on an atypical learning and weighting of priors in ASD, resulting in an abnormal perceptual inference. A Bayesian approach could help characterizing ASD and could contribute to ASD diagnosis and care
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Laurie-Anne Sapey-Triomphe. Perceptual inference and learning in autism : a behavioral and neurophysiological approach. Neuroscience. Université de Lyon, 2017. English. ⟨NNT : 2017LYSE1130⟩. ⟨tel-01613617⟩

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