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Bridging physiological and perceptual views of autism by means of\n sampling-based Bayesian inference

2021/06/08 by Rodrigo Echeveste, Enzo Ferrante, Echeveste, Rodrigo +5
Neuroscience · #Functional Brain Connectivity Studies #Neural dynamics and brain function #Autism Spectrum Disorder Research

paper · pdf · doi:10.48550/arxiv.2106.04366

Abstract

Theories for autism spectrum disorder (ASD) have been formulated at different\nlevels: ranging from physiological observations to perceptual and behavioral\ndescriptions. Understanding the physiological underpinnings of perceptual\ntraits in ASD remains a significant challenge in the field. Here we show how a\nrecurrent neural circuit model which was optimized to perform sampling-based\ninference and displays characteristic features of cortical dynamics can help\nbridge this gap. The model was able to establish a mechanistic link between two\ndescriptive levels for ASD: a physiological level, in terms of inhibitory\ndysfunction, neural variability and oscillations, and a perceptual level, in\nterms of hypopriors in Bayesian computations. We took two parallel paths:\ninducing hypopriors in the probabilistic model, and an inhibitory dysfunction\nin the network model, which lead to consistent results in terms of the\nrepresented posteriors, providing support for the view that both descriptions\nmight constitute two sides of the same coin.\n

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