Bridging physiological and perceptual views of autism by means of sampling-based Bayesian inference
AbstractTheories for autism spectrum disorder (ASD) have been formulated at different levels, ranging from physiological observations to perceptual and behavioral descriptions. Understanding the physiological underpinnings of perceptual traits in ASD remains a significant challenge i...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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The MIT Press
2022-01-01
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| Series: | Network Neuroscience |
| Online Access: | https://direct.mit.edu/netn/article/doi/10.1162/netn_a_00219/108677/Bridging-physiological-and-perceptual-views-of |
| _version_ | 1818286630090309632 |
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| author | Rodrigo Echeveste Enzo Ferrante Diego H. Milone Inés Samengo |
| author_facet | Rodrigo Echeveste Enzo Ferrante Diego H. Milone Inés Samengo |
| author_sort | Rodrigo Echeveste |
| collection | DOAJ |
| description |
AbstractTheories for autism spectrum disorder (ASD) have been formulated at different levels, ranging from physiological observations to perceptual and behavioral descriptions. Understanding the physiological underpinnings of perceptual traits in ASD remains a significant challenge in the field. Here we show how a recurrent neural circuit model that was optimized to perform sampling-based inference and displays characteristic features of cortical dynamics can help bridge this gap. The model was able to establish a mechanistic link between two descriptive levels for ASD: a physiological level, in terms of inhibitory dysfunction, neural variability, and oscillations, and a perceptual level, in terms of hypopriors in Bayesian computations. We took two parallel paths—inducing hypopriors in the probabilistic model, and an inhibitory dysfunction in the network model—which lead to consistent results in terms of the represented posteriors, providing support for the view that both descriptions might constitute two sides of the same coin. |
| first_indexed | 2024-12-13T01:27:38Z |
| format | Article |
| id | doaj.art-b7550fd42deb490084452a955f8069f3 |
| institution | Directory Open Access Journal |
| issn | 2472-1751 |
| language | English |
| last_indexed | 2024-12-13T01:27:38Z |
| publishDate | 2022-01-01 |
| publisher | The MIT Press |
| record_format | Article |
| series | Network Neuroscience |
| spelling | doaj.art-b7550fd42deb490084452a955f8069f32022-12-22T00:04:05ZengThe MIT PressNetwork Neuroscience2472-17512022-01-0111710.1162/netn_a_00219Bridging physiological and perceptual views of autism by means of sampling-based Bayesian inferenceRodrigo Echeveste0http://orcid.org/0000-0002-6155-8679Enzo Ferrante1http://orcid.org/0000-0002-8500-788XDiego H. Milone2http://orcid.org/0000-0003-2182-4351Inés Samengo3http://orcid.org/0000-0002-5241-3697Research Institute for Signals, Systems, and Computational Intelligence sinc(i) (FICH-UNL/CONICET), Santa Fe, ArgentinaResearch Institute for Signals, Systems, and Computational Intelligence sinc(i) (FICH-UNL/CONICET), Santa Fe, ArgentinaResearch Institute for Signals, Systems, and Computational Intelligence sinc(i) (FICH-UNL/CONICET), Santa Fe, ArgentinaMedical Physics Department and Balseiro Institute (CNEA-UNCUYO/CONICET), Bariloche, Argentina AbstractTheories for autism spectrum disorder (ASD) have been formulated at different levels, ranging from physiological observations to perceptual and behavioral descriptions. Understanding the physiological underpinnings of perceptual traits in ASD remains a significant challenge in the field. Here we show how a recurrent neural circuit model that was optimized to perform sampling-based inference and displays characteristic features of cortical dynamics can help bridge this gap. The model was able to establish a mechanistic link between two descriptive levels for ASD: a physiological level, in terms of inhibitory dysfunction, neural variability, and oscillations, and a perceptual level, in terms of hypopriors in Bayesian computations. We took two parallel paths—inducing hypopriors in the probabilistic model, and an inhibitory dysfunction in the network model—which lead to consistent results in terms of the represented posteriors, providing support for the view that both descriptions might constitute two sides of the same coin.https://direct.mit.edu/netn/article/doi/10.1162/netn_a_00219/108677/Bridging-physiological-and-perceptual-views-of |
| spellingShingle | Rodrigo Echeveste Enzo Ferrante Diego H. Milone Inés Samengo Bridging physiological and perceptual views of autism by means of sampling-based Bayesian inference Network Neuroscience |
| title | Bridging physiological and perceptual views of autism by means of sampling-based Bayesian inference |
| title_full | Bridging physiological and perceptual views of autism by means of sampling-based Bayesian inference |
| title_fullStr | Bridging physiological and perceptual views of autism by means of sampling-based Bayesian inference |
| title_full_unstemmed | Bridging physiological and perceptual views of autism by means of sampling-based Bayesian inference |
| title_short | Bridging physiological and perceptual views of autism by means of sampling-based Bayesian inference |
| title_sort | bridging physiological and perceptual views of autism by means of sampling based bayesian inference |
| url | https://direct.mit.edu/netn/article/doi/10.1162/netn_a_00219/108677/Bridging-physiological-and-perceptual-views-of |
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