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No increased circular inference in adults with high levels of autistic traits or autism

Autism spectrum disorders have been proposed to arise from impairments in the probabilistic integration of prior knowledge with sensory inputs. Circular inference is one such possible impairment, in which excitation-to-inhibition imbalances in the cerebral cortex cause the reverberation and amplific...

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Autores principales: Angeletos Chrysaitis, Nikitas, Jardri, Renaud, Denève, Sophie, Seriès, Peggy
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8494311/
https://www.ncbi.nlm.nih.gov/pubmed/34559803
http://dx.doi.org/10.1371/journal.pcbi.1009006
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author Angeletos Chrysaitis, Nikitas
Jardri, Renaud
Denève, Sophie
Seriès, Peggy
author_facet Angeletos Chrysaitis, Nikitas
Jardri, Renaud
Denève, Sophie
Seriès, Peggy
author_sort Angeletos Chrysaitis, Nikitas
collection PubMed
description Autism spectrum disorders have been proposed to arise from impairments in the probabilistic integration of prior knowledge with sensory inputs. Circular inference is one such possible impairment, in which excitation-to-inhibition imbalances in the cerebral cortex cause the reverberation and amplification of prior beliefs and sensory information. Recent empirical work has associated circular inference with the clinical dimensions of schizophrenia. Inhibition impairments have also been observed in autism, suggesting that signal reverberation might be present in that condition as well. In this study, we collected data from 21 participants with self-reported diagnoses of autism spectrum disorders and 155 participants with a broad range of autistic traits in an online probabilistic decision-making task (the fisher task). We used previously established Bayesian models to investigate possible associations between autistic traits or autism and circular inference. There was no correlation between prior or likelihood reverberation and autistic traits across the whole sample. Similarly, no differences in any of the circular inference model parameters were found between autistic participants and those with no diagnosis. Furthermore, participants incorporated information from both priors and likelihoods in their decisions, with no relationship between their weights and psychiatric traits, contrary to what common theories for both autism and schizophrenia would suggest. These findings suggest that there is no increased signal reverberation in autism, despite the known presence of excitation-to-inhibition imbalances. They can be used to further contrast and refine the Bayesian theories of schizophrenia and autism, revealing a divergence in the computational mechanisms underlying the two conditions.
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spelling pubmed-84943112021-10-07 No increased circular inference in adults with high levels of autistic traits or autism Angeletos Chrysaitis, Nikitas Jardri, Renaud Denève, Sophie Seriès, Peggy PLoS Comput Biol Research Article Autism spectrum disorders have been proposed to arise from impairments in the probabilistic integration of prior knowledge with sensory inputs. Circular inference is one such possible impairment, in which excitation-to-inhibition imbalances in the cerebral cortex cause the reverberation and amplification of prior beliefs and sensory information. Recent empirical work has associated circular inference with the clinical dimensions of schizophrenia. Inhibition impairments have also been observed in autism, suggesting that signal reverberation might be present in that condition as well. In this study, we collected data from 21 participants with self-reported diagnoses of autism spectrum disorders and 155 participants with a broad range of autistic traits in an online probabilistic decision-making task (the fisher task). We used previously established Bayesian models to investigate possible associations between autistic traits or autism and circular inference. There was no correlation between prior or likelihood reverberation and autistic traits across the whole sample. Similarly, no differences in any of the circular inference model parameters were found between autistic participants and those with no diagnosis. Furthermore, participants incorporated information from both priors and likelihoods in their decisions, with no relationship between their weights and psychiatric traits, contrary to what common theories for both autism and schizophrenia would suggest. These findings suggest that there is no increased signal reverberation in autism, despite the known presence of excitation-to-inhibition imbalances. They can be used to further contrast and refine the Bayesian theories of schizophrenia and autism, revealing a divergence in the computational mechanisms underlying the two conditions. Public Library of Science 2021-09-24 /pmc/articles/PMC8494311/ /pubmed/34559803 http://dx.doi.org/10.1371/journal.pcbi.1009006 Text en © 2021 Angeletos Chrysaitis et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Angeletos Chrysaitis, Nikitas
Jardri, Renaud
Denève, Sophie
Seriès, Peggy
No increased circular inference in adults with high levels of autistic traits or autism
title No increased circular inference in adults with high levels of autistic traits or autism
title_full No increased circular inference in adults with high levels of autistic traits or autism
title_fullStr No increased circular inference in adults with high levels of autistic traits or autism
title_full_unstemmed No increased circular inference in adults with high levels of autistic traits or autism
title_short No increased circular inference in adults with high levels of autistic traits or autism
title_sort no increased circular inference in adults with high levels of autistic traits or autism
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8494311/
https://www.ncbi.nlm.nih.gov/pubmed/34559803
http://dx.doi.org/10.1371/journal.pcbi.1009006
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