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Social behavioural adaptation in Autism
Autism is still diagnosed on the basis of subjective assessments of elusive notions such as interpersonal contact and social reciprocity. We propose to decompose reciprocal social interactions in their basic computational constituents. Specifically, we test the assumption that autistic individuals d...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7108744/ https://www.ncbi.nlm.nih.gov/pubmed/32176684 http://dx.doi.org/10.1371/journal.pcbi.1007700 |
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author | Forgeot d'Arc, Baudouin Devaine, Marie Daunizeau, Jean |
author_facet | Forgeot d'Arc, Baudouin Devaine, Marie Daunizeau, Jean |
author_sort | Forgeot d'Arc, Baudouin |
collection | PubMed |
description | Autism is still diagnosed on the basis of subjective assessments of elusive notions such as interpersonal contact and social reciprocity. We propose to decompose reciprocal social interactions in their basic computational constituents. Specifically, we test the assumption that autistic individuals disregard information regarding the stakes of social interactions when adapting to others. We compared 24 adult autistic participants to 24 neurotypical (NT) participants engaging in a repeated dyadic competitive game against artificial agents with calibrated reciprocal adaptation capabilities. Critically, participants were framed to believe either that they were competing against somebody else or that they were playing a gambling game. Only the NT participants did alter their adaptation strategy when they held information regarding others' competitive incentives, in which case they outperformed the AS group. Computational analyses of trial-by-trial choice sequences show that the behavioural repertoire of autistic people exhibits subnormal flexibility and mentalizing sophistication, especially when information regarding opponents’ incentives was available. These two computational phenotypes yield 79% diagnosis classification accuracy and explain 62% of the severity of social symptoms in autistic participants. Such computational decomposition of the autistic social phenotype may prove relevant for drawing novel diagnostic boundaries and guiding individualized clinical interventions in autism. |
format | Online Article Text |
id | pubmed-7108744 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-71087442020-04-03 Social behavioural adaptation in Autism Forgeot d'Arc, Baudouin Devaine, Marie Daunizeau, Jean PLoS Comput Biol Research Article Autism is still diagnosed on the basis of subjective assessments of elusive notions such as interpersonal contact and social reciprocity. We propose to decompose reciprocal social interactions in their basic computational constituents. Specifically, we test the assumption that autistic individuals disregard information regarding the stakes of social interactions when adapting to others. We compared 24 adult autistic participants to 24 neurotypical (NT) participants engaging in a repeated dyadic competitive game against artificial agents with calibrated reciprocal adaptation capabilities. Critically, participants were framed to believe either that they were competing against somebody else or that they were playing a gambling game. Only the NT participants did alter their adaptation strategy when they held information regarding others' competitive incentives, in which case they outperformed the AS group. Computational analyses of trial-by-trial choice sequences show that the behavioural repertoire of autistic people exhibits subnormal flexibility and mentalizing sophistication, especially when information regarding opponents’ incentives was available. These two computational phenotypes yield 79% diagnosis classification accuracy and explain 62% of the severity of social symptoms in autistic participants. Such computational decomposition of the autistic social phenotype may prove relevant for drawing novel diagnostic boundaries and guiding individualized clinical interventions in autism. Public Library of Science 2020-03-16 /pmc/articles/PMC7108744/ /pubmed/32176684 http://dx.doi.org/10.1371/journal.pcbi.1007700 Text en © 2020 Forgeot d'Arc et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://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 Forgeot d'Arc, Baudouin Devaine, Marie Daunizeau, Jean Social behavioural adaptation in Autism |
title | Social behavioural adaptation in Autism |
title_full | Social behavioural adaptation in Autism |
title_fullStr | Social behavioural adaptation in Autism |
title_full_unstemmed | Social behavioural adaptation in Autism |
title_short | Social behavioural adaptation in Autism |
title_sort | social behavioural adaptation in autism |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7108744/ https://www.ncbi.nlm.nih.gov/pubmed/32176684 http://dx.doi.org/10.1371/journal.pcbi.1007700 |
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