Testing predictive coding theories of autism spectrum disorder using models of active inference
dc.contributor.author | Arthur, T | |
dc.contributor.author | Vine, S | |
dc.contributor.author | Buckingham, G | |
dc.contributor.author | Brosnan, M | |
dc.contributor.author | Wilson, M | |
dc.contributor.author | Harris, D | |
dc.date.accessioned | 2023-10-12T11:18:49Z | |
dc.date.issued | 2023-09-11 | |
dc.date.updated | 2023-10-12T08:08:30Z | |
dc.description.abstract | Several competing neuro-computational theories of autism have emerged from predictive coding models of the brain. To disentangle their subtly different predictions about the nature of atypicalities in autistic perception, we performed computational modelling of two sensorimotor tasks: the predictive use of manual gripping forces during object lifting and anticipatory eye movements during a naturalistic interception task. In contrast to some accounts, we found no evidence of chronic atypicalities in the use of priors or weighting of sensory information during object lifting. Differences in prior beliefs, rates of belief updating, and the precision weighting of prediction errors were, however, observed for anticipatory eye movements. Most notably, we observed autism-related difficulties in flexibly adapting learning rates in response to environmental change (i.e., volatility). These findings suggest that atypical encoding of precision and context-sensitive adjustments provide a better explanation of autistic perception than generic attenuation of priors or persistently high precision prediction errors. Our results did not, however, support previous suggestions that autistic people perceive their environment to be persistently volatile. | en_GB |
dc.description.sponsorship | Economic and Social Research Council (ESRC) | en_GB |
dc.description.sponsorship | Leverhulme Trust | en_GB |
dc.format.extent | e1011473- | |
dc.format.medium | Electronic-eCollection | |
dc.identifier.citation | Vol. 19(9), article e1011473 | en_GB |
dc.identifier.doi | https://doi.org/10.1371/journal.pcbi.1011473 | |
dc.identifier.grantnumber | ES/P000630/1 | en_GB |
dc.identifier.uri | http://hdl.handle.net/10871/134225 | |
dc.identifier | ORCID: 0000-0003-3880-3856 (Harris, David) | |
dc.language.iso | en | en_GB |
dc.publisher | Public Library of Science (PLoS) | en_GB |
dc.relation.url | https://osf.io/5k48n/ | en_GB |
dc.relation.url | https://osf.io/6szf5 | en_GB |
dc.relation.url | https://osf.io/ewnh9/ | en_GB |
dc.relation.url | https://www.ncbi.nlm.nih.gov/pubmed/37695796 | en_GB |
dc.rights | © 2023 Arthur et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. | en_GB |
dc.title | Testing predictive coding theories of autism spectrum disorder using models of active inference | en_GB |
dc.type | Article | en_GB |
dc.date.available | 2023-10-12T11:18:49Z | |
dc.identifier.issn | 1553-734X | |
exeter.place-of-publication | United States | |
dc.description | This is the final version. Available on open access from Public Library of Science via the DOI in this record | en_GB |
dc.description | Data Availability: All relevant data and code is available online from: https://osf.io/5k48n/. Plotted curves are available at https://osf.io/r9gxf, Autism Spectrum Quotient questionnaire available at https://osf.io/6szf5; presentation sequences available at https://osf.io/ewnh9/. | en_GB |
dc.identifier.eissn | 1553-7358 | |
dc.identifier.journal | PLoS Computational Biology | en_GB |
dc.relation.ispartof | PLoS Comput Biol, 19(9) | |
dc.rights.uri | https://creativecommons.org/licenses/by/4.0/ | en_GB |
dcterms.dateAccepted | 2023-08-28 | |
dc.rights.license | CC BY | |
rioxxterms.version | VoR | en_GB |
rioxxterms.licenseref.startdate | 2023-09-11 | |
rioxxterms.type | Journal Article/Review | en_GB |
refterms.dateFCD | 2023-10-12T10:04:07Z | |
refterms.versionFCD | VoR | |
refterms.dateFOA | 2023-10-12T11:18:54Z | |
refterms.panel | A | en_GB |
refterms.dateFirstOnline | 2023-09-11 |
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Except where otherwise noted, this item's licence is described as © 2023 Arthur et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.