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Prediction learning in adults with autism and its molecular correlates
BACKGROUND: According to Bayesian hypotheses, individuals with Autism Spectrum Disorder (ASD) have difficulties making accurate predictions about their environment. In particular, the mechanisms by which they assign precision to predictions or sensory inputs would be suboptimal in ASD. These mechani...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8493731/ https://www.ncbi.nlm.nih.gov/pubmed/34615532 http://dx.doi.org/10.1186/s13229-021-00470-6 |
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author | Sapey-Triomphe, Laurie-Anne Temmerman, Joke Puts, Nicolaas A. J. Wagemans, Johan |
author_facet | Sapey-Triomphe, Laurie-Anne Temmerman, Joke Puts, Nicolaas A. J. Wagemans, Johan |
author_sort | Sapey-Triomphe, Laurie-Anne |
collection | PubMed |
description | BACKGROUND: According to Bayesian hypotheses, individuals with Autism Spectrum Disorder (ASD) have difficulties making accurate predictions about their environment. In particular, the mechanisms by which they assign precision to predictions or sensory inputs would be suboptimal in ASD. These mechanisms are thought to be mostly mediated by glutamate and GABA. Here, we aimed to shed light on prediction learning in ASD and on its neurobiological correlates. METHODS: Twenty-six neurotypical and 26 autistic adults participated in an associative learning task where they had to learn a probabilistic association between a tone and the rotation direction of two dots, in a volatile context. They also took part in magnetic resonance spectroscopy (MRS) measurements to quantify Glx (glutamate and glutamine), GABA + and glutathione in a low-level perceptual region (occipital cortex) and in a higher-level region involved in prediction learning (inferior frontal gyrus). RESULTS: Neurotypical and autistic adults had their percepts biased by their expectations, and this bias was smaller for individuals with a more atypical sensory sensitivity. Both groups were able to learn the association and to update their beliefs after a change in contingency. Interestingly, the percentage of correct predictions was correlated with the Glx/GABA + ratio in the occipital cortex (positive correlation) and in the right inferior frontal gyrus (negative correlation). In this region, MRS results also showed an increased concentration of Glx in the ASD group compared to the neurotypical group. LIMITATIONS: We used a quite restrictive approach to select the MR spectra showing a good fit, which led to the exclusion of some MRS datasets and therefore to the reduction of the sample size for certain metabolites/regions. CONCLUSIONS: Autistic adults appeared to have intact abilities to make predictions in this task, in contrast with the Bayesian hypotheses of ASD. Yet, higher ratios of Glx/GABA + in a frontal region were associated with decreased predictive abilities, and ASD individuals tended to have more Glx in this region. This neurobiological difference might contribute to suboptimal predictive mechanisms in ASD in certain contexts. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13229-021-00470-6. |
format | Online Article Text |
id | pubmed-8493731 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-84937312021-10-06 Prediction learning in adults with autism and its molecular correlates Sapey-Triomphe, Laurie-Anne Temmerman, Joke Puts, Nicolaas A. J. Wagemans, Johan Mol Autism Research BACKGROUND: According to Bayesian hypotheses, individuals with Autism Spectrum Disorder (ASD) have difficulties making accurate predictions about their environment. In particular, the mechanisms by which they assign precision to predictions or sensory inputs would be suboptimal in ASD. These mechanisms are thought to be mostly mediated by glutamate and GABA. Here, we aimed to shed light on prediction learning in ASD and on its neurobiological correlates. METHODS: Twenty-six neurotypical and 26 autistic adults participated in an associative learning task where they had to learn a probabilistic association between a tone and the rotation direction of two dots, in a volatile context. They also took part in magnetic resonance spectroscopy (MRS) measurements to quantify Glx (glutamate and glutamine), GABA + and glutathione in a low-level perceptual region (occipital cortex) and in a higher-level region involved in prediction learning (inferior frontal gyrus). RESULTS: Neurotypical and autistic adults had their percepts biased by their expectations, and this bias was smaller for individuals with a more atypical sensory sensitivity. Both groups were able to learn the association and to update their beliefs after a change in contingency. Interestingly, the percentage of correct predictions was correlated with the Glx/GABA + ratio in the occipital cortex (positive correlation) and in the right inferior frontal gyrus (negative correlation). In this region, MRS results also showed an increased concentration of Glx in the ASD group compared to the neurotypical group. LIMITATIONS: We used a quite restrictive approach to select the MR spectra showing a good fit, which led to the exclusion of some MRS datasets and therefore to the reduction of the sample size for certain metabolites/regions. CONCLUSIONS: Autistic adults appeared to have intact abilities to make predictions in this task, in contrast with the Bayesian hypotheses of ASD. Yet, higher ratios of Glx/GABA + in a frontal region were associated with decreased predictive abilities, and ASD individuals tended to have more Glx in this region. This neurobiological difference might contribute to suboptimal predictive mechanisms in ASD in certain contexts. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13229-021-00470-6. BioMed Central 2021-10-06 /pmc/articles/PMC8493731/ /pubmed/34615532 http://dx.doi.org/10.1186/s13229-021-00470-6 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Sapey-Triomphe, Laurie-Anne Temmerman, Joke Puts, Nicolaas A. J. Wagemans, Johan Prediction learning in adults with autism and its molecular correlates |
title | Prediction learning in adults with autism and its molecular correlates |
title_full | Prediction learning in adults with autism and its molecular correlates |
title_fullStr | Prediction learning in adults with autism and its molecular correlates |
title_full_unstemmed | Prediction learning in adults with autism and its molecular correlates |
title_short | Prediction learning in adults with autism and its molecular correlates |
title_sort | prediction learning in adults with autism and its molecular correlates |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8493731/ https://www.ncbi.nlm.nih.gov/pubmed/34615532 http://dx.doi.org/10.1186/s13229-021-00470-6 |
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