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Unconstrained multivariate EEG decoding can help detect lexical-semantic processing in individual children
In conditions such as minimally-verbal autism, standard assessments of language comprehension are often unreliable. Given the known heterogeneity within the autistic population, it is crucial to design tests of semantic comprehension that are sensitive in individuals. Recent efforts to develop neura...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7331680/ https://www.ncbi.nlm.nih.gov/pubmed/32616736 http://dx.doi.org/10.1038/s41598-020-67407-6 |
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author | Petit, Selene Badcock, Nicholas A. Grootswagers, Tijl Woolgar, Alexandra |
author_facet | Petit, Selene Badcock, Nicholas A. Grootswagers, Tijl Woolgar, Alexandra |
author_sort | Petit, Selene |
collection | PubMed |
description | In conditions such as minimally-verbal autism, standard assessments of language comprehension are often unreliable. Given the known heterogeneity within the autistic population, it is crucial to design tests of semantic comprehension that are sensitive in individuals. Recent efforts to develop neural signals of language comprehension have focused on the N400, a robust marker of lexical-semantic violation at the group level. However, homogeneity of response in individual neurotypical children has not been established. Here, we presented 20 neurotypical children with congruent and incongruent visual animations and spoken sentences while measuring their neural response using electroencephalography (EEG). Despite robust group-level responses, we found high inter-individual variability in response to lexico-semantic anomalies. To overcome this, we analysed our data using temporally and spatially unconstrained multivariate pattern analyses (MVPA), supplemented by descriptive analyses to examine the timecourse, topography, and strength of the effect. Our results show that neurotypical children exhibit heterogenous responses to lexical-semantic violation, implying that any application to heterogenous disorders such as autism spectrum disorder will require individual-subject analyses that are robust to variation in topology and timecourse of neural responses. |
format | Online Article Text |
id | pubmed-7331680 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-73316802020-07-06 Unconstrained multivariate EEG decoding can help detect lexical-semantic processing in individual children Petit, Selene Badcock, Nicholas A. Grootswagers, Tijl Woolgar, Alexandra Sci Rep Article In conditions such as minimally-verbal autism, standard assessments of language comprehension are often unreliable. Given the known heterogeneity within the autistic population, it is crucial to design tests of semantic comprehension that are sensitive in individuals. Recent efforts to develop neural signals of language comprehension have focused on the N400, a robust marker of lexical-semantic violation at the group level. However, homogeneity of response in individual neurotypical children has not been established. Here, we presented 20 neurotypical children with congruent and incongruent visual animations and spoken sentences while measuring their neural response using electroencephalography (EEG). Despite robust group-level responses, we found high inter-individual variability in response to lexico-semantic anomalies. To overcome this, we analysed our data using temporally and spatially unconstrained multivariate pattern analyses (MVPA), supplemented by descriptive analyses to examine the timecourse, topography, and strength of the effect. Our results show that neurotypical children exhibit heterogenous responses to lexical-semantic violation, implying that any application to heterogenous disorders such as autism spectrum disorder will require individual-subject analyses that are robust to variation in topology and timecourse of neural responses. Nature Publishing Group UK 2020-07-02 /pmc/articles/PMC7331680/ /pubmed/32616736 http://dx.doi.org/10.1038/s41598-020-67407-6 Text en © The Author(s) 2020 Open Access This 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 license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license 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 license, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Petit, Selene Badcock, Nicholas A. Grootswagers, Tijl Woolgar, Alexandra Unconstrained multivariate EEG decoding can help detect lexical-semantic processing in individual children |
title | Unconstrained multivariate EEG decoding can help detect lexical-semantic processing in individual children |
title_full | Unconstrained multivariate EEG decoding can help detect lexical-semantic processing in individual children |
title_fullStr | Unconstrained multivariate EEG decoding can help detect lexical-semantic processing in individual children |
title_full_unstemmed | Unconstrained multivariate EEG decoding can help detect lexical-semantic processing in individual children |
title_short | Unconstrained multivariate EEG decoding can help detect lexical-semantic processing in individual children |
title_sort | unconstrained multivariate eeg decoding can help detect lexical-semantic processing in individual children |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7331680/ https://www.ncbi.nlm.nih.gov/pubmed/32616736 http://dx.doi.org/10.1038/s41598-020-67407-6 |
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