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Auditory repetition suppression alterations in relation to cognitive functioning in fragile X syndrome: a combined EEG and machine learning approach
BACKGROUND: Fragile X syndrome (FXS) is a neurodevelopmental genetic disorder causing cognitive and behavioural deficits. Repetition suppression (RS), a learning phenomenon in which stimulus repetitions result in diminished brain activity, has been found to be impaired in FXS. Alterations in RS have...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5789548/ https://www.ncbi.nlm.nih.gov/pubmed/29378522 http://dx.doi.org/10.1186/s11689-018-9223-3 |
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author | Knoth, Inga Sophia Lajnef, Tarek Rigoulot, Simon Lacourse, Karine Vannasing, Phetsamone Michaud, Jacques L. Jacquemont, Sébastien Major, Philippe Jerbi, Karim Lippé, Sarah |
author_facet | Knoth, Inga Sophia Lajnef, Tarek Rigoulot, Simon Lacourse, Karine Vannasing, Phetsamone Michaud, Jacques L. Jacquemont, Sébastien Major, Philippe Jerbi, Karim Lippé, Sarah |
author_sort | Knoth, Inga Sophia |
collection | PubMed |
description | BACKGROUND: Fragile X syndrome (FXS) is a neurodevelopmental genetic disorder causing cognitive and behavioural deficits. Repetition suppression (RS), a learning phenomenon in which stimulus repetitions result in diminished brain activity, has been found to be impaired in FXS. Alterations in RS have been associated with behavioural problems in FXS; however, relations between RS and intellectual functioning have not yet been elucidated. METHODS: EEG was recorded in 14 FXS participants and 25 neurotypical controls during an auditory habituation paradigm using repeatedly presented pseudowords. Non-phased locked signal energy was compared across presentations and between groups using linear mixed models (LMMs) in order to investigate RS effects across repetitions and brain areas and a possible relation to non-verbal IQ (NVIQ) in FXS. In addition, we explored group differences according to NVIQ and we probed the feasibility of training a support vector machine to predict cognitive functioning levels across FXS participants based on single-trial RS features. RESULTS: LMM analyses showed that repetition effects differ between groups (FXS vs. controls) as well as with respect to NVIQ in FXS. When exploring group differences in RS patterns, we found that neurotypical controls revealed the expected pattern of RS between the first and second presentations of a pseudoword. More importantly, while FXS participants in the ≤ 42 NVIQ group showed no RS, the > 42 NVIQ group showed a delayed RS response after several presentations. Concordantly, single-trial estimates of repetition effects over the first four repetitions provided the highest decoding accuracies in the classification between the FXS participant groups. CONCLUSION: Electrophysiological measures of repetition effects provide a non-invasive and unbiased measure of brain responses sensitive to cognitive functioning levels, which may be useful for clinical trials in FXS. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s11689-018-9223-3) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-5789548 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-57895482018-02-08 Auditory repetition suppression alterations in relation to cognitive functioning in fragile X syndrome: a combined EEG and machine learning approach Knoth, Inga Sophia Lajnef, Tarek Rigoulot, Simon Lacourse, Karine Vannasing, Phetsamone Michaud, Jacques L. Jacquemont, Sébastien Major, Philippe Jerbi, Karim Lippé, Sarah J Neurodev Disord Research BACKGROUND: Fragile X syndrome (FXS) is a neurodevelopmental genetic disorder causing cognitive and behavioural deficits. Repetition suppression (RS), a learning phenomenon in which stimulus repetitions result in diminished brain activity, has been found to be impaired in FXS. Alterations in RS have been associated with behavioural problems in FXS; however, relations between RS and intellectual functioning have not yet been elucidated. METHODS: EEG was recorded in 14 FXS participants and 25 neurotypical controls during an auditory habituation paradigm using repeatedly presented pseudowords. Non-phased locked signal energy was compared across presentations and between groups using linear mixed models (LMMs) in order to investigate RS effects across repetitions and brain areas and a possible relation to non-verbal IQ (NVIQ) in FXS. In addition, we explored group differences according to NVIQ and we probed the feasibility of training a support vector machine to predict cognitive functioning levels across FXS participants based on single-trial RS features. RESULTS: LMM analyses showed that repetition effects differ between groups (FXS vs. controls) as well as with respect to NVIQ in FXS. When exploring group differences in RS patterns, we found that neurotypical controls revealed the expected pattern of RS between the first and second presentations of a pseudoword. More importantly, while FXS participants in the ≤ 42 NVIQ group showed no RS, the > 42 NVIQ group showed a delayed RS response after several presentations. Concordantly, single-trial estimates of repetition effects over the first four repetitions provided the highest decoding accuracies in the classification between the FXS participant groups. CONCLUSION: Electrophysiological measures of repetition effects provide a non-invasive and unbiased measure of brain responses sensitive to cognitive functioning levels, which may be useful for clinical trials in FXS. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s11689-018-9223-3) contains supplementary material, which is available to authorized users. BioMed Central 2018-01-29 /pmc/articles/PMC5789548/ /pubmed/29378522 http://dx.doi.org/10.1186/s11689-018-9223-3 Text en © The Author(s). 2018 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided 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 Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Research Knoth, Inga Sophia Lajnef, Tarek Rigoulot, Simon Lacourse, Karine Vannasing, Phetsamone Michaud, Jacques L. Jacquemont, Sébastien Major, Philippe Jerbi, Karim Lippé, Sarah Auditory repetition suppression alterations in relation to cognitive functioning in fragile X syndrome: a combined EEG and machine learning approach |
title | Auditory repetition suppression alterations in relation to cognitive functioning in fragile X syndrome: a combined EEG and machine learning approach |
title_full | Auditory repetition suppression alterations in relation to cognitive functioning in fragile X syndrome: a combined EEG and machine learning approach |
title_fullStr | Auditory repetition suppression alterations in relation to cognitive functioning in fragile X syndrome: a combined EEG and machine learning approach |
title_full_unstemmed | Auditory repetition suppression alterations in relation to cognitive functioning in fragile X syndrome: a combined EEG and machine learning approach |
title_short | Auditory repetition suppression alterations in relation to cognitive functioning in fragile X syndrome: a combined EEG and machine learning approach |
title_sort | auditory repetition suppression alterations in relation to cognitive functioning in fragile x syndrome: a combined eeg and machine learning approach |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5789548/ https://www.ncbi.nlm.nih.gov/pubmed/29378522 http://dx.doi.org/10.1186/s11689-018-9223-3 |
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