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The EEG multiverse of schizophrenia
Research on schizophrenia typically focuses on one paradigm for which clear-cut differences between patients and controls are established. Great efforts are made to understand the underlying genetical, neurophysiological, and cognitive mechanisms, which eventually may explain the clinical outcome. O...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10068296/ https://www.ncbi.nlm.nih.gov/pubmed/36030389 http://dx.doi.org/10.1093/cercor/bhac309 |
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author | Gordillo, Dario da Cruz, Janir Ramos Chkonia, Eka Lin, Wei-Hsiang Favrod, Ophélie Brand, Andreas Figueiredo, Patrícia Roinishvili, Maya Herzog, Michael H |
author_facet | Gordillo, Dario da Cruz, Janir Ramos Chkonia, Eka Lin, Wei-Hsiang Favrod, Ophélie Brand, Andreas Figueiredo, Patrícia Roinishvili, Maya Herzog, Michael H |
author_sort | Gordillo, Dario |
collection | PubMed |
description | Research on schizophrenia typically focuses on one paradigm for which clear-cut differences between patients and controls are established. Great efforts are made to understand the underlying genetical, neurophysiological, and cognitive mechanisms, which eventually may explain the clinical outcome. One tacit assumption of these “deep rooting” approaches is that paradigms tap into common and representative aspects of the disorder. Here, we analyzed the resting-state electroencephalogram (EEG) of 121 schizophrenia patients and 75 controls. Using multiple signal processing methods, we extracted 194 EEG features. Sixty-nine out of the 194 EEG features showed a significant difference between patients and controls, indicating that these features detect an important aspect of schizophrenia. Surprisingly, the correlations between these features were very low. We discuss several explanations to our results and propose that complementing “deep” with “shallow” rooting approaches might help in understanding the underlying mechanisms of the disorder. |
format | Online Article Text |
id | pubmed-10068296 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-100682962023-04-04 The EEG multiverse of schizophrenia Gordillo, Dario da Cruz, Janir Ramos Chkonia, Eka Lin, Wei-Hsiang Favrod, Ophélie Brand, Andreas Figueiredo, Patrícia Roinishvili, Maya Herzog, Michael H Cereb Cortex Original Article Research on schizophrenia typically focuses on one paradigm for which clear-cut differences between patients and controls are established. Great efforts are made to understand the underlying genetical, neurophysiological, and cognitive mechanisms, which eventually may explain the clinical outcome. One tacit assumption of these “deep rooting” approaches is that paradigms tap into common and representative aspects of the disorder. Here, we analyzed the resting-state electroencephalogram (EEG) of 121 schizophrenia patients and 75 controls. Using multiple signal processing methods, we extracted 194 EEG features. Sixty-nine out of the 194 EEG features showed a significant difference between patients and controls, indicating that these features detect an important aspect of schizophrenia. Surprisingly, the correlations between these features were very low. We discuss several explanations to our results and propose that complementing “deep” with “shallow” rooting approaches might help in understanding the underlying mechanisms of the disorder. Oxford University Press 2022-08-27 /pmc/articles/PMC10068296/ /pubmed/36030389 http://dx.doi.org/10.1093/cercor/bhac309 Text en © The Author(s) 2022. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com https://creativecommons.org/licenses/by-nc/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (https://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com |
spellingShingle | Original Article Gordillo, Dario da Cruz, Janir Ramos Chkonia, Eka Lin, Wei-Hsiang Favrod, Ophélie Brand, Andreas Figueiredo, Patrícia Roinishvili, Maya Herzog, Michael H The EEG multiverse of schizophrenia |
title | The EEG multiverse of schizophrenia |
title_full | The EEG multiverse of schizophrenia |
title_fullStr | The EEG multiverse of schizophrenia |
title_full_unstemmed | The EEG multiverse of schizophrenia |
title_short | The EEG multiverse of schizophrenia |
title_sort | eeg multiverse of schizophrenia |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10068296/ https://www.ncbi.nlm.nih.gov/pubmed/36030389 http://dx.doi.org/10.1093/cercor/bhac309 |
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