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DISCOVER-EEG: an open, fully automated EEG pipeline for biomarker discovery in clinical neuroscience
Biomarker discovery in neurological and psychiatric disorders critically depends on reproducible and transparent methods applied to large-scale datasets. Electroencephalography (EEG) is a promising tool for identifying biomarkers. However, recording, preprocessing, and analysis of EEG data is time-c...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Nature Publishing Group UK
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10495446/ https://www.ncbi.nlm.nih.gov/pubmed/37696851 http://dx.doi.org/10.1038/s41597-023-02525-0 |
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author | Gil Ávila, Cristina Bott, Felix S. Tiemann, Laura Hohn, Vanessa D. May, Elisabeth S. Nickel, Moritz M. Zebhauser, Paul Theo Gross, Joachim Ploner, Markus |
author_facet | Gil Ávila, Cristina Bott, Felix S. Tiemann, Laura Hohn, Vanessa D. May, Elisabeth S. Nickel, Moritz M. Zebhauser, Paul Theo Gross, Joachim Ploner, Markus |
author_sort | Gil Ávila, Cristina |
collection | PubMed |
description | Biomarker discovery in neurological and psychiatric disorders critically depends on reproducible and transparent methods applied to large-scale datasets. Electroencephalography (EEG) is a promising tool for identifying biomarkers. However, recording, preprocessing, and analysis of EEG data is time-consuming and researcher-dependent. Therefore, we developed DISCOVER-EEG, an open and fully automated pipeline that enables easy and fast preprocessing, analysis, and visualization of resting state EEG data. Data in the Brain Imaging Data Structure (BIDS) standard are automatically preprocessed, and physiologically meaningful features of brain function (including oscillatory power, connectivity, and network characteristics) are extracted and visualized using two open-source and widely used Matlab toolboxes (EEGLAB and FieldTrip). We tested the pipeline in two large, openly available datasets containing EEG recordings of healthy participants and patients with a psychiatric condition. Additionally, we performed an exploratory analysis that could inspire the development of biomarkers for healthy aging. Thus, the DISCOVER-EEG pipeline facilitates the aggregation, reuse, and analysis of large EEG datasets, promoting open and reproducible research on brain function. |
format | Online Article Text |
id | pubmed-10495446 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-104954462023-09-13 DISCOVER-EEG: an open, fully automated EEG pipeline for biomarker discovery in clinical neuroscience Gil Ávila, Cristina Bott, Felix S. Tiemann, Laura Hohn, Vanessa D. May, Elisabeth S. Nickel, Moritz M. Zebhauser, Paul Theo Gross, Joachim Ploner, Markus Sci Data Analysis Biomarker discovery in neurological and psychiatric disorders critically depends on reproducible and transparent methods applied to large-scale datasets. Electroencephalography (EEG) is a promising tool for identifying biomarkers. However, recording, preprocessing, and analysis of EEG data is time-consuming and researcher-dependent. Therefore, we developed DISCOVER-EEG, an open and fully automated pipeline that enables easy and fast preprocessing, analysis, and visualization of resting state EEG data. Data in the Brain Imaging Data Structure (BIDS) standard are automatically preprocessed, and physiologically meaningful features of brain function (including oscillatory power, connectivity, and network characteristics) are extracted and visualized using two open-source and widely used Matlab toolboxes (EEGLAB and FieldTrip). We tested the pipeline in two large, openly available datasets containing EEG recordings of healthy participants and patients with a psychiatric condition. Additionally, we performed an exploratory analysis that could inspire the development of biomarkers for healthy aging. Thus, the DISCOVER-EEG pipeline facilitates the aggregation, reuse, and analysis of large EEG datasets, promoting open and reproducible research on brain function. Nature Publishing Group UK 2023-09-11 /pmc/articles/PMC10495446/ /pubmed/37696851 http://dx.doi.org/10.1038/s41597-023-02525-0 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/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 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/) . |
spellingShingle | Analysis Gil Ávila, Cristina Bott, Felix S. Tiemann, Laura Hohn, Vanessa D. May, Elisabeth S. Nickel, Moritz M. Zebhauser, Paul Theo Gross, Joachim Ploner, Markus DISCOVER-EEG: an open, fully automated EEG pipeline for biomarker discovery in clinical neuroscience |
title | DISCOVER-EEG: an open, fully automated EEG pipeline for biomarker discovery in clinical neuroscience |
title_full | DISCOVER-EEG: an open, fully automated EEG pipeline for biomarker discovery in clinical neuroscience |
title_fullStr | DISCOVER-EEG: an open, fully automated EEG pipeline for biomarker discovery in clinical neuroscience |
title_full_unstemmed | DISCOVER-EEG: an open, fully automated EEG pipeline for biomarker discovery in clinical neuroscience |
title_short | DISCOVER-EEG: an open, fully automated EEG pipeline for biomarker discovery in clinical neuroscience |
title_sort | discover-eeg: an open, fully automated eeg pipeline for biomarker discovery in clinical neuroscience |
topic | Analysis |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10495446/ https://www.ncbi.nlm.nih.gov/pubmed/37696851 http://dx.doi.org/10.1038/s41597-023-02525-0 |
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