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Harmonized multi‐metric and multi‐centric assessment of EEG source space connectivity for dementia characterization
INTRODUCTION: Harmonization protocols that address batch effects and cross‐site methodological differences in multi‐center studies are critical for strengthening electroencephalography (EEG) signatures of functional connectivity (FC) as potential dementia biomarkers. METHODS: We implemented an autom...
Autores principales: | , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10329259/ https://www.ncbi.nlm.nih.gov/pubmed/37424962 http://dx.doi.org/10.1002/dad2.12455 |
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author | Prado, Pavel Mejía, Jhony A. Sainz‐Ballesteros, Agustín Birba, Agustina Moguilner, Sebastian Herzog, Rubén Otero, Mónica Cuadros, Jhosmary Z‐Rivera, Lucía O'Byrne, Daniel Franco Parra, Mario Ibáñez, Agustín |
author_facet | Prado, Pavel Mejía, Jhony A. Sainz‐Ballesteros, Agustín Birba, Agustina Moguilner, Sebastian Herzog, Rubén Otero, Mónica Cuadros, Jhosmary Z‐Rivera, Lucía O'Byrne, Daniel Franco Parra, Mario Ibáñez, Agustín |
author_sort | Prado, Pavel |
collection | PubMed |
description | INTRODUCTION: Harmonization protocols that address batch effects and cross‐site methodological differences in multi‐center studies are critical for strengthening electroencephalography (EEG) signatures of functional connectivity (FC) as potential dementia biomarkers. METHODS: We implemented an automatic processing pipeline incorporating electrode layout integrations, patient–control normalizations, and multi‐metric EEG source space connectomics analyses. RESULTS: Spline interpolations of EEG signals onto a head mesh model with 6067 virtual electrodes resulted in an effective method for integrating electrode layouts. Z‐score transformations of EEG time series resulted in source space connectivity matrices with high bilateral symmetry, reinforced long‐range connections, and diminished short‐range functional interactions. A composite FC metric allowed for accurate multicentric classifications of Alzheimer's disease and behavioral variant frontotemporal dementia. DISCUSSION: Harmonized multi‐metric analysis of EEG source space connectivity can address data heterogeneities in multi‐centric studies, representing a powerful tool for accurately characterizing dementia. |
format | Online Article Text |
id | pubmed-10329259 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | John Wiley and Sons Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-103292592023-07-09 Harmonized multi‐metric and multi‐centric assessment of EEG source space connectivity for dementia characterization Prado, Pavel Mejía, Jhony A. Sainz‐Ballesteros, Agustín Birba, Agustina Moguilner, Sebastian Herzog, Rubén Otero, Mónica Cuadros, Jhosmary Z‐Rivera, Lucía O'Byrne, Daniel Franco Parra, Mario Ibáñez, Agustín Alzheimers Dement (Amst) Research Articles INTRODUCTION: Harmonization protocols that address batch effects and cross‐site methodological differences in multi‐center studies are critical for strengthening electroencephalography (EEG) signatures of functional connectivity (FC) as potential dementia biomarkers. METHODS: We implemented an automatic processing pipeline incorporating electrode layout integrations, patient–control normalizations, and multi‐metric EEG source space connectomics analyses. RESULTS: Spline interpolations of EEG signals onto a head mesh model with 6067 virtual electrodes resulted in an effective method for integrating electrode layouts. Z‐score transformations of EEG time series resulted in source space connectivity matrices with high bilateral symmetry, reinforced long‐range connections, and diminished short‐range functional interactions. A composite FC metric allowed for accurate multicentric classifications of Alzheimer's disease and behavioral variant frontotemporal dementia. DISCUSSION: Harmonized multi‐metric analysis of EEG source space connectivity can address data heterogeneities in multi‐centric studies, representing a powerful tool for accurately characterizing dementia. John Wiley and Sons Inc. 2023-07-08 /pmc/articles/PMC10329259/ /pubmed/37424962 http://dx.doi.org/10.1002/dad2.12455 Text en © 2023 The Authors. Alzheimer's & Dementia: Diagnosis, Assessment & Disease Monitoring published by Wiley Periodicals, LLC on behalf of Alzheimer's Association. https://creativecommons.org/licenses/by-nc/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc/4.0/ (https://creativecommons.org/licenses/by-nc/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes. |
spellingShingle | Research Articles Prado, Pavel Mejía, Jhony A. Sainz‐Ballesteros, Agustín Birba, Agustina Moguilner, Sebastian Herzog, Rubén Otero, Mónica Cuadros, Jhosmary Z‐Rivera, Lucía O'Byrne, Daniel Franco Parra, Mario Ibáñez, Agustín Harmonized multi‐metric and multi‐centric assessment of EEG source space connectivity for dementia characterization |
title | Harmonized multi‐metric and multi‐centric assessment of EEG source space connectivity for dementia characterization |
title_full | Harmonized multi‐metric and multi‐centric assessment of EEG source space connectivity for dementia characterization |
title_fullStr | Harmonized multi‐metric and multi‐centric assessment of EEG source space connectivity for dementia characterization |
title_full_unstemmed | Harmonized multi‐metric and multi‐centric assessment of EEG source space connectivity for dementia characterization |
title_short | Harmonized multi‐metric and multi‐centric assessment of EEG source space connectivity for dementia characterization |
title_sort | harmonized multi‐metric and multi‐centric assessment of eeg source space connectivity for dementia characterization |
topic | Research Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10329259/ https://www.ncbi.nlm.nih.gov/pubmed/37424962 http://dx.doi.org/10.1002/dad2.12455 |
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