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Harmonized multi‐metric and multi‐centric assessment of EEG source space connectivity for dementia characterization

Authors :
Pavel Prado
Jhony A. Mejía
Agustín Sainz‐Ballesteros
Agustina Birba
Sebastian Moguilner
Rubén Herzog
Mónica Otero
Jhosmary Cuadros
Lucía Z‐Rivera
Daniel Franco O'Byrne
Mario Parra
Agustín Ibáñez
Source :
Alzheimer’s & Dementia: Diagnosis, Assessment & Disease Monitoring, Vol 15, Iss 3, Pp n/a-n/a (2023)
Publication Year :
2023
Publisher :
Wiley, 2023.

Abstract

Abstract 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.

Details

Language :
English
ISSN :
23528729
Volume :
15
Issue :
3
Database :
Directory of Open Access Journals
Journal :
Alzheimer’s & Dementia: Diagnosis, Assessment & Disease Monitoring
Publication Type :
Academic Journal
Accession number :
edsdoj.6a1cc3328624e5a88e8ccb1003e6495
Document Type :
article
Full Text :
https://doi.org/10.1002/dad2.12455