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

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. We implemented an automatic processing pipelin...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Alzheimer's & dementia : diagnosis, assessment & disease monitoring assessment & disease monitoring, 2023-07, Vol.15 (3), p.e12455-e12455
Hauptverfasser: 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
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung: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. We implemented an automatic processing pipeline incorporating electrode layout integrations, patient-control normalizations, and multi-metric EEG source space connectomics analyses. 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. 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.
ISSN:2352-8729
2352-8729
DOI:10.1002/dad2.12455