TY - JOUR
T1 - Harmonized multi-metric and multi-centric assessment of EEG source space connectivity for dementia characterization
AU - Prado, Pavel
AU - Mejía, Jhony A.
AU - Sainz-Ballesteros, Agustín
AU - Birba, Agustina
AU - Moguilner, Sebastian
AU - Herzog, Rubén
AU - Otero, Mónica
AU - Cuadros, Jhosmary
AU - Z-Rivera, Lucía
AU - O'Byrne, Daniel Franco
AU - Parra, Mario
AU - Ibáñez, Agustín
N1 - Publisher Copyright:
© 2023 The Authors. Alzheimer's & Dementia: Diagnosis, Assessment & Disease Monitoring published by Wiley Periodicals, LLC on behalf of Alzheimer's Association.
PY - 2023/7/1
Y1 - 2023/7/1
N2 - 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.
AB - 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.
KW - AD
KW - EEG
KW - automatic harmonization
KW - bvFTD
KW - dementia classification
KW - inverse solution methods
KW - multi-centric studies
KW - whole-brain functional connectivity
UR - http://www.scopus.com/inward/record.url?scp=85165508795&partnerID=8YFLogxK
U2 - 10.1002/dad2.12455
DO - 10.1002/dad2.12455
M3 - Article
AN - SCOPUS:85165508795
SN - 2352-8729
VL - 15
JO - Alzheimer's and Dementia: Diagnosis, Assessment and Disease Monitoring
JF - Alzheimer's and Dementia: Diagnosis, Assessment and Disease Monitoring
IS - 3
M1 - e12455
ER -