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

Author:

Prado Pavel12,Mejía Jhony A.134,Sainz‐Ballesteros Agustín15,Birba Agustina1567,Moguilner Sebastian158,Herzog Rubén19,Otero Mónica1011,Cuadros Jhosmary12,Z‐Rivera Lucía12,O'Byrne Daniel Franco13,Parra Mario14,Ibáñez Agustín15131516

Affiliation:

1. Latin American Brain Health Institute (BrainLat) Universidad Adolfo Ibáñez Santiago de Chile Chile

2. Escuela de Fonoaudiología Facultad de Odontología y Ciencias de la Rehabilitación Universidad San Sebastián Santiago Chile

3. Departamento de Ingeniería Biomédica Universidad de Los Andes Bogotá Colombia

4. Memory and Aging Clinic University of California San Francisco United States

5. Cognitive Neuroscience Center (CNC) Universidad de San Andrés Buenos Aires Argentina

6. Instituto Universitario de Neurociencia Universidad de La Laguna Tenerife Spain

7. Facultad de Psicología Universidad de La Laguna Tenerife Spain

8. Department of Neurology Massachusetts General Hospital and Harvard Medical School Boston United States

9. Fundación para el Estudio de la Conciencia Humana (EcoH) Santiago de Chile Chile

10. Facultad de Ingeniería, Arquitectura y Diseño Universidad San Sebastián Santiago Chile

11. Centro BASAL Ciencia & Vida; Facultad de Ingeniería y Tecnología Universidad San Sebastián Santiago de Chile Chile

12. Advanced Center for Electrical and Electronic Engineering (AC3E) Universidad Técnica Federico Santa María Valparaíso Chile

13. Center for Social and Cognitive Neuroscience (CSCN) School of Psychology Universidad Adolfo Ibáñez Santiago Chile

14. School of Psychological Sciences and Health University of Strathclyde Glasgow UK

15. National Scientific and Technical Research Council (CONICET) Buenos Aires Argentina

16. Global Brain Health Institute (GBHI) University of California San Francisco California and Trinity College Dublin Dublin Ireland

Abstract

AbstractIntroductionHarmonization 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.MethodsWe implemented an automatic processing pipeline incorporating electrode layout integrations, patient–control normalizations, and multi‐metric EEG source space connectomics analyses.ResultsSpline 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.DiscussionHarmonized multi‐metric analysis of EEG source space connectivity can address data heterogeneities in multi‐centric studies, representing a powerful tool for accurately characterizing dementia.

Funder

Alzheimer's Association

Publisher

Wiley

Subject

Psychiatry and Mental health,Neurology (clinical)

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