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

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

Research output: Contribution to journalArticlepeer-review

4 Scopus citations

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.

Original languageEnglish
Article numbere12455
JournalAlzheimer's and Dementia: Diagnosis, Assessment and Disease Monitoring
Volume15
Issue number3
DOIs
StatePublished - 1 Jul 2023
Externally publishedYes

Keywords

  • AD
  • EEG
  • automatic harmonization
  • bvFTD
  • dementia classification
  • inverse solution methods
  • multi-centric studies
  • whole-brain functional connectivity

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