Source space connectomics of neurodegeneration: One-metric approach does not fit all

PRADO, PAVEL; MOGUILNER, SEBASTIAN; MEJÍA, JHONY A.; SAINZ-BALLESTEROS, AGUSTÍN; OTERO, MÓNICA; BIRBA, AGUSTINA; SANTAMARIA-GARCIA, HERNANDO; LEGAZ, AGUSTINA; FITTIPALDI, SOL; CRUZAT, JOSEPHINE; TAGLIAZUCCHI, ENZO; PARRA, MARIO; HERZOG, RUBÉN; IBÁÑEZ, AGUSTÍN

NEUROBIOLOGY OF DISEASE

ACADEMIC PRESS INC ELSEVIER SCIENCE

Año: 2023 vol. 179

0969-9961

Brain functional connectivity in dementia has been assessed with dissimilar EEG connectivity metrics and estimation procedures, thereby increasing results´ heterogeneity. In this scenario, joint analyses integrating information from different metrics may allow for a more comprehensive characterization of brain functional interactions in different dementia subtypes. To test this hypothesis, resting-state electroencephalogram (rsEEG) was recorded in individuals with Alzheimer´s Disease (AD), behavioral variant frontotemporal dementia (bvFTD), and healthy controls (HCs). Whole-brain functional connectivity was estimated in the EEG source space using 101 different types of functional connectivity, capturing linear and nonlinear interactions in both time and frequency-domains. Multivariate machine learning and progressive feature elimination was run to discriminate AD from HCs, and bvFTD from HCs, based on joint analyses of i) EEG frequency bands, ii) complementary frequency-domain metrics (e.g., instantaneous, lagged, and total connectivity), and iii) time-domain metrics with different linearity assumption (e.g., Pearson correlation coefficient and mutual information). 1/4 of all possible connectivity measures. Joint analyses revealed patterns of hypoconnectivity (patientsHCs) in both groups was mainly identified in frontotemporal regions. These atypicalities were differently captured by frequency- and time-domain connectivity metrics, in a bandwidth-specific fashion. The multi-metric representation of source space whole-brain functional connectivity evidenced the inadequacy of single-metric approaches, and resulted in a valid alternative for the selection problem in EEG connectivity. These joint analyses reveal patterns of brain functional interdependence that are overlooked with single metrics approaches, contributing to a more reliable and interpretable description of atypical functional connectivity in neurodegeneration.