Dynamic Functional Connectivity of EEG: From Identifying Fingerprints to Gender Differences to a General Blueprint for the Brain's Functional Organization

Abstract

An individual's brain functional organization is unique and can reliably be observed using modalities such as functional magnetic resonance imaging (fMRI). Here we demonstrate that a quantification of the dynamics of functional connectivity (FC) as measured using electroencephalography (EEG) offers an alternative means of observing an individual's brain functional organization. Using data from both healthy individuals as well as from patients with Parkinson's disease (PD) (n = 103 healthy individuals, n = 57 PD patients), we show that “dynamic FC” (DFC) profiles can be used to identify individuals in a large group. Furthermore, we show that DFC profiles predict gender and exhibit characteristics shared both among individuals as well as between both hemispheres. Furthermore, DFC profile characteristics are frequency band specific, indicating that they reflect distinct processes in the brain. Our empirically derived method of DFC demonstrates the potential of studying the dynamics of the functional organization of the brain using EEG.