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

Ute Gschwandtner,Menorca Chaturvedi,Volker Roth,Guy Bogaarts,Peter Fuhr,Antonia Meyer,Florian Hatz

doi:10.3389/fnins.2021.683633

Ute Gschwandtner, Menorca Chaturvedi + Show 5 more

Open Access

https://doi.org/10.3389/fnins.2021.683633

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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.

Highlights

Due to advances in functional neuroimaging such as resting-state functional magnetic resonance imaging (fMRI), there has been an increased focus on studying functional connectivity (FC) on an individual basis rather than at a group level (Dubois and Adolphs, 2016)
Using EEG data from 105 healthy subjects scanned on two occasions up to 1 year apart, we show that, similar to an fMRI-derived FC profile (Finn et al, 2015), a dynamic FC” (DFC) profile obtained from one session can be used to uniquely identify a given individual from a set of profiles obtained in a second session
In the first part of this study we used data of 105 healthy subjects to show that intra-individual differences in DFC profiles are substantial and can reliably be observed, for example, they can act as an identifiable “fingerprint.” For each subject, a high-density resting-state EEG was obtained twice over a period ranging from 6 to 15 months

Summary

Introduction

Due to advances in functional neuroimaging such as resting-state fMRI, there has been an increased focus on studying FC on an individual basis rather than at a group level (Dubois and Adolphs, 2016). The shape of an EEG spectrum qualifies as a statistical signature of a person (Näpflin et al, 2007) Another recent advance in the field of FC research is the recognition of information contained in the temporal dynamics of functional connectivity (Hutchison et al, 2013; Allen et al, 2014; Calhoun et al, 2014; Bassett and Sporns, 2017). This dynamic FC exhibits highly structured spatiotemporal states in which distinct patterns of FC recur across time and across subjects (Allen et al, 2014).

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