FV 8 Quantifying consciousness in healthy adults using EEG phase coherence

Abstract

Background: Phase coherence (PC) is an extensively researched parameter for functional connectivity (FC) based on EEG data [1]. Functional connectivity quantifies the temporal interdependency between activity of spatially separated brain regions [2]. It can help to describe different brain states. Objective: This study investigates PC in healthy adults in wakefulness and non-REM sleep. We aim to evaluate, whether PC distinguishes different states of consciousness, and we use sleep as an example. Methods: We measured resting state EEG in 53 healthy volunteers (20–40 y, 35 females). For three-minute segments per sleep stage, we extracted the phase of the Hilbert transform and calculated the PC. As PC values were not normally distributed, we used Wilcoxon signed-rank tests for statistical analysis considering the different frequency bands (delta, theta, alpha, beta) and sleep stages (W, N1, N2, N3). Results: Alpha-frequency PC was significantly higher in W than in N1, N2, N3 (Fig. 1). In contrast, delta coupling increased with sleep depth. It was lower in wakefulness and light sleep (N1, N2) than during deep sleep (Fig. 1). Within the beta- and theta-frequency bands PC did not differ significantly between stages. Conclusions: Functional connectivity, as measured by PC, differed between sleep stages in a frequency-specific manner – corresponding to sleep stage-specific dominant frequencies as observed in clinical EEG. Sleep-like PC patterns different to those observed during wakefulness might serve to identify reduced consciousness in pathologic conditions like epilepsy or neurodegenerative diseases.