Alteration in Resting-State EEG Microstates Following 24 Hours of Total Sleep Deprivation in Healthy Young Male Subjects.

Lubin Wang,Jianpan Li,Ming Ke

doi:10.3389/fnhum.2021.636252

Abstract

Purpose: The cognitive effects of total sleep deprivation (TSD) on the brain remain poorly understood. Electroencephalography (EEG) is a very useful tool for detecting spontaneous brain activity in the resting state. Quasi-stable electrical distributions, known as microstates, carry useful information about the dynamics of large-scale brain networks. In this study, microstate analysis was used to study changes in brain activity after 24 h of total sleep deprivation.Participants and Methods: Twenty-seven healthy volunteers were recruited and underwent EEG scans before and after 24 h of TSD. Microstate analysis was applied, and six microstate classes (A–F) were identified. Topographies and temporal parameters of the microstates were compared between the rested wakefulness (RW) and TSD conditions.Results: Microstate class A (a right-anterior to left-posterior orientation of the mapped field) showed lower global explained variance (GEV), frequency of occurrence, and time coverage in TSD than RW, whereas microstate class D (a fronto-central extreme location of the mapped field) displayed higher GEV, frequency of occurrence, and time coverage in TSD compared to RW. Moreover, subjective sleepiness was significantly negatively correlated with the microstate parameters of class A and positively correlated with the microstate parameters of class D. Transition analysis revealed that class B exhibited a higher probability of transition than did classes D and F in TSD compared to RW.Conclusion: The observation suggests alterations of the dynamic brain-state properties of TSD in healthy young male subjects, which may serve as system-level neural underpinnings for cognitive declines in sleep-deprived subjects.

Highlights

Sleep is essential for the brain to recover and keep it functioning optimally (Koenis et al, 2013)
We have found that the abnormal competition between salience network (SN) and default mode network (DMN) was significantly correlated with both subjective sleepiness and working memory performance, which may be related to the instability of the awake state (Lei et al, 2015)
The six microstates across subjects in the rested wakefulness (RW) and after 24 h of total sleep deprivation (TSD) explained about 70% of the global variance (71.7% in TSD and 70.9% in RW) (Figure 1B)

Summary

Introduction

Sleep is essential for the brain to recover and keep it functioning optimally (Koenis et al, 2013). Resting-State EEG Microstates After TSD imaging (fMRI) studies have shown that functional connectivity within the default mode network (DMN) and anti-correlation between the DMN and anti-correlated network (ACN) were reduced after sleep deprivation (De Havas et al, 2012; Wang et al, 2015). Graph theory was used to analyze fMRI data in resting state of sleep deprivation to evaluate changes in the brain network structure after sleep deprivation These studies suggested that sleep deprivation severely impaired the topological properties of the brain’s small-world network (Koenis et al, 2013; Jiang et al, 2018). One approach was to use the recorded oscillation characteristics to define the “state” of the signal over time In this method, brain activity was described by state characteristics, such as the frequency of occurrence or the duration of certain states (Brunet et al, 2011)

Methods

Results

Conclusion