수면정신생리

수면정신생리 (25권2호 82-91)

The Feasibility for Whole-Night Sleep Brain Network Research Using Synchronous EEG-fMRI

수면 뇌파-기능자기공명영상 동기화 측정과 신호처리 기법을 통한 수면 단계별 뇌연결망 연구

Kim, Joong Il;Park, Bumhee;Youn, Tak;Park, Hae-Jeong;

Future Medicine Division, Korea Institute of Oriental Medicine;Department of Biomedical Informatics, Ajou University School of Medicine;Department of Psychiatry, Dongguk University Ilsan Hospital;BK21 PLUS Project for Medical Science, Yonsei University College of Medicine;

DOI : http://dx.doi.org/10.14401/KASMED.2018.25.2.82

Abstract

Objectives: Synchronous electroencephalogram (EEG) and functional magnetic resonance imaging (fMRI) has been used to explore sleep stage dependent functional brain networks. Despite a growing number of sleep studies using EEG-fMRI, few studies have conducted network analysis on whole night sleep due to difficulty in data acquisition, artifacts, and sleep management within the MRI scanner. Methods: In order to perform network analysis for whole night sleep, we proposed experimental procedures and data processing techniques for EEG-fMRI. We acquired 6-7 hours of EEG-fMRI data per participant and conducted signal processing to reduce artifacts in both EEG and fMRI. We then generated a functional brain atlas with 68 brain regions using independent component analysis of sleep fMRI data. Using this functional atlas, we constructed sleep level dependent functional brain networks. Results: When we evaluated functional connectivity distribution, sleep showed significantly reduced functional connectivity for the whole brain compared to that during wakefulness. REM sleep showed statistically different connectivity patterns compared to non-REM sleep in sleep-related subcortical brain circuits. Conclusion: This study suggests the feasibility of exploring functional brain networks using sleep EEG-fMRI for whole night sleep via appropriate experimental procedures and signal processing techniques for fMRI and EEG.

Keywords

Sleep;EEG;Resting state fMRI;EEG-fMRI;Brain network;Functional connectivity;