Citation

Yuxuan Chen, Farrand J, Tang J, Yafen Chen, O'Keeffe J, Guofa Shou, Lei Ding, Han Yuan. Conf. Proc. IEEE Eng. Med. Biol. Soc. 2017; 2017: 537-540.

Copyright

(Copyright © 2017, IEEE (Institute of Electrical and Electronics Engineers))

DOI

10.1109/EMBC.2017.8036880

PMID

29059928

Abstract

Most of the prior studies of functional connectivity in both healthy and diseased brain utilized resting-state functional magnetic resonance imaging (fMRI) as a measure to represent the temporal synchrony in blood oxygenation level dependent (BOLD) signals across brain regions. To eliminate the impact of widely distributed global signal component across the brain, many studies have adopted global signal regression (GSR) as a pre-processing approach to regress the global signal component out of BOLD signals followed by computing hemodynamic connectivity. However, the procedure of global signal regression has been debated as physiologically relevant component may be present in global signal. In this study, we aimed to address the controversy of global signal using functional non-invasive neuroimaging technology, i.e. functional near-infrared spectroscopy (fNIRS), which measures hemodynamic signals by probing local changes in oxygen consumption, a common imaging contrast measured by BOLD fMRI. In the current study, we acquired simultaneous EEG and fNIRS signals, both in high-density configuration and whole-brain coverage, in healthy individuals at eyes-open and eyes-closed resting state and at three different body positions. We explored the underlying relationship between fNIRS global signal and EEG vigilance, and have identified negative correlation between fNIRS global signal and EEG vigilance across the physiological variations of measurements.

Language: en