Global signal regression reduces connectivity patterns related to physiological signals and does not alter EEG-derived connectivity.

ABSTRACT:

Introduction

Functional brain connectivity measures extracted from resting-state functional magnetic resonance imaging (fMRI) scans have generated wide interest as potential noninvasive biomarkers. In this context, performing global signal regression (GSR) as a preprocessing step remains controversial. Specifically, while it has been shown that a considerable fraction of global signal variations is associated with physiological and motion sources, GSR may also result in removing neural activity.

Methods

Here, we address this question by examining the fundamental sources of resting global signal fluctuations using simultaneous electroencephalography (EEG)-fMRI data combined with cardiac and breathing recordings.

Results

Our results suggest that systemic physiological f

SUBMITTER: Xifra-Porxas A 

PROVIDER: S-EPMC12740878 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature