The Global Signal and Observed Anticorrelated Resting State Brain Networks

TLDR

Resting‑state fMRI studies map the brain’s intrinsic large‑scale functional architecture, and removing the global BOLD signal—common to the whole brain—has consistently revealed anticorrelations between the default mode network and an extended dorsal attention system, mirroring task‑related relationships. This study investigates whether the global signal is truly global and examines the validity of its removal, aiming to clarify how it influences observed anticorrelated brain networks. The authors mathematically and empirically analyze the effect of global signal regression on resting‑state correlation maps, demonstrating that it enhances detection of system‑specific correlations and improves alignment with anatomical structure. They find that the spatial distribution, cross‑subject consistency, persistence with modified whole‑brain masks, and pre‑existence of anticorrelated networks are independent of global signal removal, indicating a biological basis for these networks.

Abstract

Resting state studies of spontaneous fluctuations in the functional MRI (fMRI) blood oxygen level dependent (BOLD) signal have shown great promise in mapping the brain's intrinsic, large-scale functional architecture. An important data preprocessing step used to enhance the quality of these observations has been removal of spontaneous BOLD fluctuations common to the whole brain (the so-called global signal). One reproducible consequence of global signal removal has been the finding that spontaneous BOLD fluctuations in the default mode network and an extended dorsal attention system are consistently anticorrelated, a relationship that these two systems exhibit during task performance. The dependence of these resting-state anticorrelations on global signal removal has raised important questions regarding the nature of the global signal, the validity of global signal removal, and the appropriate interpretation of observed anticorrelated brain networks. In this study, we investigate several properties of the global signal and find that it is, indeed, global, not residing preferentially in systems exhibiting anticorrelations. We detail the influence of global signal removal on resting state correlation maps both mathematically and empirically, showing an enhancement in detection of system-specific correlations and improvement in the correspondence between resting-state correlations and anatomy. Finally, we show that several characteristics of anticorrelated networks including their spatial distribution, cross-subject consistency, presence with modified whole brain masks, and existence before global regression are not attributable to global signal removal and therefore suggest a biological basis.