Neurophysiological Investigation of Spontaneous Correlated and Anticorrelated Fluctuations of the BOLD Signal

Abstract

Analyses of intrinsic fMRI BOLD signal fluctuations reliably reveal correlated and anticorrelated functional networks in the brain. Since the BOLD signal is an indirect measure of neuronal activity, and anticorrelations can be introduced by preprocessing steps such as global signal regression (GSR), the neurophysiological significance of correlated and anticorrelated BOLD fluctuations is a source of debate. Here, we address this question by examining the correspondence between the spatial organization of correlated BOLD fluctuations and correlated fluctuations in electrophysiological high gamma power (HGP) signals recorded directly from the cortical surface of 5 patients. We demonstrate that both positive and negative BOLD correlations have neurophysiological correlates reflected in fluctuations of spontaneous neuronal activity. Although applying GSR to BOLD signals results in some BOLD anticorrelations that are not apparent in the ECoG data, it enhances the neuronal-hemodynamic correspondence overall. Together, these findings provide support for the neurophysiological fidelity of BOLD correlations and anticorrelations.

Resting-state networks link invasive and noninvasive brain stimulation across diverse psychiatric and neurological diseases

“…The processing approaches used to eliminate global signal fluctuations have a significant impact on observed anticorrelations (71)(72)(73)(74)(75). It is important that our results remained significant with two different processing strategies; however, further work is needed to determine the best approach to predict the results of brain stimulation.…”

Functional Integration Between Brain Regions at Rest Occurs in Multiple-Frequency Bands

“…Task-positive and task-negative networks are known to be anticorrelated (Fox et al, 2005). While in a particular class of cases this strong negative correlation is likely attributed to data processing methodology that involves global signal regression (Saad et al, 2012), other studies have confirmed the presence of anticorrelated networks in human brain (Keller et al, 2013). In the current work, no global signal regression was implemented.…”

Save the Global: Global Signal Connectivity as a Tool for Studying Clinical Populations with Functional Magnetic Resonance Imaging

“…The average proportions of negative correlations were below 1.5% in both experimental groups and did not differ between groups [t (30) = À0.41, p-value n.s.]. Due to the minority of negative correlations in the data, and considering recent claims that these correlations have neural bases (Chai et al, 2012;Chang and Glover, 2009;Fox et al, 2009;Keller et al, 2013;Uddin et al, 2009), we did not exclude negative correlation from our analyses. To obtain a gross measure of connectivity per participant, the GBC indices of all cortical voxels were averaged to produce a single global correlation value per participant, here referred to as the subject connectivity index (SCI).…”