Identification of anti-correlated resting-state networks using simultaneous EEG-fMRI and Independent Components Analysis

In the absence of an explicit task, temporal synchrony is maintained across brain regions. Taking advantage of this synchrony, resting-state fMRI has been used extensively to identify resting state networks (RSN) [1]. Fox et al. have reported that the default mode network (DMN) is anti-correlated with the task positive network (TPN) [2], reflecting the competing demands of these two networks. The goal of this study was to identify the neuro-electrical signature of these anti-correlated networks, as assessed with simultaneous EEG-fMRI. Prior EEG-fMRI studies have found that the sign of the correlation between global alpha band power and the blood oxygenation level-dependent (BOLD) signal depends on the brain region [3,4,5]. Mantini et al [6] found that the correlation between global alpha band power and the spatial ICA time courses associated with the DMN and TPN have different signs, consistent with the presence of anti-correlation between these networks. Using a group analysis (N = 14), Jann et al [7] found some evidence for a link between alpha power global field synchronization and the DMN. In this study, we hypothesized that the relation between alpha power and the DMN and TPN would be stronger when using independent components of the EEG signal, as compared to using the global alpha power.