Functional connectivity has been shown to change over short time scales of seconds to minutes, giving rise to the so-called dynamic functional connectivity (dFC). However, the electrophysiological underpinnings of dFC states remain unclear. We investigate EEG spectral correlates of dFC states using simultaneous EEG-fMRI data, by using a high temporal resolution fMRI acquisition combined with a phase coherence approach for dFC estimation and by computing k-means clustering with a varying number of dFC states. We found an association between high alpha power topographies and specific dFC states, which included regions of the frontoparietal network and the default mode network.
This abstract and the presentation materials are available to members only; a login is required.