Han Yuan1, Vadim Zotev1, Raquel Phillips1, Wayne Drevets1, Jerzy Bodurka1
1Laureate Institute for Brain Research, Tulsa, OK, United States
We developed a novel, fully data-driven approach to the analysis of EEG microstates, and applied this approach to investigate EEG microstates as electrophysiological correlates for BOLD resting state networks (RSNs) using simultaneous EEG and fMRI recordings. Thirteen main microstates were identified at the group level and the time courses of these microstates were compared to the whole-brain BOLD signal. Our results have revealed for the first time EEG microstate-associated networks that correspond to a wide range of RSNs, including visual, sensorimotor, auditory, attention, frontal, ventral stream and default mode networks.