Identification of Anti-Correlated Resting-State Networks Using Simultaneous EEG-FMRI and Independent Components Analysis

Chi Wah Wong¹, Valur Olafsson², Hongjian He², Tom Liu²

It has been shown with resting-state fMRI that the Default Mode Network (DMN) is anti-correlated with the Task Positive Network (TPN). In this study, we used simultaneous EEG-fMRI to investigate the relationship of the EEG alpha power time course with the resting-state BOLD signals in these anti-correlated networks. We found that the relation between the EEG alpha power and BOLD fMRI signals in these networks is stronger when using independent components (as determined with Independent Components Analysis) as compared to the use of the global alpha power.