Functional magnetic resonance imaging (fMRI) studies utilizing measures of hemodynamic signal, such as the blood-oxygenation-level dependent (BOLD) signal, have discovered that resting-state brain activities are organized into multiple large-scale functional networks, coined as resting state networks (RSNs). However, an important limitation of the available fMRI studies is that hemodynamic signals only provide an indirect measure of neuronal activity and that the neurobiological basis of the fMRI RSNs is not clear. Several approaches have been developed to search and identify the electrophysiological correlates of spontaneous fMRI fluctuations. The current study reviewed and compared two recently developed approaches based on the time courses and the spatial patterns of simultaneously acquired EEG and fMRI data.
['Han Yuan', 'Jerzy Bodurka', 'Lei Ding']
Exploring spatiotemporal dynamics of the human brain by multimodal imaging