An automatic ICA-based method for removing artifacts from EEG data acquired during fMRI in real time

Simultaneous EEG-fMRI recording provides complementary advantages with regard to the temporal and spatial resolution of neuronal activity measurements. However, raw EEG data collected during fMRI experiments are contaminated by imaging and ballistocardiographic (BCG) artifacts in addition to muscle, ocular, and other EEG artifacts. We describe a new method developed based on independent component analysis (ICA) to automatically detect and remove ocular, muscle and residual imaging and BCG artifacts from EEG data recorded simultaneously with fMRI. The method can be implemented in real time.