Two major non-invasive brain mapping techniques, electroencephalography (EEG) and functional magnetic resonance imaging (fMRI), have complementary advantages with regard to their spatial and temporal resolution. Recent hardware and software developments have made it feasible to acquire EEG and fMRI data simultaneously. Previous neuroimaging studies suggested that simultaneous EEG and fMRI, aiming at the fusion of the high temporal resolution of EEG and the high spatial resolution of fMRI, could be a promising way to investigate neuronal activation [Debener et al., 2005; Benar et al., 2007]. A first attempt was to use fMRI priors to estimate the contribution of the P300 sources, extracting the time-course of neuronal activation in the millisecond range [Bledowski et al., 2004; Mulert et al., 2004]. A method based on independent component analysis (ICA) was proposed for the fusion of event related potentials (ERPs) and fMRI data, jointly estimating the temporal components of the ERP response and the spatial components revealed by fMRI [Calhoun et al., 2006]. In this regard, another ICA method has been developed to match brain activity recorded by EEG and fMRI at the single-trial level [Eichele et al., 2008].
