The spatial maps of task-related networks are used as fMRI priors in the localization of the ERP IC sensor maps, performed with the Weighted Minimum Norm Least Squares (WMNLS) algorithm [Hamalainen and Ilmoniemi, 1994] with Curry 6.0 software (Neuroscan, Hamburg, Germany). An anatomical image of the standard head from the Montreal Neurological Institute (MNI) is used for constructing the head model. In particular, the image segmentation of the MNI head provides the surfaces used for the definition of the source space and of the realistic volume conductor model [Fuchs et al., 1998] obtained by a three compartment Boundary Element Method (BEM) model with the following conductivity values: σskin=0.33Sm−1, σskull=0.0042Sm−1, σbrain=0.33Sm−1. Moreover, the standard EEG electrode positions for source localizations is estimated by fitting the electrode montage to the skin compartment of the MNI head model. Current density maps are estimated by WMNLS in the source space, defined by a 3-dimensional regular grid with 4mm step. The brain areas included in all the task-related fMRI network maps are segmented, dilated by 5mm to account for the difference between electrophysiological and hemodynamic
