Incorporating higher dimensionality in joint decomposition of EEG and fMRI

EEG-fMRI research to study brain function became popular because of the complementarity of the modalities. Through the use of data-driven approaches such as jointICA, sources extracted from EEG can be linked to regions in fMRI. Joint-ICA in its standard formulation however does not allow for the inclusion of multiple EEG electrodes, so it is a rather arbitrary choice which electrode is used in the analysis. In this study, we explore several ways to include the higher dimensionality of the EEG during a joint decomposition of EEG and fMRI. Our results show that incorporation of multiple channels in the jointICA can reveal new relations between fMRI activation maps and ERP features.