OBJECTIVES: In this paper, we employed advanced methods for the modeling of human cortical activity related to voluntary right one-digit movements from combined high-resolution electroencepholography (EEG) and functional magnetic resonance imaging (fMRI). METHODS: Multimodal integration between EEG and fMRI data was performed by using realistic head models, a large number of scalp electrodes (128) and the estimation of current density strengths by linear inverse estimation. RESULTS: Increasing of spatial details of the estimated cortical density distributions has been detected by using the proposed integration method with respect to the estimation using EEG data alone. CONCLUSION: The proposed method of multimodal EEG-fMRI data is useful to increase spatial resolution of movement-related potentials and can also be applied to other kinds of event-related potentials.
OBJECTIVES: In this paper, we employed advanced methods for the modeling of human cortical activity related to voluntary right one-digit movements from combined high-resolution electroencepholography (EEG) and functional magnetic resonance imaging (fMRI). METHODS: Multimodal integration between EEG and fMRI data was performed by using realistic head models, a large number of scalp electrodes (128) and the estimation of current density strengths by linear inverse estimation. RESULTS: Increasing of spatial details of the estimated cortical density distributions has been detected by using the proposed integration method with respect to the estimation using EEG data alone. CONCLUSION: The proposed method of multimodal EEG-fMRI data is useful to increase spatial resolution of movement-related potentials and can also be applied to other kinds of event-related potentials.