In this paper, advanced methods for the estimation of cortical connectivity from combined high-resolution electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) data are presented. We used a computational approach to the estimation of cortical connectivity by computing the Directed Transfer Function (DTF), a technique used to estimate the direction of the information flow between signals gathered from EEG sensors. The proposed method was able to depict the direction of the information flows between the cortical regions of interest, since it is directional in nature. An application of these technique to the real high-resolution EEG and fMRI signals gathered during visual finger-tapping movements in three normal healthy subjects is also provided.
- Directed Transfer Function
- EEG and fMRI integration
- Linear inverse source estimate