Project Summary: Joint use of non-invasive measurement techniqeus of brain function, the electroencephalogram (EEG) with high temporal resolution and the functional magnetic resonance imaging (fMRI) with high spatial resolution, provides an important possibility for understanding both structural and dynamical properties of neural processes underlying human brain function. Complementary use of these techniques requires a correct model of the electro-vascular coupling between the EEG activities and the vascular response. Present models employed in the EEG-fMRI integration studies assume a relationship between the level of the neuronal activity and the oxygen transport to the tissue. However, changes in the EEG signal do not reflect directly the level of neural activity but synchrony. In this project, the correlations between the synchronized EEG patterns and the fMRI have been investigated in the visual modality. Steady-state visual evoked potentials (SSVEP) were used to obtain synchronized EEG patterns that remain constant along the slower simultaneous fMRI response, and correlations between changes of the EEG and fMRI due to the stimulation frequency were investigated. Although a strong correlation exists between the EEG and fMRI changes for stimulation frequencies in the beta frequency range, the correlation disappears when stimuli were applied with frequencies corresponding to the alpha and gamma frequency ranges of the EEG. This specific difference among the frequency bands of stimuli has been explained by the differences of the synchronization mechanisms and required excitatory and inhibitory inputs to synchronize oscillatory activities in the visual cortex in different frequency ranges. In EEG/fMRI integration studies it should be taken into account that both signals do not reflect same neural processes, but as long as experimental variables are used that affect both signals, and symmetrical analysis approaches are employed instead of asymmetrical approaches such as defining the solution space of one modality using information obtained from the other, the presence as well as the absence of a correlation between them can shed light on the underlying neural processes.