FMRI based connectivity analysis of perisylvian language related brain areas

Usually, the focus of fMRI studies is the identification of brain regions that change level of activations as a response to specific stimuli. On the other hand, possible connectivity modeling between activated brain areas remains an open question. Based on fMRI data, in the last decades different methods for uncovering interactions between brain areas have been proposed. In this study we used the generalized Partial Directed Coherence (gPDC) to identify directed interactions between activated brain areas during self paced block fMRI paradigm for the identification of perisylvian language related brain areas.

I. Introduction

FUNCTIONAL magnetic resonance imaging (fMRI) is based on paramagnetic properties of deoxyhemoglobin, trough formation of BOLD (Blood Oxygenation Level Dependent) signal. Noninvasive nature of this procedure, high spatial resolution, as well as relatively high availability made fMRI one of the most popular neuroimaging techniques in neuroscience.