Identification of Effective Connectivity Subregions

Understand

Standard fMRI connectivity analyses depend on aggregating the time series of individual voxels within regions of interest (ROIs).

• In certain cases, this spatial aggregation implies a loss of valuable functional and anatomical information about smaller subsets of voxels that drive the ROI level connectivity.
• We use two recently published graphical search methods to identify subsets of voxels that are highly responsible for the connectivity between larger ROIs.
• To illustrate the procedure, we apply both methods to longitudinal high-resolution resting state fMRI data from regions in the medial temporal lobe from a single individual.