A cortical and sub-cortical parcellation clustering by intrinsic functional connectivity

Network analysis of resting-state fMRI (rsfMRI) has been widely utilized to investigate the functional architecture of the whole brain. Here we propose a robust parcellation method that first divides cortical and sub-cortical regions into sub-regions by clustering the rsfMRI data for each subject independently, and then merges those individual parcellations to obtain a global whole brain parcellation. To do so our method relies on majority voting (to merge parcellations of multiple subjects) and enforces spatial constraints within a hierarchical agglomerative clustering framework to define parcels that are spatially homogeneous