We proposed a fully automatic, iterative reclustering framework in which a small number of spatially large, heterogeneous networks are initially extracted to maximize spatial reproducibility.
Then, the large networks of the brain are iteratively subdivided to create spatially reproducible subnetworks until the overall within-network homogeneity does not increase substantially.
Here, you may download the experimental results generated using the proposed clustering method. The results include a meaningful pattern for spatially hierarchical structure of the brain.
Shams et al., "Automated Iterative Reclustering Framework for Determining Hierarchical Functional Networks in Resting State fMRI". Human Brain Mapping, Accepted.