On characterizing population commonalities and subject variations in brain networks ?
We propose a new method for analysis of brain functional and structural connectivity networks in a population. We identify an atlas of network hubs that describe the population and are obtained from network commonalities across the subjects. Subject-level weights are also obtained by quantifying the intra- and inter-connectivity of network hubs that best reconstruct a subject's network. An NMF approach combined with multi-layer graph clustering is developed to find desired network hubs. The proposed method was applied to MEG and DTI datasets in the study of autism using modeled within- and between-hub connectivity.
multi-layer graph clustering connectivity analysis non-negative matrix factorization population difference autism spectrum disorder