Anatomical hubs from spectral clustering of structural connectomes

Abstract

The analysis of the structural brain networks have recently gathered extensive interest due to its crucial role in unveiling the fundamental principles of the brain. The uniformity of structural networks inferred from diffusion tensor imaging across different individuals is however, unknown. This paper presents a method to infer group-wise consistent structural clusters from the connectome Laplacian graph. The spectral clustering of the cortical networks from diffusion tensor imaging was applied on 146 healthy subjects using 3 random groups, and on groups based on gender and age, to determine the optimal number of clusters. The results show six consistent sub-networks of structural connections that was validated using known cluster validity indices, showing highly reproducible clusters for random groups and groups based on gender; while, cluster differences were observed between younger and older groups in areas related to memory.