Internet-like brain hierarchical network model: Alzheimer's disease study as an example.

BACKGROUND AND OBJECTIVE: The modular structure and hierarchy are important topological characteristics in real complex networks such as brain networks on temporal scale. However, there are few studies investigating the hierarchical structure at the spatial scale of brain networks, the application of which still remains to be further studied. METHODS: In this study, a novel model of brain hierarchical network based on the hierarchical characteristic of Internet topology is proposed for the first time, which is called Internet-like brain hierarchical network (IBHN). In this model, the whole brain network is partitioned into multiple levels: brain wide area network (Brain-WAN), brain metropolitan network (Brain-MAN), and brain local area network (Brain-LAN). A Brain-MAN is formed by the interconnection of multiple Brain-LANs, and the interconnection of multiple Brain-MANs forms a Brain-WAN. A multivariate analysis method is employed to measure overall functional connectivity between two brain networks at the same network level rather than detecting the change of each node pair's functional connection. Furthermore, we demonstrate the utility of IBHN model with application to a practical case-control study involving 64 patients with Alzheimer's disease and 75 healthy controls. RESULTS: The proposed model identified enhanced functional connectivity (P-value<0.05) at Brain-WAN level and reduced functional connectivity (P-value=0.004) at Brain-LAN level of Alzheimer's disease patients, which can be used as a multi-dimension functional reference for AD's diagnosis. CONCLUSIONS: This study not only provides insight into AD pathophysiology, but also further proves the effectiveness of the proposed IBHN model. In addition, the IBHN model makes it possible to explore the brain's functional organization from multiple dimensions and offers a multi-level perspective for the research of complex brain network.