Controllability and Synchronizability of Structural Brain Networks in Alzheimer's Disease

Alzheimers disease (AD) is a degenerative disorder of the central nervous system, characterized by progressive cognitive dysfunction and behavioral impairment. However, the impact of AD on structural brain networks remains unclear. To investigate the differences in structural brain networks between the cognitive normal (CN) and AD groups, we use diffusion tensor imaging (DTI) data from 30 subjects (15 CN subjects and 15 patients with AD) from the Alzheimer's Disease Neuroimaging Initiative (ADNI). We then apply network controllability theory and explore these differences by selecting three indicators: average controllability, modal controllability and synchronizability. Using these indicators, the support vector machine is employed to classify the two groups. Our results suggest that there are significant differences in the structural brain networks between the CN and AD groups in certain brain regions. Furthermore, the three indicators can effectively classify the two groups.