Triple-network analysis of Alzheimer’s disease based on the energy landscape - Li, Youjun; An, Simeng; Zhou, Tianlin; Su, Chunwang; Zhang, Siping; Li, Chenxi; Jiang, Junjie; Mu, Yunfeng; Yao, Nan; Huang, Zi-Gang; , Alzheimer’s Disease Neuroimaging Initiative (Frontiers in Neuroscience, 2023)
Research on the brain activity during resting state has found that brain activation is centered around three networks, including the default mode network (DMN), the salient network (SN), and the central executive network (CEN), and switches between multiple modes. As a common disease in the elderly, Alzheimer's disease (AD) affects the state transitions of functional networks in the resting state. Energy landscape, as a new method, can intuitively and quickly grasp the statistical distribution of system states and information related to state transition mechanisms. Therefore, this study mainly uses the energy landscape method to study the changes of the triple-network brain dynamics in AD patients in the resting state. Our results indicate that AD brain activity patterns are in an abnormal nonequilibrium state, and the dynamics of patients with AD tend to be unstable, with an unusually high flexibility in switching between states. The subjects' dynamic features are correlated with clinical data and the atypical balance of large-scale brain systems in patients with AD is associated with abnormally active brain dynamics. These results are helpful for further understanding the intrinsic dynamic characteristics and pathological mechanism of the resting-state brain in AD patients.