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Abstract #4331

Dynamic Whole-Brain Connectivity underlying Abnormal Brain States in Late-onset Depression

Mingze Xu1,2, Shiyang Chen2, Bing Ji2,3, Jiuquan Zhang4, Huaiqiu Zhu1, Yi Zhang5, Yonggui Yuan6, Jiahong Gao1, Yijun Liu1, and Xiaoping Hu2

1Biomedical Engineering, Peking University, Beijing, China, People's Republic of, 2Biomedical Engineering, Emory University & Georgia Institute of Technology, Atlanta, GA, United States, 3University of Shanghai for Science & Technology, Shanghai, China, People's Republic of, 4Department of Radiology, Southwest Hospital, Third Military Medical University, Chongqing, China, People's Republic of, 5School of Life Science and Technology, Xidian University, Shaanxi, China, People's Republic of, 6Department of Psychosomatics and Psychiatry, ZhongDa Hospital, School of Medicine, Southeast University, Nanjing, China, People's Republic of

We conducted dynamic whole-brain connectivity analysis in Late-onset depression (LOD) to investigate alterations in brain networks. All subjects’ ROI-to-ROI dynamic FC were explored using a data-driven method to obtain the most explanatory states. Each state indicate a particular ROI-to-ROI FC pattern. The property of each state were determined based on its scores across time. Besides decreased FC in normal state, we found LOD patients switch between brain states more frequently and tend to enter LOD-risk states, due to and its high states variance and dominating increased FC in LOD-risk states. These results suggest neural mechanisms of disorder from dynamic perspective.

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