Abstract #4331

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

Mingze Xu^1,2, Shiyang Chen², Bing Ji^2,3, 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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