Abstract #2003

Unbalanced large-scale brain networks during static and dynamic states in Alzheimer’s Disease

Xiaoqing Ji¹, Haiyang Geng^2,3, Rui Li¹, Le He¹, and Chun Yuan^1,4

¹Center for Biomedical Imaging Research, Tsinghua University, Beijing, China, ²Institute of Affective and Social Neuroscience, Shenzhen University, Shenzhen, China, ³Neuroimaging Center,University Medical Center Groningen, University of Groningen, Groningen, Netherlands, ⁴Department of Radiology, Washington Univesity, Seattle, WA, United States

In this study, we applied Independent Component Analysis (ICA) and dynamic network approaches to explore the neural network mechanisms between Alzheimer’s disease (AD) patients and normal aging healthy controls (HC) from distinct brain states. We conducted rs-fMRI scanning on 12 ADs and 12 HCs. From ICA, we got three networks including DAN, VAN and DMN. From dynamic network analysis, we achieved three dynamic states. Two sample t-test results showed that, in AD, DAN had weaker connectivity, DMN had no difference both in static and dynamic states, VAN only had increased connectivity between IFG and other regions in static state.

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