Abstract #5543

Dynamic network analysis reveals altered temporal variability in brain regions after brain stroke: A longitudinal resting-state fMRI study

Jianping Hu^1,2, Juan Du³, Qiang Xu⁴, Fang Yang³, Fanyong Zeng³, Zhiqiang Zhang⁴, and Guangming Lu⁴

¹Department of Medical Imaging, Jinling Hospital, Nanjing Clinical School, Southern Medical University, Nanjing, China, Nanjing, China, ²Department of Radiology,The First Affiliated Hospital, Fujian Medical University, Fuzhou, China., Fuzhou, China, ³Department of Neurology, Jinling Hospital, Nanjing University School of Medicine, Nanjing, China, Nanjing, China, ⁴Department of Medical Imaging, Jinling Hospital, Nanjing University School of Medicine, Nanjing, China, Nanjing, China

In this work, we seek to investigate the longitudinal alteration of temporal variability in
resting-state brain network after cerebral stroke, by using a novel dynamic network analysis. Our study
illustrated a time dependent alteration of temporal variability in brain networks following stroke
recovery. These findings expand our understanding for dynamic properties of brain networks and
provide new insight into the underlying mechanisms of reorganization and integration of functional
networks over the recovery process after stroke.

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