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Abstract #0040

Resting Brain Networks Revealed by Independent Component Analysis of Cerebral Blood Flow

Senhua Zhu1, 2, Zhuo Fang1, 2, Siyuan Hu3, Marc Korczykowski2, Ze Wang2, John A. Detre2, Hengyi Rao, 12

1Psychology, Sun Yat-sen University, Guangzhou, Guangdong, China; 2Center for Functional Neuroimaging, University of Pennsylvania, Philadelphia, PA, United States; 3State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China

The present study used independent component analysis to examine resting brain networks in a large cohort (n=149) of subjects with arterial spin labeling (ASL) perfusion MRI data. Ten CBF networks were consistently identified across the whole and sub-datasets, including the default mode network, bilateral attention networks, primary and second visual networks, auditory network, ventral-medial prefrontal network, dorsal-medial prefrontal network, and two limbic networks. These networks well replicated the resting-state BOLD networks from a sub-group (n=81) and support the feasibility of using CBF connectivity to examine resting brain function.