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.