Identification of Resting State Networks Using Whole-Brain CASL

Jingyi Xie¹, Peter Jezzard¹, Linqing Li¹, Yazhuo Kong¹, Christian F. Beckmann^1,2, Karla L. Miller¹, Stephen M. Smith¹

There is increasing interest in resting brain activity. However, to our knowledge, ASL has not yet been used to study RSNs across the whole brain with single timeseries acquisitions. In this study, we implemented a novel true whole-brain CASL technique with EPI readout to study dynamic characteristics of cerebral blood flow during the resting state. We extracted the major covarying networks in the resting brain, as imaged in 8 subjects at rest. The major brain networks are highly similar to recent published results obtained using BOLD fMRI. We also characterised very low-frequency RSN temporal behaviour for the first time.