The overall goal of this work is to optimize arterial spin labeling (ASL) MRI techniques to enable the use of baseline cerebral blood flow (CBF) fluctuations to identify major intrinsically-connected resting state networks (RSNs). We provide data in support of 3D GRASE pCASL being able to provide similar functional resting state networks as BOLD. Additionally, extremely low-frequency fluctuations, less than 0.01 Hz, were present in the CBF-weighted pCASL data, suggesting that application of pCASL may provide additional functional information relative to BOLD, which generally requires low-frequency filtering.
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