In this study, the static and dynamic characteristics of cerebral blood flow (CBF) in the resting state were investigated using an arterial spin labeling (ASL) perfusion imaging technique. Consistent with previous PET results, static CBF measured by ASL was significantly higher in the posterior cingulate cortex (PCC), thalamus, insula/superior temporal gyrus (STG) and medial prefrontal cortex (MPFC) than the average CBF of the brain. The dynamic measurement of CBF fluctuations showed high correlation (functional connectivity) between components in the default mode network. These brain regions also had high local temporal synchrony and high fluctuation amplitude, as measured by regional homogeneity (ReHo) and amplitude of low-frequency fluctuations (ALFF) analyses. The spatial pattern of the static CBF correlated well with that of the dynamic indices. The high static and dynamic activity in the PCC, MPFC, insula/STG and thalamus suggest that these regions play a vital role in maintaining and facilitating fundamental brain functions.

Synchronized low-frequency spontaneous fluctuations of the functional MRI (fMRI) signal have been shown to be associated with electroencephalography (EEG) power fluctuations in multiple brain networks within predefined frequency bands. However, it remains unclear whether frequency-specific characteristics exist in the resting-state fMRI signal. In this study, fMRI signals in five functional brain networks (sensorimotor, ‘default mode’, visual, amygdala, and hippocampus) were decomposed into various frequency bands within a low frequency range (0–0.24 Hz). Results show that the correlations in cortical networks concentrate within ultra-low frequencies (0.01–0.06 Hz) while connections within limbic networks distribute over a wider frequency range (0.01–0.14 Hz), suggesting distinct frequency-specific features in the resting-state fMRI signal within these functional networks. Moreover, the connectivity decay rates along the frequency bands are positively correlated with the physical distances between connected brain regions and seed points. This distance-frequency relationship might be attributed to a larger attenuation of synchrony of brain regions separated with longer distance and/or connected with more synaptic steps.