The link to steady-state oxidative metabolism and hemodynamics varies across rs-fMRI metrics: A whole-brain...

One of the major obstacles to the clinical application of resting-state functional magnetic resonance imaging (rs-fMRI) is the complex nature of its measurements, which limits interpretability. An approach to enhance the interpretability of the rs-fMRI metrics is to link them to more fundamental brain physiology, especially cerebral metabolism. Previous studies have established associations between glucose metabolism (CMR_glu) and rs-fMRI measurements. In spite of this, oxidative metabolism (CMRO₂) is more closely related to cerebral blood flow (CBF) and thus the blood-oxygenation level-dependent (BOLD) signal, and its relationship with CMR_glu is complex. Additionally, most currently published rs-fMRI metrics are uncorrected for macrovascular contribution, which may obscure the neuronal contributions. In this study, we measured resting CMRO₂ (along with the oxygen extraction fraction, OEF, and cerebral blood flow, CBF) using gas-free calibrated fMRI. We used linear mixed-effects (LME) models to examine associations between CMRO₂ and various rs-fMRI metrics before and after macrovascular correction. We found that (1) significant associations existed between CMRO₂ and multiple rs-fMRI metrics, with the strongest association found for the global functional density (gFCD) and the weakest for seed-based functional connectivity (FC); (2) associations with rs-fMRI metrics also varied for OEF and CBF; (3) significant sex differences were observed in the above associations; (4) the use of macrovascular correction substantially strengthened the goodness fit of all LME models examined. The latter improvement further validates the use of macrovascular correction in rs-fMRI. These results provide a framework for linking rs-fMRI metrics to fundamental brain physiology, thus improving interpretability of rs-fMRI measurements. This is the first study to formally link whole-brain MRI-based baseline CMRO₂ and rs-fMRI metrics, and helps to push the envelope for rs-fMRI in future clinical applications.