The complexity of the relationship between spontaneous brain activity and glucose metabolism

Abstract

Brain glucose metabolism as assessed by [18F]FDG positron emission tomography (PET) is expected to be significantly related to resting-state functional MRI (rs-fMRI) activity and functional connectivity (FC), but the underlying coupling model is still incompletely understood. Employing simultaneous acquisitions, we related [18F]FDG standard uptake value ratio (SUVR) to 50 features pertaining to rs-fMRI 1) signal, 2) hemodynamic response, 3) static and 4) time-varying FC, and 5) phase synchronization. To assess which rs-fMRI variables better describe SUVR across regions, we employed a hierarchical approach, identifying the model at population level, and then estimating it on individual data. Multilevel modelling explained around 40% of the SUVR variance, with signal-related features as the most relevant fMRI variables. When the model was used to characterize between-network variability of the SUVR-fMRI coupling, the ranking changed. We demonstrate that local activity and synchronization are the most important predictors of glucose metabolism, while large-scale FC properties gain importance within specific networks.

A new framework for metabolic connectivity mapping using bolus [18F]FDG PET and kinetic modeling

“…It is intriguing to wonder which reasons might be behind the correspondence between pharmacokinetic similarity among brain regions and FC, but it seems the metabolic properties underlying “hubness” in the MC network might inherently be linked to a region’s capacity to connect with other regions, both locally and globally. This also indicates that the coupling between glucose metabolism and fMRI FC, which we found to be somewhat limited when considering only local metabolic measures like SUVR, 60 may become stronger when both PET and rs-fMRI are framed into a large-scale connectivity environment.…”

A new framework for metabolic connectivity mapping using bolus [18F]FDG PET and kinetic modelling

“…It is intriguing to wonder which reasons might be behind the correspondence between pharmacokinetic similarity among brain regions and FC, but it seems the metabolic properties underlying “hubness” in the MC network might inherently be linked to a region’s capacity to connect with other regions, both locally and globally. This also indicates that the coupling between glucose metabolism and fMRI FC, which we found to be somewhat limited when considering only local metabolic measures like SUVR [40], may become stronger when both PET and rs-fMRI are framed into a large-scale connectivity environment.…”