Unveiling functional-metabolic synergy in the healthy brain: multivariate integration of dynamic [F]FDG-PET and resting-state fMRI.

INTRODUCTION

Despite accounting for only 2% of body weight, the human brain requires significant amounts of glucose, even at rest, underscoring the importance of functional-metabolic relationships. Previous studies revealed moderate associations between resting-state fMRI functional connectivity (FC) and local metabolism via [F]FDG-PET, yet much remains to be understood, particularly regarding their coupling between functional and metabolic networks.

METHODS

To this end, we employed multivariate Partial Least Squares Correlation (PLSC) to investigate the functional-metabolic relationship at both nodal and network level. From dynamic [F]FDG-PET data we estimated parameters describing glucose metabolism -delivery rate ( ), phosphorylation rate ( ), and fractional uptake ( )- and generated within-individual metabolic connectivity (MC) networks. FC was derived from fMRI data filtered into two frequency bands and summarized as region-wise strength to capture nodal characteristics.

RESULTS

Our findings revealed that glucose delivery is linked with FC strength, particularly when fMRI signal frequencies include greater hemodynamic contributions. Even stronger functional-metabolic coupling occurs at the network level in the low-frequency fMRI band, with higher MC between sensory/attention and transmodal networks supporting stronger FC within sensory/attention areas.

CONCLUSIONS

By leveraging PLSC, this work deepens our understanding of the functional-metabolic synergy in the healthy brain, providing new insights into its organization.