Mapping human brain networks using resting-state metabolic connectivity: concepts, methods, and foundational results.

Abstract

The human brain is a complex network, whose functional properties are constrained by its anatomy and energetic constraints. Metabolic connectivity refers to coherent metabolic interactions between spatially distinct regions, and is most commonly measured using [18F]-fluorodeoxyglucose (FDG) positron emission tomography (PET). While metabolic connectivity as a field predates fMRI-derived functional connectivity measures, it was not until recently that it was possible to estimate a metabolic network at the individual person level. Here, we review the theoretical and historical contexts of metabolic connectivity, its physiological bases, major methodological approaches, and key findings in health and disease. The review highlights that metabolic connectivity yields unique insight into the functional interactions of the brain relative to fMRI, is predictive of cognition and individual phenotype, and displays unique patterns of time-variant state switching and gradient architecture. We conclude the review with a forward-looking perspective of the future of metabolic connectivity, and recommendations for extending the conceptual framework of the measure.