Abstract
The correspondence between cerebral glucose metabolism (indexing energy utilization) and synchronous fluctuations in blood oxygenation (indexing neuronal activity) is relevant for neuronal specialization and is affected by brain disorders. Here, we define novel measures of relative power (rPWR, extent of concurrent energy utilization and activity) and relative cost (rCST, extent that energy utilization exceeds activity), derived from FDG-PET and fMRI. We show that resting-state networks have distinct energetic signatures and that brain could be classified into major bilateral segments based on rPWR and rCST. While medial-visual and default-mode networks have the highest rPWR, frontoparietal networks have the highest rCST. rPWR and rCST estimates are generalizable to other indexes of energy supply and neuronal activity, and are sensitive to neurocognitive effects of acute and chronic alcohol exposure. rPWR and rCST are informative metrics for characterizing brain pathology and alternative energy use, and may provide new multimodal biomarkers of neuropsychiatric disorders.
Highlights
The correspondence between cerebral glucose metabolism and synchronous fluctuations in blood oxygenation is relevant for neuronal specialization and is affected by brain disorders
In a two-dimensional map of lFCDCMRglc (Fig. 1e), we performed an orthogonal transformation with a counterclockwise π/4 (45°) rotation of axes (Fig. 1e; see Methods) and defined an relative power (rPWR) axis along which the positive end indicated high CMRglc associated with high lFCD and the negative end indicated low CMRglc associated with low lFCD
We showed that brain regions can be classified into major segments with distinct rPWR and relative cost (rCST) characteristics (Fig. 3d) and that resting-state networks differ in their rPWR and rCST (Fig. 2d, e)
Summary
The correspondence between cerebral glucose metabolism (indexing energy utilization) and synchronous fluctuations in blood oxygenation (indexing neuronal activity) is relevant for neuronal specialization and is affected by brain disorders. We propose an approach to quantify match and mismatch between measured metabolic supply and the observed level of activity across the brain and assessed whether this quantification is relevant for studying distinct energetic characteristics of brain regions and networks For this purpose, we measured cerebral metabolic rate of glucose (CMRglc, indexed by18F-flurodeoxyglucose; fluorodeoxyglucose-positron emission tomography (FDG-PET), see Methods) and synchronous fluctuations in the blood oxygenation level dependent (BOLD; measured by fMRI and indexed by local functional connectivity density: lFCD, see Methods) during resting state. We test the hypothesis that different brain networks have distinct rPWR and rCST signatures We use this characterization of the brain’s lFCD-CMRglc dynamics (indexing important components of neuronal activity demand and metabolic supply) and classify the brain into major segments based on rPWR and rCST.
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