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Updated: May 5, 2026

Cerebral Blood Flow-Based Resting State Functional Connectivity of the Human Brain using Optical Diffuse Correlation Spectroscopy
Published on: May 27, 2020
Molecular connectivity studies of cerebral glucose metabolism and blood flow: A scoping review
Carlo Cavaliere1, Alice Galli2, Chiara Meneghini3
1IRCCS SYNLAB SDN, Naples, Italy.
Abstract:
The brain's functional organization relies on neural, metabolic, and vascular interactions. Molecular neuroimaging offers powerful tools for assessing macroscale brain connectivity by capturing relationships between regional perfusion and glucose metabolism. This review summarizes molecular connectivity studies of cerebral blood flow (CBF) and metabolism, focusing on methodological approaches and key findings. A systematic search across MEDLINE, EMBASE, and Scopus identified studies employing radiotracers to examine brain perfusion or glucose metabolic connectivity. Data extraction focused on tracer type, connectivity methodology, population, and clinical relevance. Overall, 384 studies were included, covering healthy condition, dementia, movement disorders, psychiatric diseases, epilepsy, and disorders of consciousness. Both resting-state and task-based paradigms were identified, with perfusion studies being popular for detecting fast task-induced molecular connectivity changes. Metabolic connectivity, assessed via [18F]FDG-PET at rest, emerged as robust marker of functional integrity and disease progression, especially in neurodegenerative conditions. Multimodal PET/MRI studies revealed partial overlap between metabolic and hemodynamic connectivity. Noteworthy findings include the identification of default mode network through the study of CBF and disease-related covariance patterns in neurodegenerative disorders through the study of glucose metabolism. Integrating macroscale molecular brain organization studies with neurophysiological techniques will deepen the understanding of brain connectivity in health and disease. Additionally, total-body PET/MRI data may in the future elucidate brain-body interactions fostering a more comprehensive connectome framework.
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