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Related Experiment Video

Updated: Feb 28, 2026

Studying Metabolic Brain Connectivity Using 2-Deoxy-2-[18F]Fluoro-D-Glucose Dynamic Positron Emission Tomography at the Single-subject Level

Studying Metabolic Brain Connectivity Using 2-Deoxy-2-[¹⁸F]Fluoro-D-Glucose Dynamic Positron Emission Tomography at the Single-subject Level

Published on: January 24, 2025

Human Cerebral Cortex Organization Characterized by Functional PET-FDG "Metabolic Connectivity".

Penghui Du^1,2,3, Sean E Coursey^1,4, Ting Xu⁵

¹Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Brigham, Boston, MA, USA.

Biorxiv : the Preprint Server for Biology

|February 27, 2026

Summary

This summary is machine-generated.

This study reveals the brain's resting-state metabolic connectivity (RSMC) follows a superior-inferior gradient, influenced by [18F]-fluorodeoxyglucose (FDG) dynamics. These findings offer insights into brain energy organization for future research.

Keywords:

Functional PET-FDG PET–MRI functional connectivity glucose metabolism metabolic connectivity

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Cerebral Blood Flow-Based Resting State Functional Connectivity of the Human Brain using Optical Diffuse Correlation Spectroscopy

Cerebral Blood Flow-Based Resting State Functional Connectivity of the Human Brain using Optical Diffuse Correlation Spectroscopy

Published on: May 27, 2020

Area of Science:

Neuroscience
Brain Imaging
Metabolic Connectivity

Background:

Resting-state functional connectivity (RSFC) is well-studied using fMRI.
The spatial organization of brain metabolism at rest is less understood.
Metabolic connectivity provides insights into the brain's energetic framework.

Purpose of the Study:

To characterize the spatiotemporal organization of resting-state metabolic connectivity (RSMC) in the human brain using [18F]-fluorodeoxyglucose functional PET (fPET-FDG).
To examine the relationship between RSMC organization and RSFC.
To explore how RSMC relates to cortical organization principles.

Main Methods:

Analyzed resting-state fPET-FDG data from 24 individuals.
Utilized connectivity-based boundary mapping for local metabolic organization.
Employed community detection and principal gradient analyses for global metabolic organization.
Investigated the influence of temporal-frequency-specific fPET-FDG signals.
Related metabolic gradients to anatomical, functional, and energetic measures.

Main Results:

Local RSMC showed structured transitions, partly overlapping with RSFC.
Global RSMC revealed a robust organization along a superior-inferior cortical gradient.
This gradient was primarily driven by low-frequency fPET-FDG dynamics.
The metabolic organization aligns with known anatomical and energetic constraints.

Conclusions:

Characterized the spatiotemporal organizational principles of RSMC.
Deepened understanding of the brain's energetic framework.
Provided a foundation for future cognitive and clinical studies on metabolic connectivity.