Evidence map›Paper›PMID 42576072›Full record

ArticleEuropean journal of nuclear medicine and molecular imaging2026

Human cerebral cortex organization characterized by functional PET-FDG "Metabolic Connectivity".

Penghui Du, Sean E Coursey, Ting Xu, Sharna Jamadar, Sara Nolin, Bin Wan, Hsiao-Ying Wey, Jonathan R Polimeni, Julie C Price, Quanying Liu and 1 more

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Article in European journal of nuclear medicine and molecular imaging, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

Who cites it

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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

11 authors.

Penghui DuAthinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Brigham, Boston, MA, USA. penghui-du@outlook.com.
Sean E CourseyAthinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Brigham, Boston, MA, USA.
Ting XuChild Mind Institute, New York, USA.
Sharna JamadarSchool of Psychological Sciences, Monash University, Melbourne, Australia.
Sara NolinAthinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Brigham, Boston, MA, USA.
Bin WanDepartment of Psychiatry, University Hospitals of Genève, Thonex, Switzerland.
Hsiao-Ying WeyAthinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Brigham, Boston, MA, USA.
Jonathan R PolimeniAthinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Brigham, Boston, MA, USA.
Julie C PriceAthinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Brigham, Boston, MA, USA.
Quanying LiuDepartment of Biomedical Engineering, Southern University of Science and Technology, Shenzhen, China.
Jingyuan E ChenAthinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Brigham, Boston, MA, USA. jechen@mgh.harvard.edu.ORCID http://orcid.org/0000-0003-3686-2983

Funding

Australian Research Council FT250100206Brain and Behavior Research Foundation 31198BrightFocus Foundation A2023011SNIMH NIH HHS R21-MH135201NINDS NIH HHS K99-NS118120NINDS NIH HHS R00-NS118120Rappaport Foundation Rappaport Foundation
6 · The paper itself

Abstract

purposeIn this study, we characterize the spatiotemporal organization of resting-state metabolic connectivity (RSMC) in the human brain, as measured by [

methodsResting-state fPET-FDG data from 24 individuals were obtained from a publicly available repository (Monash rsPET-MR Dataset). We characterized local metabolic organization using connectivity-based boundary mapping, with adaptations to account for the low signal-to-noise ratio of fPET-FDG data. We then estimated global metabolic organization through community detection-based network and principal gradient analyses. Furthermore, we examined how metabolic connectivity is shaped by temporal-frequency-specific components of fPET-FDG signal. Finally, we contextualized metabolic organization by relating metabolic gradients to anatomical, functional, and energetic reference measures.

resultsAt the local scale, boundary mapping results revealed structured transitions shaped by a combination of both fast and slow fPET-FDG signals, partly overlapping with RSFC boundary maps. Globally, RSMC analyses revealed a robust metabolic structure organized along a superior-inferior cortical gradient. This pattern remained consistent across network community detection and principal gradient analyses and was primarily driven by low-frequency, minute-scale fPET-FDG dynamics. The identified large-scale metabolic profile aligns closely with several known anatomical and energetic constraints.

conclusionThis study characterizes the spatiotemporal organizational principles of RSMC, deepening insight into the brain's energetic framework and providing a basis for future cognitive and clinical investigations of metabolic connectivity organization.

Indexed as

Functional connectivityFunctional PET-FDGGlucose metabolismMetabolic connectivityPET–MRI

Identifiers

PMID42576072

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.