Reproducible cortical links between functional hierarchy, structure, and metabolism.

Authors

Dardo Tomasi, Nora D Volkow

Published in

Proceedings of the National Academy of Sciences of the United States of America. Volume 123. Issue 40. Pages e2614926123. Oct 06, 2026. Epub Sep 29, 2026.

Abstract

Large-scale functional connectivity gradients provide a compact description of cortical organization, capturing hierarchical transitions from unimodal sensory systems to transmodal association cortex. Although these gradients have become a central framework for studying macroscale brain organization, it remains unclear whether they systematically map onto regional cortical biology. Here we show that functional gradient position robustly predicts cortical thickness and regional glucose metabolism, measured with MRI and FDG-PET respectively. Modeling parcelwise cortical thickness and glucose metabolism as linear combinations of signed and amplitude components along functional gradients explained substantial variance in both measures across individuals, with signed gradient terms improving prediction in every subject. These relationships generalized across scanning sessions and independent cohorts and remained significant under spatial permutation testing. Gradient-based models outperformed classical graph-theoretic connectivity metrics, whereas nonlinear extensions did not improve performance. Cortical myelin was selectively associated with the signed component of the principal gradient, without an amplitude effect, and this pattern replicated across developmental, adult, and aging cohorts, supporting a microstructural basis for gradient-cortical thickness coupling. In contrast, gradient associations with glucose metabolism remained largely intact after controlling for myelination, indicating additional biological determinants. These findings establish functional gradients as a reproducible framework linking cortical hierarchy to structure and metabolism.

PMID:
42809405
Bibliographic data and abstract were imported from PubMed on 30 Sep 2026.

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