Mapping the coupling between tract reachability and cortical geometry of the human brain

The study of cortical geometry and connectivity is prevalent in human brain research. However, these two aspects of brain structure are usually examined separately, leaving the essential connections between the brain's folding patterns and white matter connectivity unexplored. In this study, we aim to elucidate the fundamental links between cortical geometry and white matter tract connectivity. We develop the concept of tract-geometry coupling (TGC) by optimizing the alignment between tract connectivity to the cortex and multiscale cortical geometry. We confirm in two independent datasets that cortical geometry reliably characterizes tract reachability, and that TGC demonstrates high test-retest reliability and individual-specificity. Interestingly, low-frequency TGC is more heritable and behaviorally informative. Finally, we find that TGC can reproduce task-evoked cortical activation patterns and exhibits non-uniform maturation during youth. Collectively, our study provides an approach to mapping cortical geometry-connectivity coupling, highlighting how these two aspects jointly shape the connected brain.

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Publication Details

Journal
Nature Communications
Published
2025-08-12
DOI
https://doi.org/10.1038/s41467-025-62812-9
Citations
4
Primary Topic
Functional Brain Connectivity Studies
Type
article
Field-Weighted Citation Impact
5.72

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article

Mapping the coupling between tract reachability and cortical geometry of the human brain

Andreas Heinz, Sylvane Desrivières, Hugh P Garavan, Rüdiger Brühl et al.
4 citations
Nature Communications
Functional Brain Connectivity Studies
5.72
article

Mapping the coupling between tract reachability and cortical geometry of the human brain

Andreas Heinz, Sylvane Desrivières, Hugh P Garavan, Rüdiger Brühl, Tobias Banaschewski, Jean‐Luc Martinot, Marie‐Laure Paillère Martinot, Arun L.W. Bokde, Andrew Zalesky, Luqi Cheng, Liang Ma, Congying Chu, Herta Flor, Antoine Grigis, Robert Whelan, Henrik Walter, Tianye Jia, Luise Poustka, Lingzhong Fan, Hervé Lemaître, Michael N. Smolka, Dimitri Papadopoulos Orfanos, Frauke Nees, Gareth J. Barker, Penny Anne Gowland, Eric Artiges A, Haiyan Wang, Yufan Wang, Deying Li, Günter Schumann, Nilakshi Vaidya
article en
4 citations

Abstract

The study of cortical geometry and connectivity is prevalent in human brain research. However, these two aspects of brain structure are usually examined separately, leaving the essential connections between the brain's folding patterns and white matter connectivity unexplored. In this study, we aim to elucidate the fundamental links between cortical geometry and white matter tract connectivity. We develop the concept of tract-geometry coupling (TGC) by optimizing the alignment between tract connectivity to the cortex and multiscale cortical geometry. We confirm in two independent datasets that cortical geometry reliably characterizes tract reachability, and that TGC demonstrates high test-retest reliability and individual-specificity. Interestingly, low-frequency TGC is more heritable and behaviorally informative. Finally, we find that TGC can reproduce task-evoked cortical activation patterns and exhibits non-uniform maturation during youth. Collectively, our study provides an approach to mapping cortical geometry-connectivity coupling, highlighting how these two aspects jointly shape the connected brain.

Nature CommunicationsVol. 16(1)
University of Vermont (US), Physikalisch-Technische Bundesanstalt (DE), Centre National de la Recherche Scientifique (FR), University of Nottingham (GB), Université de Bordeaux (FR), Shandong University of Aeronautics (CN), Inserm (FR), The University of Melbourne (AU), University of Mannheim (DE), King's College London (GB), Chinese Academy of Sciences (CN), Trinity College Dublin (IE), Heidelberg University (DE), Fudan University (CN), Commissariat à l'Énergie Atomique et aux Énergies Alternatives (FR), Université Paris-Saclay (FR), University Hospital Heidelberg (DE), Christian-Albrechts-Universität zu Kiel (DE), Humboldt-Universität zu Berlin (DE), Sorbonne Université (FR), Shanghai Institute for Science of Science (CN), Institut des Maladies Neurodégénératives (FR), Assistance Publique – Hôpitaux de Paris (FR), Beijing Academy of Artificial Intelligence (CN), Central Institute of Mental Health (DE), Institute of Automation (CN), Chinese Institute for Brain Research (CN), Pitié-Salpêtrière Hospital (FR), CEA Paris-Saclay (FR), Laboratoire de Biologie et Pharmacologie Appliquée (FR), Shanghai Center for Brain Science and Brain-Inspired Technology (CN), Health & Life (Taiwan) (TW), University of Chinese Academy of Sciences (CN), Guilin University of Electronic Technology (CN), Victoria University (AU), Technische Universität Dresden (DE), Charité - Universitätsmedizin Berlin (DE)
National Natural Science Foundation of China, Natural Science Foundation of Guangxi Province, National Institutes of Health, McDonnell Center for Systems Neuroscience
Openalex Percentile: Top 4%
Functional Brain Connectivity Studies
5.72
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