Abstract
Gradients provide low-dimensional representations of macroscale brain organization, yet how structural-functional gradient coupling develops and relates to behavioral and molecular features remains unclear. Here, we studied structural-functional gradient coupling across multiple metrics and spatial scales using high-resolution structural and functional connectivity from 5343 children in the Adolescent Brain Cognitive Development study and 875 adults from the Human Connectome Project. We find that gradient coupling shows developmental refinement from childhood to adulthood and distinct sex-specific patterns. Gradient coupling metrics are significantly associated with cognitive and mental health measures and enable robust out-of-sample prediction. Heritability analyses reveal that gradient coupling is strongly influenced by genetic factors. Transcriptomic analyses further demonstrate that highly heritable coupling patterns are enriched for genes expressed in deep-layer excitatory neurons. Together, our findings establish structural-functional gradient coupling as a biologically meaningful feature of brain organization that bridges macroscale connectivity, cognition, behavior, and molecular architecture.
Data availability
Neuroimaging and behavioral data from the ABCD Study can be obtained via the NIH Data Archive (https://nda.nih.gov/abcd) with approval from the ABCD consortium. Neuroimaging data and most behavioral measures from the HCP-YA are publicly available at https://db.humanconnectome.org; access to restricted data is subject to approval. Data from the HCP-D study are available through the NIH Data Archive (https://nda.nih.gov) and require approval for access. The raw data are protected and are not available due to data privacy laws and the terms of the original ethical approvals. Source data are provided with this paper. The data are supplied in multiple formats, including Python pickle (.pkl) files, which can be read using standard Python packages such as pickle or pandas. Source data are provided with this paper.
Code availability
The data preprocessing software FreeSurfer v6.0 is available at https://surfer.nmr.mgh.harvard.edu/. The Surface-Based Connectivity Integration pipeline can be accessed at https://github.com/sbci-brain/SBCI_Pipeline, and the BrainSpace toolbox is available at https://github.com/MICA-MNI/BrainSpace/tree/master. Python (2.7 and 3.12) and R v4.4 were used for data processing and analysis. Code used in this study is publicly available at https://github.com/Zhao-team/SF-Gradient-Coupling.git and stored at https://doi.org/10.5281/zenodo.1891252268.
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Acknowledgements
S.G., Z.G., S.D., G.W., and Y.Z. were partially supported by National Institutes of Health (NIH) grants R01AG068191, RF1AG081413 and R01EB034720 to Y.Z. We express our sincere gratitude to the participants and researchers of the ABCD Study and the HCP, and gratefully acknowledge the use of data from both consortia in this research. ABCD data were obtained from the ABCD study, held in the National Institute of Mental Health Data Archive. This is a multisite, longitudinal study designed to recruit more than 10,000 children age 9–10 years and follow them over 10 years into early adulthood. The ABCD study is supported by the NIH and additional federal partners under award numbers U01DA041022, U01DA041028, U01DA041048, U01DA041089, U01DA041106, U01DA041117, U01DA041120, U01DA041134, U01DA041148, U01DA041156, U01DA041174, U24DA041123, U24DA041147, U01DA041093 and U01DA041025. A full list of supporters is available at https://abcdstudy.org/federal-partners.html. A listing of participating sites and a complete listing of the study investigators can be found at https://abcdstudy.org/scientists/workgroups/. ABCD consortium investigators designed and implemented the study and/or provided data but did not necessarily participate in analysis or writing of this report. All procedures in the ABCD study were approved by the institutional review boards at ABCD collection sites (approval numbers 201708123 and 160091). HCP-YA and HCP-D data were provided by the HCP, WU-Minn Consortium (principal investigators D. Van Essen and K. Ugurbil; 1U54MH091657) funded by the 16 NIH institutes and centers that support the NIH Blueprint for Neuroscience Research and the McDonnell Center for Systems Neuroscience at Washington University. All experimental procedures in the HCP were approved by the institutional review boards at Washington University (approval number 201204036).
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These authors contributed equally: Simiao Gao, Zhiling Gu, Shengxian Ding. Y.Z., S.G., Z.G., and S.D. conceptualized and designed the study. Z.Z. and H.Z. collected and processed the data. S.G., Z.G., S.D., and G.W. analyzed the data. S.G., Z.G., and S.D. wrote the initial draft of the manuscript, and all authors edited and reviewed the final manuscript.
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Gao, S., Gu, Z., Ding, S. et al. Brain functional-structural gradient coupling reflects development, behavior and genetic influences. Nat Commun (2026). https://doi.org/10.1038/s41467-026-71719-y
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DOI: https://doi.org/10.1038/s41467-026-71719-y
