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. 2023 Oct 24;14:6744. doi: 10.1038/s41467-023-42053-4

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© The Author(s) 2023

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

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Fig. 3 — a The macroscale functional gradient spanning from unimodal to transmodal cortex. b Structure-function coupling R estimated by low-frequency eigenmodes is negatively correlated with the macroscale functional gradient. c Red: The empirical Pearson correlation coefficient ρ between coupling R and the functional gradient. Blue: the null distribution of correlation coefficients generated by randomly rotating nodes’ spatial positions (10,000 repetitions). d Red: correlation coefficient ρ of empirical data. Blue: the null distribution generated by randomizing structural architecture (10,000 repetitions). c, d We provided the empirical P values (one-sided, unadjusted), calculated as the proportion of correlation coefficients generated by the null model that were lower than the observed correlation coefficients. Source data are provided as a Source Data file.