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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. 4 — a A wide distribution of node-wise Pearson correlation R across 1000 nodes. b The corresponding brain map where nodes are colored from blue to red in increasing order of R values. c Node-wide R values (n = 1000 nodes) aggregated by 7 resting-state networks (RSNs). The boxplot shows the medians (circles), interquartile ranges (boxes), and min to max range (whiskers). d The average R value of each RSN is compared with those calculated after random permutation of nodes’ assignments (10,000 repetitions). e The distribution of well-predicted nodes across seven RSNs is compared with the distribution of network size. f The spatial distribution of z scores within each RSN. Source data are provided as a Source Data file.