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. 2021 Jan 12;11:845. doi: 10.1038/s41598-020-80909-7

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© The Author(s) 2021

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 licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence 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 licence, visit http://creativecommons.org/licenses/by/4.0/.

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Steps for assessing the networks of cortical thickness covariance. (a) Matrix of the morphometric descriptor (cortical thickness) for the Destrieux parcellation. (b) The data matrix was substituted by residuals of the linear regression to subtract effects of age, gender, interaction age–gender, and the global effect (global mean cortical thickness) represented in (c). (d) Correlation matrix representing the concurrent changes among all pairs of anatomical structures. (e) The thresholding process for different sparsity levels to generate binary graphs. (f) Assessment of the network properties for all binary graphs obtained in (e).