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. 2020 Jan 10;10:1358. doi: 10.3389/fneur.2019.01358

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Copyright © 2020 Pan, Wei, Ou, Jiang, Li, Lei, Liu, Guo and Luo.

This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

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3D view of classified accuracy with the best parameters using GFC values in the right precentral gyrus and right SMA to differentiate the patients from the controls. The results were obtained in LIBSVM using a “leave-one-out” approach with default Gaussian kernel. Left: Using decreased GFC values in the right SMA to differentiate the patients from the controls. Right: Using decreased GFC values in the right precentral gyrus to differentiate the patients from the controls. SVM, support vector machine; GFC, global-brain functional connectivity; SMA, supplementary motor area.