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. 2021 Oct 26;11:21036. doi: 10.1038/s41598-021-00508-y

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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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Temporal properties of the FC states analyses. (A) Bar plot represents the fractional time windows from the 2-states solution, quantitative temporal metrics from the sliding windows k-means clustering approach are represented as box plots, namely dwell time of States 1 and 2 and number of transitions. TM and CM had significant differences in the time they dwelled in State 2. The meta-state dynamic metrics are charted as violin plots. CM differed from CW and TM in the change of meta-states and the total distance between clusters. (B) FC differences in State 2 from the 2-states solution between CM < TM using the threshold-free network-based statistics. L SMA, left supplementary motor area; R Supram, right supramarginal. Surf Ice software was used (https://www.nitrc.org/projects/surfice/). (C) Bar plot represents the fractional time windows from the 4-states solution, quantitative temporal metrics from the sliding windows k-means clustering approach are represented as box plots, namely dwell time of States 1, 2, 3 and 4 and number of transitions. Finally, violin plots represent the 4-states cluster solution of the meta-state dynamics method. Plots were obtained with the ggpubr library (https://cran.r-project.org/web/packages/ggpubr/index.html) using the RStudio v1.4.1106 (PBC, Boston, MA, http://www.rstudio.com/). *Multiple comparison post-hoc test P < 0.05.