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. 2019 Mar 11;9:4072. doi: 10.1038/s41598-019-40699-z

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© The Author(s) 2019

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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Construction of the connectivity matrix and division frequency bands. (a) A connectivity matrix was constructed for each frequency bin by using Pearson’s correlation coefficient of each power spectral density (PSD) time-course through all nodes. The black rectangular small box indicates PSD time-course of specific frequencies. A 141 × 141 connectivity matrix of specific frequencies with a total of 101 frequency bins is presented. (b) The hierarchical clustering between group averaged connectivity matrices of each frequency was calculated by using Jensen Shannon divergence. For the highest silhouette value, 101 frequency matrices were clustered into 2 subbands. (c) Probability of clustering index for each frequency bin. Since the probability of the intermediate frequency band is uncertain, only the frequency bands at both ends were defined as the final 2 subbands (LF1: 0.03–0.08 Hz, LF2: 0.009–0.012 Hz).