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Frequency specific contribution of intrinsic connectivity networks to the integration in brain networks
Brain networks are integrated and segregated into several intrinsic connectivity networks (ICNs). Frequency specificity of ICNs have been studied to show that different ICNs have a unqiue contribution to brain network integration along frequencies. The purpose of this study was to evaluate the contr...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6412043/ https://www.ncbi.nlm.nih.gov/pubmed/30858433 http://dx.doi.org/10.1038/s41598-019-40699-z |
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author | Park, Yeong-Hun Cha, Jungho Bourakova, Viktoriya Lee, Jong-Min |
author_facet | Park, Yeong-Hun Cha, Jungho Bourakova, Viktoriya Lee, Jong-Min |
author_sort | Park, Yeong-Hun |
collection | PubMed |
description | Brain networks are integrated and segregated into several intrinsic connectivity networks (ICNs). Frequency specificity of ICNs have been studied to show that different ICNs have a unqiue contribution to brain network integration along frequencies. The purpose of this study was to evaluate the contribution of individual ICN to brain network integration along their frequency. We used 14 ICNs and determined 2 frequency bands (LF1, 0.03~0.08 Hz and LF2, 0.009~0.012 Hz) from the hierarchical clustering of 101 frequency bins. We proposed a novel measure, called ICN efficiency, representing the difference between the global efficiencies of the whole brain network with and without the ICN to evaluate the contribution of the ICN to brain network integration. We found that each ICN had a different ICN efficiency at 2 frequency bands. We also found that the distinct subregions of the same ICN had a frequency specific contribution to brain network integration. Futhermore, the integration with other ICNs of the distinct subregions of the same ICN were different at 2 frequency bands. In conclusion, the contribution of each ICN to brain network integration is frequency specific and distinct subregions of the same ICN have functionally distinct roles with other ICNs at 2 frequency bands. |
format | Online Article Text |
id | pubmed-6412043 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-64120432019-03-13 Frequency specific contribution of intrinsic connectivity networks to the integration in brain networks Park, Yeong-Hun Cha, Jungho Bourakova, Viktoriya Lee, Jong-Min Sci Rep Article Brain networks are integrated and segregated into several intrinsic connectivity networks (ICNs). Frequency specificity of ICNs have been studied to show that different ICNs have a unqiue contribution to brain network integration along frequencies. The purpose of this study was to evaluate the contribution of individual ICN to brain network integration along their frequency. We used 14 ICNs and determined 2 frequency bands (LF1, 0.03~0.08 Hz and LF2, 0.009~0.012 Hz) from the hierarchical clustering of 101 frequency bins. We proposed a novel measure, called ICN efficiency, representing the difference between the global efficiencies of the whole brain network with and without the ICN to evaluate the contribution of the ICN to brain network integration. We found that each ICN had a different ICN efficiency at 2 frequency bands. We also found that the distinct subregions of the same ICN had a frequency specific contribution to brain network integration. Futhermore, the integration with other ICNs of the distinct subregions of the same ICN were different at 2 frequency bands. In conclusion, the contribution of each ICN to brain network integration is frequency specific and distinct subregions of the same ICN have functionally distinct roles with other ICNs at 2 frequency bands. Nature Publishing Group UK 2019-03-11 /pmc/articles/PMC6412043/ /pubmed/30858433 http://dx.doi.org/10.1038/s41598-019-40699-z Text en © 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/. |
spellingShingle | Article Park, Yeong-Hun Cha, Jungho Bourakova, Viktoriya Lee, Jong-Min Frequency specific contribution of intrinsic connectivity networks to the integration in brain networks |
title | Frequency specific contribution of intrinsic connectivity networks to the integration in brain networks |
title_full | Frequency specific contribution of intrinsic connectivity networks to the integration in brain networks |
title_fullStr | Frequency specific contribution of intrinsic connectivity networks to the integration in brain networks |
title_full_unstemmed | Frequency specific contribution of intrinsic connectivity networks to the integration in brain networks |
title_short | Frequency specific contribution of intrinsic connectivity networks to the integration in brain networks |
title_sort | frequency specific contribution of intrinsic connectivity networks to the integration in brain networks |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6412043/ https://www.ncbi.nlm.nih.gov/pubmed/30858433 http://dx.doi.org/10.1038/s41598-019-40699-z |
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