Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | 이종민 | - |
dc.date.accessioned | 2019-08-27T01:56:11Z | - |
dc.date.available | 2019-08-27T01:56:11Z | - |
dc.date.issued | 2019-03 | - |
dc.identifier.citation | SCIENTIFIC REPORTS, v. 9, no. 4072 | en_US |
dc.identifier.issn | 2045-2322 | - |
dc.identifier.uri | https://www.nature.com/articles/s41598-019-40699-z | - |
dc.identifier.uri | https://repository.hanyang.ac.kr/handle/20.500.11754/109953 | - |
dc.description.abstract | 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 similar to 0.08 Hz and LF2, 0.009 similar to 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. | en_US |
dc.description.sponsorship | This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIP) (2016R1A2B3016609), and the Brain Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Science, ICT & Future Planning (NRF-2014M3C7A1046050). Data were provided by the Human Connectome Project, WU-Minn Consortium (Principal Investigators: David Van Essen and Kamil Ugurbil; 1U54MH091657) funded by the 16 NIH Institutes and Centers that support the NIH Blueprint for Neuroscience Research; and by the McDonnell Center for Systems Neuroscience at Washington University. | en_US |
dc.language.iso | en | en_US |
dc.publisher | NATURE PUBLISHING GROUP | en_US |
dc.subject | POSTERIOR CINGULATE CORTEX | en_US |
dc.subject | RESTING-STATE NETWORKS | en_US |
dc.subject | FUNCTIONAL CONNECTIVITY | en_US |
dc.subject | SPONTANEOUS FLUCTUATIONS | en_US |
dc.subject | WAVELET COHERENCE | en_US |
dc.subject | FMRI | en_US |
dc.title | Frequency specific contribution of intrinsic connectivity networks to the integration in brain networks | en_US |
dc.type | Article | en_US |
dc.relation.volume | 9 | - |
dc.identifier.doi | 10.1038/s41598-019-40699-z | - |
dc.relation.page | 1-10 | - |
dc.relation.journal | SCIENTIFIC REPORTS | - |
dc.contributor.googleauthor | Park, Yeong-Hun | - |
dc.contributor.googleauthor | Cha, Jungho | - |
dc.contributor.googleauthor | Bourakova, Viktoriya | - |
dc.contributor.googleauthor | Lee, Jong-Min | - |
dc.relation.code | 2019002548 | - |
dc.sector.campus | S | - |
dc.sector.daehak | COLLEGE OF ENGINEERING[S] | - |
dc.sector.department | DIVISION OF ELECTRICAL AND BIOMEDICAL ENGINEERING | - |
dc.identifier.pid | ljm | - |
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