Scale-integrated Network Hubs of the White Matter Structural Network
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Kwon, Hunki | - |
dc.contributor.author | Choi, Yong-Ho | - |
dc.contributor.author | Seo, Sang Won | - |
dc.contributor.author | Lee, Jong Min | - |
dc.date.accessioned | 2022-07-14T06:52:24Z | - |
dc.date.available | 2022-07-14T06:52:24Z | - |
dc.date.created | 2021-05-12 | - |
dc.date.issued | 2017-05 | - |
dc.identifier.issn | 2045-2322 | - |
dc.identifier.uri | https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/152465 | - |
dc.description.abstract | The 'human connectome' concept has been proposed to significantly increase our understanding of how functional brain states emerge from their underlying structural substrates. Especially, the network hub has been considered one of the most important topological properties to interpret a network as a complex system. However, previous structural brain connectome studies have reported network hub regions based on various nodal resolutions. We hypothesized that brain network hubs should be determined considering various nodal scales in a certain range. We tested our hypothesis using the hub strength determined by the mean of the "hubness" values over a range of nodal scales. Some regions of the precuneus, superior occipital gyrus, and superior parietal gyrus in a bilaterally symmetric fashion had a relatively higher level of hub strength than other regions. These regions had a tendency of increasing contributions to local efficiency than other regions. We proposed a methodological framework to detect network hubs considering various nodal scales in a certain range. This framework might provide a benefit in the detection of important brain regions in the network. | - |
dc.language | 영어 | - |
dc.language.iso | en | - |
dc.publisher | NATURE PUBLISHING GROUP | - |
dc.title | Scale-integrated Network Hubs of the White Matter Structural Network | - |
dc.type | Article | - |
dc.contributor.affiliatedAuthor | Lee, Jong Min | - |
dc.identifier.doi | 10.1038/s41598-017-02342-7 | - |
dc.identifier.scopusid | 2-s2.0-85019662145 | - |
dc.identifier.wosid | 000402045300017 | - |
dc.identifier.bibliographicCitation | SCIENTIFIC REPORTS, v.7, no.1 | - |
dc.relation.isPartOf | SCIENTIFIC REPORTS | - |
dc.citation.title | SCIENTIFIC REPORTS | - |
dc.citation.volume | 7 | - |
dc.citation.number | 1 | - |
dc.type.rims | ART | - |
dc.type.docType | Article | - |
dc.description.journalClass | 1 | - |
dc.description.isOpenAccess | Y | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
dc.relation.journalResearchArea | Science & Technology - Other Topics | - |
dc.relation.journalWebOfScienceCategory | Multidisciplinary Sciences | - |
dc.subject.keywordPlus | HUMAN CEREBRAL-CORTEX | - |
dc.subject.keywordPlus | ABNORMAL TOPOLOGICAL ORGANIZATION | - |
dc.subject.keywordPlus | GENDER-RELATED DIFFERENCES | - |
dc.subject.keywordPlus | BRAIN ANATOMICAL NETWORKS | - |
dc.subject.keywordPlus | CORTICAL NETWORKS | - |
dc.subject.keywordPlus | MRI DATA | - |
dc.subject.keywordPlus | MULTIPLE-SCLEROSIS | - |
dc.subject.keywordPlus | ALZHEIMERS-DISEASE | - |
dc.subject.keywordPlus | HUMAN CONNECTOME | - |
dc.subject.keywordPlus | CONNECTIVITY | - |
dc.identifier.url | https://www.nature.com/articles/s41598-017-02342-7 | - |
Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.
222, Wangsimni-ro, Seongdong-gu, Seoul, 04763, Korea+82-2-2220-1365
COPYRIGHT © 2021 HANYANG UNIVERSITY.
Certain data included herein are derived from the © Web of Science of Clarivate Analytics. All rights reserved.
You may not copy or re-distribute this material in whole or in part without the prior written consent of Clarivate Analytics.