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Rich-club in the brain's macrostructure: Insights from graph theoretical analysis

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dc.contributor.authorKim, Dae-Jin-
dc.contributor.authorMin, Byoung-Kyong-
dc.date.accessioned2021-08-31T16:21:39Z-
dc.date.available2021-08-31T16:21:39Z-
dc.date.created2021-06-18-
dc.date.issued2020-
dc.identifier.issn2001-0370-
dc.identifier.urihttps://scholar.korea.ac.kr/handle/2021.sw.korea/59122-
dc.description.abstractThe brain is a complex network. Growing evidence supports the critical roles of a set of brain regions within the brain network, known as the brain's cores or hubs. These regions require high energy cost but possess highly efficient neural information transfer in the brain's network and are termed the rich-club. The rich-club of the brain network is essential as it directly regulates functional integration across multiple segregated regions and helps to optimize cognitive processes. Here, we review the recent advances in rich-club organization to address the fundamental roles of the rich-club in the brain and discuss how these core brain regions affect brain development and disorders. We describe the concepts of the rich-club behind network construction in the brain using graph theoretical analysis. We also highlight novel insights based on animal studies related to the rich-club and illustrate how human studies using neuroimaging techniques for brain development and psychiatric/neurological disorders may be relevant to the rich-club phenomenon in the brain network. (C) 2020 The Author(s). Published by Elsevier B.V. on behalf of Research Network of Computational and Structural Biotechnology.-
dc.languageEnglish-
dc.language.isoen-
dc.publisherELSEVIER-
dc.subjectFUNCTIONAL CONNECTIVITY-
dc.subjectCOMMUNITY STRUCTURE-
dc.subjectHUMAN CONNECTOME-
dc.subjectSMALL-WORLD-
dc.subjectTOPOLOGICAL ORGANIZATION-
dc.subjectCORTICAL THICKNESS-
dc.subjectNETWORK STRUCTURE-
dc.subjectHUB CONNECTIVITY-
dc.subjectSTRUCTURAL CORE-
dc.subjectSCHIZOPHRENIA-
dc.titleRich-club in the brain's macrostructure: Insights from graph theoretical analysis-
dc.typeArticle-
dc.contributor.affiliatedAuthorMin, Byoung-Kyong-
dc.identifier.doi10.1016/j.csbj.2020.06.039-
dc.identifier.scopusid2-s2.0-85087587463-
dc.identifier.wosid000607338200005-
dc.identifier.bibliographicCitationCOMPUTATIONAL AND STRUCTURAL BIOTECHNOLOGY JOURNAL, v.18, pp.1761 - 1773-
dc.relation.isPartOfCOMPUTATIONAL AND STRUCTURAL BIOTECHNOLOGY JOURNAL-
dc.citation.titleCOMPUTATIONAL AND STRUCTURAL BIOTECHNOLOGY JOURNAL-
dc.citation.volume18-
dc.citation.startPage1761-
dc.citation.endPage1773-
dc.type.rimsART-
dc.type.docTypeReview-
dc.description.journalClass1-
dc.description.journalRegisteredClassscie-
dc.description.journalRegisteredClassscopus-
dc.relation.journalResearchAreaBiochemistry & Molecular Biology-
dc.relation.journalResearchAreaBiotechnology & Applied Microbiology-
dc.relation.journalWebOfScienceCategoryBiochemistry & Molecular Biology-
dc.relation.journalWebOfScienceCategoryBiotechnology & Applied Microbiology-
dc.subject.keywordPlusFUNCTIONAL CONNECTIVITY-
dc.subject.keywordPlusCOMMUNITY STRUCTURE-
dc.subject.keywordPlusHUMAN CONNECTOME-
dc.subject.keywordPlusSMALL-WORLD-
dc.subject.keywordPlusTOPOLOGICAL ORGANIZATION-
dc.subject.keywordPlusCORTICAL THICKNESS-
dc.subject.keywordPlusNETWORK STRUCTURE-
dc.subject.keywordPlusHUB CONNECTIVITY-
dc.subject.keywordPlusSTRUCTURAL CORE-
dc.subject.keywordPlusSCHIZOPHRENIA-
dc.subject.keywordAuthorRich-club-
dc.subject.keywordAuthorBrain connectivity-
dc.subject.keywordAuthorBrain network-
dc.subject.keywordAuthorGraph theory-
dc.subject.keywordAuthorNeuroimaging-
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