A Set of Functional Brain Networks for the Comprehensive Evaluation of Human Characteristics
DC Field | Value | Language |
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dc.contributor.author | Sung, Yul-Wan | - |
dc.contributor.author | Kawachi, Yousuke | - |
dc.contributor.author | Choi, Uk-Su | - |
dc.contributor.author | Kang, Daehun | - |
dc.contributor.author | Abe, Chihiro | - |
dc.contributor.author | Otomo, Yuki | - |
dc.contributor.author | Ogawa, Seiji | - |
dc.date.available | 2020-02-27T11:41:40Z | - |
dc.date.created | 2020-02-06 | - |
dc.date.issued | 2018-03-14 | - |
dc.identifier.issn | 1662-453X | - |
dc.identifier.uri | https://scholarworks.bwise.kr/gachon/handle/2020.sw.gachon/3970 | - |
dc.description.abstract | Many human characteristics must be evaluated to comprehensively understand an individual, and measurements of the corresponding cognition/behavior are required. Brain imaging by functional MRI (fMRI) has been widely used to examine brain function related to human cognition/behavior. However, few aspects of cognition/behavior of individuals or experimental groups can be examined through task-based fMRI. Recently, resting state fMRI (rs-fMRI) signals have been shown to represent functional infrastructure in the brain that is highly involved in processing information related to cognition/behavior. Using rs-fMRI may allow diverse information about the brain through a single MRI scan to be obtained, as rs-fMRI does not require stimulus tasks. In this study, we attempted to identify a set of functional networks representing cognition/behavior that are related to a wide variety of human characteristics and to evaluate these characteristics using rs-fMRI data. If possible, these findings would support the potential of rs-fMRI to provide diverse information about the brain. We used resting-state fMRI and a set of 130 psychometric parameters that cover most human characteristics, including those related to intelligence and emotional quotients and social ability/skill. We identified 163 brain regions by VBM analysis using regression analysis with 130 psychometric parameters. Next, using a 163 x 163 correlation matrix, we identified functional networks related to 111 of the 130 psychometric parameters. Finally, we made an 8-class support vector machine classifiers corresponding to these 111 functional networks. Our results demonstrate that rs-fMRI signals contain intrinsic information about brain function related to cognition/behaviors and that this set of 111 networks/classifiers can be used to comprehensively evaluate human characteristics. | - |
dc.language | 영어 | - |
dc.language.iso | en | - |
dc.publisher | FRONTIERS MEDIA SA | - |
dc.relation.isPartOf | FRONTIERS IN NEUROSCIENCE | - |
dc.subject | RESTING-STATE FMRI | - |
dc.subject | DEFAULT-MODE | - |
dc.subject | TASK-PERFORMANCE | - |
dc.subject | CONNECTIVITY | - |
dc.subject | SIGNAL | - |
dc.subject | RESPONSES | - |
dc.subject | MRI | - |
dc.subject | INTELLIGENCE | - |
dc.subject | FLUCTUATIONS | - |
dc.subject | ACTIVATION | - |
dc.title | A Set of Functional Brain Networks for the Comprehensive Evaluation of Human Characteristics | - |
dc.type | Article | - |
dc.type.rims | ART | - |
dc.description.journalClass | 1 | - |
dc.identifier.wosid | 000427411700001 | - |
dc.identifier.doi | 10.3389/fnins.2018.00149 | - |
dc.identifier.bibliographicCitation | FRONTIERS IN NEUROSCIENCE, v.12 | - |
dc.identifier.scopusid | 2-s2.0-85043784485 | - |
dc.citation.title | FRONTIERS IN NEUROSCIENCE | - |
dc.citation.volume | 12 | - |
dc.contributor.affiliatedAuthor | Choi, Uk-Su | - |
dc.type.docType | Article | - |
dc.subject.keywordAuthor | resting-state fMRI | - |
dc.subject.keywordAuthor | functional network | - |
dc.subject.keywordAuthor | neuronal plasticity | - |
dc.subject.keywordAuthor | human characteristics | - |
dc.subject.keywordAuthor | psychometric parameters | - |
dc.subject.keywordPlus | RESTING-STATE FMRI | - |
dc.subject.keywordPlus | DEFAULT-MODE | - |
dc.subject.keywordPlus | TASK-PERFORMANCE | - |
dc.subject.keywordPlus | CONNECTIVITY | - |
dc.subject.keywordPlus | SIGNAL | - |
dc.subject.keywordPlus | RESPONSES | - |
dc.subject.keywordPlus | MRI | - |
dc.subject.keywordPlus | INTELLIGENCE | - |
dc.subject.keywordPlus | FLUCTUATIONS | - |
dc.subject.keywordPlus | ACTIVATION | - |
dc.relation.journalResearchArea | Neurosciences & Neurology | - |
dc.relation.journalWebOfScienceCategory | Neurosciences | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
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