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뇌과학이미징연구단
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Structural and functional brain connectivity of people with obesity and prediction of body mass index using connectivity

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dc.contributor.authorBo-yong Park-
dc.contributor.authorJongbum Seo-
dc.contributor.authorJuneho Yi-
dc.contributor.authorHyunjin Park-
dc.date.accessioned2016-01-25T00:11:58Z-
dc.date.available2016-01-25T00:11:58Z-
dc.date.created2016-01-11-
dc.date.issued2015-11-
dc.identifier.issn1932-6203-
dc.identifier.urihttps://pr.ibs.re.kr/handle/8788114/2259-
dc.description.abstractObesity is a medical condition affecting billions of people. Various neuroimaging methods including magnetic resonance imaging (MRI) have been used to obtain information about obesity. We adopted a multi-modal approach combining diffusion tensor imaging (DTI) and resting state functional MRI (rs-fMRI) to incorporate complementary information and thus better investigate the brains of non-healthy weight subjects. The objective of this study was to explore multi-modal neuroimaging and use it to predict a practical clinical score, body mass index (BMI). Connectivity analysis was applied to DTI and rs-fMRI. Significant regions and associated imaging features were identified based on group-wise differences between healthy weight and non-healthy weight subjects. Six DTI-driven connections and 10 rs-fMRI-driven connectivities were identified. DTI-driven connections better reflected group-wise differences than did rs-fMRI-driven connectivity. We predicted BMI values using multi-modal imaging features in a partial least-square regression framework (percent error 15.0%). Our study identified brain regions and imaging features that can adequately explain BMI. We identified potentially good imaging biomarker candidates for obesity-related diseases.-
dc.description.uri1-
dc.language영어-
dc.publisherPUBLIC LIBRARY SCIENCE-
dc.titleStructural and functional brain connectivity of people with obesity and prediction of body mass index using connectivity-
dc.typeArticle-
dc.type.rimsART-
dc.identifier.wosid000364298400061-
dc.identifier.scopusid2-s2.0-84951023158-
dc.identifier.rimsid21959-
dc.date.tcdate2018-10-01-
dc.contributor.affiliatedAuthorHyunjin Park-
dc.identifier.doi10.1371/journal.pone.0141376-
dc.identifier.bibliographicCitationPLOS ONE, v.10, no.11, pp.1 - 14-
dc.citation.titlePLOS ONE-
dc.citation.volume10-
dc.citation.number11-
dc.citation.startPage1-
dc.citation.endPage14-
dc.date.scptcdate2018-10-01-
dc.description.wostc9-
dc.description.scptc8-
dc.description.journalClass1-
dc.description.journalRegisteredClassscie-
dc.description.journalRegisteredClassscopus-
dc.subject.keywordPlusMILD COGNITIVE IMPAIRMENT-
dc.subject.keywordPlusHUMAN CONNECTOME PROJECT-
dc.subject.keywordPlusHUMAN CEREBRAL-CORTEX-
dc.subject.keywordPlusALZHEIMERS-DISEASE-
dc.subject.keywordPlusCORTICAL NETWORKS-
dc.subject.keywordPlusFOOD-INTAKE-
dc.subject.keywordPlusREWARD-
dc.subject.keywordPlusTRACTOGRAPHY-
dc.subject.keywordPlusMRI-
dc.subject.keywordPlusADULTS-
Appears in Collections:
Center for Neuroscience Imaging Research (뇌과학 이미징 연구단) > 1. Journal Papers (저널논문)
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