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Connecting Openness and the Resting-State Brain Network: A Discover-Validate Approach
Wang, Junjie1; Hu, Yang2; Li, Hong3; Ge, Ling4; Li, Jing1; Cheng, Long1; Yang, Zhi2; Zuo, Xinian3; Xu, Yong1,5,6
第一作者Wang, Junjie
通讯作者邮箱zhi yang yangz@smhc.org.cn ; yong xu xuyongsmu@vip.163.com
心理所单位排序3
摘要

In personality neuroscience, the openness-brain association has been a topic of interest. Previous studies usually started from difference in openness trait and used it to infer brain functional activity characteristics, but no study has used a "brain-first" research strategy to explore that association based on more objective brain imaging data. In this study, we used a fully data-driven approach to discover and validate the association between openness and the resting-state brain network. We collected data of 120 subjects as a discovery sample and 56 subjects as a validation sample. The Neuroticism Extraversion Openness Five-Factor Inventory (NEO-FFI) was used to measure the personality characteristics of all the subjects. Using an exploratory approach based on independent component analysis of resting-state functional magnetic resonance imaging (fMRI) data, we identified a parietal network that consisted of the precuneus and inferior parietal lobe. The inter-subject similarity of the parietal memory network exhibited significant associations with openness trait, and this association was validated using the 56-subject independent sample. This finding connects the openness trait to the characteristics of a neural network and helps to understand the underlying biology of the openness trait.

关键词Openness Parietal Memory Network Resting-state Fmri Data-driven Functional Connectome
2018-10-22
语种英语
DOI10.3389/fnins.2018.00762
发表期刊FRONTIERS IN NEUROSCIENCE
ISSN1662-453X
卷号12页码:9
期刊论文类型Article
收录类别SCIE
资助项目National Science Foundation of China[81571319] ; National Science Foundation of China[81571756] ; National Science Foundation of China[81501152] ; National Science Foundation of China[81671332] ; National Key Research and Development Program of China[2016YFC1307004] ; Beijing Nova Program for Science and Technology[XXJH2015B079] ; Ministry of Science and Technology of China[2016YFC1306800] ; Shanghai Municipal Education Commission-Gaofeng Clinical Medicine Grant Support[20171929] ; Shanghai Mental Health Center[13dz2260500]
出版者FRONTIERS MEDIA SA
WOS关键词Independent Component Analysis ; Domain Criteria Rdoc ; Functional Connectivity ; Default Network ; Personality-traits ; 5-factor Model ; Nimh Research ; Big 5 ; Extroversion ; Metaanalysis
WOS研究方向Neurosciences & Neurology
WOS类目Neurosciences
WOS记录号WOS:000447874500001
资助机构National Science Foundation of China ; National Key Research and Development Program of China ; Beijing Nova Program for Science and Technology ; Ministry of Science and Technology of China ; Shanghai Municipal Education Commission-Gaofeng Clinical Medicine Grant Support ; Shanghai Mental Health Center
引用统计
被引频次:5[WOS]   [WOS记录]     [WOS相关记录]
文献类型期刊论文
条目标识符https://ir.psych.ac.cn/handle/311026/27315
专题认知与发展心理学研究室
通讯作者Yang, Zhi; Xu, Yong
作者单位1.Shanxi Med Univ, Clin Med Coll 1, Hosp 1, Dept Psychiat, Taiyuan, Shanxi, Peoples R China
2.Shanghai Jiao Tong Univ, Med Sch, Shanghai Mental Hlth Ctr, Lab Psychol Hlth & Imaging, Shanghai, Peoples R China
3.Chinese Acad Sci, Inst Psychol, Beijing, Peoples R China
4.Shanxi Med Coll Continuing Educ, Dept Med Psychol, Taiyuan, Shanxi, Peoples R China
5.Shanxi Med Univ, Hosp 1, Ctr Cognit Impairment & Sleep Disorders, Multidisciplinary Team MDT, Taiyuan, Shanxi, Peoples R China
6.Key Lab Cell Physiol Shanxi Prov, Taiyuan, Shanxi, Peoples R China
推荐引用方式
GB/T 7714
Wang, Junjie,Hu, Yang,Li, Hong,et al. Connecting Openness and the Resting-State Brain Network: A Discover-Validate Approach[J]. FRONTIERS IN NEUROSCIENCE,2018,12:9.
APA Wang, Junjie.,Hu, Yang.,Li, Hong.,Ge, Ling.,Li, Jing.,...&Xu, Yong.(2018).Connecting Openness and the Resting-State Brain Network: A Discover-Validate Approach.FRONTIERS IN NEUROSCIENCE,12,9.
MLA Wang, Junjie,et al."Connecting Openness and the Resting-State Brain Network: A Discover-Validate Approach".FRONTIERS IN NEUROSCIENCE 12(2018):9.
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