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Focusing on the Differences of Resting-State Brain Networks, Using a Data-Driven Approach to Explore the Functional Neuroimaging Characteristics of Extraversion Trait
Tian, Feng1; Wang, Junjie2; Xu, Cheng3; Li, Hong4; Ma, Xin5; Xin Ma
2018-03-05
发表期刊FRONTIERS IN NEUROSCIENCE
通讯作者邮箱maxinanding@vip.163.com
ISSN1662-453X
文章类型Article
卷号12页码:1-8
产权排序5
摘要

In recent years, functional magnetic resonance imaging (fMRI) has been widely used in studies that explored the personality-brain association. Researches on personality neuroscience have the potential to provide personality psychology with explanatory models that is, why people differ from each other rather than how they differ from each other (DeYoung and Gray, 2009). As one of the most important dimensions of personality traits, extraversion is the most stable core and a universal component in personality theory. The aim of the present study was to employ a fully data-driven approach to study the brain mechanism of extraversion in a sample of 111 healthy adults. The Eysenck Personality Questionnaire (EPQ) was used to measure the personality characteristics of all the subjects. We investigated whether the subjects can be grouped into highly homogeneous communities according to the characteristics of their intrinsic connectivity networks (ICNs). The resultant subjects communities and the representative characteristics of ICNs were then associated to personality concepts. Finally, we found one ICN (salience network) whose subject community profiles exhibited significant associations with Extraversion trait.

关键词personality traits resting-state fMRI data-driven salience network extraversion trait
DOI10.3389/fnins.2018.00109
收录类别SCI
语种英语
项目资助者National Natural Science Foundation of China(81271482 ; National key research and development program(2016YFC1307004) ; 81571319 ; 61402318)
WOS研究方向Neurosciences & Neurology
WOS类目Neurosciences
WOS记录号WOS:000426554600001
WOS标题词Science & Technology ; Life Sciences & Biomedicine
关键词[WOS]DOMAIN CRITERIA RDOC ; INTRINSIC CONNECTIVITY NETWORKS ; INDEPENDENT COMPONENT ANALYSIS ; CHILDHOOD-ONSET SCHIZOPHRENIA ; DEFAULT NETWORK ; NIMH RESEARCH ; PERSONALITY ; REPRODUCIBILITY ; PSYCHOSIS ; EMOTION
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文献类型期刊论文
条目标识符http://ir.psych.ac.cn/handle/311026/26038
专题健康与遗传心理学研究室
通讯作者Xin Ma
作者单位1.Shanxi Med Univ, Hosp 2, Dept Psychiat, Taiyuan, Shanxi, Peoples R China
2.Shanxi Med Univ, Clnibai Med Coll 1, Dept Psychiat, Hosp 1, Taiyuan, Shanxi, Peoples R China
3.Shanxi Prov Peoples Hosp, Dept Magnet Resonance Imaging, Taiyuan, Peoples R China
4.Chinese Acad Sci, Inst Psychol, Beijing, Peoples R China
5.Capital Med Univ, Beijing Anding Hosp, Beijing, Peoples R China
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Tian, Feng,Wang, Junjie,Xu, Cheng,et al. Focusing on the Differences of Resting-State Brain Networks, Using a Data-Driven Approach to Explore the Functional Neuroimaging Characteristics of Extraversion Trait[J]. FRONTIERS IN NEUROSCIENCE,2018,12:1-8.
APA Tian, Feng,Wang, Junjie,Xu, Cheng,Li, Hong,Ma, Xin,&Xin Ma.(2018).Focusing on the Differences of Resting-State Brain Networks, Using a Data-Driven Approach to Explore the Functional Neuroimaging Characteristics of Extraversion Trait.FRONTIERS IN NEUROSCIENCE,12,1-8.
MLA Tian, Feng,et al."Focusing on the Differences of Resting-State Brain Networks, Using a Data-Driven Approach to Explore the Functional Neuroimaging Characteristics of Extraversion Trait".FRONTIERS IN NEUROSCIENCE 12(2018):1-8.
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