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Functional connectivity decreases in autism in emotion, self, and face circuits identified by Knowledge-based Enrichment Analysis
Cheng, Wei1,2; Rolls, Edmund T.3,4; Zhang, Jie1,2; Sheng, Wenbo1,2; Ma, Liang8; Wan, Lin9; Luo, Qiang1,2,7; Feng, Jianfeng1,2,3,5,6
2017-03-01
发表期刊NEUROIMAGE
ISSN1053-8119
卷号148页码:169-178
摘要A powerful new method is described called Knowledge based functional connectivity Enrichment Analysis (KEA) for interpreting resting state functional connectivity, using circuits that are functionally identified using search terms with the Neurosynth database. The method derives its power by focusing on neural circuits, sets of brain regions that share a common biological function, instead of trying to interpret single functional connectivity links. This provides a novel way of investigating how task- or function-related networks have resting state functional connectivity differences in different psychiatric states, provides a new way to bridge the gap between task and resting-state functional networks, and potentially helps to identify brain networks that might be treated. The method was applied to interpreting functional connectivity differences in autism. Functional connectivity decreases at the network circuit level in 394 patients with autism compared with 473 controls were found in networks involving the orbitofrontal cortex, anterior cingulate cortex, middle temporal gyrus cortex, and the precuneus, in networks that are implicated in the sense of self, face processing, and theory of mind. The decreases were correlated with symptom severity.
关键词Autism spectrum disorder Neurosynth database Orbitofrontal cortex Precuneus Resting state fMRI
DOI10.1016/j.neuroimage.2016.12.068
语种英语
资助项目Royal Society Wolfson Research Merit Award ; National High Technology Research and Development Program of China[2015AA020507] ; key project of Shanghai Science & Technology Innovation Plan[15JC1400101] ; National Centre for Mathematics and Interdisciplinary Sciences (NCMIS) of the Chinese Academy of Sciences (CAS) ; Key Program of National Natural Science Foundation of China[91230201] ; Shanghai Soft Science Research Program[15692106604] ; National Natural Sciences Foundation of China[11471081] ; National Science Foundation of China[NSFC 61104143] ; National Science Foundation of China[61573107] ; special Funds for Major State Basic Research Projects of China[2015CB856003] ; NSFC[11571349] ; NSFC[11201460] ; NCMIS of the CAS ; Youth Innovation Promotion Association of the CAS ; Strategic Priority Research Program of the CAS[XDB13040600]
WOS研究方向Neurosciences & Neurology ; Radiology, Nuclear Medicine & Medical Imaging
WOS类目Neurosciences ; Neuroimaging ; Radiology, Nuclear Medicine & Medical Imaging
WOS记录号WOS:000396803100016
出版者ACADEMIC PRESS INC ELSEVIER SCIENCE
引用统计
文献类型期刊论文
条目标识符http://ir.amss.ac.cn/handle/2S8OKBNM/24902
专题系统科学研究所
通讯作者Feng, Jianfeng
作者单位1.Fudan Univ, Sch Math Sci, Shanghai 200433, Peoples R China
2.Fudan Univ, Ctr Computat Syst Biol, Shanghai 200433, Peoples R China
3.Univ Warwick, Dept Comp Sci, Coventry CV4 7AL, W Midlands, England
4.Oxford Ctr Computat Neurosci, Oxford, England
5.Fudan Univ, Sch Life Sci, Sch Math Sci, Shanghai 200433, Peoples R China
6.Fudan Univ, Collaborat Innovat Ctr Brain Sci, Shanghai 200433, Peoples R China
7.Fudan Univ, Sch Life Sci, Shanghai 200433, Peoples R China
8.Chinese Acad Sci, Beijing Inst Genom, Beijing 100101, Peoples R China
9.Chinese Acad Sci, Acad Math & Syst Sci, Natl Ctr Math & Interdisciplinary Sci, Beijing 100190, Peoples R China
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Cheng, Wei,Rolls, Edmund T.,Zhang, Jie,et al. Functional connectivity decreases in autism in emotion, self, and face circuits identified by Knowledge-based Enrichment Analysis[J]. NEUROIMAGE,2017,148:169-178.
APA Cheng, Wei.,Rolls, Edmund T..,Zhang, Jie.,Sheng, Wenbo.,Ma, Liang.,...&Feng, Jianfeng.(2017).Functional connectivity decreases in autism in emotion, self, and face circuits identified by Knowledge-based Enrichment Analysis.NEUROIMAGE,148,169-178.
MLA Cheng, Wei,et al."Functional connectivity decreases in autism in emotion, self, and face circuits identified by Knowledge-based Enrichment Analysis".NEUROIMAGE 148(2017):169-178.
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