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Functional connectivity decreases in autism in emotion, self, and face circuits identified by knowledge-based enrichment analysis

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Cheng, Wei, Rolls, Edmund T., Zhang, Jie, Sheng, W., Ma, L., Wan, L., Luo, Q. and Feng, Jianfeng (2017) Functional connectivity decreases in autism in emotion, self, and face circuits identified by knowledge-based enrichment analysis. NeuroImage, 148 . pp. 169-178. doi:10.1016/j.neuroimage.2016.12.068

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Official URL: http://dx.doi.org/10.1016/j.neuroimage.2016.12.068

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Abstract

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 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.

Item Type: Journal Article
Subjects: R Medicine > RC Internal medicine > RC0321 Neuroscience. Biological psychiatry. Neuropsychiatry
Divisions: Faculty of Science > Computer Science
Library of Congress Subject Headings (LCSH): Autism spectrum disorders, Neurosciences -- Methodology, Neural circuitry
Journal or Publication Title: NeuroImage
Publisher: Elsevier
ISSN: 1053-8119
Official Date: 1 March 2017
Dates:
DateEvent
1 March 2017Published
28 December 2016Available
22 December 2016Accepted
9 July 2016Submitted
Volume: 148
Page Range: pp. 169-178
DOI: 10.1016/j.neuroimage.2016.12.068
Status: Peer Reviewed
Publication Status: Published
Access rights to Published version: Restricted or Subscription Access
Funder: Royal Society (Great Britain). Wolfson Research Merit Award (RSWRMA), Guójiā gāo jìshù yánjiū fāzhǎn jìhuà (China) [National High Technology Research Development Program] (NHTRDP), China. Guo jia ke xue ji shu bu [Ministry of Science and Technology] (CMST), Zhongguo ke xue yuan [Chinese Academy of Sciences] (CAS), Guo jia zi ran ke xue ji jin wei yuan hui (China) [National Natural Science Foundation of China] (NSFC)
Grant number: 2015AA020507 (NHTRDP), 15JC1400101 (CMST), 91230201, 11471081, XDB13040600, 2015CB856003 (CAS), 61104143, 61573107, 11571349, 11201460 (NSFC)

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