title: Functional connectivity decreases in autism in emotion, self, and face circuits identified by Knowledge-based Enrichment Analysis.
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 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.
authors.affiliation: School of Mathematical Sciences and Centre for Computational Systems Biology, Fudan University, Shanghai 200433, PR China.
authors.forename: Wei
authors.initials: W
authors.lastname: Cheng
authors.affiliation: Department of Computer Science, University of Warwick, Coventry CV4 7AL, UK; Oxford Centre for Computational Neuroscience, Oxford, UK.
authors.forename: Edmund T
authors.initials: ET
authors.lastname: Rolls
authors.affiliation: School of Mathematical Sciences and Centre for Computational Systems Biology, Fudan University, Shanghai 200433, PR China.
authors.forename: Jie
authors.initials: J
authors.lastname: Zhang
authors.affiliation: School of Mathematical Sciences and Centre for Computational Systems Biology, Fudan University, Shanghai 200433, PR China.
authors.forename: Wenbo
authors.initials: W
authors.lastname: Sheng
authors.affiliation: Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, PR China.
authors.forename: Liang
authors.initials: L
authors.lastname: Ma
authors.affiliation: National Center of Mathematics and Interdisciplinary Sciences, Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing 100190, PR China.
authors.forename: Lin
authors.initials: L
authors.lastname: Wan
authors.affiliation: School of Mathematical Sciences and Centre for Computational Systems Biology, Fudan University, Shanghai 200433, PR China; School of Life Sciences, Fudan University, Shanghai 200433, PR China.
authors.forename: Qiang
authors.initials: Q
authors.lastname: Luo
authors.affiliation: School of Mathematical Sciences and Centre for Computational Systems Biology, Fudan University, Shanghai 200433, PR China; Department of Computer Science, University of Warwick, Coventry CV4 7AL, UK; School of Mathematical Sciences, School of Life Science and the Collaborative Innovation Center for Brain Science, Fudan University, Shanghai 200433, PR China. Electronic address: jianfeng.feng@warwick.ac.uk.
authors.forename: Jianfeng
authors.initials: J
authors.lastname: Feng
mesh_terms: D001321:Autistic Disorder / Q000000981:diagnostic imaging* / Q000523:psychology*; D002540:Cerebral Cortex / Q000000981:diagnostic imaging; D016208:Databases, Factual; D000066499:Facial Recognition; D006801:Humans; D007091:Image Processing, Computer-Assisted; D008279:Magnetic Resonance Imaging; D009415:Nerve Net / Q000000981:diagnostic imaging; D009434:Neural Pathways / Q000000981:diagnostic imaging*; D059906:Neuroimaging; D011597:Psychomotor Performance; D012649:Self Concept; D056345:Theory of Mind
keywords: Autism spectrum disorder; Neurosynth database; Orbitofrontal cortex; Precuneus; Resting state fMRI