精神分裂症(面向对象编程)
精神科
心理学
医学
临床心理学
作者
Yingru Wang,Yinian Yang,Wenqiang Xu,Xiaoqing Yao,Xiaohui Xie,Long Zhang,Jinmei Sun,Lu Wang,Qiang Hua,Kongliang He,Yanghua Tian,Kai Wang,Gong‐Jun Ji
标识
DOI:10.1093/schbul/sbae003
摘要
Abstract Background and Hypothesis There is a huge heterogeneity of magnetic resonance imaging findings in schizophrenia studies. Here, we hypothesized that brain regions identified by structural and functional imaging studies of schizophrenia could be reconciled in a common network. Study Design We systematically reviewed the case-control studies that estimated the brain morphology or resting-state local function for schizophrenia patients in the literature. Using the healthy human connectome (n = 652) and a validated technique “coordinate network mapping” to identify a common brain network affected in schizophrenia. Then, the specificity of this schizophrenia network was examined by independent data collected from 13 meta-analyses. The clinical relevance of this schizophrenia network was tested on independent data of medication, neuromodulation, and brain lesions. Study Results We identified 83 morphological and 60 functional studies comprising 7389 patients with schizophrenia and 7408 control subjects. The “coordinate network mapping” showed that the atrophy and dysfunction coordinates were functionally connected to a common network although they were spatially distant from each other. Taking all 143 studies together, we identified the schizophrenia network with hub regions in the bilateral anterior cingulate cortex, insula, temporal lobe, and subcortical structures. Based on independent data from 13 meta-analyses, we showed that these hub regions were specifically connected with regions of cortical thickness changes in schizophrenia. More importantly, this schizophrenia network was remarkably aligned with regions involving psychotic symptom remission. Conclusions Neuroimaging abnormalities in cross-sectional schizophrenia studies converged into a common brain network that provided testable targets for developing precise therapies.
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