精神分裂症(面向对象编程)
神经科学
心理学
精神科
作者
Fengmei Fan,Suhui Jin,Yating Lv,Shuping Tan,Yuqing Liao,Zhenzhen Luo,Jingxuan Ruan,Zhiren Wang,Hongzhen Fan,Xiaole Han,Qihong Zou,Hong Xiang,Hua Guo,Fude Yang,Yunlong Tan,Jinhui Wang
标识
DOI:10.1093/schbul/sbae218
摘要
Abstract Background and Hypothesis Population-based morphological covariance networks are widely reported to be altered in schizophrenia. Individualized morphological brain network approaches have emerged recently. We hypothesize that individualized morphological brain networks are disrupted in schizophrenia. Study Design We constructed single-subject morphological brain networks for 203 patients with first-episode schizophrenia (FES) and 131 healthy controls separately based on regional cortical thickness (CT), fractal dimension (FD), gyrification index, and sulcal depth (SD) by dividing the cerebral cortex into 360 regions in terms of the Human Connectome Project Multi-Modal Parcellation atlas. Results Compared with the controls, the patients exhibited morphological similarity reductions in all types of networks while increases in FD- and SD-based networks. The altered morphological similarities were commonly involved in cingulo-opercular and default mode networks. Interestingly, the altered morphological similarities accounted for clinical symptoms and cognitive dysfunction in the patients and distinguished the patients from controls, with better performance than altered local morphology. In addition, graph-based analysis revealed that global organization was intact while nodal centrality was altered in the patients as characterized by decreased degree and efficiency in the left inferior parietal cortex and increased efficiency in left area superior temporal gyrus for the CT-based networks, decreased degree and efficiency in the left Posterior Insular Area 2 for the FD-based networks, and decreased betweenness in the left Area 52 for the SD-based networks. Conclusions These findings indicate that FES is accompanied by characteristic disruptions in single-subject cortical morphological networks, which provide novel insights into neurobiological mechanisms underlying schizophrenia.
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