Sun Yu, Dai Zhongxiang, Li Junhua, Collinson Simon L, Sim Kang
Singapore Institute for Neurotechnology (SINAPSE), Centre for Life Science, National University of Singapore, Singapore.
Department of Psychology, National University of Singapore, Singapore.
Hum Brain Mapp. 2017 Apr;38(4):2008-2025. doi: 10.1002/hbm.23501. Epub 2016 Dec 29.
Convergent evidences have revealed that schizophrenia is associated with brain dysconnectivity, which leads to abnormal network organization. However, discrepancies were apparent between the structural connectivity (SC) and functional connectivity (FC) studies, and the relationship between structural and functional deficits in schizophrenia remains largely unknown. In this study, resting-state functional magnetic resonance imaging and structural diffusion tensor imaging were performed in 20 patients with schizophrenia and 20 matched healthy volunteers (patients/controls = 19/17 after head motion rejection). Functional and structural brain networks were obtained for each participant. Graph theoretical approaches were employed to parcellate the FC networks into functional modules. The relationships between the entries of SC and FC were estimated within each module to identify group differences and their correlations with clinical symptoms. Although five common functional modules (including the default mode, occipital, subcortical, frontoparietal, and central modules) were identified in both groups, the patients showed a significantly reduced modularity in comparison with healthy participants. Furthermore, we found that schizophrenia-related aberrations of SC-FC coupling exhibited complex patterns among modules. Compared with controls, patients showed an increased SC-FC coupling in the default mode and the central modules. Moreover, significant SC-FC decoupling was demonstrated in the occipital and the subcortical modules, which was associated with longer duration of illness and more severe clinical manifestations of schizophrenia. Taken together, these findings demonstrated that altered module-dependent SC-FC coupling may underlie abnormal brain function and clinical symptoms observed in schizophrenia and highlighted the potential for using new multimodal neuroimaging biomarkers for diagnosis and severity evaluation of schizophrenia. Hum Brain Mapp 38:2008-2025, 2017. © 2017 Wiley Periodicals, Inc.
越来越多的证据表明,精神分裂症与大脑连接异常有关,这会导致网络组织异常。然而,结构连接性(SC)和功能连接性(FC)研究之间存在明显差异,精神分裂症中结构和功能缺陷之间的关系仍不清楚。在本研究中,对20例精神分裂症患者和20名匹配的健康志愿者进行了静息态功能磁共振成像和结构扩散张量成像(排除头部运动后患者/对照 = 19/17)。为每个参与者获取了大脑功能和结构网络。采用图论方法将FC网络划分为功能模块。估计每个模块内SC和FC条目的关系,以识别组间差异及其与临床症状的相关性。虽然两组都识别出了五个常见的功能模块(包括默认模式、枕叶、皮层下、额顶叶和中央模块),但与健康参与者相比,患者的模块性显著降低。此外,我们发现精神分裂症相关的SC-FC耦合异常在模块间呈现复杂模式。与对照组相比,患者在默认模式和中央模块中SC-FC耦合增加。此外,枕叶和皮层下模块中存在显著的SC-FC解耦,这与病程较长和精神分裂症更严重的临床表现相关。综上所述,这些发现表明,模块依赖的SC-FC耦合改变可能是精神分裂症中观察到的异常脑功能和临床症状的基础,并突出了使用新的多模态神经影像学生物标志物进行精神分裂症诊断和严重程度评估的潜力。《人类大脑图谱》38:2008 - 2025, 2017。© 2017威利期刊公司