Key Laboratory for NeuroInformation of Ministry of Education, Center for Information in Medicine, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China.
Key Laboratory for NeuroInformation of Ministry of Education, Center for Information in Medicine, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China; Department of psychiatry, Chengdu Mental Health Center, Institute of Chengdu Brain Science, Chengdu, China.
Prog Neuropsychopharmacol Biol Psychiatry. 2017 Oct 3;79(Pt B):302-310. doi: 10.1016/j.pnpbp.2017.07.007. Epub 2017 Jul 10.
Schizophrenia (SCH) and depression (DEP) are prevalent psychiatric disorders and share common and distinguished elements in their pathophysiology. A triple network model composed of the default mode network (DMN), salience network (SN) and central executive network (CEN) may represent a major abnormality across several psychiatric disorders including SCH and DEP. However, common and distinct dysfunctional patterns between SCH and DEP across three core networks remain unclear.
Resting-state functional magnetic resonance imaging (fMRI) was obtained in 20 patients with SCH, 20 patients with DEP and 20 healthy controls (HC). Both functional connectivity (FC) and Granger causal connectivity across DMN, SN and CEN were evaluated to uncover common and distinct dysfunctional patterns between SCH and DEP.
Two patient groups showed identical abnormal causal connectivity between key nodes of DMN and SN, as well as opposing aberrant FC of DMN-CEN and SN-CEN. Compared with HC, the FC between CEN and DMN was increased in SCH while decreased in DEP. Conversely, DEP showed enhanced FC between CEN and SN, whereas SCH showed decreased FC.
The sample size was relatively small, and all participants were taking medication.
Our results identified common patterns including dysconnectivity between DMN and SN, which may contribute to shared cognitive and affective impairment in DEP and SCH. Moreover, opposing dysconnectivity patterns of DMN-CEN may be associated with different self-referential processing abnormalities. These opposing dysconnectivity patterns may indicate an unbalanced recruitment between SN and CEN. Therefore, this study provides dysconnectivity patterns to advance the understanding of the triple network model with regard to psychiatric disorders.
精神分裂症（SCH）和抑郁症（DEP）是常见的精神疾病，它们在病理生理学上既有共同之处，也有明显的区别。由默认模式网络（DMN）、突显网络（SN）和中央执行网络（CEN）组成的三重网络模型可能代表了包括 SCH 和 DEP 在内的几种精神疾病的主要异常。然而，SCH 和 DEP 之间三个核心网络的共同和独特的功能障碍模式仍不清楚。
对 20 例 SCH 患者、20 例 DEP 患者和 20 例健康对照者（HC）进行静息态功能磁共振成像（fMRI）检查。评估 DMN、SN 和 CEN 之间的功能连接（FC）和格兰杰因果连接，以揭示 SCH 和 DEP 之间共同和独特的功能障碍模式。
两组患者的 DMN 和 SN 的关键节点之间存在相同的异常因果连接，以及 DMN-CEN 和 SN-CEN 的相反异常 FC。与 HC 相比，SCH 中 CEN 与 DMN 之间的 FC 增加，而 DEP 中则减少。相反，DEP 显示 CEN 与 SN 之间的 FC 增强，而 SCH 显示 CEN 与 SN 之间的 FC 减少。
样本量相对较小，所有参与者都在服用药物。
我们的研究结果确定了共同的模式，包括 DMN 和 SN 之间的连接中断，这可能导致 DEP 和 SCH 中共同的认知和情感障碍。此外，DMN-CEN 的相反连接中断模式可能与不同的自我参照处理异常有关。这些相反的连接中断模式可能表明 SN 和 CEN 之间的不平衡招募。因此，这项研究提供了连接中断模式，以促进对精神疾病三重网络模型的理解。
