Zeng Can, Ross Brendan, Xue Zhimin, Huang Xiaojun, Wu Guowei, Liu Zhening, Tao Haojuan, Pu Weidan
Department of Psychiatry, The Second Xiangya Hospital, Central South University, Changsha, China.
Faculty of Medicine, McGill University, Montreal, QC, Canada.
Front Psychiatry. 2021 Mar 26;12:634299. doi: 10.3389/fpsyt.2021.634299. eCollection 2021.
Previous studies have primarily focused on the neuropathological mechanisms of the emotional circuit present in bipolar mania and bipolar depression. Recent studies applying resting-state functional magnetic resonance imaging (fMRI) have raise the possibility of examining brain-wide networks abnormality between the two oppositional emotion states, thus this study aimed to characterize the different functional architecture represented in mania and depression by employing group-independent component analysis (gICA). Forty-one bipolar depressive patients, 20 bipolar manic patients, and 40 healthy controls (HCs) were recruited and received resting-state fMRI scans. Group-independent component analysis was applied to the brain network functional connectivity analysis. Then, we calculated the correlation between the value of between-group differences and clinical variables. Group-independent component analysis identified 15 components in all subjects, and ANOVA showed that functional connectivity (FC) differed significantly in the default mode network, central executive network, and frontoparietal network across the three groups. Further -tests showed a gradient descent of activity-depression > HC > mania-in all three networks, with the differences between depression and HCs, as well as between depression and mania, surviving after family wise error (FWE) correction. Moreover, central executive network and frontoparietal network activities were positively correlated with Hamilton depression rating scale (HAMD) scores and negatively correlated with Young manic rating scale (YMRS) scores. Three brain networks heighten activity in depression, but not mania; and the discrepancy regions mainly located in prefrontal, which may imply that the differences in cognition and emotion between the two states is associated with top-down regulation in task-independent networks.
以往的研究主要集中在双相躁狂和双相抑郁中情感回路的神经病理机制。最近应用静息态功能磁共振成像（fMRI）的研究提出了检测两种对立情绪状态之间全脑网络异常的可能性，因此本研究旨在通过采用独立成分分析（gICA）来表征躁狂和抑郁中不同的功能结构。招募了41名双相抑郁患者、20名双相躁狂患者和40名健康对照者（HCs），并对他们进行了静息态fMRI扫描。将独立成分分析应用于脑网络功能连接分析。然后，我们计算了组间差异值与临床变量之间的相关性。独立成分分析在所有受试者中识别出15个成分，方差分析表明，三组之间在默认模式网络、中央执行网络和额顶网络中的功能连接（FC）存在显著差异。进一步的检验显示，在所有三个网络中，活动-抑郁>HC>躁狂呈梯度下降，抑郁与HC之间以及抑郁与躁狂之间的差异在进行家族性错误率（FWE）校正后仍然存在。此外，中央执行网络和额顶网络的活动与汉密尔顿抑郁量表（HAMD）评分呈正相关，与杨氏躁狂量表（YMRS）评分呈负相关。三个脑网络在抑郁时活动增强，但在躁狂时不增强；差异区域主要位于前额叶，这可能意味着两种状态下认知和情绪的差异与任务无关网络中的自上而下调节有关。
