Sun Fuping, Liu Zhening, Yang Jun, Fan Zebin, Xi Chang, Cheng Peng, He Zhong, Yang Jie
Department of Psychiatry, National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, China.
Department of Radiology, The Second Xiangya Hospital of Central South University, Changsha, China.
Front Psychiatry. 2022 Jul 27;13:941073. doi: 10.3389/fpsyt.2022.941073. eCollection 2022.
Previous studies have probed the brain static activity pattern in bipolar disorder across different states. However, human intrinsic brain activity is time-varying and dynamic. There is a lack of knowledge about the brain dynamical pattern in bipolar disorder across different mood states.
This study used the dynamical degree centrality (dDC) to investigate the resting-state whole-brain dynamical pattern voxel-wise in a total of 62 bipolar disorder [28 bipolar depression (BD), 13 bipolar mania (BM), 21 bipolar euthymia (BE)], and 30 healthy controls (HCs). One-way analysis of variance (ANOVA) was applied to explore the omnibus differences of the dDC pattern across all groups, and Pearson's correlation analysis was used to evaluate the relationship between the dDC variability in detected regions with clinical symptom severity.
One-way ANOVA analysis showed the omnibus differences in the left inferior parietal lobule/middle occipital gyrus (IPL/MOG) and right precuneus/posterior cingulate cortex (PCUN/PCC) across all groups. The analysis revealed that BD showed decreased dDC in the IPL/MOG compared with all other groups, and both BD and BM exhibited decreased dDC in the PCUN/PCC compared with BE and HCs. Furthermore, correlation analysis showed that the dDC variability of the IPL/MOG and PCUN/PCC negatively correlated with the depression symptom levels in all patients with bipolar disorder.
This study demonstrated the distinct and shared brain dynamical pattern of the depressive, manic, and euthymia states. Our findings provide new insights into the pathophysiology of bipolar disorder across different mood states from the dynamical brain network pattern perspective.
以往研究已探究了双相情感障碍在不同状态下的大脑静态活动模式。然而,人类大脑的内在活动是随时间变化且动态的。目前尚缺乏关于双相情感障碍在不同情绪状态下大脑动态模式的了解。
本研究使用动态度中心性(dDC),对总共62名双相情感障碍患者[28名双相抑郁(BD)、13名双相躁狂(BM)、21名双相情感正常(BE)]和30名健康对照(HC)进行全脑静息态动态模式的体素水平研究。采用单因素方差分析(ANOVA)来探究所有组间dDC模式的总体差异,并使用Pearson相关分析来评估检测区域的dDC变异性与临床症状严重程度之间的关系。
单因素方差分析显示,所有组在左侧顶下小叶/枕中回(IPL/MOG)和右侧楔前叶/后扣带回皮质(PCUN/PCC)存在总体差异。分析表明,与所有其他组相比,BD组在IPL/MOG区域的dDC降低,与BE组和HC组相比,BD组和BM组在PCUN/PCC区域的dDC均降低。此外,相关分析表明,所有双相情感障碍患者中,IPL/MOG和PCUN/PCC区域的dDC变异性与抑郁症状水平呈负相关。
本研究证明了抑郁、躁狂和情感正常状态下独特且共同的大脑动态模式。我们的研究结果从动态脑网络模式的角度为双相情感障碍在不同情绪状态下的病理生理学提供了新的见解。