Liu Shuang, Chen Sitong, Huang Zhenni, Liu Xiaoya, Li Meijuan, Su Fangyue, Hao Xinyu, Ming Dong
Academy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin, China.
School of Precision Instruments and Optoelectronics Engineering, Tianjin University, Tianjin, China.
Cogn Neurodyn. 2022 Oct;16(5):1059-1071. doi: 10.1007/s11571-022-09782-6. Epub 2022 Feb 5.
Directed brain networks may provide new insights into exploring physiological mechanism and neuromarkers for depression. This study aims to investigate the abnormalities of directed brain networks in depressive patients. We constructed the directed brain network based on resting electroencephalogram for 19 depressive patients and 20 healthy controls with eyes closed and eyes open. The weighted directed brain connectivity was measured by partial directed coherence for α, β, γ frequency band. Furthermore, topological parameters (clustering coefficient, characteristic path length, and et al.) were computed based on graph theory. The correlation between network metrics and clinical symptom was also examined. Depressive patients had a significantly weaker value of partial directed coherence at alpha frequency band in eyes-closed state. Clustering coefficient and characteristic path length were significantly lower in depressive patients (both < .01). More importantly, in depressive patients, disruption of directed connectivity was noted in left-to-left ( < .05), right-to-left ( < .01) hemispheres and frontal-to-central ( < .01), parietal-to-central ( < .05), occipital-to-central ( < .05) regions. Furthermore, connectivity in LL and RL hemispheres was negatively correlated with depression scale scores (both < .05). Depressive patients showed a more randomized network structure, disturbed directed interaction of left-to-left, right-to-left hemispheric information and between different cerebral regions. Specifically, left-to-left, right-to-left hemispheric connectivity was negatively correlated with the severity of depression. Our analysis may serve as a potential neuromarker of depression.
定向脑网络可能为探索抑郁症的生理机制和神经标志物提供新的见解。本研究旨在调查抑郁症患者定向脑网络的异常情况。我们基于静息脑电图为19名抑郁症患者和20名健康对照者构建了闭眼和睁眼状态下的定向脑网络。通过α、β、γ频段的偏定向相干性测量加权定向脑连通性。此外,基于图论计算拓扑参数(聚类系数、特征路径长度等)。还检查了网络指标与临床症状之间的相关性。抑郁症患者在闭眼状态下α频段的偏定向相干性值显著较弱。抑郁症患者的聚类系数和特征路径长度显著较低(均<0.01)。更重要的是,在抑郁症患者中,观察到左到左(<0.05)、右到左(<0.01)半球以及额到中央(<0.01)、顶到中央(<0.05)、枕到中央(<0.05)区域的定向连通性中断。此外,左左和右左半球的连通性与抑郁量表评分呈负相关(均<0.05)。抑郁症患者表现出更随机的网络结构,左到左、右到左半球信息以及不同脑区之间的定向相互作用受到干扰。具体而言,左到左、右到左半球的连通性与抑郁症的严重程度呈负相关。我们的分析可能作为抑郁症的潜在神经标志物。