Depression is a mental disease involved in emotional and cognitive impairments. Neuroimaging studies have found abnormalities in the structure and functional network of brain for major depressive disorder (MDD).However, neural mechanism of the dynamic connectivity for emotional attention of MDD is currently insufficient. In this study, event-related potentials (ERP) and time-varying network were analyzed to investigate attention bias and corresponding neural mechanisms induced by emotional facial stimuli. In the ERP results, N100 components in MDD had shorter latencies and smaller amplitudes than those in healthy controls (HC) for sad and fear faces. The P200 amplitudes induced by sad faces in MDD were significantly higher than those induced by happy and fear faces in MDD, and those induced by sad faces in HC. It was indicated that MDD patients had attention bias towards sad faces. For the time-varying network analysis, adaptive directed transfer function was explored to construct dynamic network connectivity. MDD patients had stronger information outflow from the right frontal region and weaker information outflow from parieto-occipital regions for sad faces. In addition, the network properties of sad faces were significantly correlated with PHQ-9 scores for MDD group. These findings may provide further explanation for understanding the MDD’s neural mechanism of attention bias during facial emotional tasks.

抑郁症是一种涉及情绪和认知障碍的精神疾病。神经影像学研究发现重度抑郁症（MDD）的大脑结构和功能网络存在异常。然而，目前对于MDD情绪注意动态连接的神经机制还不够了解。本研究通过分析事件相关电位（ERP）和时变网络来研究情绪面部刺激引起的注意偏差和相应的神经机制。在 ERP 结果中，MDD 中的 N100 成分比健康对照 (HC) 中的悲伤和恐惧面孔具有更短的潜伏期和更小的振幅。 MDD 中悲伤面孔引起的 P200 振幅显着高于 MDD 中快乐和恐惧面孔引起的 P200 振幅，以及 HC 中悲伤面孔引起的 P200 振幅。研究表明，重度抑郁症患者对悲伤的面孔存在注意力偏差。对于时变网络分析，探索自适应定向传递函数来构建动态网络连接。 MDD 患者对于悲伤面孔，右额叶区域的信息流出较强，而顶枕区域的信息流出较弱。此外，MDD 组悲伤面孔的网络特性与 PHQ-9 得分显着相关。这些发现可能为理解 MDD 在面部情绪任务中注意力偏差的神经机制提供进一步的解释。