特质焦虑对静态情绪面孔强化学习中的性别差异——来自ERP的证据

Gender Differences in Trait Anxiety on Static Emotional Face Reinforcement Learning: Evidence from ERP

摘要: 探讨高特质焦虑个体对静态面孔情绪信息识别与强化学习过程中的注意偏向机制和性别差异。采用ERP技术与S1~S2范式检测不同情绪面孔强化学习下高低特质焦虑的行为和脑电成分。高特质焦虑女性相比低特质焦虑女性和男性被试产生更大N170和P300波幅和更小的P100成分。高特质焦虑男性P100成分上波幅和潜伏期显著大于低特质焦虑男性。高焦虑男性相比低焦虑男性有更低的正确率和更短的反应时，高焦虑女性相比低焦虑组女性有更高的正确率和更短的反应时。特质焦虑显著影响情绪面孔的识别与学习，高特质焦虑会使个体更难以短期内准确识别面孔情绪，并且高特质焦虑女性面对负性面孔情绪时投入更多认知资源，高特质焦虑男性则表现出逃避倾向，这可能与性别差异所带来的情绪识别模式有关。

Abstract: Investigating attentional biases and gender disparities in high trait anxiety individuals during static facial emotion recognition and reinforcement learning. Utilizing ERP techniques and S1-S2 paradigms to analyze the behavioral and EEG aspects of high and low trait anxiety individuals across various emotional facial reinforcement learning scenarios. High trait anxiety females exhibit amplified N170 and P300 responses and diminished P100 components compared to low trait anxiety females and males. High trait anxiety males display heightened P100 responses compared to their low trait anxiety counterparts. Additionally, high anxiety males show reduced accuracy and quicker response times, while high anxiety females demonstrate increased accuracy and shorter response times. Trait anxiety significantly impacts emotional facial expression recognition and learning, particularly making it more challenging for high trait anxiety individuals to recognize emotions accurately in the short term. Furthermore, gender differences influence emotional recognition patterns, with high trait anxiety females allocating more cognitive resources to process negative facial emotions, while high trait anxiety males tend to exhibit avoidance tendencies.