近年来，前额脑电不对称效应在大量情绪研究中被发现，然而其
产生原因仍未有明确的共识。为验证前额脑电不对称效应的存在稳定
性及其认知神经基础，本研究采用 DREAMER 脑电数据库，并对涵
盖平静、愉悦、愤怒、悲伤、搞笑、厌恶、兴奋、惊讶和恐惧九种基
本情绪的被试进行了前额脑电不对称性的验证和被试间的一致性检
验。本研究通过频域分析技术结合机器学习算法，证明了前额脑电不
对称效应对情绪动机的分类效果优于情绪效价，进一步验证了接近-
退缩模型(Approach-withdraw model)的准确性。利用基于数据的实证
方法，研究者验证了前额脑电不对称效应的两种模型假说，并探究了
该效应作为情绪识别指标的可能性。

In recent years, the asymmetric effect of forehead EEG has been found in a large number of emotion studies, but there is still no clear consensus on its cause. In order to verify the stability of the prefrontal EEG asymmetry effect and its cognitive neural basis, this study used the DREAMER EEG database, and verified the prefrontal EEG asymmetry and tested the consistency among participants covering nine basic emotions: calm, happy, angry, sad, amusement, disgusted, excited, surprised and fearful. In this study, we proved that the asymmetric effect of forehead EEG is better than the emotional valence of emotional motivation by combining frequency domain analysis technology and machine learning algorithm, and further verified the accuracy of the approach-withdraw model. Using a data-based empirical approach, the 
researchers verified two model hypotheses of the forehead EEG 
asymmetric effect and explored the possibility of the effect as an indicator of emotion recognition.