基于快速独立分量分析算法的不同情绪下事件相关电位差异性分析

DIFFERENCE ANALYSIS OF EVENT-RELATED POTENTIALS UNDER DIFFERENT EMOTIONS BASED ON FAST INDEPENDENT COMPONENT ANALYSIS ALGORITHM

针对不同情绪诱发的脑电(Electroencephalogram,EEG)存在差异这一特性以及传统的情绪诱导方法效果不明显的问题,采用虚拟现实(Virtual Reality,VR)技术作为实验情绪诱导环境,并将三阶FastICA(Fast Independent Component Analysis)算法与事件相关电位(Event-Related Potentials,ERP)技术应用于脑电数据的伪迹处理和分析。实验结果表明:通过去伪迹处理之后的正、负性情绪和中性情绪下的脑电信号在ERP的N1、P2阶段有着显著性差异。在N1时间窗上,低效价负性刺激相较于高效价正性刺激会获得更多的注意资源的分配。在P2阶段发现大脑不仅优先加工对个体产生威胁的负性刺激,同样对具有动机意义的各类刺激也会表现出优先加工。

In view of the differences in electroencephalogram(EEG)induced by different emotions and the insignificant effects of traditional emotion induction methods,virtual reality(VR)technology was adopted as the experimental emotion induction environment.The third-order fast independent component analysis(FastICA)algorithm and event-related potential(ERP)technology were applied to the artifact processing and analysis of EEG data.The experimental results show that the EEG signals of positive and negative emotions,and neutral emotions after de-artifact processing have significant differences in the N1 and P2 stages of ERP.In the N1 time window,the low-titer negative stimuli pay more attention to the allocation of resources than the high-price positive stimulus.In the P2 stage,it is found that the brain preferentially processes not only negative stimuli that threaten the individual,but also various stimuli with motivational significance.