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

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.