Exploring the influence of emotion recognition on SSVEP through event-related potentials integration
Long Zhou, Weiao Zhou, Yunzhi Tian, Jiaqing Yan · 2024
Emotion recognition has received widespread attention as an important indicator of human psychological and physiological states. In the realm of emotion recognition utilizing EEG features, Steady State Visual Evoked Potential (SSVEP) emerges as a pivotal observation. The present study aimed to investigate the effect of Event-Related Potential (ERP) component of SSVEP. We used a new arithmetic paradigm to present emotional image stimuli in three different conditions and combined spectral and topographic analysis of SSVEP to investigate the effect of emotional stimuli on SSVEP. The results showed that the spectral characteristics of the SSVEP changed significantly when emotional stimuli were presented, as evidenced by significant differences in the amplitude and latency of the N1PC and P300 components across emotional conditions. Power Spectral Density (PSD) and topographic map analysis further revealed differences in the spatial and frequency domain distribution of these emotional effects in the EEG signal. These findings emphasize the influence of emotion on visual information processing and provide new insights into the potential mechanisms of EEG features in emotion recognition. This study is important for a deeper understanding of the relationship between emotion and cognition and the role of neural mechanisms in emotion recognition.