Bai Yicai, Yu Minchang, Li Yingjie
School of Life Sciences, Shanghai University, Shanghai 200444, China.
School of Communication and Information Engineering, Shanghai University, Shanghai 200444, China.
Brain Sci. 2024 Jan 23;14(2):113. doi: 10.3390/brainsci14020113.
Emotions play a crucial role in human life and affect mental health. Understanding the neural patterns associated with emotions is essential. Previous studies carried out some exploration of the neural features of emotions, but most have designed experiments in two-dimensional (2D) environments, which differs from real-life scenarios. To create a more real environment, this study investigated emotion-related brain activity using electroencephalography (EEG) microstate analysis in a virtual reality (VR) environment. We recruited 42 healthy volunteers to participate in our study. We explored the dynamic features of different emotions, and four characteristic microstates were analyzed. In the alpha band, microstate A exhibited a higher occurrence in both negative and positive emotions than in neutral emotions. Microstate C exhibited a prolonged duration of negative emotions compared to positive emotions, and a higher occurrence was observed in both microstates C and D during positive emotions. Notably, a unique transition pair was observed between microstates B and C during positive emotions, whereas a unique transition pair was observed between microstates A and D during negative emotions. This study emphasizes the potential of integrating virtual reality (VR) and EEG to facilitate experimental design. Furthermore, this study enhances our comprehension of neural activities during various emotional states.
情绪在人类生活中起着至关重要的作用,并影响心理健康。了解与情绪相关的神经模式至关重要。先前的研究对情绪的神经特征进行了一些探索,但大多数研究是在二维(2D)环境中设计实验的,这与现实生活场景不同。为了创建更真实的环境,本研究在虚拟现实(VR)环境中使用脑电图(EEG)微状态分析来研究与情绪相关的大脑活动。我们招募了42名健康志愿者参与我们的研究。我们探索了不同情绪的动态特征,并分析了四种特征微状态。在α波段,微状态A在消极和积极情绪中的出现频率均高于中性情绪。与积极情绪相比,微状态C在消极情绪中持续时间更长,并且在积极情绪期间微状态C和D的出现频率均更高。值得注意的是,在积极情绪期间,在微状态B和C之间观察到一个独特的转换对,而在消极情绪期间,在微状态A和D之间观察到一个独特的转换对。本研究强调了整合虚拟现实(VR)和脑电图(EEG)以促进实验设计的潜力。此外,本研究增强了我们对各种情绪状态下神经活动的理解。