Social emotion perception plays an important role in our daily social interactions and is involved in the treatments for mental disorders. Hyper-scanning technique enables to measure brain activities simultaneously from two or more persons, which was employed in this study to explore social emotion perception. We analyzed the recorded electroencephalogram (EEG) to explore emotion perception in terms of event related potential (ERP) and phase synchronization, and classified emotion categories based on convolutional neural network (CNN). The results showed that (1) ERP was significantly different among four emotion categories (i.e., anger, disgust, neutral, and happy), but there was no significant difference for ERP in the comparison of rating orders (the order of rating actions of the paired participants); (2) the intra-brain phase lag index (PLI) was higher than the inter-brain PLI but its number of connections exhibiting significant difference was less in all typical frequency bands (from delta to gamma); (3) the emotion classification accuracy of inter-PLI-Conv outperformed that of intra-PLI-Conv for all cases of using each frequency band (five frequency bands totally). In particular, the classification accuracies averaged across all participants in the alpha band were 65.55% and 50.77% (much higher than the chance level) for the inter-PLI-Conv and intra-PLI-Conv, respectively. According to our results, the emotion category of happiness can be classified with a higher performance compared to the other categories.

社交情感感知在我们的日常社交中起着重要作用，并参与精神障碍的治疗。超扫描技术能够同时测量两个或两个以上人的大脑活动，该技术在本研究中用于探索社交情感感知。我们分析了记录的脑电图（EEG），以探索事件相关电位（ERP）和相位同步方面的情绪感知，并基于卷积神经网络（CNN）对情绪类别进行了分类。结果表明：（1）情绪，愤怒，厌恶，中立和快乐这四个情绪类别的ERP差异显着，但在评级顺序的比较中，ERP没有显着差异。配对参与者）；（2）脑内相位滞后指数（PLI）高于脑间PLI，但在所有典型频段（从δ到γ）上，其表现出明显差异的连接数均较小；（3）在使用每个频带（总共五个频带）的所有情况下，PLI-Conv间的情感分类准确性均优于PLI-Conv内。尤其是，对于PLI-Conv间和PLI-Conv间，在alpha波段中所有参与者的平均分类准确率分别为65.55％和50.77％（远高于机会水平）。根据我们的结果，幸福感的情感类别可以比其他类别具有更高的表现。