EEG DYNAMICS DURING EMOTIONAL FACE PERCEPTION UNDER THE VARIABLE PRESENTATION TIME: AN ERP STUDY

Yaroslav Subin, M. Chernykh, Ihor Zyma
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Abstract

The face is one of the most significant elements of non-verbal communication, which allows humans to quickly get various types of information about a specific person. Therefore, understanding facial expressions is crucial for normal social interaction, as it lets us determine the emotional states and intentions of other people. The purpose of this study was to investigate the influence of the time factor on the happy and fearful facial expression processing, reflected in the structure and components of event-related potentials (ERPs). Accordingly, two parallel examinations were conducted with stimulus presentation periods of 500 ms and 100 ms. For the obtained data, two separate analyses (for happy and fearful faces) of the averaged ERP curves corresponding to different stimulus exposure periods were executed. The initial stages of processing (EPN, P3) demonstrated that the difference in the structure and amplitude characteristics of the ERP curve was not that significant, but it demonstrated an increase in attentional resources involvement and a strengthening of the primary emotional analysis. Later ERP components (N400, LPP) showed a more compelling difference, that reflected the complexity of semantic decoding, subsequent conscious evaluation, and processes related to decision-making. Thus, reducing the time of image display from 500 ms to 100 ms created the expected difficulties for the perception and processing of emotional facial expressions and was not sufficient for the normal course of these processes.
不同呈现时间下情绪面孔知觉的脑电动态:erp研究
脸是非语言交流中最重要的元素之一,它使人类能够快速获得关于特定人物的各种信息。因此,理解面部表情对于正常的社交互动至关重要,因为它可以让我们确定他人的情绪状态和意图。本研究的目的是探讨时间因素对快乐和恐惧面部表情加工的影响,这反映在事件相关电位(ERPs)的结构和组成上。相应的,以500ms和100ms的刺激呈现时间进行两个平行实验。对于获得的数据,分别对不同刺激暴露周期对应的平均ERP曲线进行了两次单独的分析(对于快乐和恐惧的面孔)。加工的初始阶段(EPN, P3)表明,ERP曲线的结构和振幅特征差异并不显著,但它表明注意资源投入的增加和初级情绪分析的加强。后期的ERP组件(N400, LPP)显示出更引人注目的差异,这反映了语义解码,随后的有意识评估和决策相关过程的复杂性。因此,将图像显示时间从500 ms减少到100 ms,对情绪面部表情的感知和处理产生了预期的困难,并且不足以满足这些过程的正常进行。
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