Plouffe-Demers Marie-Pier, Fiset Daniel, Saumure Camille, Duncan Justin, Blais Caroline
Département de Psychologie, Universtité du Québec en Outaouais, Gatineau, QC, Canada.
Département de Psychologie, Université du Québec à Montréal, Montreal, QC, Canada.
Front Psychol. 2019 Jul 17;10:1563. doi: 10.3389/fpsyg.2019.01563. eCollection 2019.
Facial expressions of emotion play a key role in social interactions. While in everyday life, their dynamic and transient nature calls for a fast processing of the visual information they contain, a majority of studies investigating the visual processes underlying their recognition have focused on their static display. The present study aimed to gain a better understanding of these processes while using more ecological dynamic facial expressions. In two experiments, we directly compared the spatial frequency (SF) tuning during the recognition of static and dynamic facial expressions. Experiment 1 revealed a shift toward lower SFs for dynamic expressions in comparison to static ones. Experiment 2 was designed to verify if changes in SF tuning curves were specific to the presence of emotional information in motion by comparing the SF tuning profiles for static, dynamic, and shuffled dynamic expressions. Results showed a similar shift toward lower SFs for shuffled expressions, suggesting that the difference found between dynamic and static expressions might not be linked to informative motion but to the presence of motion regardless its nature.
情绪的面部表情在社交互动中起着关键作用。在日常生活中，它们动态且短暂的特性要求对其所包含的视觉信息进行快速处理，然而，大多数研究情绪识别背后视觉过程的研究都集中在其静态展示上。本研究旨在通过使用更具生态性的动态面部表情来更好地理解这些过程。在两个实验中，我们直接比较了识别静态和动态面部表情时的空间频率（SF）调谐情况。实验1表明，与静态表情相比，动态表情的SF调谐向更低频率偏移。实验2旨在通过比较静态、动态和随机动态表情的SF调谐曲线，验证SF调谐曲线的变化是否特定于运动中情绪信息的存在。结果显示，随机表情也有类似的向更低频率的偏移，这表明动态和静态表情之间的差异可能与信息性运动无关，而是与运动的存在有关，无论其性质如何。
