Darke Hayley, Cropper Simon J, Carter Olivia
Melbourne School of Psychological Sciences, The University of Melbourne, Melbourne, VIC, Australia.
Front Psychol. 2019 Apr 9;10:757. doi: 10.3389/fpsyg.2019.00757. eCollection 2019.
Face-based tasks are used ubiquitously in the study of human perception and cognition. Video-based (dynamic) face stimuli are increasingly utilized by researchers because they have higher ecological validity than static images. However, there are few ready-to-use dynamic stimulus sets currently available to researchers that include and control stimuli. This paper outlines the development of three original dynamic stimulus sets: a set of emotional faces (fear and disgust), a set of non-emotional faces, and a set of car animations. Morphing software was employed to vary the intensity of the expression shown and to vary the similarity between actors. Manipulating these dimensions permits us to create tasks of varying difficulty that can be optimized to detect more subtle differences in face-processing ability. Using these new stimuli, two preliminary experiments were conducted to evaluate different aspects of facial identity recognition, emotion recognition, and non-face object discrimination. Results suggest that these five different tasks successfully avoided floor and ceiling effects in a healthy sample. A second experiment found that dynamic versions of the emotional stimuli were recognized more accurately than static versions, both for labeling, and discrimination paradigms. This indicates that, like previous emotion-only stimuli sets, the use of dynamic stimuli confers an advantage over image-based stimuli. These stimuli therefore provide a useful resource for researchers looking to investigate both emotional and non-emotional face-processing using dynamic stimuli. Moreover, these stimuli vary across crucial dimensions (i.e., face similarity and intensity of emotion) which allows researchers to modify task difficulty as required.
基于面部的任务在人类感知和认知研究中被广泛使用。基于视频的（动态）面部刺激越来越受到研究人员的青睐，因为它们比静态图像具有更高的生态效度。然而，目前研究人员可获得的现成动态刺激集很少，其中包括对照刺激。本文概述了三种原创动态刺激集的开发：一组情绪面孔（恐惧和厌恶）、一组非情绪面孔和一组汽车动画。使用变形软件来改变所显示表情的强度，并改变演员之间的相似度。对这些维度进行操纵使我们能够创建难度各异的任务，这些任务可以进行优化，以检测面部处理能力中更细微的差异。使用这些新的刺激，进行了两项初步实验，以评估面部身份识别、情绪识别和非面部物体辨别等不同方面。结果表明，在健康样本中，这五项不同任务成功避免了地板效应和天花板效应。第二项实验发现，无论是在标签任务还是辨别范式中，情绪刺激的动态版本都比静态版本被更准确地识别。这表明，与之前仅用于情绪的刺激集一样，使用动态刺激比基于图像的刺激具有优势。因此，这些刺激为希望使用动态刺激来研究情绪和非情绪面部处理的研究人员提供了有用的资源。此外，这些刺激在关键维度（即面部相似度和情绪强度）上有所不同，这使研究人员能够根据需要调整任务难度。
