Centre for Pain Research, University of Bath, Bath, United Kingdom; Department of Psychology, University of Bath, Bath, United Kingdom; Division of Social Sciences, Duke Kunshan University, Kunshan, Jiangsu Province, China.
Centre for Pain Research, University of Bath, Bath, United Kingdom; Department of Experimental-Clinical and Health Psychology, Ghent University, Belgium.
J Pain. 2021 Feb;22(2):196-208. doi: 10.1016/j.jpain.2020.07.004. Epub 2020 Aug 7.
We are able to recognize others' experience of pain from their facial expressions. However, little is known about what makes the recognition of pain possible and whether it is similar or different from core emotions. This study investigated the mechanisms underpinning the recognition of pain expressions, in terms of spatial frequency (SF) information analysis, and compared pain with 2 core emotions (ie, fear and happiness). Two experiments using a backward masking paradigm were conducted to examine the time course of low- and high-SF information processing, by manipulating the presentation duration of face stimuli and target-mask onset asynchrony. Overall, we found a temporal advantage of low-SF over high-SF information for expression recognition, including pain. This asynchrony between low- and high-SF happened at a very early stage of information extraction, which indicates that the decoding of low-SF expression information is not only faster but possibly occurs before the processing of high-SF information. Interestingly, the recognition of pain was also found to be slower and more difficult than core emotions. It is suggested that more complex decoding process may be involved in the successful recognition of pain from facial expressions, possibly due to the multidimensional nature of pain experiences. PERSPECTIVE: Two studies explore the perceptual and temporal properties of the decoding of pain facial expressions. At very early stages of attention, the recognition of pain was found to be more difficult than fear and happiness. It suggests that pain is a complex expression, and requires additional time to detect and process.
我们能够从他人的面部表情中识别出他们的疼痛体验。然而,对于什么使得识别疼痛成为可能,以及它是否与核心情绪相似或不同,我们知之甚少。本研究通过空间频率 (SF) 信息分析,调查了识别疼痛表情的机制,并将疼痛与 2 种核心情绪(即恐惧和快乐)进行了比较。通过操纵面部刺激呈现持续时间和目标掩蔽起始时间的异步性,进行了两个使用反向掩蔽范式的实验,以检查低和高 SF 信息处理的时间进程。总的来说,我们发现表情识别(包括疼痛)中低 SF 信息的处理时间比高 SF 信息快。这种低 SF 和高 SF 之间的异步性发生在信息提取的非常早期阶段,这表明低 SF 表情信息的解码不仅更快,而且可能在高 SF 信息处理之前发生。有趣的是,我们还发现疼痛的识别比核心情绪更慢、更困难。这表明,在成功地从面部表情中识别疼痛时,可能涉及更复杂的解码过程,这可能是由于疼痛体验的多维性质。观点:两项研究探讨了疼痛面部表情解码的感知和时间特性。在注意力的非常早期阶段,我们发现识别疼痛比识别恐惧和快乐更困难。这表明疼痛是一种复杂的表情,需要额外的时间来检测和处理。