Li Huiyun, Ji Luyan, Tong Ke, Ren Naixin, Chen Wenfeng, Liu Chang Hong, Fu Xiaolan
State Key Laboratory of Brain and Cognitive Science, Institute of Psychology, Chinese Academy of SciencesBeijing, China; University of Chinese Academy of SciencesBeijing, China.
Department of Experimental Clinical and Health Psychology, Ghent University Ghent, Belgium.
Front Psychol. 2016 Sep 7;7:1332. doi: 10.3389/fpsyg.2016.01332. eCollection 2016.
There is growing evidence that human observers are able to extract the mean emotion or other type of information from a set of faces. The most intriguing aspect of this phenomenon is that observers often fail to identify or form a representation for individual faces in a face set. However, most of these results were based on judgments under limited processing resource. We examined a wider range of exposure time and observed how the relationship between the extraction of a mean and representation of individual facial expressions would change. The results showed that with an exposure time of 50 ms for the faces, observers were more sensitive to mean representation over individual representation, replicating the typical findings in the literature. With longer exposure time, however, observers were able to extract both individual and mean representation more accurately. Furthermore, diffusion model analysis revealed that the mean representation is also more prone to suffer from the noise accumulated in redundant processing time and leads to a more conservative decision bias, whereas individual representations seem more resistant to this noise. Results suggest that the encoding of emotional information from multiple faces may take two forms: single face processing and crowd face processing.
越来越多的证据表明,人类观察者能够从一组面孔中提取平均情绪或其他类型的信息。这一现象最引人入胜的方面是,观察者往往无法识别或形成面孔集合中单个面孔的表征。然而,这些结果大多基于有限处理资源下的判断。我们研究了更广泛的曝光时间范围,并观察了平均表情提取与单个面部表情表征之间的关系将如何变化。结果表明,面孔的曝光时间为50毫秒时,观察者对平均表征比对单个表征更敏感,这重复了文献中的典型发现。然而,曝光时间更长时,观察者能够更准确地提取单个和平均表征。此外,扩散模型分析表明,平均表征也更容易受到冗余处理时间中积累的噪声影响,并导致更保守的决策偏差,而单个表征似乎对这种噪声更具抵抗力。结果表明,从多张面孔中编码情绪信息可能有两种形式:单面孔处理和群体面孔处理。