Taubert Jessica, Weldon Kimberly B, Parr Lisa A
Yerkes National Primate Research Center, Emory University, Atlanta, GA, 30329, USA.
The National Institute of Mental Health, Bethesda, MD, 20814, USA.
Anim Cogn. 2017 Mar;20(2):321-329. doi: 10.1007/s10071-016-1054-6. Epub 2016 Nov 19.
Being able to recognize the faces of our friends and family members no matter where we see them represents a substantial challenge for the visual system because the retinal image of a face can be degraded by both changes in the person (age, expression, pose, hairstyle, etc.) and changes in the viewing conditions (direction and degree of illumination). Yet most of us are able to recognize familiar people effortlessly. A popular theory for how face recognition is achieved has argued that the brain stabilizes facial appearance by building average representations that enhance diagnostic features that reliably vary between people while diluting features that vary between instances of the same person. This explains why people find it easier to recognize average images of people, created by averaging multiple images of the same person together, than single instances (i.e. photographs). Although this theory is gathering momentum in the psychological and computer sciences, there is no evidence of whether this mechanism represents a unique specialization for individual recognition in humans. Here we tested two species, chimpanzees (Pan troglodytes) and rhesus monkeys (Macaca mulatta), to determine whether average images of different familiar individuals were easier to discriminate than photographs of familiar individuals. Using a two-alternative forced-choice, match-to-sample procedure, we report a behaviour response profile that suggests chimpanzees encode the faces of conspecifics differently than rhesus monkeys and in a manner similar to humans.
无论在何处看到朋友和家人的面孔，我们都能认出他们，这对视觉系统来说是一项巨大的挑战，因为面部的视网膜图像会因人物的变化（年龄、表情、姿势、发型等）和观看条件的变化（光照方向和程度）而退化。然而，我们大多数人都能毫不费力地认出熟悉的人。一种关于人脸识别是如何实现的流行理论认为，大脑通过构建平均表征来稳定面部外观，这种平均表征增强了人与人之间可靠变化的诊断特征，同时淡化了同一个人不同实例之间变化的特征。这就解释了为什么人们发现识别通过将同一个人的多张图像平均在一起而创建的人的平均图像比识别单个实例（即照片）更容易。尽管这一理论在心理学和计算机科学领域越来越受关注，但没有证据表明这种机制是否代表了人类个体识别的独特专业化。在这里，我们测试了两种物种，黑猩猩（Pan troglodytes）和恒河猴（Macaca mulatta），以确定不同熟悉个体的平均图像是否比熟悉个体的照片更容易区分。使用二选一强制选择、匹配样本程序，我们报告了一种行为反应模式，表明黑猩猩对同种个体面孔的编码方式与恒河猴不同，且与人类相似。
