Department of Psychology, UAC 253, Texas State University, 601 University Dr., San Marcos TX 78666, USA.
Department of Psychology, The University of Texas at Austin, 108 E. Dean Keeton St., Austin, TX 78712, USA.
Cogn Psychol. 2023 Feb;140:101541. doi: 10.1016/j.cogpsych.2022.101541. Epub 2022 Dec 30.
Face perception and recognition are important processes for social interaction and communication among humans, so understanding how faces are mentally represented and processed has major implications. At the same time, faces are just some of the many stimuli that we encounter in our everyday lives. Therefore, more general theories of how we represent objects might also apply to faces. Contemporary research on the mental representation of faces has centered on two competing theoretical frameworks that arose from more general categorization research: prototype-based face representation and exemplar-based face representation. Empirically distinguishing between these frameworks is difficult and neither one has been ruled out. In this paper, we advance this area of research in three ways. First, we introduce two additional frameworks for mental representation of categories, varying abstraction and ideal representation, which have not been applied to face perception and recognition before. Second, we fit formal computational models of all four of these theories to human perceptual judgments of the typicality and attractiveness (a strong correlate of typicality) of 100 young adult Caucasian female faces, with the models expressed within a face space derived from facial similarity judgments via multidimensional scaling. Third, we predict the perceived typicality and attractiveness of the faces using these models and compare the predictive performance of each to the empirical data. We found that of all four models, the ideal representation model provided the best account of perceived typicality and attractiveness for the present set of faces, although all models showed discrepancies from the empirical data. These findings demonstrate the relevance of mental categorization processes for representing faces.
面部感知和识别是人类社会互动和交流的重要过程，因此理解面部是如何在心理上被表示和处理的具有重要意义。同时，面部只是我们日常生活中遇到的众多刺激之一。因此，关于我们如何表示物体的更一般的理论也可能适用于面部。当代对面部心理表示的研究集中在两个相互竞争的理论框架上，这两个框架源于更一般的分类研究：基于原型的面部表示和基于范例的面部表示。从经验上区分这两个框架是困难的，而且没有一个框架被排除。在本文中，我们通过三种方式推进这一研究领域。首先，我们引入了两个用于类别心理表示的附加框架，即变抽象和理想表示，以前它们都没有被应用于面部感知和识别。其次，我们将这四个理论的所有正式计算模型都应用于人类对 100 张年轻成年白种女性面孔的典型性和吸引力（典型性的强相关）的感知判断，这些模型是通过多维标度从面部相似性判断中得出的面部空间中表示的。第三，我们使用这些模型来预测面孔的感知典型性和吸引力，并将每个模型的预测性能与经验数据进行比较。我们发现，在所有四个模型中，理想表示模型最能解释本研究中这些面孔的感知典型性和吸引力，尽管所有模型都与经验数据存在差异。这些发现表明，心理分类过程对于表示面部具有重要意义。
