McGugin Rankin W, Richler Jennifer J, Herzmann Grit, Speegle Magen, Gauthier Isabel
Department of Psychology, Vanderbilt University, Nashville, TN 37203, USA.
Vision Res. 2012 Sep 15;69:10-22. doi: 10.1016/j.visres.2012.07.014. Epub 2012 Aug 2.
Individual differences in face recognition are often contrasted with differences in object recognition using a single object category. Likewise, individual differences in perceptual expertise for a given object domain have typically been measured relative to only a single category baseline. In Experiment 1, we present a new test of object recognition, the Vanderbilt Expertise Test (VET), which is comparable in methods to the Cambridge Face Memory Task (CFMT) but uses eight different object categories. Principal component analysis reveals that the underlying structure of the VET can be largely explained by two independent factors, which demonstrate good reliability and capture interesting sex differences inherent in the VET structure. In Experiment 2, we show how the VET can be used to separate domain-specific from domain-general contributions to a standard measure of perceptual expertise. While domain-specific contributions are found for car matching for both men and women and for plane matching in men, women in this sample appear to use more domain-general strategies to match planes. In Experiment 3, we use the VET to demonstrate that holistic processing of faces predicts face recognition independently of general object recognition ability, which has a sex-specific contribution to face recognition. Overall, the results suggest that the VET is a reliable and valid measure of object recognition abilities and can measure both domain-general skills and domain-specific expertise, which were both found to depend on the sex of observers.
人脸识别中的个体差异通常与使用单一物体类别进行物体识别时的差异形成对比。同样,对于给定物体领域的感知专长方面的个体差异,通常仅相对于单一类别基线进行测量。在实验1中,我们提出了一种新的物体识别测试,即范德比尔特专长测试(VET),其方法与剑桥面部记忆任务(CFMT)类似,但使用了八个不同的物体类别。主成分分析表明,VET的潜在结构在很大程度上可以由两个独立因素来解释,这两个因素显示出良好的可靠性,并捕捉到了VET结构中固有的有趣的性别差异。在实验2中,我们展示了VET如何用于区分对感知专长标准测量中特定领域和一般领域的贡献。虽然发现男性和女性在汽车匹配以及男性在飞机匹配方面存在特定领域的贡献,但该样本中的女性似乎使用更多一般领域的策略来匹配飞机。在实验3中,我们使用VET来证明对面部的整体处理独立于一般物体识别能力预测人脸识别,而一般物体识别能力对人脸识别有性别特异性贡献。总体而言,结果表明VET是物体识别能力的一种可靠且有效的测量方法,并且可以测量一般领域技能和特定领域专长,二者均被发现取决于观察者的性别。