Tests of face processing are typically designed to identify individuals performing outside of the typical range; either prosopagnosic individuals who exhibit poor face processing ability, or super recognisers, who have superior face processing abilities. Here we describe the development of the Oxford Face Matching Test (OFMT), designed to identify individual differences in face processing across the full range of performance, from prosopagnosia, through the range of typical performance, to super recognisers. Such a test requires items of varying difficulty, but establishing difficulty is problematic when particular populations (e.g., prosopagnosics, individuals with autism spectrum disorder) may use atypical strategies to process faces. If item difficulty is calibrated on neurotypical individuals, then the test may be poorly calibrated for atypical groups, and vice versa. To obtain items of varying difficulty, we used facial recognition algorithms to obtain face pair similarity ratings that are not biased towards specific populations. These face pairs were used as stimuli in the OFMT, and participants were required to judge whether the face images depicted the same individual or different individuals. Across five studies the OFMT was shown to be sensitive to individual differences in the typical population, and in groups of both prosopagnosic individuals and super recognisers. The test-retest reliability of the task was at least equivalent to the Cambridge Face Memory Test and the Glasgow Face Matching Test. Furthermore, results reveal, at least at the group level, that both face perception and face memory are poor in those with prosopagnosia, and are good in super recognisers.

面部处理测试通常旨在识别表现超出典型范围的个人；要么是人脸处理能力差的面相失认者，要么是人脸处理能力出众的超级识别者。在这里，我们描述了牛津人脸匹配测试 (OFMT) 的发展，该测试旨在识别从面容失认到典型表现到超级识别者的全方位表现中的人脸处理的个体差异。这样的测试需要不同难度的项目，但是当特定人群（例如，面容失认症患者、自闭症谱系障碍患者）可能使用非典型策略来处理面部时，确定难度是有问题的。如果项目难度在神经典型个体上进行校准，那么测试对于非典型组的校准可能会很差，反之亦然。为了获得不同难度的项目，我们使用面部识别算法来获得不偏向特定人群的面部对相似度评级。这些人脸对在 OFMT 中被用作刺激物，参与者需要判断这些人脸图像是描绘同一个人还是不同个人。在五项研究中，OFMT 被证明对典型人群中的个体差异以及在面容失认个体和超级识别者群体中的个体差异敏感。该任务的重测信度至少相当于剑桥人脸记忆测试和格拉斯哥人脸匹配测试。此外，结果显示，至少在群体层面，