Individual differences in object recognition.

There is substantial evidence for individual differences in personality and cognitive abilities, but we lack clear intuitions about individual differences in visual abilities. Previous work on this topic has typically compared performance with only 2 categories, each measured with only 1 task. This approach is insufficient for demonstration of domain-general effects. Most previous work has used familiar object categories, for which experience may vary between participants and categories, thereby reducing correlations that would stem from a common factor. In Study 1, we adopted a latent variable approach to test for the first time whether there is a domain-general object recognition ability, o. We assessed whether shared variance between latent factors representing performance for each of 5 novel object categories could be accounted for by a single higher-order factor. On average, 89% of the variance of lower-order factors denoting performance on novel object categories could be accounted for by a higher-order factor, providing strong evidence for o. Moreover, o also accounted for a moderate proportion of variance in tests of familiar object recognition. In Study 2, we assessed whether the strong association across categories in object recognition is due to third-variable influences. We find that o has weak to moderate associations with a host of cognitive, perceptual, and personality constructs and that a clear majority of the variance in and covariance between performance on different categories is independent of fluid intelligence. This work provides the first demonstration of a reliable, specific, and domain-general object recognition ability, and suggest a rich framework for future work in this area. (PsycINFO Database Record (c) 2019 APA, all rights reserved).

Gender differences in recognition of toy faces suggest a contribution of experience.

When there is a gender effect, women perform better then men in face recognition tasks. Prior work has not documented a male advantage on a face recognition task, suggesting that women may outperform men at face recognition generally either due to evolutionary reasons or the influence of social roles. Here, we question the idea that women excel at all face recognition and provide a proof of concept based on a face category for which men outperform women. We developed a test of face learning to measures individual differences with face categories for which men and women may differ in experience, using the faces of Barbie dolls and of Transformers. The results show a crossover interaction between subject gender and category, where men outperform women with Transformers' faces. We demonstrate that men can outperform women with some categories of faces, suggesting that explanations for a general face recognition advantage for women are in fact not needed.

Item response theory analyses of the Cambridge Face Memory Test (CFMT).

We evaluated the psychometric properties of the Cambridge Face Memory Test (CFMT; Duchaine & Nakayama, 2006). First, we assessed the dimensionality of the test with a bifactor exploratory factor analysis (EFA). This EFA analysis revealed a general factor and 3 specific factors clustered by targets of CFMT. However, the 3 specific factors appeared to be minor factors that can be ignored. Second, we fit a unidimensional item response model. This item response model showed that the CFMT items could discriminate individuals at different ability levels and covered a wide range of the ability continuum. We found the CFMT to be particularly precise for a wide range of ability levels. Third, we implemented item response theory (IRT) differential item functioning (DIF) analyses for each gender group and 2 age groups (age ≤ 20 vs. age > 21). This DIF analysis suggested little evidence of consequential differential functioning on the CFMT for these groups, supporting the use of the test to compare older to younger, or male to female, individuals. Fourth, we tested for a gender difference on the latent facial recognition ability with an explanatory item response model. We found a significant but small gender difference on the latent ability for face recognition, which was higher for women than men by 0.184, at age mean 23.2, controlling for linear and quadratic age effects. Finally, we discuss the practical considerations of the use of total scores versus IRT scale scores in applications of the CFMT.

Face recognition in emotional scenes: observers remember the eye shape but forget the nose.

Face recognition is believed to be a highly specialized process that allows individuals to recognize faces faster and more accurately than ordinary objects. However, when faces are viewed in highly emotional contexts, the process becomes slower and less accurate. This suggests a change in recognition strategy compared to recognition in non-arousing contexts. Here we explore this finding by using a novel paradigm to determine which face dimensions are most important for recognizing faces that were initially encoded in highly emotional contexts. Participants were asked to recognize faces from a 3-alternative display after viewing a similar face that was embedded in either a neutral, positive, or negative emotional scene. Results showed that individuals rely on eye shape when recognizing faces that were encoded while embedded in either positive or negative emotional contexts, and ignore nose shape when recognizing faces that were encoded while embedded in negative emotional scenes. The findings suggest that, after encoding that face during heightened emotional arousal, individuals are more likely to commit errors when identifying a face on the basis of nose shape, and less likely to commit errors when identifying a face on the basis of eye shape.