Department of Psychology.
Department of Neuroscience.
Psychol Rev. 2019 Mar;126(2):226-251. doi: 10.1037/rev0000129.
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).
有大量证据表明人格和认知能力存在个体差异,但我们对视觉能力的个体差异缺乏清晰的直觉。以前关于这个主题的工作通常只比较两种分类的表现,每种分类只用一项任务来衡量。这种方法不足以证明领域一般性效应。以前的大多数工作都使用了熟悉的物体类别,对于这些类别,参与者之间的经验和类别可能会有所不同,从而减少了由于共同因素而产生的相关性。在研究 1 中,我们采用了潜在变量的方法,首次测试是否存在一种领域一般性的物体识别能力 o。我们评估了代表 5 个新物体类别的每个类别的表现的潜在因素之间的共享方差是否可以由单个高阶因素来解释。平均而言,5 个新物体类别表示性能的较低阶因素的方差中有 89%可以由高阶因素来解释,这为 o 提供了强有力的证据。此外,o 还解释了熟悉物体识别测试中中等比例的方差。在研究 2 中,我们评估了物体识别中跨类别强烈关联是否归因于第三变量的影响。我们发现,o 与许多认知、感知和人格结构的关联较弱到中等,并且不同类别之间的表现和协方差的大部分差异独立于流体智力。这项工作首次证明了一种可靠、特定和领域一般性的物体识别能力,并为该领域的未来工作提供了一个丰富的框架。