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Domain-specific and domain-general individual differences in visual object recognition


Outcome:
Researchers found that performance on Novel Object Memory Tests (NOMTs) varied just as much as on familiar object, but showed more shared variance across each other (about 25%) than is typically observed among familiar object tests (about 11%). Importantly, they verified that the ability measured in the NOMTs is not explained by cognitive skills, because shared variance between NOMTs remained unchanged after controlling for performance on various measures of general intelligence. Researchers attempting to estimate a general visual ability that is distinct from intelligence should consider using NOMTs or other tasks with novel objects to avoid complications from varying experience.

Impact/benefit:
Visual skills are important in many areas of human behavior such as medical diagnosis, security and forensic professions. Accounting for variability between people that is relevant to these areas and that is independent from general intelligence may improve placement and training.The work is a stepping-stone to other new avenues of research. For instance, past studies of expertise have uncovered the neural substrates of category-specific expertise likely related to experience. New studies focusing on domain-general visual skills measured by NOMTs are needed to reveal aspects of brain structure and activity support the ability to acquire expertise in new categories.

Background/explanation:
In recent work, researchers funded by the NSF-supported Temporal Dynamics Learning Center asked if a domain-general visual recognition mechanism could apply broadly and predict how people acquire new visual skills. Because variable experience with familiar categories can contribute to differences in performance, they created Novel Object Memory Tests (NOMTs, see Figure 2). In a large sample of people tested online, performance across different NOMTs revealed a common visual ability that was not accounted for by general intelligence.

Leanne Chukoskie
Figure 2. A) Examples of novel objects in NOMTs (Richler et al., 2017). Each object in each set has unique parts although parts can be very similar across objects. There is no rule that can be generalized across categories. B) in each NOMTs, 6 targets are studied individually in two views, then all 6 are shown together to memorize for 20 sec. This is followed by a series of 3-alternatives forced choice trials as shown in C).

Richler, J.J., Wilmer, J.B., Gauthier, I. (2017). General object recognition is specific: evidence from novel and familiar objects. Cognition, 166: 42-55.