Degrees of Expertise

Abstract

Visual object recognition and categorization are fundamental abilities required for successful negotiation of the visual world. Humans effortlessly classify and recognize objects and faces within busy scenes, thousands of times a day. Thus, understanding how perceptual categorization and learning occur and how such seemingly complicated computations are implemented in brain processes is an important goal in cognitive psychology and cognitive neuroscience. One way of furthering our understanding of category learning is to examine how differences in experience with specific classes of objects (e.g., dogs, cars, faces) influence the speed and level at which these objects are categorized. Object categorization is arbitrary in the sense that a single object can be classified at multiple levels of abstraction. For instance, the same American Tree Sparrow can be classified as an ‘‘animal’’ at a general or superordinate level, a ‘‘bird’’ at the basic level, and an ‘‘American Tree Sparrow’’ at a specific or subordinate level. In contrast to object categorization, object recognition is not arbitrary in that most objects are identified at the same level of abstraction—the so-called basic level (Jolicoeur, Gluck, & Kosslyn, 1984; Murphy & Smith, 1982; Rosch, Mervis, Gray, Johnson, & Boyes-Braem, 1976). Seminal work by Rosch and colleagues demonstrated that the basic level is the optimum level of abstraction at which category members are perceptually most similar to one another and are maximally distinct from other category members. Given its structural advantage, the basic level is the preferred level in initial object recognition. However, the basic level is typically not the preferred level for experts where recognition often demands a more specific, subordinate level of identification (Johnson & Mervis, 1997; Tanaka, 2001; but see Wong & Gauthier, in press, and Chapter 10, for descriptions of basic-level expertise). For example, face processing is thought to be a universally expert skill where faces are differentiated at the level of the individual (e.g., Bob, Susan) (Tanaka, 2001). Similarly, given the demands of expertise, expert bird watchers and car enthusiasts identify birds or cars at a more subordinate level (e.g., Bachman warbler, BMW Z1) compared to nonexperts (Tanaka & Taylor, 1991). Tanaka & Taylor (1991) suggested that category specificity arises when the demands of expertise require that exemplars within a category be differentiated from one another (as we do with faces). Furthermore, different recognition strategies may be best supported by different parts of