According to the instantiation principle, when we make a judgment about a relatively superordinate category, we follow a two-step process. First, we instantiate the category into one or more subordinates. SeoHid, we make a judgment based on the subordinates. Instantiation theory :q>plied to typicality judgments makes the following predictions. W h e n subjects judge the typicality of a category A with respect to categ(My B, their mean typicality judgment should equal the weighted mean typicality (with respect to B ) of subwdinate categories of A. Furthermore, typicality judgments for category A will be unstable (i.e., have a high standard deviation) to the extent that A has a large number of diverse subordinates. The instantiation principle was implemented in a computer simulation, which used production frequencies and typicality ratings for subordinates to predict ratings for superordinate-level categories. In two experiments, subjects judged the typicalities of various animal and food categories. The instantiation model successfully predicted the means and standard deviations for the observed distributions of responses for these categories. Extensions and other applications of the instantiation principle are also briefly discussed.

This study examines how situation information is incorporated in concept learning and representation. Unlike most concept learning studies, this study includes situation information during concept learning. Unlike most studies about the influence of situations on episodic memory, this study investigates how situations affects conceptual processing. Experiment 1 demonstrates that people rely on situation information when processing concepts. Subjects verified a concept's property more quickly if the property was learned and tested in the same situation. Experiment 2 shows that in order for a situation to produce priming, the situation must be related to the property in a meaningful manner. Mere cooccurrence between a property and a situation is not sufficient.

Athough both prepositional and perceptual representations are viewed as central to human memory, propositional representations are typically assumed to underlie conceptual knowledge. Propositional models of concepts, such as feature lists, frames, and networks, embody this assumption. Recent theories across the cognitive sciences, however, have proposed that perceptual representations are central to conceptual processing. These perceptual representations are postulated to be schematic, dynamic, and multimodal images that have been extracted from perception and experience. In the experiment reported here, we used the property verification task to determine the extent to which people use perceptual representations during conceptual processing. A regression analysis revealed two kinds of evidence for the spontaneous use of perceptual representations: First, neutral and imagery subjects showed a similar pattern of reaction times on the task. Second, perceptual variables, such as the property size, predicted verification times.