Proceedings of the Annual Meeting of the Cognitive Science Society

In the first experiment, participants learned an easy rule that allowed perfect categorization that they had to automate. During learning, a new ancillary dimension was systematically associated with the defining feature of each category. In the test phase, items in which the association created during learning was broken were categorized more slowly than those in which the association was present, even for participants who did not notice the association. However, when the category-defining and the ancillary features were reversed in a second experiment, we did not get the anticipated results: there was no effect of the implicit association created during the learning phase. Results are explained in terms of dependencies between properties during processing. It is argued that similarity to previous exemplars does not explain the results obtained here.