Do Salient Features Overshadow Learning of Other Features in Category Learning?

Hundreds of associative learning experiments have examined how animals learn to predict an aversive outcome, such as a shock, loud sound, or puff of air in the eye. In this study, we reversed this pattern and examined the role of an aversive stimulus, shock, as a feature of a complex stimulus composed of several features, rather than as an outcome. In particular, we used a category learning paradigm in which multiple features predicted category membership and asked whether a salient, aversive feature would reduce learning of other category features through cue competition. Three experiments compared a condition in which 1 category had among its 6 features a painful "sting" (shock) and the other category a distinctive sound (the critical features) to a control condition in which the sting and sound were represented by much less salient (and not aversive) visual depictions. Subjects learned the categories and then were tested on their knowledge of all 6 features as predictors of the category label. Surprisingly, the experiments consistently found that the salient, aversive critical features did not reduce learning of other features relative to the control. Bayesian statistics gave positive evidence for this null result. Equally surprisingly, in a fourth experiment, a nonaversive salient feature (brightly colored patterns) increased learning of other features compared to the control. We explain the results in terms of attentional strategies that may apply in a category learning context.