A hybrid-similarity exemplar model for predicting distinctiveness effects in perceptual old-new recognition

Abstract

In 2 sets of experiments, the authors investigated the basis for old-item distinctiveness effects in perceptual recognition, whereby distinctive old items are recognized with higher probability than are typical old items. In Experiment 1, distinctive old items were defined as those lying in isolated regions of a continuous-dimension similarity space. In this case, any beneficial effects of distinctiveness were absent or small, regardless of the structure of the test list used to assess recognition memory. In Experiment 2, distinctive items were defined as those objects containing certain discrete, individuating features. In this case, large old-item distinctive effects were observed, with the nature of the effects being modulated by the structure of the test lists. A hybrid-similarity exemplar model, combining elements of continuous-dimension distance and discrete-feature matching, was used to account for these distinctiveness effects in the recognition data.