Recognizing spatial patterns: a noisy exemplar approach.

Abstract

Models of categorization typically rely on the use of stimuli composed of well-defined dimensions (e.g., Ashby & Maddox (1998) in Choice, decision, and measurement: Essays in honor of R. Duncan Luce, p. 251-301, Mahwah, NJ: Erlbaum). We apply a similar approach to the analysis of recognition memory. Using a version of short-term recognition paradigm (Sternberg, Science 153 (1966) 652), we asked whether NEMO Sternberg's, a noisy exemplar summed-similarity model, could account for variation in mean performance on individual trials. NEMO provided a very good overall fit to recognition data from three experiments. However, its failure to fit data for certain lists of stimuli suggested a revision of the summed-similarity assumption. Our model-based analysis showed that subjects used interitem similarity, in addition to probe-item similarity, as the basis for their decisions. This represents a major departure from existing recognition models that assume subjects' judgments depend exclusively on the summed similarity of the probe to the study items.