Recognizing spatial patterns: a noisy exemplar approach.
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.
Center for Complex Systems, Brandeis University, 415 South Street, Waltham, MA 02454-9110, USA. kahana@brandeis.edu
Michael J
MJ
Kahana
Robert
R
Sekuler
D004192:Discrimination, Psychological; D006801:Humans; D008960:Models, Psychological; D010364:Pattern Recognition, Visual; D010775:Photic Stimulation / Q000379:methods; D011601:Psychophysics; D021641:Recognition, Psychology