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Feature-sampling and random-walk models of individual-stimulus recognition

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Lamberts, Koen, Brockdorff, Noellie and Heit, Evan, 1965-. (2003) Feature-sampling and random-walk models of individual-stimulus recognition. Journal of Experimental Psychology: General, Vol.132 (No.3). pp. 351-378. ISSN 0096-3445

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Official URL: http://dx.doi.org/10.1037/0096-3445.132.3.351

Abstract

Traditional process models of old-new recognition have not addressed differences in accuracy and response time between individual stimuli. Two new process models of recognition are presented and applied to response time and accuracy data from 3 old-new recognition experiments. The 1st model is derived from a feature-sampling account of the time course of categorization, whereas the 2nd model is a generalization of a random-walk model of categorization. In the experiments, a new technique was used, which yielded reliable individual-stimulus data through repeated presentation of structurally equivalent items. The results from the experiments showed reliable differences in accuracy and response times between stimuli. The random-walk model provided the better account of the results from the 3 experiments. The implications of the results for process models of recognition are discussed.

Item Type: Journal Article
Subjects: B Philosophy. Psychology. Religion > BF Psychology
Divisions: Faculty of Science > Psychology
Library of Congress Subject Headings (LCSH): Human information processing, Random walks (Mathematics), Recognition (Psychology), Reaction time, Memory
Journal or Publication Title: Journal of Experimental Psychology: General
Publisher: American Psychological Association
ISSN: 0096-3445
Date: September 2003
Volume: Vol.132
Number: No.3
Number of Pages: 28
Page Range: pp. 351-378
Identification Number: 10.1037/0096-3445.132.3.351
Status: Peer Reviewed
Publication Status: Published
Funder: Biotechnology and Biological Sciences Research Council (Great Britain) (BBSRC)
URI: http://wrap.warwick.ac.uk/id/eprint/9375

Data sourced from Thomson Reuters' Web of Knowledge

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