Episodic and prototype models of category learning

Richard J. Tunney, Gordon Fernie

Research output: Contribution to journalArticle

7 Citations (Scopus)

Abstract

The question of what processes are involved in the acquisition and representation of categories remains unresolved despite several decades of research. Studies using the well-known prototype distortion task (Posner and Keele in J Exp Psychol 77:353-363, 1968) delineate three candidate models. According to exemplar-based models, we memorize each instance of a category and when asked to decide whether novel items are category members or not, the decision is explicitly based on a similarity comparison with each stored instance. By contrast, prototype models assume that categorization is based on the similarity of the target item to an implicit abstraction of the central tendency or average of previously encountered instances. A third model suggests that the categorization of prototype distortions does not depend on pre-exposure to study exemplars at all and instead reflects properties of the stimuli that are easily learned during the test. The four experiments reported here found evidence that categorization in this task is predicated on the first and third of these models, namely transfer at test and the exemplar-based model. But we found no evidence for the second candidate model that assumed that categorization is based on implicit prototype abstraction.
Original languageEnglish
Pages (from-to)41-54
Number of pages14
JournalCognitive Processing
Volume13
Issue number1
Early online date10 Apr 2011
DOIs
Publication statusPublished - 1 Feb 2012

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Keywords

  • memory
  • categorisation
  • categorization versus identification
  • episodic memory

Cite this

Episodic and prototype models of category learning. / Tunney, Richard J.; Fernie, Gordon.

In: Cognitive Processing, Vol. 13, No. 1, 01.02.2012, p. 41-54.

Research output: Contribution to journalArticle

Tunney, Richard J. ; Fernie, Gordon. / Episodic and prototype models of category learning. In: Cognitive Processing. 2012 ; Vol. 13, No. 1. pp. 41-54.
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