Episodic and prototype models of category learning.

Publisher: Springer Verlag Country of Publication: Germany NLM ID: 101177984 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1612-4790 (Electronic) Linking ISSN: 16124782 NLM ISO Abbreviation: Cogn Process Subsets: MEDLINE

Publication: <2004->: Heidelburg : Springer Verlag
Original Publication: Lengerich : Pabst Science, 2000-

Models, Neurological*; Learning/*physiology; Amnesia/psychology ; Awareness ; Concept Formation ; Confidence Intervals ; Female ; Humans ; Male ; Mental Processes/physiology ; Neuropsychological Tests ; Photic Stimulation ; Regression Analysis ; Young Adult

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.

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Date Created: 20110412 Date Completed: 20120515 Latest Revision: 20211020

20221213

10.1007/s10339-011-0403-2

21479814