Literature DB >> 17201365

Visual noise reveals category representations.

Jason M Gold1, Andrew L Cohen, Richard Shiffrin.   

Abstract

How are categories represented in human memory? Exemplar models assume that a category is represented by individual instances from that category that have been experienced. More generally, a category might be represented by multiple templates stored in memory. A new item is classified according to its similarity to these templates. Prototype models represent a category with a single summary abstraction (i.e., a single template), often the central tendency of the experienced items. A new item is classified according to its similarity to these category prototypes. Here, we show how a technique for correlating observers' responses with external noise can be used not only to distinguish single- from multiple-template representations, but also to induce the form of these templates. The technique is applied to two tasks requiring categorization of simple visual patterns; the results demonstrate that observers used multiple traces to represent their categories, and thus highlight the procedure's potential for use in more complex settings.

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Mesh:

Year:  2006        PMID: 17201365     DOI: 10.3758/bf03193976

Source DB:  PubMed          Journal:  Psychon Bull Rev        ISSN: 1069-9384


  10 in total

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Journal:  Curr Biol       Date:  2000-06-01       Impact factor: 10.834

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Authors:  Allison B Sekuler; Carl M Gaspar; Jason M Gold; Patrick J Bennett
Journal:  Curr Biol       Date:  2004-03-09       Impact factor: 10.834

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Journal:  J Acoust Soc Am       Date:  1975-02       Impact factor: 1.840

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Authors:  D L Ringach; G Sapiro; R Shapley
Journal:  Vision Res       Date:  1997-09       Impact factor: 1.886

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Authors:  John Paul Minda; J David Smith
Journal:  J Exp Psychol Learn Mem Cogn       Date:  2002-03       Impact factor: 3.051

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Authors:  R M Nosofsky
Journal:  J Exp Psychol Gen       Date:  1986-03

9.  Prototypes in category learning: the effects of category size, category structure, and stimulus complexity.

Authors:  J P Minda; J D Smith
Journal:  J Exp Psychol Learn Mem Cogn       Date:  2001-05       Impact factor: 3.051

10.  Human efficiency for recognizing 3-D objects in luminance noise.

Authors:  B S Tjan; W L Braje; G E Legge; D Kersten
Journal:  Vision Res       Date:  1995-11       Impact factor: 1.886

  10 in total

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