Literature DB >> 18604958

Executive attention and task switching in category learning: evidence for stimulus-dependent representation.

Michael A Erickson1.   

Abstract

One class of multiple-system models of category learning posits that within a single category-learning task people can learn to utilize different systems with different category representations to classify different stimuli. This is referred to as stimulus-dependent representation (SDR). The use of SDR implies that learners switch from subtask to subtask as trials demand. Thus, the use of SDR can be assessed via slowed response times, following a representation switch. Additionally, the use of SDR requires control of executive attention to keep inactive representations from interfering with the current response. Subjects were given a category learning task composed of one- and two-dimensional substructures. Control of executive attention was measured using a working memory capacity (WMC) task. Subjects most likely to be using SDR showed greater slowing of responses following a substructure switch and a greater correlation between learning performance and WMC. These results provide support for the principle of SDR in category learning and the reliance of SDR on executive attention.

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Year:  2008        PMID: 18604958     DOI: 10.3758/mc.36.4.749

Source DB:  PubMed          Journal:  Mem Cognit        ISSN: 0090-502X


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5.  ALCOVE: an exemplar-based connectionist model of category learning.

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