On the generality of optimal versus objective classifier feedback effects on decision criterion learning in perceptual categorization.

Full Abstract

Biased category payoff matrices engender separate reward- and accuracy-maximizing decision criteria Although instructed to maximize reward, observers use suboptimal decision criteria that place greater emphasis on accuracy than is optimal. In this study, objective classifier feedback (the objectively correct response) was compared with optimal classifier feedback (the optimal classifier's response) at two levels of category discriminability when zero or negative costs accompanied incorrect responses for two payoff matrix multiplication factors. Performance was superior for optimal classifier feedback relative to objective classifier feedback for both zero- and negative-cost conditions, especially when category discriminability was low, but the magnitude of the optimal classifier advantage was approximately equal for zero- and negative-cost conditions. The optimal classifier feedback performance advantage did not interact with the payoff matrix multiplication factor. Model-based analyses suggested that the weight placed on accuracy was reduced for optimal classifier feedback relative to objective classifier feedback and for high category discriminability relative to low category discriminability. In addition, the weight placed on accuracy declined with training when feedback was based on the optimal classifier and remained relatively stable when feedback was based on the objective classifier. These results suggest that feedback based on the optimal classifier leads to superior decision criterion learning across a wide range of experimental conditions.

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Author information

Author/s: Bohil, Corey J (CJ); Maddox, W Todd (WT);

Affiliation: University of Texas, Austin, Texas 78712, USA.

Grants: 5 R01MH59196-04 (Agency:United States NIMH)

Journal and publication information

Publication Type: Journal Article; Research Support, U.S. Gov't, Non-P.H.S.; Research Support, U.S. Gov't, P.H.S.

Journal: Memory & cognition (Mem Cognit), published in United States. (Language: eng)

Reference: 2003-Mar; vol 31 (issue 2) : pp 181-98

Dates: Created 2003/05/16; Completed 2003/06/17; Revised 2007/11/14;

PMID: 12749461, status: MEDLINE (last retrieval date: 11/6/2008)

Sourced from the National Library of Medicine. Abstract text and other information may be subject to copyright.

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