Document Detail


Category discriminability, base-rate, and payoff effects in perceptual categorization.
MedLine Citation:
PMID:  11281110     Owner:  NLM     Status:  MEDLINE    
Abstract/OtherAbstract:
The optimality of perceptual categorization performance under manipulations of category discriminability (i.e., d' level), base rates, and payoffs was examined. Base-rate and payoff manipulations across two category discriminabilities allowed a test of the hypothesis that the steepness of the objective reward function affects performance (i.e., the flat-maxima hypothesis), as well as the hypothesis that observers combine base-rate and payoff information independently. Performance was (1) closer to optimal for the steeper objective reward function, in line with the flat-maxima hypothesis, (2) closer to optimal in base-rate conditions than in payoff conditions, and (3) in partial support of the hypothesis that base-rate and payoff knowledge is combined independently. Implications for current theories of base-rate and payoff learning are discussed.
Authors:
C J Bohil; W T Maddox
Publication Detail:
Type:  Journal Article; Research Support, U.S. Gov't, Non-P.H.S.; Research Support, U.S. Gov't, P.H.S.    
Journal Detail:
Title:  Perception & psychophysics     Volume:  63     ISSN:  0031-5117     ISO Abbreviation:  Percept Psychophys     Publication Date:  2001 Feb 
Date Detail:
Created Date:  2001-04-02     Completed Date:  2001-05-03     Revised Date:  2007-11-14    
Medline Journal Info:
Nlm Unique ID:  0200445     Medline TA:  Percept Psychophys     Country:  United States    
Other Details:
Languages:  eng     Pagination:  361-76     Citation Subset:  IM    
Affiliation:
Department of Psychology, Mezes Hall 330, University of Texas, Austin, TX 78712, USA.
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MeSH Terms
Descriptor/Qualifier:
Adult
Attention*
Decision Making*
Female
Humans
Male
Models, Statistical
Motivation*
Pattern Recognition, Visual*
Probability Learning
Problem Solving*
Grant Support
ID/Acronym/Agency:
R01 MH59196/MH/NIMH NIH HHS

From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine


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