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Breaking the rules in perceptual information integration

Bushmakin, MA, Eidels, A and Heathcote, A ORCID: 0000-0003-4324-5537 2017 , 'Breaking the rules in perceptual information integration' , Cognitive Psychology, vol. 95 , pp. 1-16 , doi: 10.1016/j.cogpsych.2017.03.001.

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Abstract

We develop a broad theoretical framework for modelling difficult perceptual informationintegration tasks under different decision rules. The framework allows us to compare coactivearchitectures, which combine information before it enters the decision process, withparallel architectures, where logical rules combine independent decisions made about eachperceptual source. For both architectures we test the novel hypothesis that participantsbreak the decision rules on some trials, making a response based on only one stimulus eventhough task instructions require them to consider both. Our models take account of notonly the decisions made but also the distribution of the time that it takes to make them,providing an account of speed-accuracy tradeoffs and response biases occurring whenone response is required more often than another. We also test a second novel hypothesis,that the nature of the decision rule changes the evidence on which choices are based. Weapply the models to data from a perceptual integration task with near threshold stimuliunder two different decision rules. The coactive architecture was clearly rejected in favorof logical-rules. The logical-rule models were shown to provide an accurate account ofall aspects of the data, but only when they allow for response bias and the possibility forsubjects to break those rules. We discuss how our framework can be applied more broadly,and its relationship to Townsend and Nozawa’s (1995) Systems-Factorial Technology.

Item Type: Article
Authors/Creators:Bushmakin, MA and Eidels, A and Heathcote, A
Journal or Publication Title: Cognitive Psychology
Publisher: Academic Press Inc Elsevier Science
ISSN: 0010-0285
DOI / ID Number: 10.1016/j.cogpsych.2017.03.001
Copyright Information:

Copyright 2017 Elsevier Inc. All rights reserved.

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