Lu, Y, Stafford, T and Fox, C (2016) Maximum saliency bias in binocular fusion. Connection Science, 28 (3). pp. 258-269. ISSN 0954-0091
Abstract
Subjective experience at any instant consists of a single (“unitary”), coherent interpretation of sense data rather than a “Bayesian blur” of alternatives. However, computation of Bayes-optimal actions has no role for unitary perception, instead being required to integrate over every possible action-percept pair to maximise expected utility. So what is the role of unitary coherent percepts, and how are they computed? Recent work provided objective evidence for non-Bayes-optimal, unitary coherent, perception and action in humans; and further suggested that the percept selected is not the maximum a posteriori percept but is instead affected by utility. The present study uses a binocular fusion task first to reproduce the same effect in a new domain, and second, to test multiple hypotheses about exactly how utility may affect the percept. After accounting for high experimental noise, it finds that both Bayes optimality (maximise expected utility) and the previously proposed maximum-utility hypothesis are outperformed in fitting the data by a modified maximum-salience hypothesis, using unsigned utility magnitudes in place of signed utilities in the bias function.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2016 Taylor & Francis. This is an Accepted Manuscript of an article published by Taylor & Francis in Connection Science on 31/03/2016, available online: http://www.tandfonline.com/10.1080/09540091.2016.1159181 |
Keywords: | Bayesian brain, psychophysics, utility, bias, perception, binocular fusion |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Environment (Leeds) > Institute for Transport Studies (Leeds) > ITS: Safety and Technology (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 23 Jun 2016 09:06 |
Last Modified: | 14 Apr 2017 03:16 |
Published Version: | http://dx.doi.org/10.1080/09540091.2016.1159181 |
Status: | Published |
Publisher: | Taylor & Francis |
Identification Number: | 10.1080/09540091.2016.1159181 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:99258 |