Lu, Y., Fox, C. and Stafford, T. orcid.org/0000-0002-8089-9479 (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 and Francis. This is an author produced version of a paper subsequently published in Connection Science. Uploaded in accordance with the publisher's self-archiving policy. |
Keywords: | Bayesian brain; psychophysics; utility; bias; perception; binocular fusion |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Science (Sheffield) > Department of Psychology (Sheffield) |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 15 Apr 2016 15:23 |
Last Modified: | 14 Apr 2017 03:17 |
Published Version: | https://dx.doi.org/10.1080/09540091.2016.1159181 |
Status: | Published |
Publisher: | Taylor & Francis |
Refereed: | Yes |
Identification Number: | 10.1080/09540091.2016.1159181 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:97626 |