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More varieties of Bayesian theories, but no enlightenment

Published online by Cambridge University Press:  25 August 2011

Jeffrey S. Bowers  and
Colin J. Davis
Jeffrey S. Bowers
Affiliation:
School of Psychology, University of Bristol, Clifton, Bristol BS8 1TU, United Kingdom. j.bowers@bris.ac.ukhttp://psychology.psy.bris.ac.uk/people/jeffbowers.htm
Colin J. Davis
Affiliation:
Department of Psychology, Royal Holloway University of London, Egham Hill TW20 0EX, and School of Psychology, University of Bristol, Clifton, Bristol BS8 1TU, United Kingdom. c.davis@rhul.ac.ukhttp://www.pc.rhul.ac.uk/staff/c.davis/
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Abstract

We argue that Bayesian models are best categorized as methodological or theoretical. That is, models are used as tools to constrain theories, with no commitment to the processes that mediate cognition, or models are intended to approximate the underlying algorithmic solutions. We argue that both approaches are flawed, and that the Enlightened Bayesian approach is unlikely to help.

Type
Open Peer Commentary
Information
Behavioral and Brain Sciences , Volume 34 , Issue 4 , August 2011 , pp. 193 - 194
Copyright
Copyright © Cambridge University Press 2011

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References

Bowers, J. S. & Davis, C. J. (submitted) Bayesian just-so stories in cognitive psychology and neuroscience.Google Scholar
Griffiths, T. L. & Tenenbaum, J. B. (2006) Optimal predictions in everyday cognition. Psychological Science 17(9):767–73.CrossRefGoogle ScholarPubMed
Stocker, A. A. & Simoncelli, E. P. (2006) Noise characteristics and prior expectations in human visual speed perception. Nature Neuroscience 9(4):578–85.CrossRefGoogle ScholarPubMed
Thompson, P., Brooks, K. & Hammett, S. T. (2006) Speed can go up as well as down at low contrast: Implications for models of motion perception. Vision Research 46(6–7):782–86.CrossRefGoogle ScholarPubMed
Weiss, Y., Simoncelli, E. P. & Adelson, E. H. (2002) Motion illusions as optimal percepts. Nature Neuroscience 5(6):598–604.CrossRefGoogle ScholarPubMed