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International Workshop on Brain-Inspired Computing

BrainComp 2013: Brain-Inspired Computing pp 117–129Cite as

Bayes Optimality of Human Perception, Action and Learning: Behavioural and Neural Evidence

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Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 8603))

Abstract

The primary role of any biological nervous system (including the human) is to process incoming information in a way that allows motor choices to be made that increases the subjective utility of the organism. Or put slightly differently, “to make sure good things happen”. There are a number of ways that such a process can be done, but one possible hypothesis is that the human nervous system has been optimized to maximize the use of available resources, thus approximating optimal computations. In the following I will discuss the possibility of the nervous system performing such computations in perception, action and learning, and the behavioural and neural evidence supporting such ideas.

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Notes

  1. 1.

    http://www.ted.com/talks/daniel_wolpert_the_real_reason_for_brains.html

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Author information

Authors and Affiliations

  1. University of Birmingham, B15 2TT, Birmingham, UK

    Ulrik R. Beierholm

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  1. Ulrik R. Beierholm
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Correspondence to Ulrik R. Beierholm .

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Editors and Affiliations

  1. Faculty of Engineering, University of Calabria, Arcavacada di Rende, Italy

    Lucio Grandinetti

  2. Jülich Supercomputing Centre, Jülich, Germany

    Thomas Lippert

  3. Computing Science, University of Groningen Institute for Mathematics &, Groningen, The Netherlands

    Nicolai Petkov

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Beierholm, U.R. (2014). Bayes Optimality of Human Perception, Action and Learning: Behavioural and Neural Evidence. In: Grandinetti, L., Lippert, T., Petkov, N. (eds) Brain-Inspired Computing. BrainComp 2013. Lecture Notes in Computer Science(), vol 8603. Springer, Cham. https://doi.org/10.1007/978-3-319-12084-3_10

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  • DOI: https://doi.org/10.1007/978-3-319-12084-3_10

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-12083-6

  • Online ISBN: 978-3-319-12084-3

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