Implementing Bayes’ Rule with Neural Fields

  • Raymond H. Cuijpers
  • Wolfram Erlhagen
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5164)


Bayesian statistics is has been very successful in describing behavioural data on decision making and cue integration under noisy circumstances. However, it is still an open question how the human brain actually incorporates this functionality. Here we compare three ways in which Bayes rule can be implemented using neural fields. The result is a truly dynamic framework that can easily be extended by non-Bayesian mechanisms such as learning and memory.


Bayesian statistics Neural fields Decision making Population coding 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Raymond H. Cuijpers
    • 1
  • Wolfram Erlhagen
    • 2
  1. 1.Nijmegen Institute for Cognition and InformationRadboud UniversityNijmegenThe Netherlands
  2. 2.Department of Mathematics for Science and TechnologyUniversity of MinhoGuimarãesPortugal

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