Implementing Bayes' Rule with Neural Fields

  • Authors:
  • Raymond H. Cuijpers;Wolfram Erlhagen

  • Affiliations:
  • Nijmegen Institute for Cognition and Information, Radboud University, Nijmegen, The Netherlands 6500 HE;Department of Mathematics for Science and Technology, University of Minho, Guimarães, Portugal 4800-058

  • Venue:
  • ICANN '08 Proceedings of the 18th international conference on Artificial Neural Networks, Part II
  • Year:
  • 2008

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Abstract

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.