Journal of Computational Neuroscience

, Volume 5, Issue 4, pp 353–364 | Cite as

Adapting a Feedforward Heteroassociative Network to Hodgkin-Huxley Dynamics

  • William W. Lytton

Abstract

Using the original McCulloch-Pitts notion of simple on and off spike coding in lieu of rate coding, an Anderson-Kohonen artificial neural network (ANN) associative memory model was ported to a neuronal network with Hodgkin-Huxley dynamics. In the ANN, the use of 0/1 (no-spike/spike) units introduced a cross-talk term that had to be compensated by introducing balanced feedforward inhibition. The resulting ANN showed good capacity and fair selectivity (rejection of unknown input vectors). Translation to the Hodgkin-Huxley model resulted in a network that was functional but not at all robust. Evaluation of the weaknesses of this network revealed that it functioned far better using spike timing, rather than spike occurrence, as the code. The algorithm requires a novel learning algorithm for feedforward inhibition that could be sought physiologically.

associative memory inhibition artificial neural network hippocampus 

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Copyright information

© Kluwer Academic Publishers 1998

Authors and Affiliations

  • William W. Lytton
    • 1
  1. 1.Department of Neurology and Neuroscience Training Program, Wm. S. Middleton VA HospitalUniversity of WisconsinMadison

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