Adapting a feedforward heteroassociative network to Hodgkin-Huxley dynamics

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-Hu xley 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 feedf orward inhibition. The resulting ANN showed good capacity and fair selectiv ity (rejection of unknown input vectors). Translation to the Hodgkin-Huxley model resulted in a network that was functional but not at all robust. Eva luation of the weaknesses of this network revealed that it functioned far b etter using spike timing, rather than spike occurrence, as the code. The al gorithm requires a novel learning algorithm for feedforward inhibition that could be sought physiologically.