A sparse-code associative memory of Hodgkin-Huxley neuron networks with Willshaw-type synaptic couplings
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An associative memory has been discussed of neural networks consisting of spiking N (= 100) Hodgkin-Huxley (HH) neurons with time-delayed couplings, which memorize P patterns in their synaptic weights. In addition to excitatory synapses whose strengths are modified after the Willshaw-type learning rule with the 0/1 code for quiescent/active states, the network includes uniform inhibitory synapses which are introduced to reduce cross-talk noises. Our simulations of the HH neuron network for the noise-free state have shown to yield a fairly good performance with the storage capacity of αc = Pmax/N ∼ 0.4− 2.4 for the low neuron activity of f ∼ 0.04− 0.10. The network is realized not to be vulnerable to the distribution of time delays in couplings. The storage capacity of our temporal-code network with spiking HH neurons is comparable to that of the rate-code model with the Willshaw-type synapses. The variability of interspace interval (ISI) of output spike trains in the process of retrieving stored patterns is also discussed. PACS No. 84.35.+i 87.10.+e 87.18.Sn Typeset using REVTEX E-mail: hasegawa@u-gakugei.ac.jp
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