A STOCHASTIC-MODEL OF AN ARTIFICIAL NEURON

A simple model of a neuron is proposed, not intended to be biologically faithful, but to incorporate dynamic and stochastic features which seem to be realistic for both the natural and the artificial case. It is shown that the use of feedback for assemblies of such neurons can produce bistable behaviour and sharpen the discrimination of the assembly to the level of input. Particular attention is paid to bistable devices which are to serve as bit-stores (and so constitute components of a memory) and which suffer a disturbing input due to mutual interference. Approximate expressions are obtained for the equilibrium distribution of the excitation level for such assemblies and for the expected escape time of such an assembly from a metastable excitation level.