Influence of noise on the behavior of an autoassociative neural network

Recently, we simulated the activity and function of neural networks with neuronal units modelled after their physiological counterparts. Neuronal potentials, single neural spikes and their effect on postsynaptic neurons were taken into account. The neural network studied was endowed with plastic synapses. The synaptic modifications were assumed to follow Hebbian rules, i.e. the synaptic strengths increase if the pre‐ and postsynaptic cells fire a spike synchronously and decrease if there exists no synchronicity between pre‐ and postsynaptic spikes. The time scale of the synaptic plasticity was that of mental processes, i.e. a tenth of a second as proposed by v.d. Malsburg. In this contribution we extend our previous study and include random fluctuations of the neural potentials as observed in electrophysiological recordings. We will dmonstrate that random fluctuations of the membrane potentials raise the sensitivity and performance of the neural network. The fluctuations enable the network to react to wea...