Neural spike suppression by adaptive control of an unknown steady state

Abstract

A FitzHugh-Nagumo type spiking neuron model equipped with an asymmetric activation function is investigated. An analogue nonlinear electrical circuit imitating the dynamics of the model is proposed. It is demonstrated that a simple first order linear filter coupled to the system can inhibit spiking and stabilize the system on an unstable steady state, the position of which is not required to be known, since the filter operates as an adaptive controller. Analytical, numerical and experimental results are presented. © 2009 Springer Berlin Heidelberg.