A log-domain implementation of the Izhikevich neuron model

Abstract

We present an implementation of the Izhikevich neuron model which uses two first-order log-domain low-pass filters and two translinear multipliers. The neuron consists of a leaky-integrate-and-fire core, a slow adaptive state variable and quadratic positive feedback. Simulation results show that this neuron can emulate different spiking behaviours observed in biological neurons.