A rate-reduced neuron model for complex spiking

Abstract

We present a simple rate-reduced neuron model that captures a wide rangeof complex, biologically plausible, and physiologically relevant spiking behavior.This includes spike-frequency adaptation, postinhibitory rebound, phasic spiking andaccommodation, first-spike latency, and inhibition-induced spiking. Furthermore, themodel can mimic different neuronal filter properties. It can be used to extend existingneural field models, adding more biological realism and yielding a richer dynamicalstructure. The model is based on a slight variation of the Rulkov map.