An excitable electronic circuit as a sensory neuron model

TL;DR

This paper presents an electronic circuit inspired by the FitzHugh-Nagumo model that mimics sensory neuron behavior, including excitability, noise effects, and spike train variability, providing a bio-inspired neural model.

Contribution

The authors designed and experimentally validated an electronic circuit that replicates key features of sensory neurons, including bifurcation behavior and stochastic spike train dynamics.

Findings

Circuit exhibits Hopf bifurcation at spike onset

Coherence resonance observed under noise

Spike train statistics match biological neurons

Abstract

An electronic circuit device, inspired on the FitzHugh-Nagumo model of neuronal excitability, was constructed and shown to operate with characteristics compatible with those of biological sensory neurons. The nonlinear dynamical model of the electronics quantitatively reproduces the experimental observations on the circuit, including the Hopf bifurcation at the onset of tonic spiking. Moreover, we have implemented an analog noise generator as a source to study the variability of the spike trains. When the circuit is in the excitable regime, coherence resonance is observed. At sufficiently low noise intensity the spike trains have Poisson statistics, as in many biological neurons. The transfer function of the stochastic spike trains has a dynamic range of 6 dB, close to experimental values for real olfactory receptor neurons.