Responses of a Hodgkin-Huxley Neuron to Various Types of Spike-Train Inputs

TL;DR

This study numerically examines how Hodgkin-Huxley neurons respond to various spike-train inputs, revealing that output ISI distributions depend on input fluctuations and differ from simpler models due to refractory periods.

Contribution

It demonstrates the influence of deterministic, chaotic, and stochastic input modulations on HH neuron responses, highlighting differences from integrate-and-fire models.

Findings

Output ISI distribution depends on input mean and fluctuations.

Return maps distinguish input types, histograms do not.

Refractory period affects input-output ISI relation.

Abstract

Numerical investigations have been made of responses of a Hodgkin-Huxley (HH) neuron to spike-train inputs whose interspike interval (ISI) is modulated by deterministic, semi-deterministic (chaotic) and stochastic signals. As deterministic one, we adopt inputs with the time-independent ISI and with time-dependent ISI modulated by sinusoidal signal. The R\"{o}ssler and Lorentz models are adopted for chaotic modulations of ISI. Stochastic ISI inputs with the Gamma distribution are employed. It is shown that distribution of output ISI data depends not only on the mean of ISIs of spike-train inputs but also on their fluctuations. The distinction of responses to the three kinds of inputs can be made by return maps of input and output ISIs, but not by their histograms. The relation between the variations of input and output ISIs is shown to be different from that of the integrate and fire (IF) model because of the refractory period in the HH neuron.