Analysis of inverse stochastic resonance and the long-term firing of Hodgkin-Huxley neurons with Gaussian white noise
Henry C. Tuckwell, J\"urgen Jost

TL;DR
This paper investigates how Gaussian white noise influences the firing behavior of Hodgkin-Huxley neurons, revealing inverse stochastic resonance and analyzing transitions between stable states and limit cycles.
Contribution
It provides a detailed analysis of the mechanisms behind inverse stochastic resonance in Hodgkin-Huxley neurons, including linear approximations and basin of attraction properties.
Findings
Identification of the noise amplitude range where ISR occurs
Linearized oscillatory solutions around the equilibrium point
Long-term simulations showing spike count behavior across noise levels
Abstract
In previous articles we have investigated the firing properties of the standard Hodgkin-Huxley (HH) systems of ordinary and partial differential equations in response to input currents composed of a drift (mean) and additive Gaussian white noise. For certain values of the mean current, as the noise amplitude increased from zero, the firing rate exhibited a minimum and this phenomenon was called inverse stochastic resonance (ISR). Here we analyse the underlying transitions from a stable equilibrium point to the limit cycle and vice-versa. Focusing on the case of a mean input current density at which repetitive firing occurs and ISR had been found to be pronounced, some of the properties of the corresponding stable equilibrium point are found. A linearized approximation around this point has oscillatory solutions from whose maxima spikes tend to occur. A one dimensional…
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