Noise induces continuous and noncontinuous transitions in neuronal interspike intervals range

TL;DR

This paper investigates how noise influences neuronal firing patterns in the adaptive exponential integrate-and-fire model, revealing that noise can induce both continuous and abrupt changes in interspike intervals, especially near critical parameter boundaries.

Contribution

It demonstrates the specific effects of noise on neuronal firing transitions in a widely used neuron model, highlighting the conditions for continuous and noncontinuous changes.

Findings

Noise induces both continuous and abrupt transitions in interspike intervals.

Noncontinuous transitions occur near the boundary between tonic spiking and bursting.

Noise effects are significant close to critical parameter thresholds.

Abstract

Noise appears in the brain due to various sources, such as ionic channel fluctuations and synaptic events. They affect the activities of the brain and influence neuron action potentials. Stochastic differential equations have been used to model firing patterns of neurons subject to noise. In this work, we consider perturbing noise in the adaptive exponential integrate-and-fire (AEIF) neuron. The AEIF is a two-dimensional model that describes different neuronal firing patterns by varying its parameters. Noise is added in the equation related to the membrane potential. We show that a noise current can induce continuous and noncontinuous transitions in neuronal interspike intervals. Moreover, we show that the noncontinuous transition occurs mainly for parameters close to the border between tonic spiking and burst activities of the neuron without noise.