Spiking Neuron Models: An Introduction
Spiking Neuron Models: An Introduction
Characterization of subthreshold voltage fluctuations in neuronal membranes
Neural Computation
Neural Computation
Numerical simulation of stochastic PDEs for excitable media
Journal of Computational and Applied Mathematics
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We study the effects of noise in two models of spiny dendrites. Through the introduction of different types of noise to both the Spike-diffuse-spike (SDS) and Baer---Rinzel (BR) models we investigate the change in behaviour of the travelling wave solution present in both deterministic systems, as noise intensity increases. We show that the speed of wave propagation in both the SDS and BR models respectively differs as the noise intensity in the spine heads increases. In contrast the cable is very robust to noise and as such the speed shows very little variation from the deterministic system. We introduce a space-dependent spine density, 驴(x), to the original Baer---Rinzel model and show how this modified model can mimic behaviour (under influence of noise) of both original systems, through variation of one parameter. We also show that the correlation time and length scales of the noise can enhance propagation of travelling wave solutions where the white noise dominates the underlying signal and produces noise induced phenomena.