Stochastic resonance in a model neuron with reset
Hans E. Plesser, Shigeru Tanaka
Abstract
The response of a noisy integrate-and-fire neuron with reset to periodic input is investigated. We numerically obtain the first-passage-time density of the pertaining Ornstein-Uhlenbeck process and show how the power spectral density of the resulting spike train can be determined via Fourier transform. The neuron's output clearly exhibits stochastic resonance.
Create a lesson
Related papers
A Variational Framework for Nonlinear Chemical Thermodynamics Employing the Maximum Energy Dissipation Principle
Adam Moroz
Retrievable but Unencountered: The Missing Exposure Denominator in Large Academic Ebook Collections
Jette Veenstra, Mauricio Munoz Arias
Where Energy Is Spent Sets the Depth of Kinetic Proofreading
Uğur Çetiner
On the Role of Dispersion in One Model of Propagation of Elastic Excitations in Nerves
Alexander I. Kozlov
Quantifying the Biophysical Properties of Red Blood Cells in Gaucher Disease
Zhaojie Chai, Marine de Person, Pierre A. Buffet et al.
Roles of vortices and turbulent eddies in particle preferential concentration and deposition in the human respiratory tract
Mengtao Li, Yawei Wang, Wentao Feng et al.