Successive spike times predicted by a stochastic neuronal model with a variable input signal
Two different stochastic processes are used to model the evolution of the membrane voltage of a neuron exposed to a time-varying input signal. The first process is an inhomogeneous Ornstein-Uhlenbeck process and its first passage time through a constant threshold is used to model the first spike ti...
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Main Authors: | Giuseppe D'Onofrio, Enrica Pirozzi |
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Format: | Article |
Language: | English |
Published: |
AIMS Press
2015-12-01
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Series: | Mathematical Biosciences and Engineering |
Subjects: | |
Online Access: | https://www.aimspress.com/article/doi/10.3934/mbe.2016003 |
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