Gauss-Markov processes restricted from below by special reflecting boundaries are considered and the transition probability density functions are determined. Furthermore, the first-passage time density through a time-dependent threshold is studied by using analytical, numerical and asymptotic methods. The restricted Gauss-Markov processes are then used to construct inhomogeneous leaky integrate-and-fire stochastic models for single neuron’s activity in the presence of a reversal hyperpolarization potential and time-varying input signals.

Gauss-Markov processes in the presence of a reflecting boundary and some applications in neuronal models

NOBILE, Amelia Giuseppina;
2014

Abstract

Gauss-Markov processes restricted from below by special reflecting boundaries are considered and the transition probability density functions are determined. Furthermore, the first-passage time density through a time-dependent threshold is studied by using analytical, numerical and asymptotic methods. The restricted Gauss-Markov processes are then used to construct inhomogeneous leaky integrate-and-fire stochastic models for single neuron’s activity in the presence of a reversal hyperpolarization potential and time-varying input signals.
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11386/4285853
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