On a Stochastic Leaky Integrate-and-Fire Neuronal Model

Skip Nav Destination

Neural Computation (2010) 22 (10): 2558–2585.

This article has been cited by the following articles in journals that are participating in Crossref Cited-by Linking.

A Semi-Markov Leaky Integrate-and-Fire Model

Giacomo Ascione
Bruno Toaldo

Mathematics (2019) 7 (11): 1022.

Colored noise and a stochastic fractional model for correlated inputs and adaptation in neuronal firing

Enrica Pirozzi

Biological Cybernetics (2018) 112 (1-2): 25.

On two diffusion neuronal models with multiplicative noise: The mean first-passage time properties

G. D'Onofrio
P. Lansky
E. Pirozzi

Chaos: An Interdisciplinary Journal of Nonlinear Science (2018) 28 (4): 043103.

Reconstruction of the input signal of the leaky integrate-and-fire neuronal model from its interspike intervals

Saeid R. Seydnejad

Biological Cybernetics (2016) 110 (1): 3.

Successive spike times predicted by a stochastic neuronal model with a variable input signal

Giuseppe D'Onofrio
Enrica Pirozzi

Mathematical Biosciences and Engineering (2016) 13 (3): 495.

A leaky integrate-and-fire model with adaptation for the generation of a spike train

Aniello Buonocore
Luigia Caputo
Enrica Pirozzi
Maria Francesca Carfora

Mathematical Biosciences and Engineering (2016) 13 (3): 483.

Restricted Ornstein–Uhlenbeck process and applications in neuronal models with periodic input signals

A. Buonocore
L. Caputo
A.G. Nobile
E. Pirozzi

Journal of Computational and Applied Mathematics (2015) 285: 59.

Closed-form solutions for the first-passage-time problem and neuronal modeling

Aniello Buonocore
Luigia Caputo
Giuseppe D’Onofrio
Enrica Pirozzi

Ricerche di Matematica (2015) 64 (2): 421.

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

A. Buonocore
L. Caputo
A.G. Nobile
E. Pirozzi

Applied Mathematics and Computation (2014) 232: 799.

A phase transition in the first passage of a Brownian process through a fluctuating boundary with implications for neural coding

Thibaud Taillefumier
Marcelo O. Magnasco

Proceedings of the National Academy of Sciences (2013) 110 (16)

Exact Event-Driven Implementation for Recurrent Networks of Stochastic Perfect Integrate-and-Fire Neurons

Thibaud Taillefumier
Jonathan Touboul
Marcelo Magnasco

Neural Computation (2012) 24 (12): 3145.

Estimating nonstationary input signals from a single neuronal spike train

Hideaki Kim
Shigeru Shinomoto

Physical Review E (2012) 86 (5)

On the reflected Ornstein–Uhlenbeck process with catastrophes

V. Giorno
A.G. Nobile
R. di Cesare

Applied Mathematics and Computation (2012) 218 (23): 11570.

On a Stochastic Leaky Integrate-and-Fire Neuronal Model

A product of The MIT Press

MIT Press Direct

Information

MIT Press

Contact Us

On a Stochastic Leaky Integrate-and-Fire Neuronal Model

A product of The MIT Press

MIT Press Direct

Information

MIT Press

Contact Us

This Feature Is Available To Subscribers Only