A SIMPLE ALGORITHM TO GENERATE FIRING TIMES FOR LEAKY INTEGRATE-AND-FIRE NEURONAL MODEL

被引：2

作者：

Buonocore, Aniello ^{[1
]}

Caputo, Luigia ^{[1
]}

Pirozzi, Enrica ^{[1
]}

Carfora, Maria Francesca ^{[2
]}

机构：

[1] Univ Naples Federico II, Dipartimento Matemat & Applicaz, Naples, Italy

[2] CNR, Ist Appplicaz Calcolo Mauro Picone, I-80125 Naples, Italy

来源：

MATHEMATICAL BIOSCIENCES AND ENGINEERING | 2014年 / 11卷 / 01期

关键词：

Ornstein-Uhlenbeck process; first passage time; spike train generation; instantaneous firing rate; hazard rate method; 1ST PASSAGE TIMES; SIMULATION; EQUATION;

D O I：

10.3934/mbe.2014.11.1

中图分类号：

Q [生物科学];

学科分类号：

07 ; 0710 ; 09 ;

摘要：

A method to generate first passage times for a class of stochastic processes is proposed. It does not require construction of the trajectories as usually needed in simulation studies, but is based on an integral equation whose unknown quantity is the probability density function of the studied first passage times and on the application of the hazard rate method. The proposed procedure is particularly efficient in the case of the Ornstein-Uhlenbeck process, which is important for modeling spiking neuronal activity.

引用

页码：1 / 10

页数：10

共 50 条

[1] On a Stochastic Leaky Integrate-and-Fire Neuronal Model
Buonocore, A.
Caputo, L.
Pirozzi, E.
Ricciardi, L. M.
NEURAL COMPUTATION, 2010, 22 (10) : 2558 - 2585
[2] The parameters of the stochastic leaky integrate-and-fire neuronal model
Petr Lansky
Pavel Sanda
Jufang He
Journal of Computational Neuroscience, 2006, 21 : 211 - 223
[3] The parameters of the stochastic leaky integrate-and-fire neuronal model
Lansky, Petr
Sanda, Pavel
He, Jufang
JOURNAL OF COMPUTATIONAL NEUROSCIENCE, 2006, 21 (02) : 211 - 223
[4] Optimum signal in a diffusion leaky integrate-and-fire neuronal model
Lansky, Petr
Sacerdote, Laura
Zucca, Cristina
MATHEMATICAL BIOSCIENCES, 2007, 207 (02) : 261 - 274
[5] Chaotic firing in the sinusoidally forced leaky integrate-and-fire model with threshold fatigue
Chacron, MJ
Longtin, A
Pakdaman, K
PHYSICA D-NONLINEAR PHENOMENA, 2004, 192 (1-2) : 138 - 160
[6] Numerical Approximation for Nonlinear Noisy Leaky Integrate-and-Fire Neuronal Model
Sharma, Dipty
Singh, Paramjeet
Agarwal, Ravi P.
Koksal, Mehmet Emir
MATHEMATICS, 2019, 7 (04)
[7] Periodically forced leaky integrate-and-fire model
Pakdaman, K
PHYSICAL REVIEW E, 2001, 63 (04):
[8] Parameters of the Diffusion Leaky Integrate-and-Fire Neuronal Model for a Slowly Fluctuating Signal
Picchini, Umberto
Ditlevsen, Susanne
De Gaetano, Andrea
Lansky, Petr
NEURAL COMPUTATION, 2008, 20 (11) : 2696 - 2714
[9] Effect of stimulation on the input parameters of stochastic leaky integrate-and-fire neuronal model
Lansky, Petr
Sanda, Pavel
He, Jufang
JOURNAL OF PHYSIOLOGY-PARIS, 2010, 104 (3-4) : 160 - 166
[10] Noisy threshold in neuronal models: connections with the noisy leaky integrate-and-fire model
G. Dumont
J. Henry
C. O. Tarniceriu
Journal of Mathematical Biology, 2016, 73 : 1413 - 1436

← 1 2 3 4 5 →