Firing Time Statistics for Driven Neuron Models: Analytic Expressions Versus Numerics
Overview
Affiliations
Analytical expressions are put forward to investigate the forced spiking activity of abstract neuron models such as the driven leaky integrate-and-fire model. The method is valid in a wide parameter regime beyond the restraining limits of weak driving (linear response) and/or weak noise. The novel approximation is based on a discrete state Markovian modeling of the full long-time dynamics with time-dependent rates. The scheme yields excellent agreement with numerical Langevin and Fokker-Planck simulations of the full nonstationary dynamics, not only for the first-passage time statistics, but also for the important interspike interval (residence time) distribution.
Mapping input noise to escape noise in integrate-and-fire neurons: a level-crossing approach.
Schwalger T Biol Cybern. 2021; 115(5):539-562.
PMID: 34668051 PMC: 8551127. DOI: 10.1007/s00422-021-00899-1.
Threshold-varying integrate-and-fire model reproduces distributions of spontaneous blink intervals.
Nomura R, Liang Y, Morita K, Fujiwara K, Ikeguchi T PLoS One. 2018; 13(10):e0206528.
PMID: 30376565 PMC: 6207319. DOI: 10.1371/journal.pone.0206528.
Phase-locked spiking of inner ear hair cells and the driven noisy Adler equation.
Shlomovitz R, Roongthumskul Y, Ji S, Bozovic D, Bruinsma R Interface Focus. 2014; 4(6):20140022.
PMID: 25485081 PMC: 4213446. DOI: 10.1098/rsfs.2014.0022.
Phase transitions in the first-passage time of scale-invariant correlated processes.
Carretero-Campos C, Bernaola-Galvan P, Ivanov P, Carpena P Phys Rev E Stat Nonlin Soft Matter Phys. 2012; 85(1 Pt 1):011139.
PMID: 22400544 PMC: 3518899. DOI: 10.1103/PhysRevE.85.011139.
Stochastic hierarchical systems: excitable dynamics.
Leonhardt H, Zaks M, Falcke M, Schimansky-Geier L J Biol Phys. 2009; 34(5):521-38.
PMID: 19669511 PMC: 2652551. DOI: 10.1007/s10867-008-9112-1.