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Noise-induced escape in an excitable system

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Noise-induced escape in an excitable system. / Khovanov, I. A.; Polovinkin, A. V.; Luchinsky, D. G. et al.
In: Physical Review E, Vol. 87, No. 3, ARTN 032116, 07.03.2013.

Research output: Contribution to Journal/Magazine › Journal article › peer-review

Harvard

Khovanov, IA, Polovinkin, AV, Luchinsky, DG & McClintock, PVE 2013, 'Noise-induced escape in an excitable system', Physical Review E, vol. 87, no. 3, ARTN 032116. https://doi.org/10.1103/PhysRevE.87.032116

APA

Khovanov, I. A., Polovinkin, A. V., Luchinsky, D. G., & McClintock, P. V. E. (2013). Noise-induced escape in an excitable system. Physical Review E, 87(3), Article ARTN 032116. https://doi.org/10.1103/PhysRevE.87.032116

Vancouver

Khovanov IA, Polovinkin AV, Luchinsky DG, McClintock PVE. Noise-induced escape in an excitable system. Physical Review E. 2013 Mar 7;87(3):ARTN 032116. doi: 10.1103/PhysRevE.87.032116

Author

Khovanov, I. A. ; Polovinkin, A. V. ; Luchinsky, D. G. et al. / Noise-induced escape in an excitable system. In: Physical Review E. 2013 ; Vol. 87, No. 3.

Bibtex

@article{c4edb84fa93d499fb0b9fcb594af7219,
title = "Noise-induced escape in an excitable system",
abstract = "We consider the stochastic dynamics of escape in an excitable system, the FitzHugh-Nagumo (FHN) neuronal model, for different classes of excitability. We discuss, first, the threshold structure of the FHN model as an example of a system without a saddle state. We then develop a nonlinear (nonlocal) stability approach based on the theory of large fluctuations, including a finite-noise correction, to describe noise-induced escape in the excitable regime. We show that the threshold structure is revealed via patterns of most probable (optimal) fluctuational paths. The approach allows us to estimate the escape rate and the exit location distribution. We compare the responses of a monostable resonator and monostable integrator to stochastic input signals and to a mixture of periodic and stochastic stimuli. Unlike the commonly used local analysis of the stable state, our nonlocal approach based on optimal paths yields results that are in good agreement with direct numerical simulations of the Langevin equation. DOI: 10.1103/PhysRevE.87.032116",
keywords = "CHAOS, FLUCTUATIONS, EXIT PROBLEM, DRIVEN, DYNAMICAL-SYSTEMS, BEHAVIOR, COHERENCE RESONANCE, RESONANT ACTIVATION",
author = "Khovanov, {I. A.} and Polovinkin, {A. V.} and Luchinsky, {D. G.} and McClintock, {P. V. E.}",
note = "{\textcopyright}2013 American Physical Society",
year = "2013",
month = mar,
day = "7",
doi = "10.1103/PhysRevE.87.032116",
language = "English",
volume = "87",
journal = "Physical Review E",
issn = "1539-3755",
publisher = "American Physical Society",
number = "3",

}

RIS

TY - JOUR

T1 - Noise-induced escape in an excitable system

AU - Khovanov, I. A.

AU - Polovinkin, A. V.

AU - Luchinsky, D. G.

AU - McClintock, P. V. E.

N1 - ©2013 American Physical Society

PY - 2013/3/7

Y1 - 2013/3/7

N2 - We consider the stochastic dynamics of escape in an excitable system, the FitzHugh-Nagumo (FHN) neuronal model, for different classes of excitability. We discuss, first, the threshold structure of the FHN model as an example of a system without a saddle state. We then develop a nonlinear (nonlocal) stability approach based on the theory of large fluctuations, including a finite-noise correction, to describe noise-induced escape in the excitable regime. We show that the threshold structure is revealed via patterns of most probable (optimal) fluctuational paths. The approach allows us to estimate the escape rate and the exit location distribution. We compare the responses of a monostable resonator and monostable integrator to stochastic input signals and to a mixture of periodic and stochastic stimuli. Unlike the commonly used local analysis of the stable state, our nonlocal approach based on optimal paths yields results that are in good agreement with direct numerical simulations of the Langevin equation. DOI: 10.1103/PhysRevE.87.032116

AB - We consider the stochastic dynamics of escape in an excitable system, the FitzHugh-Nagumo (FHN) neuronal model, for different classes of excitability. We discuss, first, the threshold structure of the FHN model as an example of a system without a saddle state. We then develop a nonlinear (nonlocal) stability approach based on the theory of large fluctuations, including a finite-noise correction, to describe noise-induced escape in the excitable regime. We show that the threshold structure is revealed via patterns of most probable (optimal) fluctuational paths. The approach allows us to estimate the escape rate and the exit location distribution. We compare the responses of a monostable resonator and monostable integrator to stochastic input signals and to a mixture of periodic and stochastic stimuli. Unlike the commonly used local analysis of the stable state, our nonlocal approach based on optimal paths yields results that are in good agreement with direct numerical simulations of the Langevin equation. DOI: 10.1103/PhysRevE.87.032116

KW - CHAOS

KW - FLUCTUATIONS

KW - EXIT PROBLEM

KW - DRIVEN

KW - DYNAMICAL-SYSTEMS

KW - BEHAVIOR

KW - COHERENCE RESONANCE

KW - RESONANT ACTIVATION

U2 - 10.1103/PhysRevE.87.032116

DO - 10.1103/PhysRevE.87.032116

M3 - Journal article

VL - 87

JO - Physical Review E

JF - Physical Review E

SN - 1539-3755

IS - 3

M1 - ARTN 032116

ER -