Phase reduction for FitzHugh-Nagumo neuron with large timescale separation

Jinjie Zhu, Jiong Wang, Shang Gao, and Xianbin Liu
Phys. Rev. E 101, 042203 – Published 7 April 2020

Abstract

Phase reduction approach is a useful tool to reduce the dimension of limit-cycle oscillators. In this paper, it is applied to the FitzHugh-Nagumo neuron model with large timescale separation. To quantitate the response of the oscillator to the external perturbations, the asymptotic behaviors of the phase sensitivity functions for fast and slow variables are obtained. It is shown that in the relaxation limit, apart from the jump points which are the vertices of the cubic nullcline, the phase is insensitive to the perturbations on the fast variable. By using the phase sensitivity functions, two cases, namely, periodic pulse train perturbation and common noise perturbation, are investigated. Theoretical and numerical results suggest better performance for the synchronization behaviors of the perturbations on the slow variable for large timescale separation.

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  • Received 19 December 2019
  • Revised 9 February 2020
  • Accepted 12 March 2020

DOI:https://doi.org/10.1103/PhysRevE.101.042203

©2020 American Physical Society

Physics Subject Headings (PhySH)

Nonlinear DynamicsInterdisciplinary PhysicsPhysics of Living Systems

Authors & Affiliations

Jinjie Zhu1,*, Jiong Wang1, Shang Gao1, and Xianbin Liu2

  • 1School of Mechanical Engineering, Nanjing University of Science and Technology, Nanjing 210094, China
  • 2State Key Laboratory of Mechanics and Control of Mechanical Structures, College of Aerospace Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China

  • *Corresponding author: zhujinjie95@njust.edu.cn

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Vol. 101, Iss. 4 — April 2020

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