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Numerical Effects in Computer Simulation of Simplified Hodgkin-huxley Model

Published: 08 July 2019 Publication History

Abstract

In this paper, we consider the impact of the discretization effects on the dynamical behaviour of the single-compartment neuron model represented by simplified Hodgkin-Huxley equations. In order to implement numerical simulation, one need to discretize the continuous model of the system or use the discrete operator preserving the main properties of the continuous prototype. However, discrete models can suffer from negative effects caused by the applied method, discretization step and round-off errors. This fact is particularly important for the analysis of nonlinear systems, e.g. the biological neuron models. Within this study, the impact of the application of the most common one-step integration methods is examined through the series of computational experiments, where the dynamical system is put into the resonant and chaotic oscillation modes. The results of the study are visualized as two-parameter dynamical maps and interspike interval histograms.

References

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Uhlhaas, P. J., and Singer, W. 2010. Abnormal neural oscillations and synchrony in schizophrenia. Nature reviews neuroscience, 11(2), 100.
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Hodgkin, A. L., and Huxley, A. F. 1952. A quantitative description of membrane current and its application to conduction and excitation in nerve. The Journal of physiology, 117(4), 500--544.
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FitzHugh, R. 1961. Impulses and physiological states in theoretical models of nerve membrane. Biophysical journal, 1(6), 445--466.
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Wilson, H.R. Spikes, decisions, and actions: the dynamical foundations of neurosciences. Oxford UP, 1999.
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Ostrovskii, V.Y., Butusov, D.N., Belkin, D.A. and Okoli, G. 2018. Studying the dynamics of memristive synapses in spiking neuromorphic systems. In Proceedings of the IEEE Conference of Russian Young Researchers in Electrical and Electronic Engineering (EIConRus) (Saint Petersburg, Russia, 29 January - 1 February, 2018)

Cited By

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  • (2020)Revealing Spectrum Features of Stochastic Neuron Spike TrainsMathematics10.3390/math80610118:6(1011)Online publication date: 20-Jun-2020
  • (2020)Synthesis and Analysis of the Fixed-Point Hodgkin–Huxley Neuron ModelElectronics10.3390/electronics90304349:3(434)Online publication date: 5-Mar-2020

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ICoMS '19: Proceedings of the 2019 2nd International Conference on Mathematics and Statistics
July 2019
112 pages
ISBN:9781450371681
DOI:10.1145/3343485
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

In-Cooperation

  • UBI: Universidade da Beira Interior
  • Universidade Nova de Lisboa

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 08 July 2019

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Author Tags

  1. Biological neuron model
  2. Computer simulation
  3. Hodjkin-Huxley
  4. Neural chaos
  5. Nonlinear dynamics
  6. Numerical integration

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Cited By

View all
  • (2020)Revealing Spectrum Features of Stochastic Neuron Spike TrainsMathematics10.3390/math80610118:6(1011)Online publication date: 20-Jun-2020
  • (2020)Synthesis and Analysis of the Fixed-Point Hodgkin–Huxley Neuron ModelElectronics10.3390/electronics90304349:3(434)Online publication date: 5-Mar-2020

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