EN
Observer Design for the Hodgkin-Huxley Neuronal Model
Abstract
Hodgkin-Huxley (HH) neuronal model has been widely accepted neuronal
model in neuroscience. The variation of the ionic currents in neuron cell
causes the variations in the membrane potential. The level of membrane
potential indicates the activation and inactivation dynamics. In this paper, in
order to observe the unmeasurable states and parameters of HH neuron
accurately, Runge-Kutta discretization based nonlinear observer is designed. In
numerical simulations, the membrane potential is measured and the ionic
currents are estimated. The numerical results provide accurate estimation
results that can be used both in monitoring and control of neuron dynamics.
Keywords
References
- [1] Dayan, P.; Abbott, L. (2005). Theoretical Neuroscience: Computational &Mathematical modelling of neural systems. ISBN-10: 0262541858. MIT Press.
- [2] Hodgkin, A.; Huxley, A. (1952). A quantitative description of membrane current and its application to conduction and excitation in nerve. The Journal of Physiology 117: (4), 500–544.
- [3] Neefs, P. J.; Steur, E.; Nijmeijer, (2010). H. Network complexity and synchronous behavior - an experimental approach. International Journal of Neural Systems 20: (03), 233–247.
- [4] Dahasert, N.; Öztürk, İ.; Kılıç, R. (2012). Experimental realizations of the HR neuron model with programmable hardware and synchronization applications. Nonlinear Dynamics 70: (4), 2343–2358.
- [5] Li, W.; Cheung, R.; Chan, R.; Song, D.; Berger, T. (2013). Real-time prediction of neuronal population spiking activity using fpga. Biomedical Circuits and Systems, IEEE Transactions on 7: (4), 489–498.
- [6] Luenberger, D. (1966). Observers for multivariable systems. IEEE Trans. Autom. Control 11: (2), 190–197.
- [7] Thau, E.E. (1973). Observing the state of nonlinear systems. Int.J. Control 17: 471–479.
- [8] Birk, J.; Zeitz, M. (1988). Extended-Luenberger observer for non-linear multivariable systems. Int. J. Control 47: (6), 1823–1836.
Details
Primary Language
English
Subjects
Engineering
Journal Section
Research Article
Publication Date
December 1, 2016
Submission Date
November 9, 2016
Acceptance Date
December 1, 2016
Published in Issue
Year 2016 Number: Special Issue-1
APA
Cetin, M., & Beyhan, S. (2016). Observer Design for the Hodgkin-Huxley Neuronal Model. International Journal of Applied Mathematics Electronics and Computers, Special Issue-1, 66-71. https://doi.org/10.18100/ijamec.265327
AMA
1.Cetin M, Beyhan S. Observer Design for the Hodgkin-Huxley Neuronal Model. International Journal of Applied Mathematics Electronics and Computers. 2016;(Special Issue-1):66-71. doi:10.18100/ijamec.265327
Chicago
Cetin, Meric, and Selami Beyhan. 2016. “Observer Design for the Hodgkin-Huxley Neuronal Model”. International Journal of Applied Mathematics Electronics and Computers, no. Special Issue-1: 66-71. https://doi.org/10.18100/ijamec.265327.
EndNote
Cetin M, Beyhan S (December 1, 2016) Observer Design for the Hodgkin-Huxley Neuronal Model. International Journal of Applied Mathematics Electronics and Computers Special Issue-1 66–71.
IEEE
[1]M. Cetin and S. Beyhan, “Observer Design for the Hodgkin-Huxley Neuronal Model”, International Journal of Applied Mathematics Electronics and Computers, no. Special Issue-1, pp. 66–71, Dec. 2016, doi: 10.18100/ijamec.265327.
ISNAD
Cetin, Meric - Beyhan, Selami. “Observer Design for the Hodgkin-Huxley Neuronal Model”. International Journal of Applied Mathematics Electronics and Computers. Special Issue-1 (December 1, 2016): 66-71. https://doi.org/10.18100/ijamec.265327.
JAMA
1.Cetin M, Beyhan S. Observer Design for the Hodgkin-Huxley Neuronal Model. International Journal of Applied Mathematics Electronics and Computers. 2016;:66–71.
MLA
Cetin, Meric, and Selami Beyhan. “Observer Design for the Hodgkin-Huxley Neuronal Model”. International Journal of Applied Mathematics Electronics and Computers, no. Special Issue-1, Dec. 2016, pp. 66-71, doi:10.18100/ijamec.265327.
Vancouver
1.Meric Cetin, Selami Beyhan. Observer Design for the Hodgkin-Huxley Neuronal Model. International Journal of Applied Mathematics Electronics and Computers. 2016 Dec. 1;(Special Issue-1):66-71. doi:10.18100/ijamec.265327