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Neuron Dynamics of Single-Compartment Traub Model for Hardware Implementations
Authors: J. C. Moctezuma, V. Breña-Medina, Jose Luis Nunez-Yanez, Joseph P. McGeehan
Abstract:
In this work we make a bifurcation analysis for a single compartment representation of Traub model, one of the most important conductance-based models. The analysis focus in two principal parameters: current and leakage conductance. Study of stable and unstable solutions are explored; also Hop-bifurcation and frequency interpretation when current varies is examined. This study allows having control of neuron dynamics and neuron response when these parameters change. Analysis like this is particularly important for several applications such as: tuning parameters in learning process, neuron excitability tests, measure bursting properties of the neuron, etc. Finally, a hardware implementation results were developed to corroborate these results.Keywords: Traub model, Pinsky-Rinzel model, Hopf bifurcation, single-compartment models, Bifurcation analysis, neuron modeling.
Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1339087
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[1] Traub, R.D., et al., "A model of a CA3 hippocampal pyramidal neuron incorporating voltage-clamp data on intrinsic conductances". J Neurophysiol, 1991. 66(2): p. 635-50.
[2] Zhang, Y., J. Nunez, and J. McGeehan, "Biophysically Accurate Floating Point Neuroprocessor"s. University of Bristol, 2010.
[3] Pinsky, P.F. and J. Rinzel, "Intrinsic and network rhythmogenesis in a reduced Traub model for Ca3 neuron"s. Journal of Computational Neuroscience, 1995. 2(3): p. 275-275.
[4] Guckenheimer, J. and I.S. Labouriau, "Bifurcation of the Hodgkin and Huxley Equations - a New Twist". Bulletin of Mathematical Biology, 1993. 55(5): p. 937-952.
[5] Jiang, W., G. Jianming, and F. Xiangyang, "Two-parameter Hopf bifurcation in the Hodgkin-Huxley model". Chaos, Solitons & Fractals, 2005. 23: p. 973-980.
[6] Beuter, A., et al., "Nonlinear dynamics in Physiology and Medicine". 2003: Springer.
[7] Izhikevich, E.M., "Neural Excitability, Spiking and Bursting". International Journal of Bifurcation and Chaos, 2000. 10(6): p. 1171- 1266.
[8] Guevara, M., "Bifurcations Involving Fixed Points and Limit Cycles in Biological Systems, in Nonlinear Dynamics in Physiology and Medicine", A. Beuter, et al., Editors. 2003, Springer New York. p. 41- 85.
[9] Fei, X.Y., Jiangwang, and L.Q. Chen, "Bifurcation control of Hodgkin- Huxley model of nerve system". WCICA 2006: Sixth World Congress on Intelligent Control and Automation, Vols 1-12, Conference Proceedings, 2006: p. 9406-9410.
[10] Moctezuma, J.C., J.P. McGeehan, and J.L. Nunez-Yanez. "Numerically efficient and biophysically accurate neuroprocessing platform". International Conference in Reconfigurable Computing and FPGAs (ReConFig). 2013.
[11] Hirsch, M.W., S. Smale, and R.L. Devaney, "Differential equations, dynamical systems, and an introduction to chaos". 2004: ElSevier.
[12] Wiggins, S., Introduction to Applied Nonlinear Dynamical Systems and Chaos. 2000: Springer.