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Modelling firing nerve cells. A. Lessig. Self-organization in physical systems: rhythms, patterns and chaos. 2010-11-17. Contents. Physiology of nerve cells Structure of a „typical“ neuron Stimulus conduction via action potentials Neurons as excitable system Hodgkin-Huxley model
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Modelling firing nerve cells A. Lessig Self-organization in physical systems: rhythms, patterns and chaos 2010-11-17
Contents • Physiology of nerve cells • Structure of a „typical“ neuron • Stimulus conduction via action potentials • Neurons as excitable system • Hodgkin-Huxley model • FitzHugh-Nagumo model • Summary • Literature
Structure Source: Carlson, Niel A. (1992). Foundations of Physiological Psychology. Needham Heights, Massachusetts: Simon & Schuster. pp. 36
Structure Source: „Neurevolution“, http://www.neurevolution.net/page/3/
Resting potential cK+ cNa+ + - Source: „Neurosignaling“, http://www.columbia.edu/cu/psychology/courses/1010/mangels/neuro/neurosignaling/neurosignaling.html
Resting potential Nernst equation:
Action potential gNa = max gK = max Source: „Action potential“, openwetware.org/images/thumb/a/a6/Action-potential.png
Hodgkin-Huxley model Source: Cross, M. & Greenside, H. (2009). Pattern Formation and Dynamics in Nonequilibrium Systems. Cambridge: Cambridge University Press. pp. 405
Hodgkin-Huxley model Source: A. L. Hodgkin, A. F. Huxley: A Quantitative Description of Membrane Current and its Application to Conduction and Excitation in Nerve.Journal of Physiology. 117, 1952, pp. 530
FitzHugh-Nagumo model Nullclines:
FitzHugh-Nagumo model fixed point u* ≈ -1.51 v* ≈ -1.07 a = -1.3 b = 0.2 Source: Cross, M. & Greenside, H. (2009). Pattern Formation and Dynamics in Nonequilibrium Systems. Cambridge: Cambridge University Press. pp. 416
FitzHugh-Nagumo model Linear stability analysis: fixed point
FitzHugh-Nagumo model Linear stability analysis: Source: Strogatz, S. H. (1994). Nonlinear Dynamics and Chaos. New York: Perseus Books Publishing, LLC. pp. 137
FitzHugh-Nagumo model Linear stability analysis:
FitzHugh-Nagumo model weak stimulus strong stimulus Source: „ Das FitzHugh-Nagumo Modell einer Nervenzelle“, http://www.math.uni-hamburg.de/home/gunesch/Vorlesung/SoSe2007/Sem_DS_ODE/Vortrag/Brouwer.pdf
FitzHugh-Nagumo model Source: „ FitzHugh-Nagumo model“, http://www.scholarpedia.org/article/FitzHugh-Nagumo_model
FitzHugh-Nagumo model Source: „ Das FitzHugh-Nagumo Modell einer Nervenzelle“, http://www.math.uni-hamburg.de/home/gunesch/Vorlesung/SoSe2007/Sem_DS_ODE/Vortrag/Brouwer.pdf
FitzHugh-Nagumo model Source: „ Das FitzHugh-Nagumo Modell einer Nervenzelle“, http://www.math.uni-hamburg.de/home/gunesch/Vorlesung/SoSe2007/Sem_DS_ODE/Vortrag/Brouwer.pdf
FitzHugh-Nagumo model Source: „ Das FitzHugh-Nagumo Modell einer Nervenzelle“, http://www.math.uni-hamburg.de/home/gunesch/Vorlesung/SoSe2007/Sem_DS_ODE/Vortrag/Brouwer.pdf
Summary • stimulus conduction via action potentials • neurons are classic excitable systems: sufficient perturbations cause large and amplified response • 4-D Hodgkin-Huxley model very close to physiology • reduced version of Hodgkin-Huxley model: 2-D FitzHugh-Nagumo model • FitzHugh-Nagumo model retains most important features of the Hodgkin-Huxley model (excitability, quasi-threshold, refractory period, …) • FitzHugh-Nagumo model example for activator-inhibitor system • propagation of action potentials: diffusion term (next week)
Literature • Hodgkin A. L., Huxley A. F. (1952) A Quantitative Description of Membrane Current and its Application to Conduction and Excitation in Nerve. Journal of Physiology. 117:500-544 • FitzHugh R. (1955) Mathematical models of threshold phenomena in the nerve membrane. Bull. Math. Biophysics. 17:257-278 • Nagumo J., Arimoto S., and Yoshizawa S. (1962) An active pulse transmission line simulating nerve axon. Proc IRE. 50:2061-2070 • „ FitzHugh-Nagumo model“, http://www.scholarpedia.org/article/FitzHugh-Nagumo_model • Cross, M. & Greenside, H. (2009). Pattern Formation and Dynamics in Nonequilibrium Systems. Cambridge: Cambridge University Press • Strogatz, S. H. (1994). Nonlinear Dynamics and Chaos. New York: Perseus Books Publishing, LLC