Frequency Switches at Transition Temperature in Voltage-Gated Ion Channel Dynamics of Neural Oscillators

doi:10.1088/0256-307X/35/5/058702

Chin. Phys. Lett.

2018, Vol. 35

Issue (5): 058702 DOI: 10.1088/0256-307X/35/5/058702

CROSS-DISCIPLINARY PHYSICS AND RELATED AREAS OF SCIENCE AND TECHNOLOGY

Frequency Switches at Transition Temperature in Voltage-Gated Ion Channel Dynamics of Neural Oscillators

Yasuomi D. Sato^1,2**

¹Department of System Information Sciences, Graduate School of Information Sciences, Tohoku University, 6-1-01, aza Aoba, Aramaki, Aoba-ku, Sendai, 980-8579, Japan
²Institute of Industrial Science, University of Tokyo, 4-6-1, Komaba, Meguro, Tokyo, 153-8505, Japan

Cite this article:

Yasuomi D. Sato 2018 Chin. Phys. Lett. 35 058702

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Abstract Understanding of the mechanisms of neural phase transitions is crucial for clarifying cognitive processes in the brain. We investigate a neural oscillator that undergoes different bifurcation transitions from the big saddle homoclinic orbit type to the saddle node on an invariant circle type, and the saddle node on an invariant circle type to the small saddle homoclinic orbit type. The bifurcation transitions are accompanied by an increase in thermodynamic temperature that affects the voltage-gated ion channel in the neural oscillator. We show that nonlinear and thermodynamical mechanisms are responsible for different switches of the frequency in the neural oscillator. We report a dynamical role of the phase response curve in switches of the frequency, in terms of slopes of frequency-temperature curve at each bifurcation transition. Adopting the transition state theory of voltage-gated ion channel dynamics, we confirm that switches of the frequency occur in the first-order phase transition temperature states and exhibit different features of their potential energy derivatives in the ion channel. Each bifurcation transition also creates a discontinuity in the Arrhenius plot used to compute the time constant of the ion channel.

Received: 16 January 2018 Published: 30 April 2018

PACS:	87.19.ld	(Electrodynamics in the nervous system)
	05.70.Fh	(Phase transitions: general studies)
	82.40.Bj	(Oscillations, chaos, and bifurcations)

Fund: Supported by JST, CREST, and JSPS KAKENHI under Grant No 15H05919.

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https://cpl.iphy.ac.cn/10.1088/0256-307X/35/5/058702 OR https://cpl.iphy.ac.cn/Y2018/V35/I5/058702

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	Yasuomi D. Sato

[1]	Wilson M A and Mcnaughton B L 1994 Science 265 676
[2]	Vaadia E et al 1995 Nature 373 515
[3]	Steriade M et al 2001 J. Neurophysiol. 85 1969
[4]	Steyn-Ross D A and Steyn-Ross M 2010Modeling Phase Transitions in the Brain (New York: Springer)
[5]	Fujisawa S et al 2006 Cereb. Cortex 16 639
[6]	Chiu S Y et al 1979 Nature 279 327
[7]	Schwarz W 1979 Puegers Arch 382 27
[8]	Antonov V F et al 1980 Nature 283 585
[9]	Gutkin B S and Ermentrout G B 1998 Neural Comput. 10 1047
[10]	Izhikevich E M 2007 Dynamical Systems in Neuroscience: The Geometry of Excitability and Bursting (Cambridge: MIT Press)
[11]	Frankenhaeuser B and Huxley A F 1964 J. Physiol. 171 302
[12]	Sterratt D et al 2011 Principles of Computational Modelling in Neuroscience (Cambridge: Cambridge University Press)
[13]	Hodgkin A L et al 1952 J. Physiol. 116 424
[14]	Sato Y D 2013 Europhys. Lett. 102 58004
[15]	Sato Y D and Aihara K 2014 Neural Comput. 26 2395
[16]	Feudel U et al 2000 Chaos 10 231
[17]	Fukai H et al 2000 Biol. Cybern. 82 215
[18]	Fukai H et al 2000 Biol. Cybern. 82 223

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