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带有忆阻器的Morris-Lecar神经元模型的放电模式分析和电路实现
Firing Pattern Analysis and Circuit Implementation of Morris-Lecar Neuron Model with Memristor

DOI: 10.12677/OJCS.2020.94009, PP. 61-77

Keywords: Morris-Lecar神经元系统,忆阻器,电磁感应,ISI分岔,电路设计
Morris-Lecar (M-L) Neuron Model
, Memristor, Electromagnetic Induction, ISI Bifurcation, Circuit De-sign

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Abstract:

根据神经元生物物理环境来完善神经元模型,有助于分析其真实的动力学活动的机理,提高人类对脑活动的认知,在应用上有助于给出正确的神经元信息编码。Morris-Lecar (M-L)是基于离子通道建立的具有代表性的神经元模型,但是该模型未考虑电磁感应效应带来的影响。真实的神经元复杂的离子跨膜运动产生的时变电磁场会影响膜电位。在神经元等效电路中可以用忆阻器来模拟膜电位和电磁感应之间的耦合。本论文选择代表磁通和电荷关系的阈值忆阻器描述细胞膜上电磁感应现象,完善M-L神经元模型,使其更符合人体神经元所处生理环境,提出了一种带有忆阻器的M-L神经元模型。数值模拟证实了不同强度的电磁场可以使神经元的电活动产生明显的膜态跃迁。从峰峰间隔(ISI)角度,利用多参数平面上的ISIs分叉、ISIs放电周期、ISIs方差等研究了带有忆阻器电磁感应的神经元放电模式的转换趋势。最后利用Multisim设计出能够复现神经元生物特性的实用电路,能帮助理解神经元的放电开关机制。
Improving neurons and studying their electrical activities according to the real biophysical envi-ronment are of great significance for human cognitive brain activity and neural behavior. Mor-ris-Lecar (M-L) is a representative neuron model based on ion channel, but it does not consider the effect of electromagnetic induction. The complex transmembrane motion of ions on the neuronal cell membrane can establish time-varying electromagnetic fields and affect the transition firing patterns of neurons. In this paper, a threshold memristor is used to describe the electromagnetic induction and magnetic field effects of neuron cell membrane ion exchangeto improve the neuron model, and a memristive Morris-Lecar neuron model is proposed. Numerical simulation confirms that different intensities of electromagnetic fields can produce distinct pattern transition in elec-trical activities of the neuron. From the perspective of neuron’s interspike interval (ISI), the ISIs bi-furcation in the multi-parameter planes, ISIs firing periods, the variance of ISIs and other methods are used to find the trend of the neuron firing pattern transition. Finally, a practical circuit which can reproduce the biological characteristics of neurons is designed by using Multisim, which can help to understand the mechanism of neuronal firing switching.

References

[1]  Bertram, R., Butte, M.J., Kiemel, T. and Sherman, A. (1995) Topological and Phenomenological Classification of Burst-ing Oscillations. Bulletin of Mathematical Biology, 57, 413-439.
https://doi.org/10.1016/S0092-8240(05)81776-8
[2]  Chay, T.R., Fan, Y.S. and Lee, Y.S. (1995) Bursting Spiking Chaos Fractals and Universality in Biological Rhythms. International Journal of Bifurcation and Chaos, 5, 595-635.
https://doi.org/10.1142/S0218127495000491
[3]  Rabinovich, M.I., Abarbanel, H.D.I., Huerta, R. and Selverston, A.I. (1997) Self-Regularization of Chaos in Neural Systems: Experimental and Theoretical Results. IEEE Transactions on Circuits and Systems I, 44, 997-1005.
https://doi.org/10.1109/81.633889
[4]  Ermentrout, G.B. and Terman, D. (2010) Foundations of Mathematical Neuroscience. Interdisciplinary Applied Mathematics, Springer, Berlin.
[5]  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, 500-544.
https://doi.org/10.1113/jphysiol.1952.sp004764
[6]  Morris, C. and Lecar, H. (1981) Voltage Oscillations in the Barnacle Giant Muscle Fiber. Biophysical Journal, 35, 193-213.
https://doi.org/10.1016/S0006-3495(81)84782-0
[7]  Rinzel, J. and Ermentrout, G.B. (1989) Analysis of Neural Excitability and Oscillations. Methods in Neuronal Modeling. MIT Press, Cambridge.
[8]  Tsumoto, K., Kitajima, H., Yoshinaga, T., Aihara, K. and Kawakami, H. (2006) Bifurcations in Morris-Lecar Neuron Model. Neurocomputing, 69, 293-316.
https://doi.org/10.1016/j.neucom.2005.03.006
[9]  Shi, M. and Wang, Z. (2014) Abundant Bursting Pat-terns of a Fractional-Order Morris-Lecar Neuron Model. Communications in Nonlinear Science and Numerical Simula-tion, 19, 1956-1969.
https://doi.org/10.1016/j.cnsns.2013.10.032
[10]  Izhikevich, E.M. (2000) Neural Excitability, Spiking and Bursting. International Journal of Bifurcation and Chaos, 10, 1171-1266.
https://doi.org/10.1142/S0218127400000840
[11]  Wang, H., Lu, Q. and Wang, Q. (2005) Generation of Firing Rhythm Patterns and Synchronization in the Morris-Lecar Neuron Model. International Journal of Nonlinear Sciences and Numerical Simulation, 6, 7-12.
https://doi.org/10.1515/IJNSNS.2005.6.1.7
[12]  Wang, H., Lu, Q. and Zheng, Y. (2009) Complex Dynamics of Neuron Models: Bifurcation and Coding. Journal of Dynamics and Control, 3, 7-10.
[13]  Upadhyay, R.K. and Mondal, A. (2017) Synchronization of Bursting Neurons with a Slowly Varying d. c. Current. Chaos, Solitons and Fractals, 99, 195-208.
https://doi.org/10.1016/j.chaos.2017.03.063
[14]  Song, X., Wang, H. and Chen, Y. (2019) Au-tapse-Induced Firing Patterns Transitions in the Morris-Lecar Neuron Model. Nonlinear Dynamics, 96, 2341-2350.
https://doi.org/10.1007/s11071-019-04925-7
[15]  Chua, L. (1997) Memristor—The Missing Circuit Element. IEEE Transactions on Circuit Theory, 18, 507-519.
https://doi.org/10.1109/TCT.1971.1083337
[16]  Strukov, D.B., Snider, G.S., Stewart, D.R. and Williams, R.S. (2008) The Missing Memristor Found. Nature, 453, 80-83.
https://doi.org/10.1038/nature06932
[17]  Lv, M., Wang, C., Ren, G., Ma, J. and Song, X. (2016) Model of Electrical Activity in a Neuron under Magnetic Flow Effect. Nonlinear Dynamics, 85, 1479-1490.
https://doi.org/10.1007/s11071-016-2773-6
[18]  Lv, M. and Ma, J. (2016) Multiple Modes of Electrical Activities in a New Neuron Model under Electromagnetic Radiation. Neurocomputing, 205, 375-381.
https://doi.org/10.1016/j.neucom.2016.05.004
[19]  Bao, H., Hu, A., Liu, W. and Bao, B. (2019) Hidden Bursting Firings and Bifurcation Mechanisms in Memristive Neuron Model with Threshold Electromagnetic Induction. IEEE Transactions on Neural Networks and Learning Systems, 31, 502-511.
https://doi.org/10.1109/TNNLS.2019.2905137
[20]  Han, I.S. (2006) Mixed-Signal Neuron-Synapse Implementa-tion for Large-Scale Neural Network. Neurocomputing, 69, 1860-1867.
https://doi.org/10.1016/j.neucom.2005.11.013
[21]  Sun, X., Perc, M. and Kurths, J. (2018) Fast Regular Firings Induced by Intra- and Inter-Time Delays in Two Clustered Neuronal Networks. Chaos, 28, Article ID: 106310.
https://doi.org/10.1063/1.5037142
[22]  Ahmadi, A. and Gomar, S. (2014) Digital Multiplierless Implementation of Biological Adaptive-Exponential Neuron Model. IEEE Transactions on Circuits and Systems I, 61, 1206-1219.
https://doi.org/10.1109/TCSI.2013.2286030
[23]  Silver, R., Boahen, K., Grillner, S., Kopell, N. and Olsen, K.L. (2007) Neurotech for Neuroscience: Unifying Concepts, Organizing Principles and Emerging Tools. Journal of Neuro-science, 27, 11807-11819.
https://doi.org/10.1523/JNEUROSCI.3575-07.2007
[24]  Wu, X., Ma, J., Yuan, L. and Liu, Y. (2014) Simulating Electric Activities of Neurons by Using PSPICE. Nonlinear Dynamics, 75, 113-126.
https://doi.org/10.1007/s11071-013-1053-y
[25]  Behdad, R., Binczak, S., Dmitrichev, A.S., Nekorkin, V.I. and Bilbault, J.M. (2014) Artificial Electrical Morris-Lecar Neuron. IEEE Transactions on Neural Networks and Learning Systems, 26, 1875-1884.
https://doi.org/10.1109/TNNLS.2014.2360072
[26]  Hu, X., Liu, C., Liu, L., Ni, J. and Li, S. (2016) An Electronic Implementation for Morris-Lecar Neuron Model. Nonlinear Dynamics, 4, 2317-2332.
https://doi.org/10.1007/s11071-016-2647-y

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