A new memristive map neuron, self-regulation and coherence resonance

IF 1.6 4区物理与天体物理 Q3 PHYSICS, CONDENSED MATTER

The European Physical Journal B Pub Date : 2024-08-17 DOI:10.1140/epjb/s10051-024-00760-x

Binchi Wang, Xiaofeng Zhang, Zhigang Zhu, Guodong Ren

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Abstract

Activation of firing patterns requires continuous energy exchange between magnetic and electric field in the neurons. Complexity of ion channels supports energy diversity among capacitive, inductive and memristive channel, and then the Calcium, sodium and potassium flows are pumped and diffused to trigger suitable firing modes in the neural activities. In this work, a magnetic flux-controlled memristor connected with an inductor in series is used to describe the physical effect of propagated ions, and an additive nonlinear resistor and a capacitor are connected to design a simple neural circuit. A memristive neuron model is suggested for dynamical analysis and energy description. Furthermore, linear transformation including time scale is used to convert this memristive oscillator into an equivalent memristive map. Energy function is given for this memristive map and an adaptive control law is used to control the mode transition in this map neuron. Furthermore, coherence resonance is discussed under noisy disturbance.

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新型记忆图谱神经元、自我调节和一致性共振

激活点火模式需要神经元中磁场和电场之间持续不断的能量交换。离子通道的复杂性支持电容、电感和忆阻通道之间的能量多样性，然后钙、钠和钾流被泵送和扩散，以触发神经活动中的适当点火模式。在这项工作中，使用了一个与电感串联的磁通量控制忆阻器来描述离子传播的物理效应，并连接了一个加性非线性电阻器和一个电容器来设计一个简单的神经回路。建议使用记忆神经元模型进行动态分析和能量描述。此外，还利用包括时间尺度在内的线性变换将该记忆振荡器转换为等效记忆图。给出了该记忆图谱的能量函数，并使用自适应控制法则来控制该图谱神经元的模式转换。此外，还讨论了噪声干扰下的相干共振问题。

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