Biophysical neurons, energy, and synapse controllability: a review

Abstract

Diffusive intracellular and extracellular ions induce a gradient electromagnetic field that regulates membrane potential, and energy injection from external stimuli breaks the energy balance between the magnetic and electric fields in a cell. Indeed, any activation of biophysical function and self-adaption of biological neurons may be dependent on energy flow, and synapse connection is controlled to reach energy balance between neurons. When more neurons are clustered and gathered closely, field energy is exchanged and shape formation is induced to achieve local energy balance. As a result, the coexistence of multiple firing modes in neural activities is fostered to prevent the occurrence of bursting synchronization and seizure. In this review, a variety of biophysical neuron models are presented and explained in terms of their physical aspects, and the controllability of functional synapses, formation of heterogeneity, and defects are clarified for knowing the synchronization stability and cooperation between functional regions. These models and findings are summarized to provide new insights into nonlinear physics and computational neuroscience.

概要

目的

阐明功能性神经元设计的物理机理, 揭示能量调控神经元放电模态和突触活性的物理机理, 并论证神经元自适 应性选频的路径和神经元网络内异质性和缺陷的形成。

创新点

1. 建立了包含表达电磁感应、热效应和温度感知、光敏、压电感知和磁场感知的系列神经元模型; 2. 定义了 神经元中哈密顿能量并解释其来源和计算方法; 3. 指出哈密顿能量对神经元突触调控的物理机理和方法; 4. 解 释了听觉神经元和视觉神经元在外界刺激下的选频响应机理; 5. 解释了神经元网络内异质性和缺陷形成的能 量机理。

方法

把忆阻器、热敏电阻、光电管、压电陶瓷、约瑟夫森结等嵌入简单的电感-电容和电阻耦合的神经元电路, 实 现对外界物理信号的捕获和感知。从神经元电路场能量方程和赫姆霍兹定理分别得出功能神经元模型的能量函 数, 确认其表达式的唯一性和一致性。以神经元能量函数为控制开关, 对神经元突触进行自适应控制来实现能 量平衡。

结论

1. 特定物理器件嵌入神经元电路可以增强其物理感知能力; 2. 能量驱动和调控可以有效控制神经元和神经元 网络放电模态和时空斑图; 3. 生物神经元的多重自适应性源于能量流的平衡分配。