Phase synchronization and energy balance between neurons

Abstract

A functional neuron has been developed from a simple neural circuit by incorporating a phototube and a thermistor in different branch circuits. The physical field energy is controlled by the photocurrent across the phototube and the channel current across the thermistor. The firing mode of this neuron is controlled synchronously by external temperature and illumination. There is energy diversity when two functional neurons are exposed to different illumination and temperature conditions. As a result, synapse connections can be created and activated in an adaptive way when field energy is exchanged between neurons. We propose two kinds of criteria to discuss the enhancement of synapse connections to neurons. The energy diversity between neurons determines the increase of the coupling intensity and synaptic current for neurons, and the realization of synchronization is helpful in maintaining energy balance between neurons. The first criterion is similar to the saturation gain scheme in that the coupling intensity is increased with a constant step within a certain period until it reaches energy balance or complete synchronization. The second criterion is that the coupling intensity increases exponentially before reaching energy balance. When two neurons become non-identical, phase synchronization can be controlled during the activation of synapse connections to neurons. For two identical neurons, the second criterion for taming synaptic intensity is effective for reaching complete synchronization and energy balance, even in the presence of noise. This indicates that a synapse connection may prefer to enhance its coupling intensity exponentially. These results are helpful in discovering why synapses are awaken and synaptic current becomes time-varying when any neurons are excited by external stimuli. The potential biophysical mechanism is that energy balance is broken and then synapse connections are activated to maintain an adaptive energy balance between the neurons. These results provide guidance for designing and training intelligent neural networks by taming the coupling channels with gradient energy distribution.

摘要

在一类简单的神经元电路不同支路嵌入光电管和热敏电阻来设计一种功能性神经元. 通过光电管的光电流和流经热敏电阻的通道电流可以控制神经元电路的场能量. 神经元的放电模态同时依赖于外界光照和温度. 在不同的光照和温度刺激下, 两个功能神经元存在能量差. 因此, 在场能量传递和交换过程中神经元之间开始建立突触连接并相互耦合. 我们提出两种规则来讨论神经元之间突触耦合增强问题, 神经元之间的能量差控制着神经元之间突触耦合强度的增长和突触电流变化, 且神经元之间的同步有利于维持神经元之间的能量平衡. 第一类规则类似于饱和增益法, 即神经元在达到完全同步之前其突触耦合强度以恒定的增益周期性增长. 第二类规则指出神经元突触耦合强度以恰当的增益呈现指数型增长, 直到神经元之间达到能量平衡. 两个不同的神经元在突触耦合增强的过程中可以实现相位同步. 两个完全相同的神经元即使在噪声环境下, 神经元耦合突触按照第二类规则增长强度依旧可以有效实现完全同步和能量平衡. 此结果表明神经元突触更倾向于以指数型方式来增长其耦合强度. 这些研究结果有助于揭示外界刺激如何唤醒和激活神经元之间的突触连接, 进一步理解突触耦合电流时变的特性. 潜在的生物物理机制在于外界差异性的刺激打破了神经元之间的能量平衡, 因此突触耦合不断被增强来实现神经元之间能量动态平衡. 这些研究结果为设计和训练智能神经元电路提供了思路, 即通过设置梯度性能量分布来调控耦合通道.