<p>Proposal of neuron models provides a pathway for perceiving and predicting transition in neural activities via dynamical analysis, which is consistent with the dynamical characteristic in the electrical activities detected from biological neurons. Mathematical neuron models can produce similar time series in one or two variables as those recorded membrane potentials in experimental data. Indeed, from single neuron to clustered neurons in functional region in the brain, complex electromagnetic induction and energy level should be clarified before building any equivalent neural circuits and neural networks. Each neuron contains distinct energy level and the mode transition in the electrical activities results from shift between different energy levels, and the self-adaption in synapse function is dependent on the energy release and absorption. The membrane potentials are detectable, and many nonlinear circuits can be adjusted to control the output voltage across the capacitor for mimicking the changes of membrane potentials in biological neurons. It is a challenge to remark the physical significances of the neuron models derived from neural circuits, for example, cell membrane structures, electromagnetic induction, distribution of ion channels, energy conversion, and polarization effect on the media subjected to external electric field should be considered and described in feasible way. In this review, the physical characteristics of some electric components are clarified, and the physical criteria for building neural circuits are discussed accompanying with exact description in the energy function. The reliability of neural circuit is confirmed, physical equations for the neural circuit are converted into equivalent theoretical models in presenting oscillator and even map forms, and dimensionless energy function is derived and proofed from physical aspect. The main scheme and achievements in functional neural circuits are summarized, approach of energy function for neural circuits and neuron models are presented for further investigation in computational neuroscience. It suggests that neural circuits should use two coupled capacitors for discerning the diversity in potentials for outer and inner cell membrane, and thus the field effect of the membrane material can be estimated. When the media is exposed to electric field, the circuit approach requires connection voltage source to the capacitor in the branch circuit, and the polarization effect on the cell membrane is estimated by the controllable biased voltage in the capacitive branch circuit. For potential application of neural circuits, energy exchange is discussed when neural circuits are used to drive and control simple electromechanical arms.</p>

Biological neurons to neural circuit, review from physical perspective

期刊论文
发表日期：

2025年7月4日

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Jun Ma

摘要

Proposal of neuron models provides a pathway for perceiving and predicting transition in neural activities via dynamical analysis, which is consistent with the dynamical characteristic in the electrical activities detected from biological neurons. Mathematical neuron models can produce similar time series in one or two variables as those recorded membrane potentials in experimental data. Indeed, from single neuron to clustered neurons in functional region in the brain, complex electromagnetic induction and energy level should be clarified before building any equivalent neural circuits and neural networks. Each neuron contains distinct energy level and the mode transition in the electrical activities results from shift between different energy levels, and the self-adaption in synapse function is dependent on the energy release and absorption. The membrane potentials are detectable, and many nonlinear circuits can be adjusted to control the output voltage across the capacitor for mimicking the changes of membrane potentials in biological neurons. It is a challenge to remark the physical significances of the neuron models derived from neural circuits, for example, cell membrane structures, electromagnetic induction, distribution of ion channels, energy conversion, and polarization effect on the media subjected to external electric field should be considered and described in feasible way. In this review, the physical characteristics of some electric components are clarified, and the physical criteria for building neural circuits are discussed accompanying with exact description in the energy function. The reliability of neural circuit is confirmed, physical equations for the neural circuit are converted into equivalent theoretical models in presenting oscillator and even map forms, and dimensionless energy function is derived and proofed from physical aspect. The main scheme and achievements in functional neural circuits are summarized, approach of energy function for neural circuits and neuron models are presented for further investigation in computational neuroscience. It suggests that neural circuits should use two coupled capacitors for discerning the diversity in potentials for outer and inner cell membrane, and thus the field effect of the membrane material can be estimated. When the media is exposed to electric field, the circuit approach requires connection voltage source to the capacitor in the branch circuit, and the polarization effect on the cell membrane is estimated by the controllable biased voltage in the capacitive branch circuit. For potential application of neural circuits, energy exchange is discussed when neural circuits are used to drive and control simple electromechanical arms.