探讨了局部脑皮层网络活动中,耦合条件下的大规模神经振子群的能量消耗与神经信号编码之间的内禀关系,得到了神经元集群在阈下和阈上互相耦合时神经元膜电位变化的函数.这个能量函数能够精确地再现神经电生理学实验中的EPSP,IPSP,动作电位以及动作电流.最近功能性核磁共振实验证明了神经信号的编码是与能量的消耗紧密地耦合在一起的,因此研究结果表明利用能量原理研究大脑在神经网络层次上是如何进行编码的这一重大科学问题的讨论是十分有益的.可以预计得到的能量函数将是生物学神经网络动力学稳定性计算的基础.
This paper explores the intrinsic relationship between energy consumption of a large scale neural population and neural signal processing under coupling condition in neural networks in activity of local brain, and energy functions of variety of the neuronal membrane potential are obtained for interactive neural population at the sub-threshold and the supra-threshold states. These energy functions can accurately reproduce excitatory postsynaptic potentials (EPSP), inhibitory postsynaptic potentials (IPSP), action potential, and action potential given by the neuro-electrophysiological experimental data. Recently, it has been proved that signal transmission and neuronal energetic demands are tightly coupled to information coding in the cerebral cortex in functional magnetic resonance imaging (fMRI) experiments. Therefore, the analytic results obtained in this paper show that the principle of energy coding is quite fundamental and is beneficial to the study of the important scientific problem as how the brain performs coding at the level of local neural networks.