An Energy-Based Complex Brain Network Model—Part 1: Local Electrophysiological Dynamics

Chunbin Yang, N. Shettigar, C. Suh
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Abstract

The human brain is a complex network of connected neurons whose dynamics are difficult to describe. Brain dynamics are the global manifestation of individual neuron dynamics and the synaptic coupling between neurons. Membrane potential is a function of synaptic dynamics and electrophysiological coupling, with the parameters of postsynaptic potential, action potential, and ion pump dynamics. By modelling synaptic dynamics using physical laws and the time evolution of membrane potential using energy, neuron dynamics can be described. This local depiction can be scaled up to describe mesoscopic and macroscopic hierarchical complexity in the brain. Modelling results are favorably compared with physiological observation and physically acquired action potential profiles as reported in the literature.
基于能量的复杂脑网络模型-第一部分:局部电生理动力学
人脑是一个由相互连接的神经元组成的复杂网络,其动态难以描述。脑动力学是单个神经元动力学和神经元间突触耦合的全局表现。膜电位是突触动力学和电生理耦合的函数,参数包括突触后电位、动作电位和离子泵动力学。利用物理定律模拟突触动力学,利用能量模拟膜电位的时间演化,可以描述神经元动力学。这种局部描述可以扩展到描述大脑中观和宏观的层次复杂性。建模结果与文献中报道的生理观察和物理获得的动作电位剖面相比较是有利的。
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