Wang Vincent Qiqian, Liu Shenquan
School of Mathematics, South China University of Technology, Guangzhou, China.
Front Comput Neurosci. 2019 Jan 22;12:110. doi: 10.3389/fncom.2018.00110. eCollection 2018.
Current mainstream neural computing is based on the electricity model proposed by Hodgkin and Huxley in 1952, the core of which is ion passive transmembrane transport controlled by ion channels. However, studies on the evolutionary history of ion channels have shown that some neuronal ion channels predate the neurons. Thus, to deepen our understanding of neuronal activities, ion channel models should be applied to other cells. Expanding the scope of electrophysiological experiments from nerve to muscle, animal to plant, and metazoa to protozoa, has lead the discovery of a number of ion channels. Moreover, the properties of these newly discovered ion channels are too complex to be described by current common models. Hence this paper has presented a convenient method for estimating the distribution of ions under an electric field and established a general ionic concentration-based model of ion passive transmembrane transport that is simple but capable of explaining and simulating the complex phenomena of patch clamp experiments, is applicable to different ion channels in different cells of different species, and conforms to the current general understanding of ion channels. Finally, we designed a series of mathematical experiments, which we have compared with the results of typical electrophysiological experiments conducted on plant cells, oocytes, myocytes, cardiomyocytes, and neurocytes, to verify the model.
当前主流的神经计算基于霍奇金和赫胥黎于1952年提出的电学模型，其核心是由离子通道控制的离子被动跨膜运输。然而，对离子通道进化史的研究表明，一些神经元离子通道早于神经元出现。因此，为了加深我们对神经元活动的理解，应将离子通道模型应用于其他细胞。将电生理实验的范围从神经扩展到肌肉、从动物扩展到植物、从后生动物扩展到原生动物，已经导致发现了许多离子通道。此外，这些新发现的离子通道的特性过于复杂，无法用当前常见的模型来描述。因此，本文提出了一种在电场下估计离子分布的简便方法，并建立了一个基于离子浓度的通用离子被动跨膜运输模型，该模型简单但能够解释和模拟膜片钳实验的复杂现象，适用于不同物种不同细胞中的不同离子通道，并且符合当前对离子通道的一般理解。最后，我们设计了一系列数学实验，并将其与在植物细胞、卵母细胞、肌细胞、心肌细胞和神经细胞上进行的典型电生理实验结果进行了比较，以验证该模型。
