A General Model of Ion Passive Transmembrane Transport Based on Ionic Concentration - Wang, Vincent Qiqian; Liu, Shenquan (Frontiers in Computational Neuroscience, 2019)
The current mainstream neural computing continues the idea of Hodgkin and Huxley in 1952, of which the core is ion passive transmembrane transport controlled by ion channels. However, the studies on the evolutionary history of ion channels have shown that the ion channels are related to each other, and some of the ion channels in neurons were born before neurons, which suggest all the ion channels may have a common origin that was never created to generate electrical signals for nerve. Thus, to reveal the nature of neuronal activities, the ion channel models should be applied to other cells as well. Nevertheless, by expanding the scope of the electrophysiological experiments, from nerve to muscle, animal to plant, metazoa to protozoa, a growing number of ion channels were discovered, of which the properties are too complex to be described by the common models. Whereupon this paper has presented a convenient method for estimating the distribution of ions under electric ﬁeld, and established a general model of ion passive transmembrane transport based on ionic concentration, which is simple enough but capable of explaining and simulating the complex phenomena of patch clamp experiments, applicable to different ion channels in different cells of different species, and conforms to the general understanding of ion channel today. Finally, we have designed a series of mathematical experiments, compared with the results of typical electrophysiological experiments on plant cells, oocytes, myocytes, cardiomyocytes, and neurocytes, to verify the model.