A General Model of Ion Passive Transmembrane Transport Based on Ionic Concentration
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 p...
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2019-01-01
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| Series: | Frontiers in Computational Neuroscience |
| Subjects: | |
| Online Access: | https://www.frontiersin.org/article/10.3389/fncom.2018.00110/full |
| _version_ | 1811328702137499648 |
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| author | Vincent Qiqian Wang Shenquan Liu |
| author_facet | Vincent Qiqian Wang Shenquan Liu |
| author_sort | Vincent Qiqian Wang |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-04-13T15:30:46Z |
| format | Article |
| id | doaj.art-2dd300a3fc0b494199ea1e896ceb04b1 |
| institution | Directory Open Access Journal |
| issn | 1662-5188 |
| language | English |
| last_indexed | 2024-04-13T15:30:46Z |
| publishDate | 2019-01-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Computational Neuroscience |
| spelling | doaj.art-2dd300a3fc0b494199ea1e896ceb04b12022-12-22T02:41:23ZengFrontiers Media S.A.Frontiers in Computational Neuroscience1662-51882019-01-011210.3389/fncom.2018.00110421474A General Model of Ion Passive Transmembrane Transport Based on Ionic ConcentrationVincent Qiqian WangShenquan LiuCurrent 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.https://www.frontiersin.org/article/10.3389/fncom.2018.00110/fullmembraneion channelgatefilterionic concentration and fluxelectrophysiology |
| spellingShingle | Vincent Qiqian Wang Shenquan Liu A General Model of Ion Passive Transmembrane Transport Based on Ionic Concentration Frontiers in Computational Neuroscience membrane ion channel gate filter ionic concentration and flux electrophysiology |
| title | A General Model of Ion Passive Transmembrane Transport Based on Ionic Concentration |
| title_full | A General Model of Ion Passive Transmembrane Transport Based on Ionic Concentration |
| title_fullStr | A General Model of Ion Passive Transmembrane Transport Based on Ionic Concentration |
| title_full_unstemmed | A General Model of Ion Passive Transmembrane Transport Based on Ionic Concentration |
| title_short | A General Model of Ion Passive Transmembrane Transport Based on Ionic Concentration |
| title_sort | general model of ion passive transmembrane transport based on ionic concentration |
| topic | membrane ion channel gate filter ionic concentration and flux electrophysiology |
| url | https://www.frontiersin.org/article/10.3389/fncom.2018.00110/full |
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