Neural Energy Supply-Consumption Properties Based on Hodgkin-Huxley Model
Electrical activity is the foundation of the neural system. Coding theories that describe neural electrical activity by the roles of action potential timing or frequency have been thoroughly studied. However, an alternative method to study coding questions is the energy method, which is more global...
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| Format: | Article |
| Language: | English |
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Wiley
2017-01-01
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| Series: | Neural Plasticity |
| Online Access: | http://dx.doi.org/10.1155/2017/6207141 |
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| author | Yihong Wang Rubin Wang Xuying Xu |
| author_facet | Yihong Wang Rubin Wang Xuying Xu |
| author_sort | Yihong Wang |
| collection | DOAJ |
| description | Electrical activity is the foundation of the neural system. Coding theories that describe neural electrical activity by the roles of action potential timing or frequency have been thoroughly studied. However, an alternative method to study coding questions is the energy method, which is more global and economical. In this study, we clearly defined and calculated neural energy supply and consumption based on the Hodgkin-Huxley model, during firing action potentials and subthreshold activities using ion-counting and power-integral model. Furthermore, we analyzed energy properties of each ion channel and found that, under the two circumstances, power synchronization of ion channels and energy utilization ratio have significant differences. This is particularly true of the energy utilization ratio, which can rise to above 100% during subthreshold activity, revealing an overdraft property of energy use. These findings demonstrate the distinct status of the energy properties during neuronal firings and subthreshold activities. Meanwhile, after introducing a synapse energy model, this research can be generalized to energy calculation of a neural network. This is potentially important for understanding the relationship between dynamical network activities and cognitive behaviors. |
| format | Article |
| id | doaj-art-d3e7fe45ba114e9cbc9e83fc702f13f3 |
| institution | OA Journals |
| issn | 2090-5904 1687-5443 |
| language | English |
| publishDate | 2017-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Neural Plasticity |
| spelling | doaj-art-d3e7fe45ba114e9cbc9e83fc702f13f32025-08-20T02:19:45ZengWileyNeural Plasticity2090-59041687-54432017-01-01201710.1155/2017/62071416207141Neural Energy Supply-Consumption Properties Based on Hodgkin-Huxley ModelYihong Wang0Rubin Wang1Xuying Xu2Institute for Cognitive Neurodynamics, East China University of Science and Technology, 130 Meilong Road, Shanghai, ChinaInstitute for Cognitive Neurodynamics, East China University of Science and Technology, 130 Meilong Road, Shanghai, ChinaInstitute for Cognitive Neurodynamics, East China University of Science and Technology, 130 Meilong Road, Shanghai, ChinaElectrical activity is the foundation of the neural system. Coding theories that describe neural electrical activity by the roles of action potential timing or frequency have been thoroughly studied. However, an alternative method to study coding questions is the energy method, which is more global and economical. In this study, we clearly defined and calculated neural energy supply and consumption based on the Hodgkin-Huxley model, during firing action potentials and subthreshold activities using ion-counting and power-integral model. Furthermore, we analyzed energy properties of each ion channel and found that, under the two circumstances, power synchronization of ion channels and energy utilization ratio have significant differences. This is particularly true of the energy utilization ratio, which can rise to above 100% during subthreshold activity, revealing an overdraft property of energy use. These findings demonstrate the distinct status of the energy properties during neuronal firings and subthreshold activities. Meanwhile, after introducing a synapse energy model, this research can be generalized to energy calculation of a neural network. This is potentially important for understanding the relationship between dynamical network activities and cognitive behaviors.http://dx.doi.org/10.1155/2017/6207141 |
| spellingShingle | Yihong Wang Rubin Wang Xuying Xu Neural Energy Supply-Consumption Properties Based on Hodgkin-Huxley Model Neural Plasticity |
| title | Neural Energy Supply-Consumption Properties Based on Hodgkin-Huxley Model |
| title_full | Neural Energy Supply-Consumption Properties Based on Hodgkin-Huxley Model |
| title_fullStr | Neural Energy Supply-Consumption Properties Based on Hodgkin-Huxley Model |
| title_full_unstemmed | Neural Energy Supply-Consumption Properties Based on Hodgkin-Huxley Model |
| title_short | Neural Energy Supply-Consumption Properties Based on Hodgkin-Huxley Model |
| title_sort | neural energy supply consumption properties based on hodgkin huxley model |
| url | http://dx.doi.org/10.1155/2017/6207141 |
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