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作 者:Takaaki Shirahata Takaaki Shirahata(Institute of Neuroscience and Kagawa School of Pharmaceutical Sciences, Tokushima Bunri University, Sanuki, Japan)
出 处:《Applied Mathematics》2016年第10期1134-1139,共7页应用数学(英文)
摘 要:A previous study has proposed a mathematical model of type-A medial vestibular nucleus neurons (mVNn). This model is described by a system of nonlinear ordinary differential equations, which is based on the Hodgkin-Huxley formalism. The type-A mVNn model contains several ionic conductances, such as the sodium conductance, calcium conductance, delayed-rectifier potassium conductance, transient potassium conductance, and calcium-dependent potassium conductance. The previous study revealed that spontaneous repetitive spiking in the type-A mVNn model can be suppressed by hyperpolarizing stimulation. However, how this suppression is affected by the ionic conductances has not been clarified in the previous study. The present study performed numerical simulation analysis of the type-A mVNn model to clarify how variations in the different ionic conductance values affect the suppression of repetitive spiking. The present study revealed that the threshold for the transition from a repetitive spiking state to a quiescent state is differentially sensitive to variations in the ionic conductances among the different types of ionic conductance.A previous study has proposed a mathematical model of type-A medial vestibular nucleus neurons (mVNn). This model is described by a system of nonlinear ordinary differential equations, which is based on the Hodgkin-Huxley formalism. The type-A mVNn model contains several ionic conductances, such as the sodium conductance, calcium conductance, delayed-rectifier potassium conductance, transient potassium conductance, and calcium-dependent potassium conductance. The previous study revealed that spontaneous repetitive spiking in the type-A mVNn model can be suppressed by hyperpolarizing stimulation. However, how this suppression is affected by the ionic conductances has not been clarified in the previous study. The present study performed numerical simulation analysis of the type-A mVNn model to clarify how variations in the different ionic conductance values affect the suppression of repetitive spiking. The present study revealed that the threshold for the transition from a repetitive spiking state to a quiescent state is differentially sensitive to variations in the ionic conductances among the different types of ionic conductance.
关 键 词:Mathematical Model Numerical Simulation Type-A Medial Vestibular Nucleus Neurons Ionic Conductance
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