A New Neuron Ion Channel Model with Noisy Input Current - Khudhur, Ahmed Mahmood; Abdalla, Ahmed N. (Penerbit Universiti Malaysia Pahang, 2015)
The data processing fundamental problem affects all aspects of nervous-system function by the noise of ion channels. The conducting and non conducting of ion channels depends on random transitions of channel noise, which affect the states of several numbers of gates in every single individual ion channel. This paper, introduce a new ion channel model in the neuron with noisy input current as approximations of the HH model. It briefly introduces the ion channel based on stochastic Hodgkin-Huxley model. The method is able to fully constrain the HH model and obtain all models capable of reproducing the data. Therefore, this method overcomes the limitations of other parameter estimation methods. The stochastic Markov process method is simply applied to simulate each gate individually to determine the relationship between channel noise and the spike frequency.