The Influence Of Stochastic Factors Upon Information Processing In Neuronal Systems

The neural system is a huge net composed of neurons, and its basic framework and functional cell is neuron. The electrical activity of neurons is the basis of electrical activity of neural system. In this thesis we mainly study the dynamic features and physical mechanisms of neuron, especially, the effect of stochastic factors in neuronal information processing.A major task in physical research is to search for general physical principles behind various natural processes by using relatively simple models, which can catch the main factors in the concerned aspects and help us to understand the complicated behaviors happened in the brain. We research the model theory and experimental support of HH model, in addition to two similar models which can describe the main characteristics of real neurons.First of all, we study the membrane features and frequency characteristics by effect of stochastic noise. Different kinds of noise may have effect on neuron system with different degree. The stochastic ion channel noise is the dominant source of neuron at any reasonable temperature. The analysis of this effect may provide some cues for approximation of different kinds of noise in our further work.Second, a 10-RM-neuron chain is created in order to study the effect of stochastic factors during the neuronal signal propagation. Creating spikes using RM converts the information to event timings, and the interspike intervals imply the information of signals. It is shown by example that stochastic factors may be useful for the information processing by prolonging the interspike interval, which means the timing of the signal is changed.