Neurodynamics On Up And Down Transitions Of Membrane Potentials

Neuroscience is one of the natural sciences that rapidly developing in recent years whose main study object is the brain. Cognitive neuroscience, a subfield of neuroscience, is a new multidisciplinary and interdisciplinary field concerned with the structure and function of nervous system. It blends with disciplines such as neuroscience, psychology, neurobiology, computing science, nonlinear dynamics in order to explain brain activities and neural mechanisms of cognition.We know that different behaviors correspond to different brain activities including overall activities of cerebral cortex level and specific activities of neuron level. In vivo and vitro recordings, cortical pyramidal neurons show spontaneous up and down transitions of membrane potentials. This phenomenon was firstly found in slow wave sleep, and later also found in somatosensory cortex during quiet wakefulness. What we concern about is the mechanisms of these sub-threshold activities.Firstly, in this paper, we started from one single neuron model to discuss these up and down transitions and the results exhibit three characteristics:bistability, directivity and spontaneity of these transitions, which we explain the molecular mechanisms from the perspective of ionic channel. The simulation results cohered with ones observed in experiments. So we may base it on to study the up and down transitions of neural population and the role of one single neuron plays in these transitions. It was an encouraging start for deeply understanding the mechanism of neural information process in brain, and was also a basic and effective research method.Then we discussed the neurodynamics of network behaviors to try to understand the relationship between single neuron and network transitions, which was the base to study on cognitive behaviors. As an interim study, we focused on a simple network to research the up and down transitions of network level and one single neuron, respectively, and also the role of one single neuron played in the network. Further, we considered the situations under different conductance of ionic channel and corresponding transition directions. Specifically, we discussed the influences of sodium conductance and potassium conductance on up and down transitions, respectively, with control variable method. Then we stimulated the whole network or just one neuron of the network which exhibiting spontaneous up and down transitions and compared the different effect on transitions between them.In the last part of the research, we extended the biological model mainly from the following two aspects. One was to classify the neurons to excitatory neurons and inhibitory neurons, which involved the same intrinsic ionic currents and different types of synaptic currents. The other was to improve the connection between every two neurons from constant connection to variable one, which involved pre-synaptic and post-synaptic mechanism of the release of neurotransmitters. We hoped that these improvements were benefit to make the model closer to actual physiology. Then based on the improved model, we continued our study to discuss what factors would affect the transitions of the network and how they affect on it. We found that the network parameters, including the size and structure of the network, the ratio of the excitatory neurons to inhibitory ones, and the original state of the network, had little influence on transitions of the network. In this process, the intrinsic currents were responsible for it mainly through the mechanism of ionic channel. Then we found that the opening degree of ionic channel had a major impact on periodic spontaneous up and down transitions, especially the duration of membrane potential in the up state in one cycle. Another part we studied was the effect of stimulations on transitions of the network. We believed that stimulus on one single neuron was not strong enough to change the states of the whole network, but was able to cause a switch in local area with certain delay.