Dynamical Analysis Of Two Kinds Of CA1 Pyramidal Neurons Model

Neurons are the basic unit of all neural tissues, and they are considered to be the minimal modules which play the role of neural information processing, they can encode information through the action potentials. Study the firing patterns of neurons and InterSpike Intervals of action potentials can provide clues for understanding the neural mechanisms of information coding. There are many factors affect the firing patterns of neurons, such as the channel type, the concentration of various ions and external stimuli and so on. In this paper, we systematically analyze the dynamic properties of single compartment model and multi-compartment model of CA1 pyramidal neurons, the main results obtained are as follows:For the single compartment model of CA1 pyramidal neurons, firstly, using numer-ical simulation, we study the impact of DC and AC external stimulation on the firing patterns, and get rich firing patterns. Then in AC stimulation, we discover that neurons can generate new bursting activities with the change of gated variable parameters. Com-bined with the diagram of ISIs, under different external stimulation, the firing patterns caused by the change within a certain range of the gated variable parameter, equilibri-um potential of potassium ions and the conductance of leakage current have a very big difference, such as spiking, bursting and complex firing patterns. Between these firing patterns, several typical nonlinear dynamical bifurcation phenomenon are investigated, such as period adding bifurcation and period doubling bifurcation, etc. In the end, we study multi-compartment model of CA1 pyramidal neurons, firstly, the soma will be cou-pled with dendrite which is far away from the soma, give the new coupling coefficient, and find that the electrical signals are attenuated during both forward propagation and back propagation. At the same time, we study the effect of external stimulation current on the firing patterns under different coupling coefficient and get a different pattern of bi-furcation. Finally, under certain coupling coefficient, we discover that the change of some physiological parameters can result in rich firing patterns, make the research results more abundant, and help us have more understanding in the firing patterns and information encoding of pyramidal neurons.