Dynamical model of neuronal activity and ion channel dynamics over the
aortic wall
Abstract
The transmission of nerve signals is closely related to the incidence of
aortic dis- eases. However, due to the multilayer and complex structure
of the vascular wall, the mechanism of ion channel dynamics of aortic
diseases has not been under- standing well. Here, we demonstrate that
the ion channel dynamic behavior on neural information can be simulated
by a stochastic differential equation (SDEs) based on discrete Markov
chains. The continuous approximation model is formu- lated and solved
numerically. It can analyze the variation of voltage with time, and the
value of voltage is related to the trajectory of past voltage. By chang-
ing ion channel dynamics, our model can replicate in vitro and downward
spike adaptations in neocortical pyramidal cells and cap neurons.
Moreover, it also produces an inter-peak power-law distribution with a
longer first peak latency and higher peak-to-peak variability. The
results obtained in close agreement with the statistical data on ion
channels and potential actions. Our research extends the knowledge into
the biological mechanisms induced by ion channels and neural information
networks.