title: Identifying type I excitability using dynamics of stochastic neural firing patterns.
abstract: The stochastic firing patterns are simulated near saddle-node bifurcation on an invariant cycle corresponding to type I excitability in stochastic Morris-Lecar model. In absence of external periodic signal, the stochastic firing manifests continuous distribution in ISI histogram (ISIH), whose amplitude at first increases sharply and then decreases exponentially. In presence of the external periodic signal, stochastic firing patterns appear as two cases of integer multiple firing with multiple discrete peaks in ISIH. One manifests perfect exponential decay in all peaks and the other imperfect exponential decay except a lower first peak. These stochastic firing patterns simulated with or without external periodic signal can be demonstrated in the experiments on rat hippocampal CA1 pyramidal neurons. The exponential decay laws in the multiple peaks are also acquired using probability analysis method. The perfect decay law is determined by the independent characteristic within the firing while the imperfect decay law is from the inhibitory effect. In addition, the stochastic firing patterns corresponding to type I excitability are compared to those of type II excitability. The results not only reveal the dynamics of stochastic firing patterns with or without external signal corresponding to type I excitability, but also provide practical indicators to availably identify type I excitability.
authors.affiliation: School of Aerospace Engineering and Applied Mechanics, Tongji University, Shanghai, 200092 China.
authors.forename: Bing
authors.initials: B
authors.lastname: Jia
authors.forename: Huaguang
authors.initials: H
authors.lastname: Gu
keywords: Excitability; Integer multiple firing; Neural firing pattern; Saddle-node bifurcation on an invariant cycle; Stochastic process; Type I excitability