Characterizing persistence and pause dynamical behaviors in biological systems

Abstract

This paper analyzed motion that randomly switches between the persistent motion runs and pause periods. A two-state continuous-time Markov chain is used to model the motion, which led to a system with coupled differential equations. Using a combined Fourier–Laplace transform, an analytical expression for calculating the mean-squared displacement is derived. The overall motion is investigated and identified from the obtained mean-squared displacement. The mean-squared displacement is a nonlinear function in time that is dependent on the phase transition rate, the direction switching rate, the average speed, and the initial state. It decays and grows with increasing the direction switching and average speed, respectively. The effective diffusivity descents exponentially in short times and remains constant in long times. The waiting time in each phase decayed exponentially. The probability density function for the position of a particle at a given time tends to be Gaussian in long times. The motion can be interpreted as a super-diffusion in short times and a standard diffusion in long times with a diffusion coefficient dependent on the phase transition rates, the direction switching rate and the average speed. Persistence influences the dynamical behavior for short times while for long times diffusive behavior is exhibited.