Confined modes of single-particle trajectories induced by stochastic resetting

TL;DR

This paper demonstrates that confined particle trajectories in living cells follow Linnik distributions due to stochastic resetting, providing a new statistical framework for analyzing single-particle motion beyond normal diffusion.

Contribution

It introduces the concept that stochastic resetting causes confined particle motions to follow Linnik distributions, linking experimental data with theoretical models.

Findings

Confined particle trajectories follow Linnik distribution.

Stochastic resetting explains the distribution of particle positions.

Experimental data supports the resetting-induced confinement model.

Abstract

Random trajectories of single particles in living cells contain information about the interaction between particles, as well as, with the cellular environment. However, precise consideration of the underlying stochastic properties, beyond normal diffusion, remains a challenge as applied to each particle trajectory separately. In this paper, we show how positions of confined particles in living cells can obey not only the Laplace distribution, but the Linnik one. This feature is detected in experimental data for the motion of G proteins and coupled receptors in cells, and its origin is explained in terms of stochastic resetting. This resetting process generates power-law waiting times, giving rise to the Linnik statistics in confined motion, and also includes exponentially distributed times as a limit case leading to the Laplace one. The stochastic process, which is affected by the resetting, can be Brownian motion commonly found in cells. Other possible models producing similar effects are discussed.