Modelling Active Non-Markovian Oscillations

TL;DR

This paper introduces a linear stochastic model driven by non-Markovian bistable noise to accurately simulate active, self-sustained oscillations in biological systems, with analytical predictions matching experimental data.

Contribution

The paper presents a novel minimal linear stochastic model with non-Markovian noise that captures active oscillations and aligns with experimental observations.

Findings

Model accurately reproduces hair bundle oscillations

Estimates energy consumption per oscillation cycle

Analytical predictions match experimental data

Abstract

Modelling noisy oscillations of active systems is one of the current challenges in physics and biology. Because the physical mechanisms of such processes are often difficult to identify, we propose a linear stochastic model driven by a non-Markovian bistable noise that is capable of generating self-sustained periodic oscillation. We derive analytical predictions for most relevant dynamical and thermodynamic properties of the model. This minimal model turns out to describe accurately bistable-like oscillatory motion of hair bundles in bullfrog sacculus, extracted from experimental data. Based on and in agreement with these data, we estimate the power required to sustain such active oscillations to be of the order of one hundred $k_B T$ per oscillation cycle.