Stochastic Feedback and the Regulation of Biological Rhythms

TL;DR

This paper introduces a stochastic feedback model to explain how biological rhythms, like heart rate variability, self-regulate through complex dynamics, accounting for observed features such as 1/f spectra and phase correlations.

Contribution

It presents a novel stochastic feedback framework that models biological rhythm regulation and successfully reproduces key features of cardiac variability.

Findings

Model reproduces 1/f power spectrum of heart rate variability

Captures distribution and correlations of cardiac fluctuations

Suggests control mechanisms prevent extreme and constant states

Abstract

We propose a general approach to the question of how biological rhythms spontaneously self-regulate, based on the concept of ``stochastic feedback''. We illustrate this approach by considering the neuroautonomic regulation of the heart rate. The model generates complex dynamics and successfully accounts for key characteristics of cardiac variability, including the $1/f$ power spectrum, the functional form and scaling of the distribution of variations, and correlations in the Fourier phases. Our results suggest that in healthy systems the control mechanisms operate to drive the system away from extreme values while not allowing it to settle down to a constant output.