On the Aging Dynamics in an Immune Network Model

TL;DR

This paper explores the aging dynamics of an immune network model, revealing similarities to glassy systems and showing how perturbations influence long-term behavior and attractor states.

Contribution

It demonstrates that an immune network model exhibits aging and attractor dynamics similar to glassy systems, with insights into perturbation effects on system states.

Findings

Model reproduces refractory and aging effects seen in experiments.

System can reach long-period attractors depending on initial conditions.

Perturbations can shift the system between attractors.

Abstract

Recently we have used a cellular automata model which describes the dynamics of a multi-connected network to reproduce the refractory behavior and aging effects obtained in immunization experiments performed with mice when subjected to multiple perturbations. In this paper we investigate the similarities between the aging dynamics observed in this multi-connected network and the one observed in glassy systems, by using the usual tools applied to analyze the latter. An interesting feature we show here is that the model reproduces the biological aspects observed in the experiments during the long transient time it takes to reach the stationary state. Depending on the initial conditions, and without any perturbation, the system may reach one of a family of long-period attractors. The pertrubations may drive the system from its natural attractor to other attractors of the same family. We discuss the different roles played by the small random perturbations (noise) and by the large periodic perturbations (immunizations).