Information propagation in multilayer systems with higher-order interactions across timescales

TL;DR

This paper develops a framework to understand how information propagates across multilayer systems with higher-order interactions and different timescales, revealing principles that govern multiscale information flow in complex systems.

Contribution

It introduces a novel approach to model multiscale multilayer networks with higher-order interactions and analyzes their information propagation mechanisms.

Findings

Information flow depends on timescale differences between layers.

Higher-order interactions significantly influence information coupling.

Framework applies to biological and environmental systems.

Abstract

Complex systems are characterized by multiple spatial and temporal scales. A natural framework to capture their multiscale nature is that of multilayer networks, where different layers represent distinct physical processes that often regulate each other indirectly. We model these regulatory mechanisms through triadic higher-order interactions between nodes and edges. In this work, we focus on how the different timescales associated with each layer impact their effective couplings in terms of their mutual information. We unravel the general principles governing how such information propagates across the multiscale structure, and apply them to study archetypal examples of biological signaling networks and effective environmental dependencies in stochastic processes. Our framework generalizes to any dynamics on multilayer networks, paving the way for a deeper understanding of how the multiscale nature of real-world systems shapes their information content and complexity.