activity
20222026
most citedA Framework for the Time- and Frequency-Domain Assessment of High-Order Interactions in Brain and Physiological Networks

5 citations · 10 across the 10 of their papers we have counts for

collaborators

11 papers

stat.ME2026

From Statistical to Structural Synergy: A Predictability Framework to Quantify the Effects due to High-Order Mechanisms

Yuri Antonacci, Chiara Barà, Laura Sparacino +3

High-order interactions are increasingly recognized as a hallmark of collective dynamics in complex systems. The relationship between high-order behaviours (HOBs), observed as syne…

nlin.CD2025

Redundant and synergistic interactions in a complex network of single-transistor electronic chaotic oscillators and in neurophysiological recordings

Chiara Barà, Yuri Antonacci, Laura Sparacino +8

Complex networks often exhibit emergent behaviors, where simple dyadic interactions yield collective dynamics that cannot be explained by examining the system's units individually…

q-bio.QM2025

Investigating High-Order Behaviors in Multivariate Cardiovascular Interactions via Nonlinear Prediction and Information-Theoretic Tools

Chiara Barà, Yuri Antonacci, Laura Sparacino +4

Assessing the synergistic high-order behaviors (HOBs) that emerge from underlying structural mechanisms is crucial to characterize complex systems. This work leverages the combined…

stat.AP2025

A Method for the Time-Frequency Analysis of High-Order Interactions in Non-Stationary Physiological Networks

Yuri Antonacci, Chiara Bara', Laura Sparacino +3

Several data-driven approaches based on information theory have been proposed for analyzing high-order interactions involving three or more components of a network system. Most of…

stat.AP2025

Predictive Information Decomposition as a Tool to Quantify Emergent Dynamical Behaviors In Physiological Networks

Luca Faes, Gorana Mijatovic, Laura Sparacino +1

Objective: This work introduces a framework for multivariate time series analysis aimed at detecting and quantifying collective emerging behaviors in the dynamics of physiological…

stat.ME2025

Decomposing Multivariate Information Rates in Networks of Random Processes

Laura Sparacino, Gorana Mijatovic, Yuri Antonacci +4

The Partial Information Decomposition (PID) framework has emerged as a powerful tool for analyzing high-order interdependencies in complex network systems. However, its application…