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

Measures of causal emergence provide a practical tool to quantify the mechanisms of causal influence that determine the dynamic state of cardiovascular and neural network systems across distinct physiopathological conditions.

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Publication Details

Journal
IEEE Transactions on Biomedical Engineering
Published
2025-05-16
DOI
https://doi.org/10.1109/tbme.2025.3570937
Citations
1
Primary Topic
Gene Regulatory Network Analysis
Type
article
Field-Weighted Citation Impact
0.81
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article

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

Gorana Mijatović, Laura Sparacino, Alberto Porta, Luca Faes
1 citations
IEEE Transactions on Biomedical Engineering
Gene Regulatory Network Analysis
0.81
article

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

Gorana Mijatović, Laura Sparacino, Alberto Porta, Luca Faes
article en
1 citations

Abstract

Measures of causal emergence provide a practical tool to quantify the mechanisms of causal influence that determine the dynamic state of cardiovascular and neural network systems across distinct physiopathological conditions.

IEEE Transactions on Biomedical EngineeringVol. 72(12)
University of Novi Sad (RS), University of Milan (IT), University of Palermo (IT)
Openalex Percentile: Top 28%
Gene Regulatory Network Analysis
0.81
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