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IEEE Transactions on Bio-Medical Engineering|December 6, 2023
A Method to Assess Granger Causality, Isolation and Autonomy in the Time and Frequency Domains: Theory and Application to Cerebrovascular VariabilityLaura Sparacino, Yuri Antonacci, Chiara Bara, et al.
Medical & Biological Engineering & Computing|April 24, 2016
Causal analysis of short-term cardiovascular variability: state-dependent contribution of feedback and feedforward mechanismsMichal Javorka, Barbora Czippelova, Zuzana Turianikova, et al.
Journal of Neural Engineering|October 21, 2025
A method for the time-frequency analysis of high-order interactions in non-stationary physiological networksYuri Antonacci, Chiara Bará, Laura Sparacino, et al.
Physiological Measurement|June 19, 2026
Dissecting the integrated information of cardiovascular and cardiorespiratory systems at rest and during physiological stressIrene Franzone, Roberta Saputo, Yuri Antonacci, et al.
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference|December 12, 2023
Statistical Approaches to Characterize Functional Connectivity in Brain and Physiologic Networks on a Single-Subject BasisLaura Sparacino, Martina Valentino, Yuri Antonacci, et al.
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference|December 12, 2023
Investigating Dynamic High-Order Interactions in Physiological Networks through Predictive Information DecompositionLuca Faes, Gorana Mijatovic, Laura Sparacino, et al.
Frontiers in Network Physiology|April 19, 2024
A method to assess linear self-predictability of physiologic processes in the frequency domain: application to beat-to-beat variability of arterial complianceLaura Sparacino, Yuri Antonacci, Chiara Barà, et al.
Physical Review. E|April 18, 2025
Assessing high-order effects in feature importance via predictability decompositionMarlis Ontivero-Ortega, Luca Faes, Jesus M Cortes, et al.
Neural Networks : the Official Journal of the International Neural Network Society|September 11, 2015
Neural networks with non-uniform embedding and explicit validation phase to assess Granger causalityAlessandro Montalto, Sebastiano Stramaglia, Luca Faes, et al.
Philosophical Transactions. Series A, Mathematical, Physical, and Engineering Sciences|October 25, 2021
Extending the spectral decomposition of Granger causality to include instantaneous influences: application to the control mechanisms of heart rate variabilityD Nuzzi, S Stramaglia, M Javorka, et al.
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