Comparison of frequency domain measures based on spectral decomposition for spontaneous baroreflex sensitivity assessment after Acute Myocardial Infarction. - Riccardo Pernice; Laura Sparacino; Giandomenico Nollo; Salvatore Stivala; Alessandro Busacca; Luca Faes (Biomed. Signal Process. Control., 2021)

Quantifying High-Order Interactions in Complex Physiological Networks: A Frequency-Specific Approach. - Laura Sparacino; Yuri Antonacci; Daniele Marinazzo; Sebastiano Stramaglia; Luca Faes (COMPLEX NETWORKS (1), 2022)

Assessing High-Order Interdependencies Through Static O-Information Measures Computed on Resting State fMRI Intrinsic Component Networks. - Simone Valenti; Laura Sparacino; Riccardo Pernice; Daniele Marinazzo; Hannes Almgren; Albert Comelli; Luca Faes (ICIAP Workshops (1), 2022)

A portable multisensor system to assess cardiorespiratory interactions through photoplethysmography. - Gabriele Volpes; Laura Sparacino; Simone Valenti; Antonino Parisi; Alessandro Busacca; Luca Faes; Riccardo Pernice (MeMeA, 2022)

A New Framework for the Time- and Frequency-Domain Assessment of High-Order Interactions in Networks of Random Processes. - Luca Faes; Gorana Mijatovic; Yuri Antonacci; Riccardo Pernice; Chiara Barà; Laura Sparacino; Marco Sammartino; Alberto Porta; Daniele Marinazzo; Sebastiano Stramaglia (IEEE Trans. Signal Process., 2022)

Investigating Dynamic High-Order Interactions in Physiological Networks through Predictive Information Decomposition. - Luca Faes; Gorana Mijatovic; Laura Sparacino; Yuri Antonacci; Daniele Marinazzo; Sebastiano Stramaglia (EMBC, 2023)

Statistical Approaches to Characterize Functional Connectivity in Brain and Physiologic Networks on a Single-Subject Basis. - Laura Sparacino; Martina Valentino; Yuri Antonacci; Giuseppe Parla; Gianvincenzo Sparacia; Luca Faes (EMBC, 2023)

A Method to Assess Granger Causality, Isolation and Autonomy in the Time and Frequency Domains: Theory and Application to Cerebrovascular Variability. - Laura Sparacino; Yuri Antonacci; Chiara Barà; Angela Valenti; Alberto Porta; Luca Faes (IEEE Trans. Biomed. Eng., 2024)

Measuring hierarchically-organized interactions in dynamic networks through spectral entropy rates: Theory, estimation, and illustrative application to physiological networks. - Laura Sparacino; Yuri Antonacci; Gorana Mijatovic; Luca Faes (Neurocomputing, 2025)

Decomposing Multivariate Information Rates in Networks of Random Processes. - Laura Sparacino; Gorana Mijatovic; Yuri Antonacci; Leonardo Ricci; Daniele Marinazzo; Sebastiano Stramaglia; Luca Faes (CoRR, 2025)

Spectral Information Dynamics of Cortical Signals Uncover the Hierarchical Organization of the Human Brain's Motor Network. - Yuri Antonacci; Chiara Barà; Laura Sparacino; Ileana Pirovano; Alfonso Mastropietro; Giovanna Rizzo; Luca Faes (IEEE Trans. Biomed. Eng., 2025)