title: Predictability decomposition detects the impairment of brain-heart dynamical networks during sleep disorders and their recovery with treatment.
abstract: This work introduces a framework to study the network formed by the autonomic component of heart rate variability (cardiac processη) and the amplitude of the different electroencephalographic waves (brain processes δ, θ, α, σ, β) during sleep. The framework exploits multivariate linear models to decompose the predictability of any given target process into measures of self-, causal and interaction predictability reflecting respectively the information retained in the process and related to its physiological complexity, the information transferred from the other source processes, and the information modified during the transfer according to redundant or synergistic interaction between the sources. The framework is here applied to theη,δ,θ,α,σ,βtime series measured from the sleep recordings of eight severe sleep apnoea-hypopnoea syndrome (SAHS) patients studied before and after long-term treatment with continuous positive airway pressure (CPAP) therapy, and 14 healthy controls. Results show that the full and self-predictability of η, δ and θ decreased significantly in SAHS compared with controls, and were restored with CPAP forδandθbut not forη The causal predictability of η and δ occurred through significantly redundant source interaction during healthy sleep, which was lost in SAHS and recovered after CPAP. These results indicate that predictability analysis is a viable tool to assess the modifications of complexity and causality of the cerebral and cardiac processes induced by sleep disorders, and to monitor the restoration of the neuroautonomic control of these processes during long-term treatment.
authors.affiliation: Biotech, Department of Industrial Engineering, University of Trento, Trento, Italy IRCS Program, PAT-FBK Trento, Italy faes.luca@gmail.com.
authors.forename: Luca
authors.identifier: http://orcid.org/0000-0002-3271-5348
authors.initials: L
authors.lastname: Faes
authors.affiliation: Department of Data Analysis, University of Ghent, Ghent, Belgium.
authors.forename: Daniele
authors.identifier: http://orcid.org/0000-0002-9803-0122
authors.initials: D
authors.lastname: Marinazzo
authors.affiliation: Department of Physics, University of Bari, Bari, Italy INFN Sezione di Bari, Bari, Italy.
authors.forename: Sebastiano
authors.initials: S
authors.lastname: Stramaglia
authors.affiliation: Sleep Laboratory, Department of Psychiatry, ULB-Erasme Academic Hospital, Brussels, Belgium.
authors.forename: Fabrice
authors.initials: F
authors.lastname: Jurysta
authors.affiliation: Department of Biomedical Sciences for Health, University of Milan, Milan, Italy Department of Cardiothoracic, Vascular Anesthesia and Intensive Care, IRCCS Policlinico San Donato, San Donato Milanese, Milan, Italy.
authors.forename: Alberto
authors.identifier: http://orcid.org/0000-0002-6720-9824
authors.initials: A
authors.lastname: Porta
authors.affiliation: Biotech, Department of Industrial Engineering, University of Trento, Trento, Italy IRCS Program, PAT-FBK Trento, Italy.
authors.forename: Nollo
authors.initials: N
authors.lastname: Giandomenico
mesh_terms: D001921:Brain
keywords: Granger causality; autonomic nervous system; brain–heart interactions; delta sleep electroencephalogram; heart rate variability; synergy and redundancy