title: Quantifying Net Synergy/Redundancy of Spontaneous Variability Regulation via Predictability and Transfer Entropy Decomposition Frameworks.
abstract: Objective:Indexes assessing the balance between redundancy and synergy were hypothesized to be helpful in characterizing cardiovascular control from spontaneous beat-to-beat variations of heart period (HP), systolic arterial pressure (SAP), and respiration (R).Methods:Net redundancy/synergy indexes were derived according to predictability and transfer entropy decomposition strategies via a multivariate linear regression approach. Indexes were tested in two protocols inducing modifications of the cardiovascular regulation via baroreflex loading/unloading (i.e., head-down tilt at -25° and graded head-up tilt at 15°, 30°, 45°, 60°, 75°, and 90°, respectively). The net redundancy/synergy of SAP and R to HP and of HP and R to SAP were estimated over stationary sequences of 256 successive values.Results:We found that: 1) regardless of the target (i.e., HP or SAP) redundancy was prevalent over synergy and this prevalence was independent of type and magnitude of the baroreflex challenge; 2) the prevalence of redundancy disappeared when decoupling inputs from output via a surrogate approach; 3) net redundancy was under autonomic control given that it varied in proportion to the vagal withdrawal during graded head-up tilt; and 4) conclusions held regardless of the decomposition strategy.Conclusion:Net redundancy indexes can monitor changes of cardiovascular control from a perspective completely different from that provided by more traditional univariate and multivariate methods.Significance:Net redundancy measures might provide a practical tool to quantify the reservoir of effective cardiovascular regulatory mechanisms sharing causal influences over a target variable.Objective:Indexes assessing the balance between redundancy and synergy were hypothesized to be helpful in characterizing cardiovascular control from spontaneous beat-to-beat variations of heart period (HP), systolic arterial pressure (SAP), and respiration (R).Methods:Net redundancy/synergy indexes were derived according to predictability and transfer entropy decomposition strategies via a multivariate linear regression approach. Indexes were tested in two protocols inducing modifications of the cardiovascular regulation via baroreflex loading/unloading (i.e., head-down tilt at -25° and graded head-up tilt at 15°, 30°, 45°, 60°, 75°, and 90°, respectively). The net redundancy/synergy of SAP and R to HP and of HP and R to SAP were estimated over stationary sequences of 256 successive values.Results:We found that: 1) regardless of the target (i.e., HP or SAP) redundancy was prevalent over synergy and this prevalence was independent of type and magnitude of the baroreflex challenge; 2) the prevalence of redundancy disappeared when decoupling inputs from output via a surrogate approach; 3) net redundancy was under autonomic control given that it varied in proportion to the vagal withdrawal during graded head-up tilt; and 4) conclusions held regardless of the decomposition strategy.Conclusion:Net redundancy indexes can monitor changes of cardiovascular control from a perspective completely different from that provided by more traditional univariate and multivariate methods.Significance:Net redundancy measures might provide a practical tool to quantify the reservoir of effective cardiovascular regulatory mechanisms sharing causal influences over a target variable.
authors.affiliation: Department of Biomedical Sciences for Health, University of Milan, Milan 20122, Italy.
authors.forename: Alberto
authors.initials: A
authors.lastname: Porta
authors.affiliation: Department of Cardiothoracic, Vascular Anesthesia and Intensive Care, IRCCS Policlinico San Donato, San Donato Milanese, Milan, Italy.
authors.forename: Vlasta
authors.initials: V
authors.lastname: Bari
authors.affiliation: IRCCS Istituti Clinici Scientifici Maugeri, Istituto di Milano, Milan, Italy.
authors.forename: Beatrice
authors.initials: B
authors.lastname: De Maria
authors.affiliation: Department of Physiotherapy, Federal University of São Carlos, São Carlos, Brazil.
authors.forename: Anielle C M
authors.initials: ACM
authors.lastname: Takahashi
authors.affiliation: Department of Emergency, L. Sacco Hospital, Milan, Italy.
authors.forename: Stefano
authors.initials: S
authors.lastname: Guzzetti
authors.affiliation: Department of Emergency, L. Sacco Hospital, Milan, Italy.
authors.forename: Riccardo
authors.initials: R
authors.lastname: Colombo
authors.affiliation: Department of Physiotherapy, Federal University of São Carlos, São Carlos, Brazil.
authors.forename: Aparecida M
authors.initials: AM
authors.lastname: Catai
authors.affiliation: Department of Anesthesia and Intensive Care, IRCCS Humanitas Clinical and Research Center, Rozzano, Italy.
authors.forename: Ferdinando
authors.initials: F
authors.lastname: Raimondi
authors.affiliation: BIOtech, Department of Industrial Engineering, University of Trento, Trento, Italy.
authors.forename: Luca
authors.initials: L
authors.lastname: Faes
mesh_terms: D000328:Adult; D001341:Autonomic Nervous System / Q000502:physiology*; D017704:Baroreflex; D001794:Blood Pressure / Q000502:physiology; D004562:Electrocardiography; D019277:Entropy; D005260:Female; D018475:Head-Down Tilt / Q000502:physiology; D006339:Heart Rate / Q000502:physiology*; D006801:Humans; D008297:Male; D008875:Middle Aged; D015233:Models, Statistical; D012815:Signal Processing, Computer-Assisted; D055815:Young Adult
keywords: Biomedical measurement; Computational modeling; Entropy; Indexes; Measurement uncertainty; Redundancy; Uncertainty