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Lag-specific transfer entropy as a tool to assess cardiovascular and cardiorespiratory information transfer

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Abstract
In the study of interacting physiological systems, model-free tools for time series analysis are fundamental to provide a proper description of how the coupling among systems arises from the multiple involved regulatory mechanisms. This study presents an approach which evaluates direction, magnitude, and exact timing of the information transfer between two time series belonging to a multivariate dataset. The approach performs a decomposition of the well-known transfer entropy (TE) which achieves 1) identifying, according to a lag-specific information-theoretic formulation of the concept of Granger causality, the set of time lags associated with significant information transfer, and 2) assigning to these delays an amount of information transfer such that the total contribution yields the aggregate TE. The approach is first validated on realizations of simulated linear and nonlinear multivariate processes interacting at different time lags and with different strength, reporting a high accuracy in the detection of imposed delays, and showing that the estimated lag-specific TE follows the imposed coupling strength. The subsequent application to heart period, systolic arterial pressure and respiration variability series measured from healthy subjects during a tilt test protocol illustrated how the proposed approach quantifies the modifications in the involvement and latency of important mechanisms of short-term physiological regulation, like the baroreflex and the respiratory sinus arrhythmia, induced by the orthostatic stress.
Keywords
Autonomic nervous system, cardiovascular control, conditional entropy (CE), dynamical systems, Granger causality, multivariate time series, mutual information, SYSTOLIC ARTERIAL-PRESSURE, HEART-RATE, VARIABILITY SERIES, TIME-SERIES, HUMANS, OSCILLATIONS, RESPIRATION, MECHANISMS, CAUSALITY, PERIOD

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Citation

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MLA
Faes, Luca, Daniele Marinazzo, Alessandro Montalto, et al. “Lag-specific Transfer Entropy as a Tool to Assess Cardiovascular and Cardiorespiratory Information Transfer.” IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING 61.10 (2014): 2556–2568. Print.
APA
Faes, L., Marinazzo, D., Montalto, A., & Nollo, G. (2014). Lag-specific transfer entropy as a tool to assess cardiovascular and cardiorespiratory information transfer. IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING, 61(10), 2556–2568.
Chicago author-date
Faes, Luca, Daniele Marinazzo, Alessandro Montalto, and Giandomenico Nollo. 2014. “Lag-specific Transfer Entropy as a Tool to Assess Cardiovascular and Cardiorespiratory Information Transfer.” Ieee Transactions on Biomedical Engineering 61 (10): 2556–2568.
Chicago author-date (all authors)
Faes, Luca, Daniele Marinazzo, Alessandro Montalto, and Giandomenico Nollo. 2014. “Lag-specific Transfer Entropy as a Tool to Assess Cardiovascular and Cardiorespiratory Information Transfer.” Ieee Transactions on Biomedical Engineering 61 (10): 2556–2568.
Vancouver
1.
Faes L, Marinazzo D, Montalto A, Nollo G. Lag-specific transfer entropy as a tool to assess cardiovascular and cardiorespiratory information transfer. IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING. 2014;61(10):2556–68.
IEEE
[1]
L. Faes, D. Marinazzo, A. Montalto, and G. Nollo, “Lag-specific transfer entropy as a tool to assess cardiovascular and cardiorespiratory information transfer,” IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING, vol. 61, no. 10, pp. 2556–2568, 2014.
@article{5717882,
  abstract     = {In the study of interacting physiological systems, model-free tools for time series analysis are fundamental to provide a proper description of how the coupling among systems arises from the multiple involved regulatory mechanisms. This study presents an approach which evaluates direction, magnitude, and exact timing of the information transfer between two time series belonging to a multivariate dataset. The approach performs a decomposition of the well-known transfer entropy (TE) which achieves 1) identifying, according to a lag-specific information-theoretic formulation of the concept of Granger causality, the set of time lags associated with significant information transfer, and 2) assigning to these delays an amount of information transfer such that the total contribution yields the aggregate TE. The approach is first validated on realizations of simulated linear and nonlinear multivariate processes interacting at different time lags and with different strength, reporting a high accuracy in the detection of imposed delays, and showing that the estimated lag-specific TE follows the imposed coupling strength. The subsequent application to heart period, systolic arterial pressure and respiration variability series measured from healthy subjects during a tilt test protocol illustrated how the proposed approach quantifies the modifications in the involvement and latency of important mechanisms of short-term physiological regulation, like the baroreflex and the respiratory sinus arrhythmia, induced by the orthostatic stress.},
  author       = {Faes, Luca and Marinazzo, Daniele and Montalto, Alessandro and Nollo, Giandomenico},
  issn         = {0018-9294},
  journal      = {IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING},
  keywords     = {Autonomic nervous system,cardiovascular control,conditional entropy (CE),dynamical systems,Granger causality,multivariate time series,mutual information,SYSTOLIC ARTERIAL-PRESSURE,HEART-RATE,VARIABILITY SERIES,TIME-SERIES,HUMANS,OSCILLATIONS,RESPIRATION,MECHANISMS,CAUSALITY,PERIOD},
  language     = {eng},
  number       = {10},
  pages        = {2556--2568},
  title        = {Lag-specific transfer entropy as a tool to assess cardiovascular and cardiorespiratory information transfer},
  url          = {http://dx.doi.org/10.1109/TBME.2014.2323131},
  volume       = {61},
  year         = {2014},
}

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