Cardiovascular control and time domain Granger causality: insights from selective autonomic blockade

We studied causal relations among heart period (HP), systolic arterial pressure (SAP) and respiration (R) according to the definition of Granger causality in the time domain. Autonomic pharmacological challenges were used to alter the complexity of cardiovascular control. Atropine (AT), propranolol and clonidine (CL) were administered to block muscarinic receptors, β-adrenergic receptors and centrally sympathetic outflow, respectively. We found that: (i) at baseline, HP and SAP interacted in a closed loop with a dominant causal direction from HP to SAP; (ii) pharmacological blockades did not alter the bidirectional closed-loop interactions between HP and SAP, but AT reduced the dominance of the causal direction from HP to SAP; (iii) at baseline, bidirectional interactions between HP and R were frequently found; (iv) the closed-loop relation between HP and R was unmodified by the administration of drugs; (v) at baseline, unidirectional interactions from R to SAP were often found; and (vi) while AT induced frequently an uncoupling between R and SAP, CL favoured bidirectional interactions. These results prove that time domain measures of Granger causality can contribute to the description of cardiovascular control by suggesting the temporal direction of the interactions and by separating different causality schemes (e.g. closed loop versus unidirectional relations).

[1]  Petre Stoica,et al.  Decentralized Control , 2018, The Control Systems Handbook.

[2]  J Strackee,et al.  Hemodynamic fluctuations and baroreflex sensitivity in humans: a beat-to-beat model. , 1987, The American journal of physiology.

[3]  J. Taylor,et al.  Short‐term cardiovascular oscillations in man: measuring and modelling the physiologies , 2002, The Journal of physiology.

[4]  A. Guz,et al.  Within‐breath modulation of left ventricular function during normal breathing and positive‐pressure ventilation in man. , 1993, The Journal of physiology.

[5]  A. Patzak,et al.  Blunted arterial baroreflex causes "pathological" heart rate turbulence. , 2000, American journal of physiology. Regulatory, integrative and comparative physiology.

[6]  C. Grebogi,et al.  Inference of Granger causal time-dependent influences in noisy multivariate time series , 2012, Journal of Neuroscience Methods.

[7]  C. Granger Investigating Causal Relations by Econometric Models and Cross-Spectral Methods , 1969 .

[8]  D. Eckberg,et al.  The human respiratory gate. , 2003, The Journal of physiology.

[9]  N. A. Coulter,et al.  Respiratory sinus arrhythmia: a frequency dependent phenomenon , 1964 .

[10]  Fumiyasu Yamasaki,et al.  Artificial Baroreflex: Clinical Application of a Bionic Baroreflex System , 2006, Circulation.

[11]  M. H. Perrott,et al.  An efficient approach to ARMA modeling of biological systems with multiple inputs and delays , 1996, IEEE Transactions on Biomedical Engineering.

[12]  K. Yana,et al.  A time domain approach for the fluctuation analysis of heart rate related to instantaneous lung volume , 1993, IEEE Transactions on Biomedical Engineering.

[13]  A. Malliani,et al.  Heart rate variability. Standards of measurement, physiological interpretation, and clinical use , 1996 .

[14]  Masaru Sugimachi,et al.  Input-size dependence of the baroreflex neural arc transfer characteristics. , 2003, American journal of physiology. Heart and circulatory physiology.

[15]  Milan Palus,et al.  Direction of coupling from phases of interacting oscillators: an information-theoretic approach. , 2003, Physical review. E, Statistical, nonlinear, and soft matter physics.

[16]  J. Taylor,et al.  Probing the arterial baroreflex: is there a ‘spontaneous’ baroreflex? , 2006, Clinical Autonomic Research.

[17]  A. Porta,et al.  Causal relationships between heart period and systolic arterial pressure during graded head-up tilt. , 2011, American journal of physiology. Regulatory, integrative and comparative physiology.

[18]  R. Hughson,et al.  Spontaneous cardiac baroreflex in humans. Comparison with drug-induced responses. , 1995, Hypertension.

[19]  A. Malliani,et al.  Model for the assessment of heart period and arterial pressure variability interactions and of respiration influences , 1994, Medical and Biological Engineering and Computing.

[20]  Giuseppe Baselli,et al.  Prediction of short cardiovascular variability signals based on conditional distribution , 2000, IEEE Transactions on Biomedical Engineering.

[21]  D. Jordan,et al.  Synaptic mechanisms involved in the inspiratory modulation of vagal cardio‐inhibitory neurones in the cat. , 1984, The Journal of physiology.

[22]  J. Saul,et al.  Transfer function analysis of autonomic regulation. I. Canine atrial rate response. , 1989, The American journal of physiology.

[23]  L. Faes,et al.  A framework for assessing frequency domain causality in physiological time series with instantaneous effects , 2013, Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences.

[24]  A. Porta,et al.  Accounting for Respiration is Necessary to Reliably Infer Granger Causality From Cardiovascular Variability Series , 2012, IEEE Transactions on Biomedical Engineering.

[25]  H. Robbe,et al.  Assessment of baroreceptor reflex sensitivity by means of spectral analysis. , 1987, Hypertension.

[26]  G. Breithardt,et al.  Heart rate variability: standards of measurement, physiological interpretation and clinical use. Task Force of the European Society of Cardiology and the North American Society of Pacing and Electrophysiology. , 1996 .

[27]  D L Eckberg,et al.  Temporal response patterns of the human sinus node to brief carotid baroreceptor stimuli. , 1976, The Journal of physiology.

[28]  D. Chicharro,et al.  On the spectral formulation of Granger causality , 2011, Biological Cybernetics.

[29]  P. Reddy,et al.  Respiratory sinus arrhythmia in the denervated human heart. , 1989, Journal of applied physiology.

[30]  A. Porta,et al.  Model-based assessment of baroreflex and cardiopulmonary couplings during graded head-up tilt , 2012, Comput. Biol. Medicine.

[31]  S Cerutti,et al.  Evaluation of respiratory influences on left ventricular function parameters extracted from echocardiographic acoustic quantification. , 2000, Physiological measurement.

[32]  L. Quintin,et al.  Cardioinhibitory actions of clonidine assessed by cardiac vagal motoneuron recordings , 2008, Journal of hypertension.

[33]  J. B. Kernan,et al.  An Information‐Theoretic Approach* , 1971 .

[34]  G. Parati,et al.  Scale exponents of blood pressure and heart rate during autonomic blockade as assessed by detrended fluctuation analysis , 2011, The Journal of physiology.

[35]  Niels Wessel,et al.  Short-term couplings of the cardiovascular system in pregnant women suffering from pre-eclampsia , 2010, Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences.

[36]  A. Porta,et al.  Assessing Causal Interactions among Cardiovascular Variability Series through a Time-Domain Granger Causality Approach , 2014 .

[37]  Luca Faes,et al.  Exploring directionality in spontaneous heart period and systolic pressure variability interactions in humans: implications in the evaluation of baroreflex gain. , 2005, American journal of physiology. Heart and circulatory physiology.

[38]  R J Cohen,et al.  System identification of closed-loop cardiovascular control: effects of posture and autonomic blockade. , 1997, The American journal of physiology.

[39]  J. Taylor,et al.  Spontaneous Indices Are Inconsistent With Arterial Baroreflex Gain , 2003, Hypertension.

[40]  A Pedotti,et al.  Advancements in estimating baroreflex function. , 2001, IEEE engineering in medicine and biology magazine : the quarterly magazine of the Engineering in Medicine & Biology Society.

[41]  K. Hlavácková-Schindler,et al.  Causality detection based on information-theoretic approaches in time series analysis , 2007 .

[42]  W. Hesse,et al.  The use of time-variant EEG Granger causality for inspecting directed interdependencies of neural assemblies , 2003, Journal of Neuroscience Methods.

[43]  A. Malliani,et al.  Changes in Autonomic Regulation Induced by Physical Training in Mild Hypertension , 1988, Hypertension.

[44]  G. Moody,et al.  Clinical Validation of the ECG-Derived Respiration (EDR) Technique , 2008 .

[45]  M. Eriksen,et al.  Respiration‐synchronous fluctuations in stroke volume, heart rate and arterial pressure in humans. , 1993, The Journal of physiology.

[46]  Raffaello Furlan,et al.  Quantifying the strength of the linear causal coupling in closed loop interacting cardiovascular variability signals , 2002, Biological Cybernetics.

[47]  H. P. Koepchen,et al.  Physiology of Rhythms and Control Systems: An Integrative Approach , 1991 .

[48]  G. Pickering,et al.  Reflex Regulation of Arterial Pressure during Sleep in Man: A Quantitative Method of Assessing Baroreflex Sensitivity , 1969, Circulation research.

[49]  L. Faes,et al.  Information-based detection of nonlinear Granger causality in multivariate processes via a nonuniform embedding technique. , 2011, Physical review. E, Statistical, nonlinear, and soft matter physics.

[50]  H. Stauss,et al.  Frequency response characteristics of sympathetically mediated vasomotor waves in humans. , 1998, American journal of physiology. Heart and circulatory physiology.

[51]  G. Baselli,et al.  Spectral decomposition in multichannel recordings based on multivariate parametric identification , 1997, IEEE Transactions on Biomedical Engineering.

[52]  J. Saul,et al.  Transfer function analysis of autonomic regulation. II. Respiratory sinus arrhythmia. , 1989, The American journal of physiology.

[53]  H. Akaike A new look at the statistical model identification , 1974 .

[54]  C. Granger Investigating causal relations by econometric models and cross-spectral methods , 1969 .

[55]  M. Hakumäki Seventy years of the Bainbridge reflex. , 1987, Acta physiologica Scandinavica.

[56]  J. Saul,et al.  Transfer function analysis of the circulation: unique insights into cardiovascular regulation. , 1991, The American journal of physiology.

[57]  D. Randall,et al.  First-order differential-delay equation for the baroreflex predicts the 0.4-Hz blood pressure rhythm in rats. , 1997, American journal of physiology. Regulatory, integrative and comparative physiology.

[58]  Luca Faes,et al.  Evidence of unbalanced regulatory mechanism of heart rate and systolic pressure after acute myocardial infarction. , 2002, American journal of physiology. Heart and circulatory physiology.

[59]  F R Calaresu,et al.  Frequency response model of vagal control of heart rate in the cat. , 1971, The American journal of physiology.