On the validity of the state space correspondence strategy based on k-nearest neighbor cross-predictability in assessing directionality in stochastic systems: Application to cardiorespiratory coupling estimation.

We tested the validity of the state space correspondence (SSC) strategy based on k-nearest neighbor cross-predictability (KNNCP) to assess the directionality of coupling in stochastic nonlinear bivariate autoregressive (NBAR) processes. The approach was applied to assess closed-loop cardiorespiratory interactions between heart period (HP) variability and respiration (R) during a controlled respiration (CR) protocol in 19 healthy humans (aged from 27 to 35 yrs, 11 females) and during active standing (STAND) in 25 athletes (aged from 20 to 40 yrs, all men) and 25 non-athletes (aged from 20 to 40 yrs, all men). Over simulated NBAR processes, we found that (i) the SSC approach can detect the correct causal relationship as the direction leads to better KNNCP from the past of the driver to the future state of the target and (ii) simulations suggest that the ability of the method is preserved in any condition of complexity of the interacting series. Over CR and STAND protocols, we found that (a) slowing the breathing rate increases the strength of the causal relationship in both temporal directions in a balanced modality; (b) STAND is more powerful in modulating the coupling strength on the pathway from HP to R; (c) regardless of protocol and experimental condition, the strength of the link from HP to R is stronger than that from R to HP; (d) significant causal relationships in both temporal directions are found regardless of the level of complexity of HP variability and R. The SSC strategy is useful to disentangle closed-loop cardiorespiratory interactions.

Autonomic Function and Baroreflex Control in COVID-19 Patients Admitted to the Intensive Care Unit.

Background: Autonomic function and baroreflex control might influence the survival rate of coronavirus disease 2019 (COVID-19) patients admitted to the intensive care unit (ICU) compared to respiratory failure patients without COVID-19 (non-COVID-19). This study describes physiological control mechanisms in critically ill COVID-19 patients admitted to the ICU in comparison to non-COVID-19 individuals with the aim of improving stratification of mortality risk. Methods: We evaluated autonomic and baroreflex control markers extracted from heart period (HP) and systolic arterial pressure (SAP) variability acquired at rest in the supine position (REST) and during a modified head-up tilt (MHUT) in 17 COVID-19 patients (age: 63 ± 10 years, 14 men) and 33 non-COVID-19 patients (age: 60 ± 12 years, 23 men) during their ICU stays. Patients were categorized as survivors (SURVs) or non-survivors (non-SURVs). Results: We found that COVID-19 and non-COVID-19 populations exhibited similar vagal and sympathetic control markers; however, non-COVID-19 individuals featured a smaller baroreflex sensitivity and an unexpected reduction in the HP-SAP association during the MHUT compared to the COVID-19 group. Nevertheless, none of the markers of the autonomic and baroreflex functions could distinguish SURVs from non-SURVs in either population. Conclusions: We concluded that COVID-19 patients exhibited a more preserved baroreflex control compared to non-COVID-19 individuals, even though this information is ineffective in stratifying mortality risk.

Cardiac autonomic profile, perceived stress and environmental comfort in healthy employees during remote and in-office work.

Remote work (REMOTE) causes an overlap between working and domestic demands. The study of the cardiac autonomic profile (CAP) by means of heart rate variability (HRV) provides information about the impact of REMOTE on workers' health. The primary aim was to determine whether CAP, self-perceived stress, environmental and workstation comfort are modified during REMOTE. The secondary aim was to explore how these indices are influenced by individual and environmental work-related factors. Fifty healthy office employees alternating REMOTE and in-office (OFFICE) working were enrolled, rated self-perceived stress, environmental and workstation comfort using a visual analogue scale and performed a 24-h electrocardiogram during REMOTE and OFFICE. Stress was lower (5.6 ± 2.2 vs. 6.4 ± 1.8), environmental comfort higher (7.7 ± 1.9 vs. 7.0 ± 1.5), and the workstation comfort poorer (6.2 ± 1.8 vs. 7.5 ± 1.2) during REMOTE. CAP was similar during REMOTE and OFFICE. CAP was influenced by some work-related factors, including the presence of offspring, absence of a dedicated workspace during REMOTE and number of working hours. All these variables determined a decreased vagal modulation. The working setting seems to impact the levels of perceived stress and comfort, but not the CAP. However, individual and environmental work-related factors reduce cardiac vagal modulation during REMOTE, potentially increasing the risk of developing cardiovascular diseases.

Cardiorespiratory coupling is associated with exercise capacity in athletes: A cross-sectional study.

PURPOSE: To determine the association between exercise capacity based on peak oxygen uptake (VO2peak) and resting cardiorespiratory coupling (CRC) levels in athletes and non-athletes' subjects. METHODS: A cross-sectional study was carried out in 42 apparently healthy male subjects, aged between 20 and 40 years old. The participants were allocated into athletes (n = 21) and non-athletes (n = 21) groups. Resting electrocardiogram and respiratory movement (RESP) were simultaneously acquired during 15 min in supine position and quiet breathing. The beat-to-beat heart period (HP) and RESP series were determined from the recorded signals. Traditional analysis of HP based on frequency domain indexes was performed considering the high-frequency (0.15 - 0.45 Hz) components. To compute the CRC, the linear association between HP and RESP series was determined via squared coherence function and directionality of interaction was investigated through the causal extension of this approach. The exercise capacity was assessed through incremental cardiopulmonary exercise testing in order to determine the VO2peak. RESULTS: Traditional analysis of HP based on high-frequency index was not correlated with exercise capacity in the athletes (r = -0.1, p = 0.5) and non-athletes (r = -0.1, p = 0.3) cohorts. However, resting CRC values was associated with exercise capacity in athletes (r = 0.4, p = 0.03), but not in the non-athletes group (r = -0.2, p = 0.3). CONCLUSION: These results suggest that improved resting values of CRC is associated with higher exercise capacity (VO2peak) in endurance athletes. Moreover, frequency domain of HP was not sensitive to identifying this relationship, probably because effects of training on parasympathetic modulation might be affected by respiratory dynamics, and this influence has a directionality (i.e., from RESP to HP).

Link Between Cardiovascular and Cerebrovascular Controls in Patients Undergoing Surgical Aortic Valve Replacement.

Although the autonomic influence on cardiovascular (CV) and cerebrovascular (CBV) regulations has been widely recognized, their relationship is poorly explored especially in pathological situations. This study investigates the correlation between CV and CBV markers in 73 patients (48 males, age 63.6±13.1 yrs) undergoing surgical aortic valve replacement (SAVR) evaluated before the intervention (PRE), within 1-week post-surgery (POST) and after a 3-month follow-up (POST3). Patients were acquired before and after an orthostatic challenge. Frequency domain analysis assessing transfer function gain (TFG), phase (Ph), and squared coherence (K2) between heart period and systolic arterial pressure was exploited to evaluate CV control. The same frequency domain functions were derived to assess CBV regulation from mean cerebral blood velocity and mean arterial pressure. A correlation analysis between indexes of CV and CBV controls was carried out. Results showed that CV control was impaired in PRE, worsened in POST, and recovered in POST3, while CBV markers were almost unchanged. A significant positive relationship between CV and CBV markers was observed, especially in POST and POST3, thus suggesting that the compensation of a baroreflex impairment with a more efficient CBV control and vice versa. The maintenance of this relationship between CV and CBV controls in patients undergoing SAVR could be fundamental to prevent risky situations.Clinical Relevance- After surgical aortic valve replacement an impaired baroreflex control could be compensated by a more efficient cerebral autoregulation.

On the Validity of Single Regression Strategy for Granger Causality Assessment in Cardiovascular and Cardiorespiratory Control Studies.

Granger causality (GC) analysis is based on the comparison between prediction error variances computed over the full and restricted models after identifying the coefficients of appropriate vector regressions. GC markers can be computed via a double regression (DR) approach identifying two separate, independent models and a single regression (SR) strategy optimizing the description of the dynamics of the target over the full model and, then, reusing some parts of it in the restricted model. The present study compares the SR and DR strategies over heart period (HP), systolic arterial pressure (SAP) and respiration (R) beat-to-beat series collected during a graded orthostatic challenge induced by head-up tilt in 17 healthy individuals (age: 21-36 yrs; median: 29 yrs; 9 females and 8 males). We found that the DR approach was more powerful than the SR one in detecting the expected stronger involvement of the baroreflex during the challenge, while the expected weaker cardiorespiratory coupling was identified by both SR and DR strategies. The less powerful ability of the SR approach was the result of the greater variance of GC markers compared to the DR strategy. We conclude that, contrary to the suggestions present in literature, the SR approach is not necessarily associated with a smaller dispersion of GC markers. Moreover, we suggest that additional factors, such as the strategy utilized to build embedding spaces and metric utilized to compare prediction error variances, might play an important role in differentiating SR and DR approaches.

Characterization of Multiple Regimes of Cardiorespiratory Phase Synchronization in Athletes Undergoing Inspiratory Muscle Training.

Cardiorespiratory phase synchronization (CRPS) is defined as the stable occurrence of n heartbeats within m respiratory cycles according to the n:m phase locking ratio (PLR). Since CRPS is an intermittent phenomenon where different phase synchronization regimes and epochs of phase unlocking can alternate within the same recording, an index of CRPS ideally should assess all potential PLRs present in the recording. However, traditional approaches compute the synchronization index (SYNC%) over a single n:m PLR, namely the one that maximizes CRPS. In the present work, we tested a synchronization index assessing the total percentage of heartbeats coupled to the inspiratory onset regardless of phase locking regimes (SYNC%sum) and we compared its efficacy to the more traditional SYNC%. Analysis was carried out in a cohort of 25 male amateur cyclists (age: 20-40 yrs) undergoing inspiratory muscle training (IMT) at different intensities. CRPS was assessed before and after the IMT protocol, during an experimental condition known to modify CRPS, namely active standing (STAND). We found that after a moderate intensity IMT at 60% of the maximal inspiratory pressure, SYNC%sum could detect the decrease in CRPS following STAND. This result was not visible using the more traditional SYNC%. Therefore, we stress the significant presence of different phase locking regimes in athletes and the importance of accounting for multiple PLRs in CRPS analysis.Clinical Relevance- Multiple phase locking regimes contribute significantly to cardiorespiratory control in amateur cyclists especially after inspiratory muscle training of moderate intensity.

A Method to Assess Granger Causality, Isolation and Autonomy in the Time and Frequency Domains: Theory and Application to Cerebrovascular Variability.

OBJECTIVE: Concepts of Granger causality (GC) and Granger autonomy (GA) are central to assess the dynamics of coupled physiologic processes. While causality measures have been already proposed and largely applied in time and frequency domains, measures quantifying self-dependencies are still limited to the time-domain formulation and lack of a clear spectral representation. METHODS: We embed into the classical linear parametric framework for computing GC from a driver random process X to a target process Y a measure of Granger Isolation (GI) quantifying the part of the dynamics of Y not originating from X, and a new spectral measure of GA assessing frequency-specific patterns of self-dependencies in Y. The framework is formulated in a way such that the full-frequency integration of the spectral GC, GI and GA measures returns the corresponding time-domain measures. The measures are illustrated in theoretical simulations and applied to time series of mean arterial pressure and cerebral blood flow velocity obtained in subjects prone to develop postural syncope and healthy controls. RESULTS: simulations show that GI is complementary to GC but not trivially related to it, while GA reflects the regularity of the internal dynamics of the analyzed target process. In the application to cerebrovascular interactions, spectral GA quantified the physiological response to postural stress of slow cerebral blood flow oscillations, while spectral GC and GI detected an altered response to postural stress in subjects prone to syncope, likely related to impaired cerebral autoregulation. CONCLUSION AND SIGNIFICANCE: The new spectral measures of GI and GA are useful complements to GC for the analysis of interacting oscillatory processes, and detect physiological and pathological responses to postural stress which cannot be traced in the time domain. The thorough assessment of causality, isolation and autonomy opens new perspectives for the analysis of coupled biological processes in both physiological and clinical investigations.

The degree of engagement of cardiac and sympathetic arms of the baroreflex does not depend on the absolute value and sign of arterial pressure variations.

Objective.The percentages of cardiac and sympathetic baroreflex patterns detected via baroreflex sequence (SEQ) technique from spontaneous variability of heart period (HP) and systolic arterial pressure (SAP) and of muscle nerve sympathetic activity (MSNA) burst rate and diastolic arterial pressure (DAP) are utilized to assess the level of the baroreflex engagement. The cardiac baroreflex patterns can be distinguished in those featuring both HP and SAP increases (cSEQ++) and decreases (cSEQ--), while the sympathetic baroreflex patterns in those featuring a MSNA burst rate decrease and a DAP increase (sSEQ+-) and vice versa (sSEQ-+). The present study aims to assess the modifications of the involvement of the cardiac and sympathetic arms of the baroreflex with age and postural stimulus intensity.Approach.We monitored the percentages of cSEQ++ (%cSEQ++) and cSEQ-- (%cSEQ--) in 100 healthy subjects (age: 21-70 years, 54 males, 46 females), divided into five sex-balanced groups consisting of 20 subjects in each decade at rest in supine position and during active standing (STAND). We evaluated %cSEQ++, %cSEQ--, and the percentages of sSEQ+- (%sSEQ+-) and sSEQ-+ (%sSEQ-+) in 12 young healthy subjects (age 23 ± 2 years, 3 females, 9 males) undergoing incremental head-up tilt.Main results.We found that: (i) %cSEQ++ and %cSEQ-- decreased with age and increased with STAND and postural stimulus intensity; (ii) %sSEQ+- and %sSEQ-+ augmented with postural challenge magnitude; (iii) the level of cardiac and sympathetic baroreflex engagement did not depend on either the absolute value of arterial pressure or the direction of its changes.Significance.This study stresses the limited ability of the cardiac and sympathetic arms of the baroreflex in controlling absolute arterial pressure values and the equivalent ability of both positive and negative arterial pressure changes in soliciting them.

Soluble interleukin-1 receptor type 2 plasma levels in Parkinson's disease: relationship with cardiac autonomic profile before and after peripheral mechanical somatosensory stimulation.

Introduction: Systemic inflammation promotes neurodegeneration in Parkinson's disease (PD). Interleukin-1 receptor type 2 (sIL-1R2) plasma levels increase during inflammation. Data on sIL-1R2 in PD patients and its relationship with PD cardiac autonomic profile are limited, given the possible anti-inflammatory effect of vagal activation. Previously, automated mechanical peripheral somatosensory stimulation (AMPSS) enhanced cardiac vagal modulation. Objectives were to 1) evaluate sIL-1R2 plasma concentrations in PD patients and healthy controls and 2) investigate the correlations between sIL-1R2 and cardiac autonomic indices obtained by spectrum analysis of heart rate variability before and after AMPSS. Methods: sIL-1R2 plasma levels were assessed in 48 PD patients and 50 healthy controls. Electrocardiogram and beat-by-beat arterial pressure were recorded at baseline and after 5 AMPSS sessions in 16 PD patients. Results: PD patients had higher sIL-1R2 levels than controls. In the PD subgroup, an inverse correlation between sIL-1R2 and HFnu was found. There was a negative correlation between changes induced by AMPSS on HFnu and sIL-1R2. Discussion: Higher sIL-1R2 levels in PD patients reflect the inflammatory dysregulation associated with the disease. In PD patients, higher sIL-1R2 was associated with reduced cardiovagal tone. Increased cardiovagal modulation following AMPSS was associated with lower sIL-1R2 levels in Parkinson's disease patients, suggesting inflammatory state improvement.

Characterization of cardiovascular and cerebrovascular controls via spectral causality analysis in patients undergoing surgical aortic valve replacement during a three-month follow-up.

Objective.Aortic valve stenosis (AVS) induces left ventricular function adaptations and surgical aortic valve replacement (SAVR) restores blood flow profile across aortic valve. Modifications of cardiac hemodynamics induced by AVS and SAVR might alter cardiovascular (CV) and cerebrovascular (CBV) controls. The study aims at characterizing CV and CBV regulations one day before SAVR (PRE), within one week after SAVR (POST), and after a three-month follow-up (POST3) in 73 AVS patients (age: 63.9 ± 12.9 yrs; 48 males, 25 females) from spontaneous fluctuations of heart period (HP), systolic arterial pressure, mean arterial pressure and mean cerebral blood velocity.Approach.CV and CBV regulations were typified via a bivariate autoregressive approach computing traditional frequency domain markers and causal squared coherence (CK2) from CV and CBV variabilities. Univariate time and frequency domain indexes were calculated as well. Analyses were carried out in frequency bands typical of CV and CBV controls at supine rest and during active standing. A surrogate method was exploited to check uncoupling condition.Main results.We found that: (i) CV regulation is impaired in AVS patients; (ii) CV regulation worsens in POST; (iii) CV regulation recovers in POST3 and CV response to active standing is even better than in PRE; (iv) CBV regulation is preserved in AVS patients; (v) SAVR does not affect CBV control; (vi) parameters of the CBV control in POST3 and PRE are similar.Significance.CK2is particularly useful to characterize CV and CBV controls in AVS patients and to monitor of patient's evolution after SAVR.

Assessing cardiorespiratory interactions via lagged joint symbolic dynamics during spontaneous and controlled breathing.

Introduction: Joint symbolic analysis (JSA) can be utilized to describe interactions between time series while accounting for time scales and nonlinear features. JSA is based on the computation of the rate of occurrence of joint patterns built after symbolization. Lagged JSA (LJSA) is obtained from the more classical JSA by introducing a delay/lead between patterns built over the two series and combined to form the joint scheme, thus monitoring coordinated patterns at different lags. Methods: In the present study, we applied LJSA for the assessment of cardiorespiratory coupling (CRC) from heart period (HP) variability and respiratory activity (R) in 19 healthy subjects (age: 27-35 years; 8 males, 11 females) during spontaneous breathing (SB) and controlled breathing (CB). The R rate of CB was selected to be indistinguishable from that of SB, namely, 15 breaths·minute-1 (CB15), or slower than SB, namely, 10 breaths·minute-1 (CB10), but in both cases, very rapid interactions between heart rate and R were known to be present. The ability of the LJSA approach to follow variations of the coupling strength was tested over a unidirectionally or bidirectionally coupled stochastic process and using surrogate data to test the null hypothesis of uncoupling. Results: We found that: i) the analysis of surrogate data proved that HP and R were significantly coupled in any experimental condition, and coupling was not more likely to occur at a specific time lag; ii) CB10 reduced CRC strength at the fastest time scales while increasing that at intermediate time scales, thus leaving the overall CRC strength unvaried; iii) despite exhibiting similar R rates and respiratory sinus arrhythmia, SB and CB15 induced different cardiorespiratory interactions; iv) no dominant temporal scheme was observed with relevant contributions of HP patterns either leading or lagging R. Discussion: LJSA is a useful methodology to explore HP-R dynamic interactions while accounting for time shifts and scales.

Concomitant evaluation of cardiovascular and cerebrovascular controls via Geweke spectral causality to assess the propensity to postural syncope.

The evaluation of propensity to postural syncope necessitates the concomitant characterization of the cardiovascular and cerebrovascular controls and a method capable of disentangling closed loop relationships and decomposing causal links in the frequency domain. We applied Geweke spectral causality (GSC) to assess cardiovascular control from heart period and systolic arterial pressure variability and cerebrovascular regulation from mean arterial pressure and mean cerebral blood velocity variability in 13 control subjects and 13 individuals prone to develop orthostatic syncope. Analysis was made at rest in supine position and during head-up tilt at 60°, well before observing presyncope signs. Two different linear model structures were compared, namely bivariate autoregressive and bivariate dynamic adjustment classes. We found that (i) GSC markers did not depend on the model structure; (ii) the concomitant assessment of cardiovascular and cerebrovascular controls was useful for a deeper comprehension of postural disturbances; (iii) orthostatic syncope appeared to be favored by the loss of a coordinated behavior between the baroreflex feedback and mechanical feedforward pathway in the frequency band typical of the baroreflex functioning during the postural challenge, and by a weak cerebral autoregulation as revealed by the increased strength of the pressure-to-flow link in the respiratory band. GSC applied to spontaneous cardiovascular and cerebrovascular oscillations is a promising tool for describing and monitoring disturbances associated with posture modification.

Evaluation of cardiovascular and cerebrovascular control mechanisms in postural orthostatic tachycardia syndrome via conditional transfer entropy: the impact of the respiratory signal type.

Objective.Closed loop cardiovascular (CV) and cerebrovascular (CBV) variability interactions are assessed via transfer entropy (TE) from systolic arterial pressure (SAP) to heart period (HP) and vice versa and from mean arterial pressure (MAP) to mean cerebral blood velocity (MCBv) and vice versa. This analysis is exploited to assess the efficiency of baroreflex and cerebral autoregulation. This study aims at characterizing CV and CBV controls in postural orthostatic tachycardiac syndrome (POTS) subjects experiencing exaggerated sympathetic response during orthostatic challenge via unconditional TE and TE conditioned on respiratory activity (R).Approach.In 18 healthy controls (age: 28 ± 13 yrs; 5 males, 13 females) and 15 POTS individuals (age: 29 ± 11 yrs; 3 males, 12 females) we acquired beat-to-beat variability of HP, SAP, MAP and MCBv and twoRsignals, namely respiratory chest movement (RCM) and capnogram (CAP). Recordings were made at sitting rest and during active standing (STAND). TE was computed via vector autoregressive approach.Main results.We found that: (i) when assessing CV interactions, the increase of the TE from SAP to HP during STAND, indicating baroreflex activation, is detected solely when conditioning on RCM; (ii) when assessing CBV interactions, the impact ofRon the TE computation is negligible; (iii) POTS shows baroreflex impairment during STAND; (iv) POTS exhibits a normal CBV response to STAND.Significance.TE is useful for detecting the impairment of specific regulatory mechanisms in POTS. Moreover, using differentRsignals highlights the sensitivity of CV and CBV controls to specificRaspects.

On the Different Abilities of Cross-Sample Entropy and K-Nearest-Neighbor Cross-Unpredictability in Assessing Dynamic Cardiorespiratory and Cerebrovascular Interactions.

Nonlinear markers of coupling strength are often utilized to typify cardiorespiratory and cerebrovascular regulations. The computation of these indices requires techniques describing nonlinear interactions between respiration (R) and heart period (HP) and between mean arterial pressure (MAP) and mean cerebral blood velocity (MCBv). We compared two model-free methods for the assessment of dynamic HP-R and MCBv-MAP interactions, namely the cross-sample entropy (CSampEn) and k-nearest-neighbor cross-unpredictability (KNNCUP). Comparison was carried out first over simulations generated by linear and nonlinear unidirectional causal, bidirectional linear causal, and lag-zero linear noncausal models, and then over experimental data acquired from 19 subjects at supine rest during spontaneous breathing and controlled respiration at 10, 15, and 20 breaths·minute-1 as well as from 13 subjects at supine rest and during 60° head-up tilt. Linear markers were computed for comparison. We found that: (i) over simulations, CSampEn and KNNCUP exhibit different abilities in evaluating coupling strength; (ii) KNNCUP is more reliable than CSampEn when interactions occur according to a causal structure, while performances are similar in noncausal models; (iii) in healthy subjects, KNNCUP is more powerful in characterizing cardiorespiratory and cerebrovascular variability interactions than CSampEn and linear markers. We recommend KNNCUP for quantifying cardiorespiratory and cerebrovascular coupling.

Model-based spectral causality of cardiovascular variability interactions during head-down tilt.

Objective. Cardiovascular control mechanisms are commonly studied during baroreceptor unloading induced by head-up tilt. Conversely, the effect of a baroreceptor loading induced by head-down tilt (HDT) is less studied especially when the stimulus is of moderate intensity and using model-based spectral causality markers. Thus, this study computes model-based causality markers in the frequency domain derived via causal squared coherence and Geweke spectral causality approach from heart period (HP) and systolic arterial pressure (SAP) variability series.Approach. We recorded HP and SAP variability series in 12 healthy men (age: from 41 to 71 yrs, median: 57 yrs) during HDT at -25°. The approaches are compared by considering two different bivariate model structures, namely the autoregressive and dynamic adjustment models. Markers are computed in traditional frequency bands utilized in cardiovascular control analysis, namely the low frequency (LF, from 0.04 to 0.15 Hz) and high frequency (HF, from 0.15 to 0.4 Hz) bands.Main results. We found that: (i) the two spectral causality metrics are deterministically related but spectral causality markers exhibit different discriminative ability; (ii) HDT reduces the involvement of the baroreflex in regulating HP-SAP variability interactions in the LF band, while leaving unmodified the action of mechanical feedforward mechanisms in both LF and HF bands; (iii) this conclusion does not depend on the model structure.Significance. We conclude that HDT can be utilized to reduce the impact of baroreflex and to study the contribution of regulatory mechanisms different from baroreflex to the complexity of cardiovascular control in humans.

Comparison of discretization strategies for the model-free information-theoretic assessment of short-term physiological interactions.

This work presents a comparison between different approaches for the model-free estimation of information-theoretic measures of the dynamic coupling between short realizations of random processes. The measures considered are the mutual information rate (MIR) between two random processes X and Y and the terms of its decomposition evidencing either the individual entropy rates of X and Y and their joint entropy rate, or the transfer entropies from X to Y and from Y to X and the instantaneous information shared by X and Y. All measures are estimated through discretization of the random variables forming the processes, performed either via uniform quantization (binning approach) or rank ordering (permutation approach). The binning and permutation approaches are compared on simulations of two coupled non-identical Hènon systems and on three datasets, including short realizations of cardiorespiratory (CR, heart period and respiration flow), cardiovascular (CV, heart period and systolic arterial pressure), and cerebrovascular (CB, mean arterial pressure and cerebral blood flow velocity) measured in different physiological conditions, i.e., spontaneous vs paced breathing or supine vs upright positions. Our results show that, with careful selection of the estimation parameters (i.e., the embedding dimension and the number of quantization levels for the binning approach), meaningful patterns of the MIR and of its components can be achieved in the analyzed systems. On physiological time series, we found that paced breathing at slow breathing rates induces less complex and more coupled CR dynamics, while postural stress leads to unbalancing of CV interactions with prevalent baroreflex coupling and to less complex pressure dynamics with preserved CB interactions. These results are better highlighted by the permutation approach, thanks to its more parsimonious representation of the discretized dynamic patterns, which allows one to explore interactions with longer memory while limiting the curse of dimensionality.

Changes of the cardiac baroreflex bandwidth during postural challenges.

Baroreflex is commonly typified from heart period (HP) and systolic arterial pressure (SAP) spontaneous variations in the frequency domain mainly by estimating its sensitivity. However, an informative parameter linked to the rapidity of the HP response to SAP changes, such as the baroreflex bandwidth, remains unquantified. We propose a model-based parametric approach for estimating the baroreflex bandwidth from the impulse response function (IRF) of the HP-SAP transfer function (TF). The approach accounts explicitly for the action of mechanisms modifying HP regardless of SAP changes. The method was tested during graded baroreceptor unloading induced by head-up tilt (HUT) at 15°, 30°, 45°, 60°, and 75° (T15, T30, T45, T60, and T75) in 17 healthy individuals (age: 21-36 yr; 9 females and 8 males) and during baroreceptor loading obtained via head-down tilt (HDT) at -25° in 13 healthy men (age: 41-71 yr). The bandwidth was estimated as the decay constant of the monoexponential IRF fitting. The method was robust because the monoexponential fitting described adequately the HP dynamics following an impulse of SAP. We observed that 1) baroreflex bandwidth is reduced during graded HUT and this narrowing is accompanied by the reduction of the bandwidth of mechanisms that modify HP regardless of SAP changes and 2) baroreflex bandwidth is not affected by HDT but that of SAP-unrelated mechanisms becomes wider. This study provides a method for estimating a baroreflex feature that provides different information compared with the more usual baroreflex sensitivity while accounting explicitly for the action of mechanisms changing HP irrespective of SAP.

Cardiorespiratory coupling in mechanically ventilated patients studied via synchrogram analysis.

Respiration and cardiac activity are strictly interconnected with reciprocal influences. They act as weakly coupled oscillators showing varying degrees of phase synchronization and their interactions are affected by mechanical ventilation. The study aims at differentiating the impact of three ventilatory modes on the cardiorespiratory phase coupling in critically ill patients. The coupling between respiration and heartbeat was studied through cardiorespiratory phase synchronization analysis carried out via synchrogram during pressure control ventilation (PCV), pressure support ventilation (PSV), and neurally adjusted ventilatory assist (NAVA) in critically ill patients. Twenty patients were studied under all the three ventilatory modes. Cardiorespiratory phase synchronization changed significantly across ventilatory modes. The highest synchronization degree was found during PCV session, while the lowest one with NAVA. The percentage of all epochs featuring synchronization regardless of the phase locking ratio was higher with PCV (median: 33.9%, first-third quartile: 21.3-39.3) than PSV (median: 15.7%; first-third quartile: 10.9-27.8) and NAVA (median: 3.7%; first-third quartile: 3.3-19.2). PCV induces a significant amount of cardiorespiratory phase synchronization in critically ill mechanically ventilated patients. Synchronization induced by patient-driven ventilatory modes was weaker, reaching the minimum with NAVA. Findings can be explained as a result of the more regular and powerful solicitation of the cardiorespiratory system induced by PCV. The degree of phase synchronization between cardiac and respiratory activities in mechanically ventilated humans depends on the ventilatory mode.