Comparison between probabilistic and Wiener-Granger causality in assessing modifications of the cardiac baroreflex control with age

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.

Sleep Deprivation Deteriorates Heart Rate Variability and Photoplethysmography

Introduction

Sleep deprivation has deleterious effects on cardiovascular health. Using wearable health trackers, non-invasive physiological signals, such as heart rate variability (HRV), photoplethysmography (PPG), and baroreflex sensitivity (BRS) can be analyzed for detection of the effects of partial sleep deprivation on cardiovascular responses.

Methods

Fifteen participants underwent 1 week of baseline recording (BSL, usual day activity and sleep) followed by 3 days with 3 h of sleep per night (SDP), followed by 1 week of recovery with sleep ad lib (RCV). HRV was recorded using an orthostatic test every morning [root mean square of the successive differences (RMSSD), power in the low-frequency (LF) and high-frequency (HF) bands, and normalized power nLF and nHF were computed]; PPG and polysomnography (PSG) were recorded overnight. Continuous blood pressure and psychomotor vigilance task were also recorded. A questionnaire of subjective fatigue, sleepiness, and mood states was filled regularly.

Results

RMSSD and HF decreased while nLF increased during SDP, indicating a decrease in parasympathetic activity and a potential increase in sympathetic activity. PPG parameters indicated a decrease in amplitude and duration of the waveforms of the systolic and diastolic periods, which is compatible with increases in sympathetic activity and vascular tone. PSG showed a rebound of sleep duration, efficiency, and deep sleep in RCV compared to BSL. BRS remained unchanged while vigilance decreased during SDP. Questionnaires showed an increased subjective fatigue and sleepiness during SDP.

Conclusion

HRV and PPG are two markers easily measured with wearable devices and modified by partial sleep deprivation, contradictory to BRS. Both markers showed a decrease in parasympathetic activity, known as detrimental to cardiovascular health.

Temporal orders and causal vector for physiological data analysis

In addition to the global parameter- and time-series-based approaches, physiological analyses should constitute a local temporal one, particularly when analyzing data within protocol segments. Hence, we introduce the R package implementing the estimation of temporal orders with a causal vector (CV). It may use linear modeling or time series distance. The algorithm was tested on cardiorespiratory data comprising tidal volume and tachogram curves, obtained from elite athletes (supine and standing, in static conditions) and a control group (different rates and depths of breathing, while supine). We checked the relation between CV and body position or breathing style. The rate of breathing had a greater impact on the CV than does the depth. The tachogram curve preceded the tidal volume relatively more when breathing was slower.

Strength and Latency of the HP-SAP Closed Loop Variability Interactions in Subjects Prone to Develop Postural Syncope

The coupling and latency between heart period (HP) and systolic arterial pressure (SAP) variability can be investigated along the two arms of the HP-SAP closed loop, namely along the baroreflex feedback from SAP to HP, and along the feedforward pathway from HP to SAP. This study investigates the HP-SAP closed loop variability interactions through cross-correlation function (CCF). Coupling strength and delay between HP and SAP variability series were monitored in 13 subjects prone to develop orthostatic syncope (SYNC, 28±9 yrs, 5 males) and in 13 subjects with no history of postural syncope (noSYNC, age: 27±8 yrs, 5 males). Analysis was carried out at rest in supine position (REST) and during head-up tilt (TILT) at 60 degrees. The null hypothesis of HP-SAP uncoupling was tested through a surrogate analysis associating the HP series of a subject with a SAP sequence of a different one. Results showed that during TILT the coupling strength increased along the baroreflex and latency augmented along the mechanical feedforward pathway exclusively in noSYNC subjects. Finally, closed loop HP-SAP interactions were detected in about one third of subjects and the situation of full uncoupling was rarely found. CCF analysis was found to be a straightforward and easily applicable method to investigate HP-SAP control deserving a direct comparison with more sophisticated signal processing tools assessing causality.

Characterization of the Asymmetry of the Cardiac and Sympathetic Arms of the Baroreflex From Spontaneous Variability During Incremental Head-Up Tilt

Hysteresis of the baroreflex (BR) is the result of the different BR sensitivity (BRS) when arterial pressure (AP) rises or falls. This phenomenon has been poorly studied and almost exclusively examined by applying pharmacological challenges and static approaches disregarding causal relations. This study inspects the asymmetry of the cardiac BR (cBR) and vascular sympathetic BR (sBR) in physiological closed loop conditions from spontaneous fluctuations of physiological variables, namely heart period (HP) and systolic AP (SAP) leading to the estimation of cardiac BRS (cBRS) and muscle sympathetic nerve activity (MSNA) and diastolic AP (DAP) leading to the estimation of vascular sympathetic BRS (sBRS). The assessment was carried out in 12 young healthy subjects undergoing incremental head-up tilt with table inclination gradually increased from 0 to 60°. Two analytical methods were exploited and compared, namely the sequence (SEQ) and phase-rectified signal averaging (PRSA) methods. SEQ analysis is based on the detection of joint causal schemes representing the HP and MSNA burst rate delayed responses to spontaneous SAP and DAP modifications, respectively. PRSA analysis averages HP and MSNA burst rate patterns after aligning them according to the direction of SAP and DAP changes, respectively. Since cBRSs were similar when SAP went up or down, hysteresis of cBR was not detected. Conversely, hysteresis of sBR was evident with sBRS more negative when DAP was falling than rising. sBR hysteresis was no longer visible during sympathetic activation induced by the orthostatic challenge. These results were obtained via the SEQ method, while the PRSA technique appeared to be less powerful in describing the BR asymmetry due to the strong association between BRS estimates computed over positive and negative AP variations. This study suggests that cBR and sBR provide different information about the BR control, sBR exhibits more relevant non-linear features that are evident even during physiological changes of AP, and the SEQ method can be fruitfully exploited to characterize the BR hysteresis with promising applications to BR branches different from cBR and sBR.