The control mechanisms of heart rate dynamics in a new heart rate nonlinear time series model

Non-stationary physiological noise in the cardiovascular system during sympatho-vagal changes

This study introduces a novel estimation methodology for identifying non-stationary physiological noise, specifically applied to complex biomedical signals such as heart rate variability (HRV) series. By treating physiological noise as a dynamical recursive realization of independent and identically distributed (IID) Gaussian random variables, we employ an information-theoretic quantifier, the Approximate Entropy, to estimate noise power through a sliding window process. Our method effectively identifies noise levels in synthetic time series with varying dynamical noise powers, demonstrating accuracy even with relatively short window lengths. We further exploit this approach on real cardiovascular variability recordings during different postural changes, namely, stand-up, slow tilt, and fast tilt. The results reveal significant time-resolved variations in physiological noise, functionally linked with changes in autonomic regulation due to postural shifts. Specifically, in the absolute sense, physiological noise in the cardiovascular system tends to increase in the first 60 s of upright position with respect to a supine resting state, directly following sympathetic dynamics and inversely following vagal dynamics. Then, over 60 s physiological noise tends to decrease with respect to the resting state, almost monotonically. Moreover, results corroborate earlier findings where elevated stochasticity in HRV series biases complexity assessment through entropy analysis. Our work highlights the method's robustness and potential to improve the understanding of physiological noise dynamics, with implications for more accurate cardiovascular signal analysis and potential clinical applications.

Computational modeling of autonomic nerve stimulation: Vagus et al

Computational models of electrical stimulation, block and recording of autonomic nerves enable analysis of mechanisms of action underlying neural responses and design of optimized stimulation parameters. We reviewed advances in computational modeling of autonomic nerve stimulation, block, and recording over the past five years, with a focus on vagus nerve stimulation, including both implanted and less invasive approaches. Few models achieved quantitative validation, but integrated computational pipelines increase the reproducibility, reusability, and accessibility of computational modeling. Model-based optimization enabled design of electrode geometries and stimulation parameters for selective activation (across fiber locations or types). Growing efforts link models of neural activity to downstream physiological responses to represent more directly the therapeutic effects and side effects of stimulation. Thus, computational modeling is an increasingly important tool for analysis and design of bioelectronic therapies.

Relationship between central autonomic effective connectivity and heart rate variability: A Resting-state fMRI dynamic causal modeling study

The central autonomic network (CAN) serves as a regulatory hub with top-down regulatory control and integration of bottom-up physiological feedback via the autonomic nervous system. Heart rate variability (HRV)-the time variance of the heart's beat-to-beat intervals-is an index of the CAN's affective and behavioral regulatory capacity. Although neural functional connectivities that are associated with HRV and CAN have been well studied, no published report to date has studied effective (directional) connectivities (EC) that are associated with HRV and CAN. Better understanding of neural EC in the brain has the potential to improve our understanding of how the CAN sub-regions regulate HRV. To begin to address this knowledge gap, we employed resting-state functional magnetic resonance imaging and dynamic causal modeling (DCM) with parametric empirical Bayes analyses in 34 healthy adults (19 females; mean age= 32.68 years [SD= 14.09], age range 18-68 years) to examine the bottom-up and top-down neural circuits associated with HRV. Throughout the whole brain, we identified 12 regions associated with HRV. DCM analyses revealed that the ECs from the right amygdala to the anterior cingulate cortex and to the ventrolateral prefrontal cortex had a negative linear relationship with HRV and a positive linear relationship with heart rate. These findings suggest that ECs from the amygdala to the prefrontal cortex may represent a neural circuit associated with regulation of cardiodynamics.

Psychophysiological reactions during the trauma-film paradigm and their predictive value for intrusions

Background: Adequate adaptation of the autonomic nervous system (ANS) is crucial in potentially life-threatening situations. The defence cascade provides a descriptive model of progressing dominant physiological reactions in such situations, including cardiovascular parameters and body mobility. The empirical evidence for this model is scarce, and the influence of physiological reactions in this model for predicting trauma-induced intrusions is unresolved.Objectives: Using a trauma-film paradigm, we aimed to test physiological reactions to a highly stressful film as an analogue to a traumatic event along the defence cascade model. We also aimed to examine the predictive power of physiological activity for subsequent intrusive symptoms.Method: Forty-seven healthy female participants watched a stressful and a neutral film in randomized order. Heart rate (HR), heart rate variability (HRV), and body sway were measured. Participants tracked frequency, distress, and quality of subsequent intrusions in a diary for 7 consecutive days.Results: For the stressful film, we observed an initial decrease in HR, followed by an increase, before the HR stabilized at a high level, which was not found during the neutral film. No differences in HRV were observed between the two films. Body sway and trembling frequency were heightened during the stressful film. Neither HR nor HRV predicted subsequent intrusions, whereas perceived distress during the stressful film did.Conclusions: Our results suggest that the physiological trauma-analogue response is characterized by an orientation response and subsequent hyperarousal, reaching a high physiological plateau. In contrast to the assumptions of the defence cascade model, the hyperarousal was not followed by downregulation. Potential explanations are discussed. For trauma-associated intrusions in the subsequent week, psychological distress during the film seems to be more important than physiological distress. Understanding the interaction between physiological and psychological responses during threat informs the study of ANS imbalances in mental disorders such as post-traumatic stress disorder.

When blood pressure refuses to budge: exploring the complexity of resistant hypertension

Resistant hypertension, defined as blood pressure that remains above goal despite using three or more antihypertensive medications, including a diuretic, affects a significant proportion of the hypertensive population and is associated with increased cardiovascular morbidity and mortality. Despite the availability of a wide range of pharmacological therapies, achieving optimal blood pressure control in patients with resistant hypertension remains a significant challenge. However, recent advances in the field have identified several promising treatment options, including spironolactone, mineralocorticoid receptor antagonists, and renal denervation. In addition, personalized management approaches based on genetic and other biomarkers may offer new opportunities to tailor therapy and improve outcomes. This review aims to provide an overview of the current state of knowledge regarding managing resistant hypertension, including the epidemiology, pathophysiology, and clinical implications of the condition, as well as the latest developments in therapeutic strategies and future prospects.

Entropy of Heart Rate on Self-Selected Interval Exercises in Older Women

Non-linear analyzes such as Approximated Entropy (ApEn) and Sample Entropy (SampEn) could show the adaptability of the autonomic nervous system in relation to the dynamic changes caused by exercise. The aims of the study were: a) Investigate the effects of different Self-Selected based Interval Exercises (SSIE) configurations on Heart Rate (HR) entropy; b) Determine whether the stimuli time promote different entropy responses; c) Observe whether exercises with passive self-selected recovery time (SSRT) promote different HR entropy responses compared to those with imposed time and active recovery; and d) Determine whether post-training entropy responses quickly return to baseline. Fifteen older women were randomized to perform six sessions of SSIE and one session of Self-Selected Continuous Exercise (SSCE), with approximately 24 min duration each. The results showed increases on ApEn during the exercises compared to the moments of rest Pre (p < 0.001), Post 6 min (p = 0.003) and Post 12 min (p < 0.001). Results demonstrated that interval exercises (IE) with SSRT, present lower values of ApEn and SampEn regarding the continuous activity (p < 0.05). It was also observed that the entropy values after training returned quickly to levels close to those of pre-exercise rest with a tendency to decrease more pronounced for the continuous. The SSIE were able to promote greater complexity in the HR entropy of older women, allowing greater stabilization of the cardiovascular system, including after training.

Beetroot Juice Produces Changes in Heart Rate Variability and Reduces Internal Load during Resistance Training in Men: A Randomized Double-Blind Crossover

Beetroot juice (BJ) has been used as a sport supplement, improving performance in resistance training (RT). However, its effect on the modulation of the autonomic nervous system has not yet been widely studied. Therefore, the objective of this randomized double-blind crossover study was to assess the effect of acute BJ supplementation compared to placebo in blood pressure (BP), heart rate (HR), heart rate variability (HRV) and internal load during RT measure as Root Mean Square of the Successive Differences between adjacent RR intervals Slope (RMSSD and RMSSD-Slope, respectively). Eleven men performed an incremental RT test (three sets at 60%, 70% and 80% of their repetition maximum) composed by back squat and bench press with. HR, HRV and RMSSD-Slope were measured during and post exercise. As the main results, RMSSD during exercise decrease in the BJ group compared to placebo (p = 0.023; ES = 0.999), there were no differences in RMSSD post-exercise, and there were differences in RMSSD-Slope between groups in favor of the BJ group (p = 0.025; ES = 1.104) with a lower internal load. In conclusion, BJ supplementation seems to be a valuable tool for the reduction in the internal load of exercise during RT measured as RMSSD-Slope while enhancing performance.

Biological noise is a key determinant of the reproducibility and adaptability of cardiac pacemaking and EC coupling

Each heartbeat begins with the generation of an action potential in pacemaking cells in the sinoatrial node. This signal triggers contraction of cardiac muscle through a process termed excitation-contraction (EC) coupling. EC coupling is initiated in dyadic structures of cardiac myocytes, where ryanodine receptors in the junctional sarcoplasmic reticulum come into close apposition with clusters of CaV1.2 channels in invaginations of the sarcolemma. Cooperative activation of CaV1.2 channels within these clusters causes a local increase in intracellular Ca2+ that activates the juxtaposed ryanodine receptors. A salient feature of healthy cardiac function is the reliable and precise beat-to-beat pacemaking and amplitude of Ca2+ transients during EC coupling. In this review, we discuss recent discoveries suggesting that the exquisite reproducibility of this system emerges, paradoxically, from high variability at subcellular, cellular, and network levels. This variability is attributable to stochastic fluctuations in ion channel trafficking, clustering, and gating, as well as dyadic structure, which increase intracellular Ca2+ variance during EC coupling. Although the effects of these large, local fluctuations in function and organization are sometimes negligible at the macroscopic level owing to spatial-temporal summation within and across cells in the tissue, recent work suggests that the "noisiness" of these intracellular Ca2+ events may either enhance or counterintuitively reduce variability in a context-dependent manner. Indeed, these noisy events may represent distinct regulatory features in the tuning of cardiac contractility. Collectively, these observations support the importance of incorporating experimentally determined values of Ca2+ variance in all EC coupling models. The high reproducibility of cardiac contraction is a paradoxical outcome of high Ca2+ signaling variability at subcellular, cellular, and network levels caused by stochastic fluctuations in multiple processes in time and space. This underlying stochasticity, which counterintuitively manifests as reliable, consistent Ca2+ transients during EC coupling, also allows for rapid changes in cardiac rhythmicity and contractility in health and disease.

Frailty Identification Using Heart Rate Dynamics: A Deep Learning Approach

Previous research showed that frailty can influence autonomic nervous system and consequently heart rate response to physical activities, which can ultimately influence the homeostatic state among older adults. While most studies have focused on resting state heart rate characteristics or heart rate monitoring without controlling for physical activities, the objective of the current study was to classify pre-frail/frail vs non-frail older adults using heart rate response to physical activity (heart rate dynamics). Eighty-eight older adults (≥65 years) were recruited and stratified into frailty groups based on the five-component Fried frailty phenotype. Groups consisted of 27 non-frail (age = 78.80±7.23) and 61 pre-frail/frail (age = 80.63±8.07) individuals. Participants performed a normal speed walking as the physical task, while heart rate was measured using a wearable electrocardiogram recorder. After creating heart rate time series, a long short-term memory model was used to classify participants into frailty groups. In 5-fold cross validation evaluation, the long short-term memory model could classify the two above-mentioned frailty classes with a sensitivity, specificity, F1-score, and accuracy of 83.0%, 80.0%, 87.0%, and 82.0%, respectively. These findings showed that heart rate dynamics classification using long short-term memory without any feature engineering may provide an accurate and objective marker for frailty screening.

Pseudo and resistant hypertension: A chaotic perspective

Systemic blood pressure (BP) may oscillate for homeostatic needs (equilibrium by constancy) or just as shifts in other intrinsic and extrinsic variables known as allostatic changes. This transitory pressure often rises alerts physicians to out‐of‐control hypertension or even hypertensive crisis. There is a very complex theory underlying these stochastic phenomena, which physicists and mathematicians translate into a single word: chaos. These changes happen according to a stochastic probabilistic pattern that presumes chaotic but somewhat predictable and nonlinear modeling of BP‐related dynamics as a mathematical approach. Based on the chaos theory, small changes at the initial BP (baseline overtime) values could disturb the homeostasis leading to extreme BP chaotic shifts. These almost insignificant oscillations may also affect other variables and systems, leading to the misdiagnosis of hypertension, “out‐of‐control” BP levels, and resistant hypertension (RHT). Thus, these unpredictable and transient increases in BP values may be improperly diagnosed as the white coat and masked or resistant hypertension. Indeed, the interference of the chaos in any phenotype of (true or false) hard to control BP is not considered in clinical settings. This review provides some basic concepts on chaos theory and BP regulation. Besides pseudoresistant hypertension (lack of adherence, circadian variations, and others (white‐coat, masked, early morning effects or hypertension), chaotic changes can be responsible for out‐of‐control hypertension.

The effect of passive lower limb training on heart rate asymmetry

OBJECTIVE

Heart rate asymmetry (HRA) is an approach for quantitatively assessing the uneven distribution of heart rate accelerations and decelerations for sinus rhythm. We aimed to investigate whether automatic regulation led to HRA alternation during passive lower limb training.

METHODS

Thirty healthy participants were recruited in this study. The protocol included a baseline (Pre-E) and three passive lower limb training trials (E1, E2 and E3) with a randomized order. Several variance-based HRA variables were established. Heart rate variability (HRV) parameters, i.e., mean RR, SDNN, RMSSD, LF (n.u.), HF (n.u.) and VLF (ms2), and HRA variables, i.e., SD1a, SD1d, SD2a, SD2d, SDNNa and SDNNd, were calculated by using 5-min RR time series, as well as the normalized HRA variables, i.e., C1a, C1d, C2a, C2d, Ca and Cd.

RESULTS

Our results showed that the performance of HRA was distinguished. The normalized HRA was observed with significant changes in E1, E2 and E3 compared to Pre -E. Moreover, parts of non-normalized HRA variables correlated with HRV parameters, which indicated that HRA might benefit in assessing cardiovascular modulation in passive lower limb training.

CONCLUSIONS

In summary, this study suggested that passive training led to significant HRA alternation and the application of HRA gave us the possibility for autonomic assessment.

Prevalence and Risk Factors for Hypertension in Adolescents Aged 12 to 17 Years: A School-Based Study in China

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Pre- and postoperative heart rate variability and vagus nerve stimulation in patients with drug-resistant epilepsy - A meta-analysis

OBJECTIVE

The effect of vagus nerve stimulation (VNS), an important auxiliary therapy for treating drug-resistant epilepsy (DRE), on autonomic nerve function is still controversial. Heart rate variability is a widely used indicator of autonomic nerve function. To clarify the relationship between VNS and heart rate variability (HRV), we performed a meta-analysis to systematically evaluate the effect of VNS on HRV in patients with epilepsy.

METHODS

We performed a systematic review by searching the following online databases: PubMed, Web of Science, EMBASE and the Cochrane Library. The key search terms were "vagal nerve stimulation," "epilepsy" and "heart rate variability". Other features of VNS in patients with epilepsy include postoperative changes in low-frequency (LF), high-frequency (HF) and low-frequency/high-frequency (LF/HF) heart rate variability, which were used as evaluation indices, and the Newcastle-Ottawa Quality Assessment Scale and Stata 14.0 statistical software were used for literature quality evaluation and meta-analysis.

RESULTS

Twelve studies published in English were obtained, and 229 patients with epilepsy who underwent VNS were ultimately included after elimination of duplicate articles and those that did not meet the inclusion criteria. Regarding LF heart rate variability, in the response subgroup, patients with DRE with VNS presented a lower value (-0.58) before surgery than after surgery, with a 95% confidence interval (CI) ranging from -1.00 to -0.15. For HF heart rate variability, patients with DRE with VNS had a lower value (-0.45) before surgery than after surgery in the response subgroup, with a 95% CI ranging from -0.74 to -0.17. No differences were found for LF/HF values or the LF and HF values of other subgroups.

CONCLUSION

VNS has little effect on the balance of sympathetic and parasympathetic nerve activity and would not be expected to cause cardiovascular autonomic dysfunction in patients with DRE. For patients with DRE, VNS can control seizures and has little effect on autonomic nervous function.