Vagal Efficiency: A Novel Metrics Refined for Brainstem‑Specific Autonomic Control

Vagal Efficiency: A Novel Metrics Refined for Brainstem‑Specific Autonomic Control | Authorea try { document.documentElement.classList.add('js'); } catch (e) { } var _gaq = _gaq || []; _gaq.push(['_setAccount', 'G-8VDV14Y67G']); _gaq.push(['_trackPageview']); (function() { var ga = document.createElement('script'); ga.type = 'text/javascript'; ga.async = true; ga.src = ('https:' == document.location.protocol ? 'https://ssl' : 'http://www') + '.google-analytics.com/ga.js'; var s = document.getElementsByTagName('script')[0]; s.parentNode.insertBefore(ga, s); })(); Skip to main content Preprints Collections Wiley Open Research IET Open Research Ecological Society of Japan All Collections About About Authorea FAQs Contact Us Quick Search anywhere Search for preprint articles, keywords, etc. Search Search ADVANCED SEARCH SCROLL This is a preprint and has not been peer reviewed. Data may be preliminary. 21 July 2025 V1 Latest version Share on Vagal Efficiency: A Novel Metrics Refined for Brainstem‑Specific Autonomic Control Authors : Shyama Shah 0009-0007-8894-424X [email protected] , Gregory Lewis , and Stephen W. Porges Authors Info & Affiliations https://doi.org/10.22541/au.175311024.49743829/v1 354 views 132 downloads Contents Abstract Information & Authors Metrics & Citations View Options References Figures Tables Media Share Abstract Central autonomic drive is conventionally inferred from peripheral heart‑rate metrics—Heart Rate Variability and Respiratory Sinus Arrhythmia (RSA)—which conflate brainstem modulation with cholinergic transmission at the sinoatrial node. Here, we introduce Vagal Efficiency (VE), defined as the slope of heart‑period versus RSA changes in 15 s ECG epochs, as a direct, non‑invasive index of brainstem vagal control, offering new insights into autonomic control that is less influenced by peripheral factors than traditional metrics like RSA. In a double‑blind infusion study (n = 65), we administered glycopyrrolate to block peripheral muscarinic receptors and saline as control. While glycopyrrolate sharply reduced RSA (p < 0.001) and shortened heart period (p 0.15), confirming its independence from peripheral transmission. By isolating a brainstem “vagal switch” that allocates cardiac output to metabolic demands, VE opens new avenues for diagnosing and monitoring dysautonomia, sleep‑state transitions, and gut–brain disorders. This metric provides a powerful bridge between central autonomic mechanisms and accessible peripheral signals, with broad implications for neuroscience, clinical practice and sports science. Introduction In vertebrates, breathing and heartbeat are tightly coupled oscillators: each breath produces predictable modulation of cardiac rhythm known as respiratory sinus arrhythmia (RSA) (Dong, 2016) . During inspiration the heart rate accelerates, and during expiration it decelerates, reflecting rhythmic gating of parasympathetic (vagal) outflow by the respiratory cycle (Dong, 2016; Porges, 1995). This phenomenon was noted as early as 1733 by Stephen Hales and later quantitatively recorded by Carl Ludwig in 1847 (Billman, 2011; Porges, 2022). Today, RSA is recognized not merely as a curious resonance but as a clinically and biologically meaningful signature of cardio-vagal control. More broadly, the coordinated interplay of breathing and heart rhythms exemplifies the challenge of understanding coupled biological oscillators – a key problem spanning life sciences, bioengineering, and medicine. In this context, cardiorespiratory coupling (via RSA) serves as an accessible window into autonomic regulation, with implications for many fields. Classical studies laid the physiological foundations of RSA. In the early 1900s, Wilhelm Wundt (1902) and Ewald Hering (1910) provided some of the first systematic descriptions of this cardio-respiratory link ( Hering,1931 .; Porges, 2022) . Wundt noted that respiratory movements are “regularly accompanied by fluctuations of the pulse, whose rapidity increases in inspiration and decreases in expiration” (Porges, 2006) . Hering similarly reported that the heart- rate slowing during exhalation can serve as a “functional test of vagal control,” such that a marked post-expiratory deceleration of heart rate is “indicative of the function of the vagi” (Porges, 2006) . Later work by Bainbridge (1920) (Bainbridge, 1920) and Anrep et al. (1936) elucidated underlying mechanisms: Bainbridge attributed RSA to reflex changes in baroreceptor signaling due to respiratory swings, while Anrep showed that RSA amplitude varies with breathing depth, rate, blood gas levels, and intact vagal pathways (Billman, 2011; Porges, 2006) . These classical experiments established that RSA is a dynamic feedback phenomenon: the medulla implements a “vagal brake” on the heart that is rhythmically modulated by respiration, producing synchronized oscillations in cardiac period. Over the past century, cardiac vagal control and RSA have become important in many fields. In psychophysiology and cardiology, vagal-mediated heart rate variability (HRV) – of which RSA is the dominant high-frequency component – is widely used as a marker of autonomic balance. For example, indices of vagal HRV correlate inversely with cardiometabolic risk factors (Dong, 2016) . Reduced resting RSA has been observed in conditions such as heart disease and diabetes, whereas higher RSA (greater vagal tone) associates with health and longevity (Tonhajzerova et al., 2016). In behavioral science and sports physiology, RSA is interpreted as a marker of regulatory capacity: resting HRV tends to decline under acute stress and aging, and conversely it increases with regular physical training (Dong, 2016; Porges, 2021) . Notably, comparisons of active versus sedentary individuals reveal distinct HRV profiles, and monitoring RSA/HRV is now common in athletic training to guide recovery and performance (Dong, 2016) . Likewise, in psychology and neuroscience RSA has been studied as a proxy for emotional and cognitive resilience – individuals with high baseline vagal tone typically show greater stress tolerance and faster recovery from perturbation, whereas anxiety or mood disorders are often associated with chronically low RSA (Fanning et al., 2020). In all these diverse contexts, the basic physiology of breathing–heart coupling links autonomic neuroscience to clinical practice and human performance. Current HRV metrics rely only on peripheral measures assumed to reflect central control; variability in vagal transmission can bias their reliability and timing. Conventionally, RSA is quantified using spectral or time-domain analysis of ECG and respiration signals (Dong, 2016; Lewis et al., 2012) . These measures assume a roughly linear correspondence between respiratory-driven vagal activity and heart rate changes. However, emerging evidence suggests this relationship itself may vary across subjects and conditions, so that two people with the same RSA amplitude could differ in how strongly their heart responds to vagal input (Kovacic et al., 2020; Porges, 2024). These limitations highlight the need for more reliable, accurate, and comprehensive metrics to advance our understanding of autonomic regulation (Mansi et al., 2021). To capture this nuance, recent research has introduced the concept of vagal efficiency (VE) (Kolacz et al., 2025; Porges, 2024) . Vagal efficiency is defined as the slope of the correlation between instantaneous cardiac vagal tone (indexed by RSA) and the resulting change in heart period. A steeper slope (high VE) means that small vagal shifts produce large heart rate changes – the “vagal brake” is highly effective – whereas a shallow slope (low VE) indicates a blunted cardiac response for the same vagal input. In practical terms, VE quantifies the dynamic efficiency of brainstem vagal pathways linking blood pressure and cardiac control (Porges, 2024) . Importantly, VE and RSA amplitude provide complementary information. Kolacz and colleagues emphasize that both RSA and VE can noninvasively index parasympathetic output (Kolacz et al., 2025) . Indeed, representative data show two individuals with identical baseline RSA can have dramatically different VE (Fig. 1C,D). For example, Porges et al. (2024) illustrated a pair of adolescents who shared the same RSA range but differed in VE: one had a low slope (VE≈14) and the other a high slope (VE≈87) (Porges, 2024) . This shows that VE reveals individual differences in cardio-vagal coupling beyond what RSA magnitude alone captures. The vagal efficiency concept has immediate translational implications. By treating the heart–respiration feedback loop as a modifiable gain mechanism, VE can serve as a biomarker of autonomic flexibility. Recent studies already suggest its sensitivity to intervention: for instance, vagal neuromodulation (ear stimulation) acutely increased VE in adolescents without affecting conventional RSA or mean heart rate (Kolacz et al., 2025) . Similarly, VE has been found to covary with clinical syndromes; Porges (2024) reports that VE appears to track features of gut–brain disorders, reflecting dysregulation of autonomic feedback circuits (Porges, 2024). Further research has demonstrated that VE decreases in response to alcohol consumption (Reed et al., 1999), low VE is associated with clinical conditions, including joint hypermobility syndrome (Kolacz et al., 2021), cyclic vomiting syndrome (Kolacz et al., 2023), and adversity history (Dale et al., 2022). These findings imply that VE may be a more responsive indicator of autonomic state in certain contexts – capturing rapid “switches” in vagal output that static HRV measures miss. In the present study, we leverage these insights to examine cardiorespiratory coupling in a translational framework. We analyze ECG and respiratory recordings from human subjects undergoing controlled interventions (including pharmacological infusion) quantifying both RSA amplitude and vagal efficiency to determine whether VE is an indicator of central autonomic function independent of peripheral blockade. Our results include representative examples of high-VE and low-VE individuals (see Methods/Results for details), which clarify how these metrics manifest in real signals. By comparing VE across conditions and subjects, we reveal how autonomic control efficiency can differ within a population and respond to challenge. Ultimately, this multidisciplinary perspective on RSA and VE bridges a deep physiological tradition with current needs in medicine, psychophysiology and sports science. Understanding these oscillatory interactions advances fundamental science and may improve applications ranging from clinical diagnostics (e.g. neuromodulation therapies) to performance optimization in athletics and psychological resilience training. Methods Subjects: Sixty-five male participants between the ages of 18 and 34 (M = 25.48, SD = 3.99) were recruited at the UIC Hospital, and the UIC psychology student subject pool. Participants self-identified as Caucasian (58.5%), African American (21.5%), Asian (10.8%), or other (9.2%) and were excluded from the study if, in the preceding 24 hours, they had used a tobacco product, consumed more than 3 alcoholic beverages, taken any non-prescription drugs, or had a caffeine drink within the two hours prior to the experimental session. In addition, no participant was taking prescription medications, including central nervous system depressants or stimulants, hypertension medications, or anti- cholinergic agents that could influence autonomic regulation. For details about the data collection protocol please refer to Lewis et al., (2012). Protocol: During the clinically supervised session participants received an intravenous bolus infusion of either saline vehicle or glycopyrrolate (.006mg/kg). Data were collected from 65 participants. 47 participants had complete data from two seated baseline sessions in both the laboratory and hospital sessions. Sample sizes were maximized in the analyses presented below (i.e., in the research laboratory 65 participants were tested at the first baseline and 48 participants at the second baseline, in the hospital 50 participants were tested). Of the 50 participants tested in the hospital, 25 received glycopyrrolate infusion and 25 received a “control” saline infusion. Details of the protocol is available in Lewis et al., (2012). In the hospital setting, clinical staff set up an intravenous apparatus to deliver an infusion of saline or glycopyrrolate. Data are reported from the initial 5-minute baseline in the research laboratory and a 5-minute post-baseline monitored 45 minutes following a protocol involving a sequence of psychological tests evaluating affect recognition and auditory processing. The same experimental protocol (i.e., psychological tests) was administered in both research settings. In the hospital setting, the effect of vagal blockade was assessed during a 5-minute pre-infusion baseline and approximately 45 minutes following infusion during a 5-minute post-infusion seated baseline. Data Collection: Consistent with the University of Illinois at Chicago Institutional Review Board, participants read and signed consent forms and were screened for health status to assure compliance with the exclusion criteria (i.e., brain injury, chronic bronchitis, smoking more than one cigarette per day). ECG and LifeShirt® (VivometricsTM) were used to monitor respiration parameters and heart rate. The LifeShirt® is made of a stretchable fabric with two embedded inductance plethysmography bands at the thoracic and abdominal levels, which accurately measures continuous changes in tidal volume and provides accurate measures of beat-to-beat heart rate (Heilman & Porges, 2007). The heart period time series were visually inspected and missed R-wave detections and errors were corrected with CardioEdit (Brain-Body Center, Chicago, IL). Heart Period (HP): The average time between sequential heart periods in ms. Statistically, this measure is the reciprocal of heart rate (i.e., as heart period expands in duration, heart rate slows) but has better distributional features for parametric analyses. 1. Respiratory Sinus Arrhythmia (RSA): The average of the natural log‐transformed epoch‐based measures of the amplitude of RSA. Details on the Porges-Bohrer method of RSA quantification are provided in Lewis at al., 2012. (Ellis et al., 2016; Fanning et al., 2020; Lewis et al., 2012; Porges et al., 2019) 2. Vagal Efficiency (VE): RSA and heart period were calculated in sequential, discrete 15s epochs, both before and after infusion. Regression analysis of the heart period and RSA values epoch values were used to assess the efficiency of vagal regulation of heart rate (Porges et al., 1999). VE is measured by the slope of this regression (VE), which reports the change in HP (ms) for a one-unit change in RSA (Ln(ms 2 )). 3. VE-offset: the estimated HP at RSA = 0.0 in the VE regression. This exploratory parameter may yield information on the peripheral influence of sympathetic activity on the SA node and is moderately correlated with VE. Regression analyses were used to evaluate the dynamic coupling between RSA and heart period. Repeated measures analyses of variance (ANOVA), with TIME [pre-/post-infusion] as the repeated measure and INFUSION [glyco/saline], were conducted to evaluate state differences in the physiological variables {RSA, HP, VE, and VE-offset}. There were no differences in physiological measures as a function of gender, and all analyses reported are collapsed across gender. All metrics were quantified from the beat-to-beat heart period time series. Epoch duration: In the previous paper (Lewis et al., 2012) we investigated the stability of small epoch estimates of RSA and demonstrated that the RSA P-B metric gave a reasonable estimate of the 5-minute steady-state average from as short as a single 10- second epoch. For this analysis of vagal efficiency, we return to the short epoch estimates of RSA and HP to calculate VE during the two resting conditions (pre- and post-infusion) with a partial cholinergic blockade (or placebo) to evaluate the dependence of VE on the ventral vagal pathway. We use the longer epoch duration of 15s, as opposed to 10s, to be conservative in this exploratory analysis and because 15s epochs demonstrate consistent agreement with the assumptions of stationarity. We hypothesized that VE would be independent of INFUSION as it is a measure of the central autonomic regulation and not a functional measure of cardiac vagal tone. Short data epochs are necessary to evaluate the instantaneous shifts in the coupling between RSA and heart period, providing the opportunity to evaluate the influence of epoch duration on the amplitude of RSA. Although spectral analysis cannot be reliably applied to short duration heart period epochs, the mixed time-frequency domain Porges-Bohrer method (Lewis et al., 2012; Porges et al., 1985) implemented here in MATLAB functions, processes the heart-period time series with two symmetrical cascading filters i.e., moving polynomial and bandpass. The residual data from these filters contain only the heart period variability activity within the user defined Results Repeated measures ANOVA confirmed the significant TIMExINFUSION contrast for both RSA amplitude, F (1,52) = 32.1, p <.001, and HP, F (1,52) = 17.6, p <.001. In contrast, the TIMExINFUSION effect was not significant for either VE-slope, F (1,52) = 1.963, p = .17, or VE-offset F (1,52) = 0.819, p = .37. Between-subjects contrasts were consistent with the hypothesized independence of VE parameters on cholinergic blockade, revealing significant differences in only RSA, F (1,52) = 13.92, p <.001 and HP, F(1,52) = 4.49, p =.039. For VE-slope and VE-offset p = .69 and .78 respectively. Beyond group-level contrasts, we visualized individual variability in vagal efficiency by plotting RSA and heart period time series in two representative subjects: one with high VE and one with low VE. These signal traces (Fig. 1a, b) illustrate how comparable RSA amplitudes can correspond to markedly different heart period modulation, emphasizing VE as a dynamic coupling measure rather than a static index. Group-level estimated marginal means (Fig. 2c, d) complement these individual examples, highlighting the dissociation between robust RSA/HP changes under glycopyrrolate and the relative stability of VE parameters. Together, these figures illustrate how VE captures brainstem-mediated autonomic regulation that is not apparent from conventional RSA or mean heart period alone. 1a. Example, High VE subject, pre-infusion. 1b. Example. Low VE subject, pre-infusion. In the experiment, subjects were either infused with a partial vagal blockade drug, glycopyrrolate, or a saline placebo. Using repeated measures ANOVA, we establish that the glyco-blockade has a large effect on peripheral autonomic measures that are putatively linked to cholinergic parasympathetic outflow. In descending order of effect, we observe changes ( Cohen’s d ) within the glyco-infusion group in: RSA (1.09), HP (0.83), VE (0.36), and VE-offset (0.27). In our comparison of changes in these parameters between the placebo and glyco group, Welch’s robust test for equality of means indicates that only the RSA and HP changes are statistically significant (all VE related metrics p’s > 0.15). Thus, VE appears to reflect a unique and potentially central index of autonomic activity not captured by peripheral measures of RSA or HP. This aligns with the theoretical interpretation of VE as reflecting, not an index of summated vagal efferent influences, but the efficiency of the brainstem in optimizing the output of the vagal efferent cardioinhibitory pathway. Fig. 2 c, d Discussion Building on Hering’s early 20th-century insight that respiration rhythmically modulates cardioinhibitory vagal fibers, vagal efficiency extends this physiological concept into a dynamic brainstem metric ( Hering , 1931; Porges, 2007). Hering’s observation—that heart rate slowing during expiration signals vagal function—was later expanded by Bainbridge and Anrep, who explored RSA’s dependence on breathing patterns and cardioregulatory pathways (Bainbridge, 1920). VE refines this tradition by quantifying how effectively brainstem signals translate into heart period modulation, providing a modern lens on the regulatory capacity of the vagus across physiological and pathological states. Our data show that VE—calculated as the slope of heart period versus RSA across short epochs—remains stable under peripheral muscarinic blockade, whereas RSA amplitude and mean heart period decrease significantly. This dissociation suggests VE captures brainstem-mediated modulation largely independent of peripheral cholinergic transmission. We present here follow-up analyses to an important study used to validate the sensitivity of commonly used statistical measurements of a peripheral index of cardiac vagal tone, respiratory sinus arrhythmia. That paper highlights the limitations of several frequently used metrics of RSA and unambiguously documents that the metrics are not equivalent in their sensitivity to vagal regulation. Thus, confirming that the Porges-Bohrer method for RSA quantification was more sensitive to a partial vagal blockade and statistically less influenced by measurement confounds due to nonstationarity and respiratory activity (rate and tidal volume) when contrasted to peak-to-trough and spectral methods. This does not preclude the possibility other methods being developed that would incorporate complex detrending to remove non-stationarity disruptions in the time series and transformations to conform to parametric assumptions. However, perhaps most relevant to the current analyses of VE, the previous paper Lewis et al., (2012), established the ability for the Porges-Bohrer method to accurately quantify RSA magnitude in epochs as short as 10 seconds. The other methods, regardless of their poor sensitivity to vagal function, could not be used to generate an estimate within an epoch of only a few seconds. In this study, we measure an additional aspect of autonomic control that focuses on whether an index of the dynamic central brainstem regulation of the efficiency of the vagus can be derived that is independent of peripheral vagal tone. To accomplish this task, we leveraged the relatively high temporal resolution of Porges-Bohrer RSA to investigate the covariation of RSA magnitude and mean heart period in order to quantify the efficiency of cardio-vagal inhibition, or vagal efficiency. From the within-subject variance of [HP, RSA] short epochs, we extract three parameters of their linear relationship: the slope (VE-slope), the HP offset (VE-offset, or estimate of HP when RSA = 0.0), and the correlation. Measurement of VE is straightforward with an appropriate method for extracting short-duration epochs (<20 sec) of HP and RSA. The interpretation of VE in future research will be more consistent if it was measured in a controlled task that expands the observed range of both sympathetic and parasympathetic activity. Obviously glycopyrrolate and other infusions of cholinergic blocking drugs is not feasible in most environments. Since the ANS is responsive to an enormous range of task demands, we suggest a modest adjustment to the typical baseline measurement of HRV that limits the source of variance to one domain. Our suggestion is to adjust the posture of the subject to create periods during which the brainstem is challenged to adaptively produce low- and high- parasympathetic activity. In recent work, we have explored both supine-seated-standing baseline measures and seated-standing-seated measures, in order to quantify VE across this wider range of autonomic states. Both protocols offer advantages: the supine posture allows for the widest range of observed autonomic states, while the seated-standing-seated protocol has the benefit of the initial seated period being comparable to the many seated baseline measures of autonomic activity. We suggest that wherever feasible, psychophysiologists both integrate a posture shift into their baseline measurements and deploy a signal processing strategy, such as the Porges-Bohrer method, that is capable of generating reliable, short epoch estimates of both heart rate and HRV parameters, from which VE may be derived. VE’s stability under pharmacological challenge suggests utility across disciplines. Clinically, VE could help diagnose and monitor dysautonomia or cardiac risk by distinguishing central from peripheral contributions to autonomic regulation. In neurogastroenterology, it could characterize gut–brain disorders involving vagal pathways. Beyond medicine, VE could serve as a biomarker of autonomic flexibility and resilience in sports science and performance psychology. We speculate that chronic exposure to abusive and stressful conditions, which lead to impaired VE (Dale et al., 2022), may serve as a precursor to cardiovascular disease and dysfunction. Such conditions likely disrupt the neural circuits responsible for autonomic regulation, resulting in progressive maladaptive changes. Specifically, under chronic threat, the organism may experience a weakening or reduced reliability of the vagal brake, a key mechanism for parasympathetic control. This shift may represent an adaptive response to ensure survival, as the body prioritizes sympathetic nervous system activation and possibly engages in dorsal vagal pathways that might disrupt gut function (e.g., irritable bowel disorders) to cope with prolonged stress. In this context, VE may serve as a crucial metric to that might be useful in providing a function index capable of monitoring autonomic features leading to dysautonomia, offering insights into how autonomic dysregulation contributes to long-term cardiovascular and systemic health risks. This operationalization of VE could provide a valuable tool for identifying individuals at heightened risk for autonomic dysfunction, particularly in environments characterized by chronic stress or trauma. By bridging historical physiological insights with modern translational needs, VE offers a refined tool for psychophysiology, neuroscience, clinical practice, and human performance research. Reference: Bainbridge, F. A. (1920). The relation between respiration and the pulse-rate. The Journal of Physiology , 54 (3), 192–202. https://doi.org/10.1113/JPHYSIOL.1920.SP001918 Billman, G. E. (2011). Heart rate variability - A historical perspective. 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The Indian Journal of Medical Research , 144 (6), 815. https://doi.org/10.4103/IJMR.IJMR_1447_14 Information & Authors Information Version history V1 Version 1 21 July 2025 Copyright This work is licensed under a Non Exclusive No Reuse License. Authors Affiliations Shyama Shah 0009-0007-8894-424X [email protected] Indiana University Luddy School of Informatics Computing and Engineering View all articles by this author Gregory Lewis Indiana University Luddy School of Informatics Computing and Engineering View all articles by this author Stephen W. Porges Indiana University Bloomington Kinsey Institute for Research in Sex Gender and Reproduction View all articles by this author Metrics & Citations Metrics Article Usage 354 views 132 downloads .FvxKWukQNSOunydq8rnd { width: 100px; } Citations Download citation Shyama Shah, Gregory Lewis, Stephen W. Porges. Vagal Efficiency: A Novel Metrics Refined for Brainstem‑Specific Autonomic Control. Authorea . 21 July 2025. 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