Neuro-Cardiac Interactions of Transcutaneous Auricular Vagus Nerve Stimulation: A Focus on Stress Effects

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Alrikabi¹, Hakan Solmaz¹ This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7386946/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Transcutaneous auricular Vagus Nerve Stimulation (taVNS) has emerged as a promising non-invasive method for modulating the Autonomic Nervous System (ANS). However, its impact on cardiac autonomic regulation during acute stress remains underexplored. This study investigates taVNS effects on Heart Rate Variability (HRV) indices in response to psychological stress in healthy individuals across time and frequency domains. Sixty participants were randomly assigned to three groups: control, sham, and stimulation. Each underwent a three-phase experimental protocol: pre-stress, stress induction, and post-stress. Time domain (RR interval, pNN50, SDNN, RMSSD), frequency domain (HF, LF, LF/HF) were computed from ECG signals and analyzed using repeated-measures comparisons. Results revealed that stimulation group exhibited a sharper drop in RR intervals (753 ms pre-stress, 648 ms stress, and 745 ms post-stress), pNN50 (11.1% → 4.3% → 8.7%), and LF/HF rose from (0.6) under stress to (1.1) in recovery, suggesting enhanced vagal reactivation. While the sham group showed limited improvement, the control group demonstrated minimal restoration in pNN50. SDNN values for the stimulation group increased steadily (48.7 ms → 56.8 ms → 63.9 ms), indicating broader autonomic adaptability. These results indicate a targeted influence of taVNS on cardiac vagal tone and overall autonomic regulation, potentially promoting parasympathetic engagement under stress. Health sciences/Cardiology Biological sciences/Neuroscience Biological sciences/Physiology Transcutaneous Auricular Vagus Nerve Stimulation (taVNS) Heart Rate Variability (HRV) Psychological Stress Parasympathetic Activity Time-Domain Analysis Frequency-Domain Analysis Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Key Points • The Vagus nerve helps regulate heart rate and responds to signals from the brain and body. • We studied how a non-invasive ear stimulation method, called transcutaneous auricular Vagus Nerve Stimulation (taVNS), affects heart activity during stress. • We tested Heart Rate Variability (HRV), which measures how heartbeats vary over time, in healthy people before, during, and after a stressful task. • People who received real stimulation showed stronger recovery after stress, meaning their heart rhythms became more balanced again. • This study suggests that taVNS may help the body return to a relaxed state after stress, which could be useful for health and emotional well-being in the future. INTRODUCTION Electrophysiology refers to the study of electrical activity in the body. In the case of an Electrocardiogram (ECG), it specifically reflects the electrical signals of the heart. The heart typically beats 60 to 100 times per minute, amounting to over 100,000 beats per day. Heart Rate (HR) measurement is based on two principles: the pumping activity of the heart that causes blood flow and the examination of a pulse wave produced ]1[. When there's a noticeable change in HR, it often signals the need for a more detailed analysis—this is where Heart Rate Variability (HRV) comes in. HRV, which is the variability in the time intervals between consecutive heartbeats, is a non-invasive indicator derived from ECG data, reflecting the dynamic interaction between the Autonomic Nervous System (ANS) and the cardiovascular system. It represents how the ANS regulates the activity of the Sinoatrial (SA) node, using electrical signals from the heart to assess heart rate fluctuations in real time ]2[. The gold standard for assessing HRV involves detecting successive ECG peaks using surface electrodes placed on the skin ]3[. The medulla is the key region in the brain responsible for regulating sympathetic and parasympathetic signals directed to the heart and blood vessels, thereby controlling cardiac function. External environmental effects are known to affect the dominance of the sympathetic and parasympathetic systems, such as the increase or decrease in the HR and cardiac output, which namely is the volume of blood pumped by the heart in one minute ]4[. The Vagus Nerve (VN), also known as the tenth cranial nerve , is a central component of the parasympathetic nervous system and is often described as a “broad neural network” due to its extensive distribution and influence. It originates in the brainstem, specifically the medulla oblongata, and extends throughout the body, forming connections with major organs such as the heart, lungs, and abdominal viscera. Research has identified that the branches of the VN involved in cardiac regulation are in specific regions. Those that affect the SA node are near the right pulmonary vein, while those that affect the Atrioventricular (AV) node are near the lower left atrium. Both left and right Vagus nerves send signals to these heart-control areas ]5[. VN contains both sensory (afferent) fibers—comprising approximately 65–80% of its total fiber count—and motor (efferent) fibers, which account for around 20% 6. Activating the VN helps restore autonomic balance by influencing both central and peripheral components of the nervous system [ 7 ]. HRV is widely recognized as a key indicator of vagal activity. In ECG-based analysis, HRV is typically assessed by measuring the intervals between successive R-peaks, commonly referred to as RR intervals (or NN intervals when only normal beats are considered). Fluctuations in heart rate are known to reflect a variety of physiological and psychological influences, under both healthy and pathological conditions. Transcutaneous auricular Vagus Nerve Stimulation (taVNS) is a non-invasive technique designed to engage the vagal system by stimulating the auricular branch of the Vagus nerve. Because of the Vagus nerve’s central role in regulating cardiac function via its projections to brainstem nuclei, taVNS has attracted attention as a method to support vagal tone and potentially improve HRV. Evidence from both clinical and healthy populations suggests that taVNS can elicit parasympathetic activation and influence HRV-related physiological markers [ 8 ]. In this context, analyzing HRV serves as a practical and informative index to assess the autonomic effects of taVNS. Among the various HRV indices, time-domain measures such as RRinterval, SDNN, RMSSD, and pNN50 are especially sensitive to short-term and phase-specific autonomic changes. While frequency-domain measures such as LF, HF, and the LF/HF ratio provide insight into the sympathetic–parasympathetic balance and vagal modulation. These metrics enable researchers to evaluate not only baseline vagal tone but also the dynamic adaptability of the autonomic nervous system during stress and recovery. This study investigated how bilateral transcutaneous auricular Vagus Nerve Stimulation (taVNS) influences time and frequency domain HRV indices—specifically RRinterval, SDNN, RMSSD, pNN50, LF, HF, LF/HF—before, during, and after exposure to psychological stress in healthy individuals. METHODS A total of 60 healthy volunteers were randomly assigned to one of three groups: Control (n = 20), Sham (n = 20), or Stimulation (n = 20), according to predefined inclusion and exclusion criteria. Each group underwent three experimental phases, namely: pre-stress, stress induction, and post-stress, to evaluate whether taVNS modulates parasympathetic activity during periods of elevated sympathetic activation caused by acute stress. Ethical approval was obtained from the Non-Interventional Clinical Research Ethics Committee of Istanbul Medipol University (Decision No. 481, 2025) and deemed appropriate. All participants were anonymized through assigned ID numbers, and no identifiable participant information, images, or videos are included in this manuscript. Only individuals deemed physically and cognitively eligible were enrolled, and each provided written informed consent prior to participation. All methods were conducted in compliance with relevant guidelines and regulations. Data Collection : Prior to the experimental procedures, participants provided information regarding their demographic characteristics (Table 1 ), including age and Body Mass Index (BMI), as well as lifestyle-related factors. All measurements were conducted in a quiet room between 10:30 and 14:30 under standard laboratory lighting conditions. To minimize potential sources of interference, all electronic devices, including smartphones and other smart devices, were removed from the laboratory, and the air conditioning system was turned off. Before data collection, participants’ skin was prepared to ensure they were clean, dry, hair-free, and free of oils. Additionally, video recordings of the experimental sessions were collected to observe the behavioral response of each participant during the non-stress and stress-induced sessions. Table 1 Demographic and digital questionnaires for participant characterization. Parameter Control Mean or % ± SD Sham Mean or % ± SD Stimulation Mean or % ± SD Total Mean or % ± SD Number of subjects 20 20 20 60 Average age 22 ± 3.5 22 ± 3.0 23 ± 3.9 22 ± 3.4 Average BMI (kg/m) 2 25 ± 3.8 23 ± 3.6 23 ± 4.2 24 ± 3.9 The stress induction protocol used in this study was the Improvisation (IMPRO) Stress Test, a ten-minute procedure designed to elicit both cognitive and social stress. IMPRO consisted of three sequential tasks: free improvisation, a random word challenge, and a mental arithmetic task with increasing difficulty levels (easy, medium, and hard) 9. Participants were unfamiliar with the tasks before the experiment, and observers were present throughout the session to enhance the social evaluative component. For ECG monitoring, the Lead II configuration was used. Two electrodes were placed on the medial surfaces of both legs, just above the ankles, and a third electrode was positioned on the right anterior forearm at the wrist, in accordance with the manufacturer’s guidelines ]10[. Data Collection Setup Bilateral transcutaneous auricular Vagus Nerve Stimulation (taVNS) was delivered using the Vagustim® device (Vagustim Technologies), a non-invasive neuromodulation tool designed for individual use. The stimulation was applied via surface electrodes placed on the cymba conchae region of the auricle, consistent with protocols targeting the auricular branch of the VN. ECG data were collected using the BIOPAC Systems Inc. (MP36) in conjunction with the Biopac Student Lab software. Signal analyses were done on MATLAB R2024a, while data organization and statistical analyses were performed using Microsoft® Excel and IBM SPSS Statistics (Version 29.0.2.0; IBM Corp.). Graphs and visualizations were created using GraphPad Prism (Version 10.4.1). Each recording session lasted for a total of 20 minutes and was divided into three distinct phases. Depending on the experimental protocol, participants were instructed to either sit or stand. All three measurement periods were completed for each participant, with taVNS applied to both the stimulation and sham groups, while the sham group participants didn’t receive any real stimulation. The measurement phases during the three periods of measurement were as follows: Period 1 (Pre-Stimulation): The stimulator was not placed in the participant’s ear. Period 2 (Stimulation): Low intensity taVNS applied bilaterally (both ears) until a tingling sensation was felt. Period 3 (Post-Stimulation): The stimulator was removed. During Period 2, taVNS was delivered at an intensity just above each participant’s sensory detection threshold. This phase lasted 10 minutes, while Periods 1 and 3—serving as resting phases—each lasted 5 minutes. ECG recordings were collected throughout all three periods. Data Analysis ECG signals were pre-processed using standard artifact correction and feature extraction methods, as described in prior studies [ 11 , 12 ]. HR analysis was conducted by identifying R-peaks within the QRS complex, while HRV analysis focused on time and frequency domain measures to evaluate autonomic modulation. R-peak detection and quantification were performed using the MATLAB Signal Processing Toolbox, incorporating custom-modified code tailored to the study’s requirements. Once all peaks were accurately identified, RR intervals were calculated, enabling the computation of both HR and HRV indices. Time-domain parameters analyzed included RR interval, pNN50, SDNN, and RMSSD, which were derived from the NN intervals included in the data collected. The RR interval, which measures the time interval between two successive R peaks on an ECG, gives a direct sense of heart rate changes. As stress increases, RR intervals typically shorten, indicating sympathetic activation and vice versa. pNN50 reflects the percentage of adjacent heartbeats differing by more than 50 ms and is a valuable marker of parasympathetic tone. It is used to track how vagal activity responds to stress induction. SDNN reflects the standard deviation of normal-to-normal (NN) intervals over time and is widely used as a general indicator of overall HRV. It captures input from both sympathetic and parasympathetic branches, offering a broad picture of autonomic flexibility. And lastly, RMSSD, namely the Root Mean Square of Successive Differences, measures rapid, short-term fluctuations in heart rate and is closely tied to vagal modulation. While frequency-domain parameters analyzed included LF, HF, and LF/HF, which were calculated by Fast Fourier Transform (FFT) to transform a time-domain signal into its frequency components, producing a Power Spectral Density (PSD) estimate— power distribution (in ms 2 ) across the frequency range (in Hz) 13[. LF (Low Frequency) and HF (High Frequency) were calculated based on the spectral components, along with the LF/HF ratio. LF metric is associated with both sympathetic and parasympathetic activity and captures the sympathetic dominance. HF may be a direct measure of vagal tone and represents the parasympathetic dominance. LF/HF reflects the ANS balance, giving a comprehensive picture of vagal modulation effects on the nervous system. Statistical evaluations Data were first tested for normality. Since the assumptions for parametric testing were not met, within-group comparisons across the three experimental phases (pre-stress, stress, and post-stress) were performed using the non-parametric Mann–Whitney U test. Statistical analyses and visualizations of HRV parameter changes were conducted using GraphPad Prism software. RESULTS Before establishing the effects of the stimulation on stress management, it was important to test whether the experimental design might have induced stress in participants. This is tested by evaluating the changes in heart rate before, during, and after stress (Table 2 ). HR of control and sham groups has shown rises from the median during stress, followed by a return close to baseline, while HR of participants in the stimulation group shows the lowest HR increase during stress, and post-stress values decrease to nearly pre-stress levels. This might show a better adaptation of the heart rhythm between phases for the participants in the stimulation group. The HR-post phase represents the carry-over effect in the stimulation group. This suggests that taVNS may positively influence heart rhythm not only during stress, but also in the post-stress recovery phase. Table 2 Changes in HR in beats per minute (bpm) between groups and phases. Group Parameter pre-stress during stress post-stress Control (n = 20) Median [Q1–Q3] 83 (76–92) 105 (90–113) 85 (80–94) Sham (n = 20) Median [Q1–Q3] 80 (74–86) 96 (90–99) 85 (78–91) Stimulation (n = 20) Median [Q1–Q3] 79 (73–88) 94 (89–106) 80 (77–90) Time domain Time-domain analysis of HRV revealed distinct changes in autonomic function across the experimental phases. The use of taVNS appeared to promote parasympathetic modulation, particularly evident during the recovery period following stress. Among the evaluated parameters (RRinterval, pNN50, SDNN, and RMSSD), clear phase-dependent patterns were observed, reflecting shifts in cardiac autonomic regulation as participants transitioned from baseline to stress and back to recovery. The findings of RR interval, pNN50, SDNN, and RMSSD are presented in Table 3 , which reports the median and interquartile ranges (Q1–Q3) for each parameter across the experimental groups, and are also illustrated in Figs. 1 to 4 . Similarly, frequency-domain analysis revealed complementary patterns in autonomic dynamics. Changes in HF power were indicative of enhanced vagal activity during the post-stress recovery phase in the taVNS group, whereas LF power and the LF/HF ratio reflected the overall sympathovagal balance across phases. These results, summarized in Table 3 and illustrated in Figs. 5 to 7 , further support the modulatory effect of taVNS on cardiac autonomic function. Statistical evaluations indicated that most HRV metrics changed significantly over time within each group (Control, Sham, and Stimulation). This highlights the responsiveness of the ANS to both acute stress and vagal stimulation. These temporal changes likely reflect fluctuations in beat-to-beat interval timing, as sympathetic activity dominates under stress and vagal tone gradually returns during recovery. Table 3 Statistical test results for HRV parameters of the control, sham, and stimulation groups. Data are represented as the median and 1st and 3rd quartile values, namely, Median (Q1–Q3), based on the Mann-Whitney U test findings. Group Parameter Pre-Stress Stress Post-Stress Control (n = 20) RRinterval (ms) pNN50 (%) SDNN (ms) RMSSD (ms) LF (ms 2 ) HF (ms 2 ) LF/HF 731.0 (654.1–790.6) 3.7 (2.1–10.1) 44.7 (34.7–56.9) 27.5 (22.2–42.3) 557.0 (316.7–760.8) 722.0 (374.6–1371.0) 0.8 (0.5–1.0) 575.3 (534.8–671.0) 3.4 (1.4–5.2) 53.2 (48.6–63.7) 26.4 (23.7–46.5) 773.0 (535.7–1142.0) 1076.0 (731.4–1842.0) 0.7 (0.6–0.9) 710.0 (632.9–758.1) 5.2 (2.0–11.5) 66.9 (49.4–84.5) 30.7 (22.3–43.4) 644.0 (277.1–1006.0) 855.0 (513.4–1293.0) 0.7 (0.5–0.8) Sham (n = 20) RRinterval (ms) pNN50 (%) SDNN (ms) RMSSD (ms) LF (ms 2 ) HF (ms 2 ) LF/HF 742.0 (683.9–811.4) 10.6 (8.0–17.4) 50.3 (41.7–79.5) 41.7 (28.2–53.9) 561.0 (401.2–1004.0) 617.7 (458.0–1437.0) 0.9 (0.5–1.2) 620.3 (601–677.2) 6.9 (3.4–9.4) 65.0 (45.8–73.2) 39.7 (26.0–53.2) 1020.0 (820.7–1944.0) 1780.0 (1289.0–2204.0) 0.6 (0.4–0.7) 712.0 (662.2–786.5) 8.4 (5.7–13.3) 67.8 (57.4–76.0) 40.3 (29.8–54.8) 1068.0 (386.1–1529.0) 1222.0 (657.5–2064.0) 0.9 (0.5–0.8) Stimulation (n = 20) RRinterval (ms) pNN50 (%) SDNN (ms) RMSSD (ms) LF (ms 2 ) HF (ms 2 ) LF/HF 753.0 (668.4–857.6) 11.1 (3.0–13.3) 48.7 (32.5–55.0) 38.8 (22.1–48.6) 477.5 (201.6–785.6) 422.3 (245.1–1010.0) 1.1 (0.5–1.4) 648.0 (556.5–682.1) 4.3 (1.3–8.1) 56.8 (44.7–65.7) 34.0 (20.8–51.2) 663.0 (385.8–1244.0) 1105.0 (774.5–1620.0) 0.6 (0.5–1.0) 745.0 (645.1–802.2) 8.7 (4.2–11.7) 63.9 (46.2–89.2) 36.7 (28.0–53.3) 597.3 (241.3–872.1) 512.1 (400.7–993.4) 1.1 (0.5–1.3) RRinterval Analysis Across Experimental Phases During the stress phase, a pronounced decrease in RRinterval was observed in all groups, indicating a shift toward sympathetic dominance under acute stress conditions, with the stimulation group showing the most pronounced recovery post-stress. In the stimulation group, the RRinterval dropped from 753 ms (pre-stress) to 648 ms (stress), followed by a notable recovery to 745 ms post-stress. This considerable change suggests that taVNS may enhance vagal reactivation and facilitate faster cardiac recovery following stress exposure. The sham group exhibited a similar pattern with RRinterval decreasing from 742 ms to 620 ms, then partially recovering to 712 ms post-stress, implying a limited recovery, possibly due to placebo effects or non-specific factors. In contrast, the control group showed the sharpest drop (from 731 ms to 575 ms), with only partial recovery to 710 ms, reflecting minimal autonomic restoration in the absence of any stimulation. These findings support the hypothesis that taVNS modulates cardiac autonomic function, primarily by promoting parasympathetic re-engagement after sympathetic activation. pNN50 Analysis Across Experimental Phases The pNN50 parameter, representing the percentage of successive normal heartbeats that differ by more than 50 milliseconds, is a well-established marker of parasympathetic (vagal) activity. Across all groups, pNN50 values demonstrated phase-dependent variation, with the most prominent changes occurring in the stimulation group (Fig. 2 ). In the stimulation group, the baseline pNN50 was relatively high (11.1%) during the pre-stress phase, which is consistent with elevated vagal tone. During the stress phase, pNN50 dropped significantly to 4.3%, indicating sympathetic dominance and vagal withdrawal under acute stress. Following stimulation, pNN50 rebounded to 8.7%, which might suggest that taVNS promoted parasympathetic reactivation and cardiac recovery. The sham group also showed a decline in pNN50 from 10.6–6.9% during stress, followed by a moderate increase to 8.4% post-stress. While this suggests some recovery, the absence of real vagal stimulation limits the extent of parasympathetic engagement. In contrast, the control group maintained consistently low pNN50 values across all phases (3.7%, 3.4%, and 5.2%, respectively), indicating minimal vagal responsiveness and no meaningful autonomic recovery. Overall, these results highlight pNN50 as a sensitive indicator of taVNS efficacy, reflecting both the stress-induced vagal suppression and the subsequent restoration of parasympathetic activity. SDNN Analysis Across Experimental Phases SDNN (Standard Deviation of NN intervals) reflects overall HRV and is influenced by both sympathetic and parasympathetic branches of the ANS. Across all groups, SDNN values increased progressively from pre-stress to post-stress, reflecting dynamic autonomic adaptations to stress and recovery. In the sham group, SDNN showed the most pronounced rise, from 50.3 ms (pre-stress) to 65.0 ms (stress), peaking at 67.8 ms (post-stress). This pattern suggests that even without active stimulation, anticipation, or placebo-related factors may contribute to increased variability. The stimulation group also exhibited a steady increase from 48.7 ms (pre-stress) to 56.8 ms (stress), reaching 63.9 ms (post-stress), supporting the idea that taVNS enhances overall autonomic flexibility during the recovery phase. In the control group, SDNN increased from 44.7 ms (pre-stress) to 66.9 ms (post-stress), indicating a delayed but robust autonomic response. However, without vagal stimulation, the mechanisms driving this increase may reflect non-specific stress adaptation rather than targeted modulation. RMSSD Analysis Across Experimental Phases RMSSD (Root Mean Square of Successive Differences) is a more specific time-domain metric reflecting short-term vagal (parasympathetic) activity. The parameter was particularly informative for assessing the effects of taVNS on parasympathetic rebound. In the stimulation group, RMSSD declined from 38.8 ms (pre-stress) to 34.0 ms (stress), followed by a partial recovery to 36.7 ms (post-stress). This pattern aligns with parasympathetic withdrawal under stress and partial reactivation with taVNS, although the recovery was not complete. Similarly, the sham group showed a slight reduction from 41.7 ms (pre-stress) to 39.7 ms (stress), then stabilization at 40.3 ms (post-stress), suggesting modest vagal fluctuations, possibly due to psychological or environmental effects rather than physiological stimulation. The control group remained relatively stable across all phases, namely 27.5 ms (pre-stress), 26.4 ms (stress), and 30.7 ms (post-stress), indicating limited autonomic responsiveness in the absence of intervention. These findings demonstrate that RMSSD, as a parasympathetic-specific indicator, is sensitive to both stress-induced vagal suppression and stimulation-driven recovery, particularly when interpreted alongside pNN50, and are consistent with previous findings in the literature and align with expectations based on earlier studies [ 14 – 17 ]. LF Analysis Across Experimental Phases The LF (Low Frequency) band oscillations are reported to be in the range of 0.04–0.15 Hz and generate the highest classification rate compared to the other statistical features. This metric is associated with both sympathetic and parasympathetic activity, usually considered as a marker of how active the sympathetic system is. LF power increased in the control group from 557 ms 2 to 773 ms 2 during stress, then slightly decreased to 644 ms 2 post-stress, indicating typical sympathetic activation with limited recovery. The sham group showed a strong LF increase from 561 ms 2 to 1020 ms 2 during stress and further to 1068 ms 2 after, suggesting prolonged sympathetic arousal, possibly linked to anticipatory effects. In contrast, the stimulation group had a milder LF rise (477.5 ms 2 → 663 ms 2 ) and a post-stress drop to 597.3 ms 2 , suggesting that taVNS dampened the sympathetic response and aided autonomic recovery. The control and sham groups faced a significant increase in LF metric between pre and stress phases, “sympathetic activation,” which was expected. Compared with the stimulation group, which does not show this increase, these patterns support the role of Vagus nerve stimulation in promoting better autonomic regulation under stress. HF Analysis Across Experimental Phases HF (High Frequency), another metric of the frequency domain, may be a direct measure of vagal tone and is typically associated with respiratory sinus arrhythmia. HF band oscillations are reported to be in the range of 0.15–0.4 Hz. Contrary to theoretical expectations, our results presented no decreased HF during stress, widely associated with vagal withdrawal [ 18 , 19 ]. In the control group, HF increased from 722 ms 2 at baseline to 1076 ms 2 during stress, followed by a moderate decline to 855 ms 2 post-stress. This unusual stress-phase increase may suggest compensatory vagal activation or interindividual variability. The sham group showed a dramatic HF rise from 618 ms 2 to 1780 ms 2 during stress, with a drop to 1222 ms 2 post-stress. This exaggerated parasympathetic pattern may reflect a placebo-related overcompensation or stress-related misinterpretation. In contrast, the stimulation group started with a low HF (422 ms 2 ), increased to 1105 ms 2 during stress, and slightly declined to 512 ms 2 post-stress. This sharp rise and partial retention suggest effective vagal engagement under stress and a more stable autonomic shift. Overall, these findings indicate that taVNS may support parasympathetic modulation, though the complex HF responses across groups suggest further investigation is needed into context-dependent vagal dynamics. LF/HF Analysis Across Experimental Phases The Low Frequency/High Frequency ratio represents the ANS balance—where elevated values suggest sympathetic dominance, and lower values indicate stronger parasympathetic influence. The statistical significance of the stress phase (p = 0.038) in the sham group indicates a placebo effect, which we could see in the change of values between 0.9 (pre-stress) and the highly drop of 0.6 (stress), then rebound to 0.9 (post-stress). This pattern may indicate some form of temporary vagal activation or reduction in sympathetic tone during the stress task, perhaps because of some anticipatory effects or participant expectations. The sham and control groups show relatively stable values in LF/HF post return close to baseline, suggesting autonomic rebalancing after the stressor. In the stimulation group, the variation between phases’ values was indicated by 1.1 (pre-stress), 0.6 (stress), and 1.1 (post-stress This suggests that the effect of stimulation may facilitate autonomic recovery and modulate sympathetic-parasympathetic balance, promoting faster return to baseline homeostasis. DISCUSSION This study investigated the effects of bilateral transcutaneous auricular Vagus Nerve Stimulation (taVNS) on cardiac autonomic regulation in healthy individuals, under conditions of real-time stress. Participants were randomly assigned to control, sham, or stimulation groups and underwent three experimental phases: pre-stress, stress, and post-stress. Heart Rate Variability (HRV) was evaluated using time-domain indices to characterize shifts in autonomic balance across phases. Among the time domain HRV parameters, pNN50 and RMSSD are well-established indicators of parasympathetic modulation, while SDNN reflects overall HRV, influenced by both branches of the autonomic nervous system [ 2 , 20 ]. In line with previous findings, this study observed significant fluctuations in HRV variables across time. Notably, pNN50 levels in the stimulation group decreased sharply during the stress phase and rebounded during the post-stress period, indicating a parasympathetic recovery facilitated by taVNS. In contrast, the control group showed minimal variation, and the sham group exhibited only partial recovery, suggesting that the observed effects are likely due to real vagal stimulation rather than placebo or expectation. The RMSSD values showed similar trends, although changes were less pronounced and not statistically significant between groups. As RMSSD reflects rapid, short-term vagal fluctuations [ 21 , 22 ], the pattern still suggests some degree of taVNS-induced parasympathetic engagement. SDNN increased significantly in the stimulation group, with median values rising steadily from pre-stress to post-stress phases. Since SDNN represents broader autonomic variability, its enhancement may reflect a global autonomic adaptability reinforced by vagal stimulation. The participants with higher baseline SDNN values tended to exhibit stronger autonomic flexibility across phases. The frequency domain variables ratio, LF/HF showed no significant change in the stimulation group against the control group. Median values decreased during the stress phase in both the sham and stimulation groups, contrary to the expected increase in the control group. This suggests that the participants of the sham group could have induced sensations similar to those in the stimulation group. Upon further inspection of the data, the overall distribution shifted downward irreversibly for both the sham and stimulation groups compared to that of the control. This indicates that individuals with a high LF/HF baseline value (indicative of an imbalanced ANS) experienced a decrease in LF/HF during stimulation, maintaining the distribution range in the post phase, leading to a more balanced system. Independently, LF showed no significant change in the stimulation group during stress, confirming the effect of stimulation and its role in regulating sympathetic dominance. The relationship between HF and the parasympathetic system is complex (as illustrated in this study); HF (the respiratory band) provides a different understanding of what should decrease during stress. Variations in study design and taVNS protocols contribute to the heterogeneity across studies, making it essential to identify potential moderator and mediator variables. The change in HF between group phases does not necessarily indicate improved vagal tone; if this increases under stress, it may suggest over-activation of the parasympathetic system and suppressed heart rate variability [ 23 , 24 ]. Additionally, HF power may be sensitive to breathing frequency, which differentiates this distribution in the HF range [ 19 ]. Evaluating this parameter in this study suggests that HF reflects the HRV distributions, representing parasympathetic and sympathetic activity together. This suggests that baseline HRV may serve as a predictor of resilience, echoing findings from other work that link autonomic variability to both physiological adaptability and cognitive-emotional processing under pressure. In summary, the results support the conclusion that taVNS facilitates parasympathetic recovery following acute stress, with effects most evident in pNN50, SDNN, LF, HF, and LF/HF indices. While further research is needed to explore individual variability, long-term stimulation effects, and underlying neural mechanisms, these findings contribute to the growing evidence base for non-invasive vagal stimulation as a tool for autonomic regulation. The mechanisms underlying the observed parasympathetic reactivation are still not entirely understood. One possible explanation is offered by homeostatic adaptation theories, which suggest that controlled or transient stress may promote physiological resilience, enabling individuals to return to baseline or even an enhanced autonomic state [ 25 ]. From a neurobiological perspective, it has also been proposed that stress-related neuromodulators may influence large-scale neuronal dynamics, altering functional patterns across brain regions involved in autonomic control [ 26 ]. Within this framework, taVNS may act as a neuromodulatory tool, reinforcing adaptive brain-heart communication and supporting physiological recovery under stress. CONCLUSION In this study, we examined how bilateral taVNS influences cardiac autonomic regulation before, during, and after acute stress. The findings suggest that taVNS may support the reactivation of parasympathetic activity in the recovery period, particularly reflected in the pNN50 and SDNN measures. Participants who received active stimulation showed clearer signs of autonomic rebound compared to those in the sham and control groups. Although some parameters, such as RMSSD, did not show statistically significant differences between groups, the overall pattern was consistent with enhanced vagal modulation, whereas frequency-domain outcomes provide additional context to the autonomic patterns observed in the time-domain measures. The LF values remained relatively stable across phases in the stimulation group, in contrast to the significant increases seen in the sham and control groups—an effect that likely reflects reduced sympathetic activation due to taVNS. While HF power unexpectedly peaked during the stress phase across all groups, only the stimulation group showed a sharp decline in the post-stress period, suggesting a distinct recovery trajectory. The LF/HF ratio further supports this interpretation, as the stimulation group maintained a more balanced profile across phases, whereas the sham group showed a transient disruption during stress. These results offer additional support for the potential use of taVNS in modulating stress responses, especially in contexts where autonomic flexibility plays a key role. Further research is needed to clarify the underlying mechanisms and determine how individual baseline differences may shape the physiological response to stimulation. Declarations AUTHOR CONTRIBUTIONS STATEMENT Amani Alrikabi: Conceptualization, Methodology, Investigation, Data curation, Formal analysis, Visualization, Writing – original draft; Asst. Prof. Hakan Solmaz: Supervision, Validation, Writing – review & editing. ADDITIONAL INFORMATION Competing interests The author(s) declare no competing interests. FUNDING This research received no external funding. Author Contribution Amani Alrikabi: Conceptualization, Methodology, Investigation, Data curation, Formal analysis, Visualization, Writing – original draft; Asst. Prof. Hakan Solmaz: Supervision, Validation, Writing – review & editing. Acknowledgement The authors would like to thank Prof. Dr. Abdulameer Nasser Ghaloub, Prof. Dr. Lamyaa Yaseen Zghair, Dr. Ali Veysel Özden, and Dr. Mehmet Ozansoy for their valuable guidance and insightful suggestions throughout the development of this research. Data Availability The datasets generated and analysed during the current study, including HRV time and frequency domain, are not publicly available due to participant privacy and confidentiality requirements. However, anonymized datasets are available from the corresponding author upon reasonable request, provided that the request is compliant with ethical approval and institutional data-sharing policies. References Hon, E. H. & Lee, S. T. Electronic evaluation of the fetal heart rate. VIII. Patterns preceding fetal death further observations. Am. J. Obstet. Gynecol. 87 , 814–826 (1963). 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. Circulation 93 , 1043–1065 (1996). Bachler, M., Mayer, C., Hametner, B., Wassertheurer, S. & Holzinger, A. 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Effects of short and prolonged transcutaneous vagus nerve stimulation on heart rate variability in healthy subjects. Auton. Neurosci. 203 , 88–96. https://doi.org/10.1016/j.autneu.2016.11.003 (2016). DeGiorgio, C. M. et al. RMSSD, a measure of vagus-mediated heart rate variability, is associated with risk factors for SUDEP: The SUDEP 7 Inventory. Epilepsy Behav. 19 , 78–81. https://doi.org/10.1016/j.yebeh.2010.06.011 (2010). Goldberger, J. J., Challapalli, S., Tung, R., Parker, M. A. & Kadish, A. H. Relationship of heart rate variability to parasympathetic effect. Circulation 103 , 1977–1983. https://doi.org/10.1161/01.cir.103.15.1977 (2001). Grossman, P. & Taylor, E. W. Toward understanding respiratory sinus arrhythmia: Relations to cardiac vagal tone, evolution, and biobehavioral functions. Biol. Psychol. 74 , 263–285. https://doi.org/10.1016/j.biopsycho.2005.11.014 (2006). Yoo, H. H., Yune, S. J., Im, S. J., Kam, B. S. & Lee, S. Y. Heart rate variability-measured stress and academic achievement in medical students. Med Princ Pract (2021). Castillo, G. et al. Transcutaneous cervical vagus nerve stimulation induces changes in the electroencephalogram and heart rate variability of healthy dogs: A pilot study. Front. Vet. Sci. 9 , 878962. https://doi.org/10.3389/fvets.2022.878962 (2022). Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7386946","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":510696496,"identity":"eefa7481-2dc0-426c-b2e9-2bdcb89b6b5c","order_by":0,"name":"Amani A. Alrikabi¹","email":"data:image/png;base64,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","orcid":"","institution":"Bahçeşehir University","correspondingAuthor":true,"prefix":"","firstName":"Amani","middleName":"A.","lastName":"Alrikabi¹","suffix":""},{"id":510696497,"identity":"e3ce99ac-5834-4d02-b9a6-f4f1b9093feb","order_by":1,"name":"Hakan Solmaz¹","email":"","orcid":"","institution":"Bahçeşehir University","correspondingAuthor":false,"prefix":"","firstName":"Hakan","middleName":"","lastName":"Solmaz¹","suffix":""}],"badges":[],"createdAt":"2025-08-16 10:53:09","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7386946/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7386946/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":91067612,"identity":"eaa823b4-8add-41be-a51a-161230af42cf","added_by":"auto","created_at":"2025-09-11 10:13:17","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":78880,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eRRinterval variations of each group between phases (**p \u0026lt; 0.01; ***p \u0026lt; 0.001; without asterisks are not significant).\u003c/em\u003e \u003cem\u003e(Pre: pre-stress, Stress: During stress, Post: Post-stress).\u003c/em\u003e\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-7386946/v1/ca7c209e9b84460176b293e2.png"},{"id":91067593,"identity":"1de9b6ff-afe5-4e2e-83bf-2f211d22cb83","added_by":"auto","created_at":"2025-09-11 10:13:15","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":64775,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003epNN50 variations of each group between phases (*p \u0026lt; 0.05; **p \u0026lt; 0.01; without asterisks are not significant). (Pre: pre-stress, Stress: During stress, Post: Post-stress).\u003c/em\u003e\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-7386946/v1/55cf54729df943103aeb11fa.png"},{"id":91068463,"identity":"1cc31fc0-9c32-492f-ac13-199cc93aba9e","added_by":"auto","created_at":"2025-09-11 10:21:16","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":65252,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eSDNN variations of each group between phases (*p \u0026lt; 0.05; **p \u0026lt; 0.01; ***p \u0026lt; 0.001; without asterisks are not significant). (Pre: pre-stress, Stress: During stress, Post: Post-stress).\u003c/em\u003e\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-7386946/v1/895a343bde5c7b75f0674a33.png"},{"id":91068464,"identity":"d2370b19-6019-41a1-a4d4-1b2469f73282","added_by":"auto","created_at":"2025-09-11 10:21:16","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":66671,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eRMSSD values of each group between phases, without asterisks, are not significant.\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e(Pre: pre-stress, Stress: During stress, Post: Post-stress).\u003c/em\u003e\u003c/p\u003e","description":"","filename":"floatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-7386946/v1/b58715a960ecb27c3a3fae80.png"},{"id":91067596,"identity":"15340595-affe-457e-8cbb-92fada71ed37","added_by":"auto","created_at":"2025-09-11 10:13:16","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":71126,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eSpectral power for the LF values of each group between phases (*p \u0026lt; 0.05; **p \u0026lt; 0.01; without asterisks are not significant). (Pre: pre-stress, Stress: During stress, Post: Post-stress).\u003c/em\u003e\u003c/p\u003e","description":"","filename":"floatimage5.png","url":"https://assets-eu.researchsquare.com/files/rs-7386946/v1/53f49d752fdfaf164fd6cf8e.png"},{"id":91068469,"identity":"746d9052-371c-4b95-bb8c-7861371556a9","added_by":"auto","created_at":"2025-09-11 10:21:16","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":73323,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eSpectral power for the HF values of each group between phases (*p \u0026lt; 0.05; **p \u0026lt; 0.01; ***p \u0026lt; 0.001; without asterisks are not significant). (Pre: pre-stress, Stress: During stress, Post: Post-stress).\u003c/em\u003e\u003c/p\u003e","description":"","filename":"floatimage6.png","url":"https://assets-eu.researchsquare.com/files/rs-7386946/v1/c5dceb89b052bde410e576b5.png"},{"id":91067604,"identity":"9739d3c6-0a1a-4023-979e-2ba145bf08fe","added_by":"auto","created_at":"2025-09-11 10:13:16","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":58659,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eSpectral power for the LF/HF values of each group between phases (*p \u0026lt; 0.05; without asterisks are not significant). (Pre: pre-stress, Stress: During stress, Post: Post-stress).\u003c/em\u003e\u003c/p\u003e","description":"","filename":"floatimage7.png","url":"https://assets-eu.researchsquare.com/files/rs-7386946/v1/a08e23698425e0a22f2e2c83.png"},{"id":92924963,"identity":"42dbb7b0-4075-48f2-a28d-ea120444caf3","added_by":"auto","created_at":"2025-10-07 07:39:54","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1160475,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7386946/v1/86c94771-fee8-4346-8568-4016636c137d.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"\u003cp\u003eNeuro-Cardiac Interactions of Transcutaneous Auricular Vagus Nerve Stimulation: A Focus on Stress Effects\u003c/p\u003e","fulltext":[{"header":"Key Points","content":"\u003cp\u003e\u0026bull; The Vagus nerve helps regulate heart rate and responds to signals from the brain and body.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026bull; We studied how a non-invasive ear stimulation method, called transcutaneous auricular Vagus Nerve Stimulation (taVNS), affects heart activity during stress.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026bull; We tested Heart Rate Variability (HRV), which measures how heartbeats vary over time, in healthy people before, during, and after a stressful task.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026bull; People who received real stimulation showed stronger recovery after stress, meaning their heart rhythms became more balanced again.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026bull; This study suggests that taVNS may help the body return to a relaxed state after stress, which could be useful for health and emotional well-being in the future.\u003c/p\u003e"},{"header":"INTRODUCTION","content":"\u003cp\u003eElectrophysiology refers to the study of electrical activity in the body. In the case of an Electrocardiogram (ECG), it specifically reflects the electrical signals of the heart. The heart typically beats 60 to 100 times per minute, amounting to over 100,000 beats per day. Heart Rate (HR) measurement is based on two principles: the pumping activity of the heart that causes blood flow and the examination of a pulse wave produced ]1[. When there's a noticeable change in HR, it often signals the need for a more detailed analysis\u0026mdash;this is where Heart Rate Variability (HRV) comes in. HRV, which is the variability in the time intervals between consecutive heartbeats, is a non-invasive indicator derived from ECG data, reflecting the dynamic interaction between the Autonomic Nervous System (ANS) and the cardiovascular system. It represents how the ANS regulates the activity of the Sinoatrial (SA) node, using electrical signals from the heart to assess heart rate fluctuations in real time ]2[. The gold standard for assessing HRV involves detecting successive ECG peaks using surface electrodes placed on the skin ]3[.\u003c/p\u003e\u003cp\u003eThe medulla is the key region in the brain responsible for regulating sympathetic and parasympathetic signals directed to the heart and blood vessels, thereby controlling cardiac function. External environmental effects are known to affect the dominance of the sympathetic and parasympathetic systems, such as the increase or decrease in the HR and cardiac output, which namely is the volume of blood pumped by the heart in one minute ]4[.\u003c/p\u003e\u003cp\u003eThe Vagus Nerve (VN), also known as the \u003cem\u003etenth cranial nerve\u003c/em\u003e, is a central component of the parasympathetic nervous system and is often described as a \u0026ldquo;broad neural network\u0026rdquo; due to its extensive distribution and influence. It originates in the brainstem, specifically the medulla oblongata, and extends throughout the body, forming connections with major organs such as the heart, lungs, and abdominal viscera. Research has identified that the branches of the VN involved in cardiac regulation are in specific regions. Those that affect the SA node are near the right pulmonary vein, while those that affect the Atrioventricular (AV) node are near the lower left atrium. Both left and right Vagus nerves send signals to these heart-control areas ]5[. VN contains both sensory (afferent) fibers\u0026mdash;comprising approximately 65\u0026ndash;80% of its total fiber count\u0026mdash;and motor (efferent) fibers, which account for around 20% 6. Activating the VN helps restore autonomic balance by influencing both central and peripheral components of the nervous system [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eHRV is widely recognized as a key indicator of vagal activity. In ECG-based analysis, HRV is typically assessed by measuring the intervals between successive R-peaks, commonly referred to as RR intervals (or NN intervals when only normal beats are considered). Fluctuations in heart rate are known to reflect a variety of physiological and psychological influences, under both healthy and pathological conditions.\u003c/p\u003e\u003cp\u003eTranscutaneous auricular Vagus Nerve Stimulation (taVNS) is a non-invasive technique designed to engage the vagal system by stimulating the auricular branch of the Vagus nerve. Because of the Vagus nerve\u0026rsquo;s central role in regulating cardiac function via its projections to brainstem nuclei, taVNS has attracted attention as a method to support vagal tone and potentially improve HRV. Evidence from both clinical and healthy populations suggests that taVNS can elicit parasympathetic activation and influence HRV-related physiological markers [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. In this context, analyzing HRV serves as a practical and informative index to assess the autonomic effects of taVNS. Among the various HRV indices, time-domain measures such as RRinterval, SDNN, RMSSD, and pNN50 are especially sensitive to short-term and phase-specific autonomic changes. While frequency-domain measures such as LF, HF, and the LF/HF ratio provide insight into the sympathetic\u0026ndash;parasympathetic balance and vagal modulation. These metrics enable researchers to evaluate not only baseline vagal tone but also the dynamic adaptability of the autonomic nervous system during stress and recovery. This study investigated how bilateral transcutaneous auricular Vagus Nerve Stimulation (taVNS) influences time and frequency domain HRV indices\u0026mdash;specifically RRinterval, SDNN, RMSSD, pNN50, LF, HF, LF/HF\u0026mdash;before, during, and after exposure to psychological stress in healthy individuals.\u003c/p\u003e"},{"header":"METHODS","content":"\u003cp\u003eA total of 60 healthy volunteers were randomly assigned to one of three groups: Control (n\u0026thinsp;=\u0026thinsp;20), Sham (n\u0026thinsp;=\u0026thinsp;20), or Stimulation (n\u0026thinsp;=\u0026thinsp;20), according to predefined inclusion and exclusion criteria. Each group underwent three experimental phases, namely: pre-stress, stress induction, and post-stress, to evaluate whether taVNS modulates parasympathetic activity during periods of elevated sympathetic activation caused by acute stress. Ethical approval was obtained from the Non-Interventional Clinical Research Ethics Committee of Istanbul Medipol University (Decision No. 481, 2025) and deemed appropriate. All participants were anonymized through assigned ID numbers, and no identifiable participant information, images, or videos are included in this manuscript. Only individuals deemed physically and cognitively eligible were enrolled, and each provided written informed consent prior to participation. All methods were conducted in compliance with relevant guidelines and regulations.\u003c/p\u003e\u003cp\u003e\u003cem\u003eData Collection\u003c/em\u003e: Prior to the experimental procedures, participants provided information regarding their demographic characteristics (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e), including age and Body Mass Index (BMI), as well as lifestyle-related factors. All measurements were conducted in a quiet room between 10:30 and 14:30 under standard laboratory lighting conditions. To minimize potential sources of interference, all electronic devices, including smartphones and other smart devices, were removed from the\u003c/p\u003e\u003cp\u003elaboratory, and the air conditioning system was turned off. Before data collection, participants\u0026rsquo; skin was prepared to ensure they were clean, dry, hair-free, and free of oils. Additionally, video recordings of the experimental sessions were collected to observe the behavioral response of each participant during the non-stress and stress-induced sessions.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eDemographic and digital questionnaires for participant characterization.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eParameter\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eControl\u003c/p\u003e\u003cp\u003eMean or % \u0026plusmn; SD\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSham\u003c/p\u003e\u003cp\u003eMean or % \u0026plusmn; SD\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eStimulation\u003c/p\u003e\u003cp\u003eMean or % \u0026plusmn; SD\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eTotal\u003c/p\u003e\u003cp\u003eMean or % \u0026plusmn; SD\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNumber of subjects\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e20\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e20\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e20\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e60\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAverage age\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e22\u0026thinsp;\u0026plusmn;\u0026thinsp;3.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e22\u0026thinsp;\u0026plusmn;\u0026thinsp;3.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e23\u0026thinsp;\u0026plusmn;\u0026thinsp;3.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e22\u0026thinsp;\u0026plusmn;\u0026thinsp;3.4\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAverage BMI (kg/m)\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e25\u0026thinsp;\u0026plusmn;\u0026thinsp;3.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e23\u0026thinsp;\u0026plusmn;\u0026thinsp;3.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e23\u0026thinsp;\u0026plusmn;\u0026thinsp;4.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e24\u0026thinsp;\u0026plusmn;\u0026thinsp;3.9\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eThe stress induction protocol used in this study was the Improvisation (IMPRO) Stress Test, a ten-minute procedure designed to elicit both cognitive and social stress. IMPRO consisted of three sequential tasks: free improvisation, a random word challenge, and a mental arithmetic task with increasing difficulty levels (easy, medium, and hard) 9. Participants were unfamiliar with the tasks before the experiment, and observers were present throughout the session to enhance the social evaluative component. For ECG monitoring, the Lead II configuration was used. Two electrodes were placed on the medial surfaces of both legs, just above the ankles, and a third electrode was positioned on the right anterior forearm at the wrist, in accordance with the manufacturer\u0026rsquo;s guidelines ]10[.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eData Collection Setup\u003c/strong\u003e\u003cp\u003eBilateral transcutaneous auricular Vagus Nerve Stimulation (taVNS) was delivered using the Vagustim\u0026reg; device (Vagustim Technologies), a non-invasive neuromodulation tool designed for individual use. The stimulation was applied via surface electrodes placed on the cymba conchae region of the auricle, consistent with protocols targeting the auricular branch of the VN. ECG data were collected using the BIOPAC Systems Inc. (MP36) in conjunction with the Biopac Student Lab software. Signal analyses were done on MATLAB R2024a, while data organization and statistical analyses were performed using Microsoft\u0026reg; Excel and IBM SPSS Statistics (Version 29.0.2.0; IBM Corp.). Graphs and visualizations were created using GraphPad Prism (Version 10.4.1). Each recording session lasted for a total of 20 minutes and was divided into three distinct phases. Depending on the experimental protocol, participants were instructed to either sit or stand. All three measurement periods were completed for each participant, with taVNS applied to both the stimulation and sham groups, while the sham group participants didn\u0026rsquo;t receive any real stimulation.\u003c/p\u003e\u003c/p\u003e\u003cp\u003eThe measurement phases during the three periods of measurement were as follows:\u003c/p\u003e\u003cp\u003e\u003cul\u003e\u003cli\u003e\u003cp\u003ePeriod 1 (Pre-Stimulation): The stimulator was not placed in the participant\u0026rsquo;s ear.\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003ePeriod 2 (Stimulation): Low intensity taVNS applied bilaterally (both ears) until a tingling sensation was felt.\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003ePeriod 3 (Post-Stimulation): The stimulator was removed.\u003c/p\u003e\u003c/li\u003e\u003c/ul\u003e\u003c/p\u003e\u003cp\u003e During Period 2, taVNS was delivered at an intensity just above each participant\u0026rsquo;s sensory detection threshold. This phase lasted 10 minutes, while Periods 1 and 3\u0026mdash;serving as resting phases\u0026mdash;each lasted 5 minutes. ECG recordings were collected throughout all three periods.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eData Analysis\u003c/strong\u003e\u003cp\u003eECG signals were pre-processed using standard artifact correction and feature extraction methods, as described in prior studies [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. HR analysis was conducted by identifying R-peaks within the QRS complex, while HRV analysis focused on time and frequency domain measures to evaluate autonomic modulation. R-peak detection and quantification were performed using the MATLAB Signal Processing Toolbox, incorporating custom-modified code tailored to the study\u0026rsquo;s requirements. Once all peaks were accurately identified, RR intervals were calculated, enabling the computation of both HR and HRV indices.\u003c/p\u003e\u003c/p\u003e\u003cp\u003eTime-domain parameters analyzed included RR interval, pNN50, SDNN, and RMSSD, which were derived from the NN intervals included in the data collected. The RR interval, which measures the time interval between two successive R peaks on an ECG, gives a direct sense of heart rate changes. As stress increases, RR intervals typically shorten, indicating sympathetic activation and vice versa. pNN50 reflects the percentage of adjacent heartbeats differing by more than 50 ms and is a valuable marker of parasympathetic tone. It is used to track how vagal activity responds to stress induction. SDNN reflects the standard deviation of normal-to-normal (NN) intervals over time and is widely used as a general indicator of overall HRV. It captures input from both sympathetic and parasympathetic branches, offering a broad picture of autonomic flexibility. And lastly, RMSSD, namely the Root Mean Square of Successive Differences, measures rapid, short-term fluctuations in heart rate and is closely tied to vagal modulation.\u003c/p\u003e\u003cp\u003eWhile frequency-domain parameters analyzed included LF, HF, and LF/HF, which were calculated by Fast Fourier Transform (FFT) to transform a time-domain signal into its frequency components, producing a Power Spectral Density (PSD) estimate\u0026mdash; power distribution (in ms\u003csup\u003e2\u003c/sup\u003e) across the frequency range (in Hz) 13[. LF (Low Frequency) and HF (High Frequency) were calculated based on the spectral components, along with the LF/HF ratio. LF metric is associated with both sympathetic and parasympathetic activity and captures the sympathetic dominance. HF may be a direct measure of vagal tone and represents the parasympathetic dominance. LF/HF reflects the ANS balance, giving a comprehensive picture of vagal modulation effects on the nervous system.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eStatistical evaluations\u003c/strong\u003e\u003cp\u003eData were first tested for normality. Since the assumptions for parametric testing were not met, within-group comparisons across the three experimental phases (pre-stress, stress, and post-stress) were performed using the non-parametric Mann\u0026ndash;Whitney U test. Statistical analyses and visualizations of HRV parameter changes were conducted using GraphPad Prism software.\u003c/p\u003e\u003c/p\u003e"},{"header":"RESULTS","content":"\u003cp\u003eBefore establishing the effects of the stimulation on stress management, it was important to test whether the experimental design might have induced stress in participants. This is tested by evaluating the changes in heart rate before, during, and after stress (Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e). HR of control and sham groups has shown rises from the median during stress, followed by a return close to baseline, while HR of participants in the stimulation group shows the lowest HR increase during stress, and post-stress values decrease to nearly pre-stress levels. This might show a better adaptation of the heart rhythm between phases for the participants in the stimulation group. The HR-post phase represents the carry-over effect in the stimulation group. This suggests that taVNS may positively influence heart rhythm not only during stress, but also in the post-stress recovery phase.\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n \u003ctable id=\"Tab2\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eChanges in HR in beats per minute (bpm) between groups and phases.\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eGroup\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eParameter\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003epre-stress\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eduring stress\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003epost-stress\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eControl (n\u0026thinsp;=\u0026thinsp;20)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eMedian [Q1\u0026ndash;Q3]\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e83 (76\u0026ndash;92)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e105 (90\u0026ndash;113)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e85 (80\u0026ndash;94)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSham (n\u0026thinsp;=\u0026thinsp;20)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eMedian [Q1\u0026ndash;Q3]\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e80 (74\u0026ndash;86)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e96 (90\u0026ndash;99)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e85 (78\u0026ndash;91)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eStimulation (n\u0026thinsp;=\u0026thinsp;20)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eMedian [Q1\u0026ndash;Q3]\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e79 (73\u0026ndash;88)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e94 (89\u0026ndash;106)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e80 (77\u0026ndash;90)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u003cstrong\u003eTime domain\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTime-domain analysis of HRV revealed distinct changes in autonomic function across the experimental phases. The use of taVNS appeared to promote parasympathetic modulation, particularly evident during the recovery period following stress. Among the evaluated parameters (RRinterval, pNN50, SDNN, and RMSSD), clear phase-dependent patterns were observed, reflecting shifts in cardiac autonomic regulation as participants transitioned from baseline to stress and back to recovery. The findings of RR interval, pNN50, SDNN, and RMSSD are presented in Table \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e, which reports the median and interquartile ranges (Q1\u0026ndash;Q3) for each parameter across the experimental groups, and are also illustrated in Figs. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e to \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e. Similarly, frequency-domain analysis revealed complementary patterns in autonomic dynamics. Changes in HF power were indicative of enhanced vagal activity during the post-stress recovery phase in the taVNS group, whereas LF power and the LF/HF ratio reflected the overall sympathovagal balance across phases. These results, summarized in Table \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e and illustrated in Figs. \u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003e to \u003cspan class=\"InternalRef\"\u003e7\u003c/span\u003e, further support the modulatory effect of taVNS on cardiac autonomic function.\u003c/p\u003e\n\u003cp\u003eStatistical evaluations indicated that most HRV metrics changed significantly over time within each group (Control, Sham, and Stimulation). This highlights the responsiveness of the ANS to both acute stress and vagal stimulation. These temporal changes likely reflect fluctuations in beat-to-beat interval timing, as sympathetic activity dominates under stress and vagal tone gradually returns during recovery.\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n \u003cdiv align=\"left\" class=\"colspec\"\u003e\u003cbr\u003e\u003c/div\u003e\n \u003ctable id=\"Tab3\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eStatistical test results for HRV parameters of the control, sham, and stimulation groups. Data are represented as the median and 1st and 3rd quartile values, namely, Median (Q1\u0026ndash;Q3), based on the Mann-Whitney U test findings.\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eGroup\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eParameter\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ePre-Stress\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eStress\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ePost-Stress\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eControl\u003c/p\u003e\n \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;20)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRRinterval (ms)\u003c/p\u003e\n \u003cp\u003epNN50 (%)\u003c/p\u003e\n \u003cp\u003eSDNN (ms)\u003c/p\u003e\n \u003cp\u003eRMSSD (ms)\u003c/p\u003e\n \u003cp\u003eLF (ms\u003csup\u003e2\u003c/sup\u003e)\u003c/p\u003e\n \u003cp\u003eHF (ms\u003csup\u003e2\u003c/sup\u003e)\u003c/p\u003e\n \u003cp\u003eLF/HF\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e731.0 (654.1\u0026ndash;790.6)\u003c/p\u003e\n \u003cp\u003e3.7 (2.1\u0026ndash;10.1)\u003c/p\u003e\n \u003cp\u003e44.7 (34.7\u0026ndash;56.9)\u003c/p\u003e\n \u003cp\u003e27.5 (22.2\u0026ndash;42.3)\u003c/p\u003e\n \u003cp\u003e557.0 (316.7\u0026ndash;760.8)\u003c/p\u003e\n \u003cp\u003e722.0 (374.6\u0026ndash;1371.0)\u003c/p\u003e\n \u003cp\u003e0.8 (0.5\u0026ndash;1.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e575.3 (534.8\u0026ndash;671.0)\u003c/p\u003e\n \u003cp\u003e3.4 (1.4\u0026ndash;5.2)\u003c/p\u003e\n \u003cp\u003e53.2 (48.6\u0026ndash;63.7)\u003c/p\u003e\n \u003cp\u003e26.4 (23.7\u0026ndash;46.5)\u003c/p\u003e\n \u003cp\u003e773.0 (535.7\u0026ndash;1142.0)\u003c/p\u003e\n \u003cp\u003e1076.0 (731.4\u0026ndash;1842.0)\u003c/p\u003e\n \u003cp\u003e0.7 (0.6\u0026ndash;0.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e710.0 (632.9\u0026ndash;758.1)\u003c/p\u003e\n \u003cp\u003e5.2 (2.0\u0026ndash;11.5)\u003c/p\u003e\n \u003cp\u003e66.9 (49.4\u0026ndash;84.5)\u003c/p\u003e\n \u003cp\u003e30.7 (22.3\u0026ndash;43.4)\u003c/p\u003e\n \u003cp\u003e644.0 (277.1\u0026ndash;1006.0)\u003c/p\u003e\n \u003cp\u003e855.0 (513.4\u0026ndash;1293.0)\u003c/p\u003e\n \u003cp\u003e0.7 (0.5\u0026ndash;0.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSham\u003c/p\u003e\n \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;20)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRRinterval (ms)\u003c/p\u003e\n \u003cp\u003epNN50 (%)\u003c/p\u003e\n \u003cp\u003eSDNN (ms)\u003c/p\u003e\n \u003cp\u003eRMSSD (ms)\u003c/p\u003e\n \u003cp\u003eLF (ms\u003csup\u003e2\u003c/sup\u003e)\u003c/p\u003e\n \u003cp\u003eHF (ms\u003csup\u003e2\u003c/sup\u003e)\u003c/p\u003e\n \u003cp\u003eLF/HF\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e742.0 (683.9\u0026ndash;811.4)\u003c/p\u003e\n \u003cp\u003e10.6 (8.0\u0026ndash;17.4)\u003c/p\u003e\n \u003cp\u003e50.3 (41.7\u0026ndash;79.5)\u003c/p\u003e\n \u003cp\u003e41.7 (28.2\u0026ndash;53.9)\u003c/p\u003e\n \u003cp\u003e561.0 (401.2\u0026ndash;1004.0)\u003c/p\u003e\n \u003cp\u003e617.7 (458.0\u0026ndash;1437.0)\u003c/p\u003e\n \u003cp\u003e0.9 (0.5\u0026ndash;1.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e620.3 (601\u0026ndash;677.2)\u003c/p\u003e\n \u003cp\u003e6.9 (3.4\u0026ndash;9.4)\u003c/p\u003e\n \u003cp\u003e65.0 (45.8\u0026ndash;73.2)\u003c/p\u003e\n \u003cp\u003e39.7 (26.0\u0026ndash;53.2)\u003c/p\u003e\n \u003cp\u003e1020.0 (820.7\u0026ndash;1944.0)\u003c/p\u003e\n \u003cp\u003e1780.0 (1289.0\u0026ndash;2204.0)\u003c/p\u003e\n \u003cp\u003e0.6 (0.4\u0026ndash;0.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e712.0 (662.2\u0026ndash;786.5)\u003c/p\u003e\n \u003cp\u003e8.4 (5.7\u0026ndash;13.3)\u003c/p\u003e\n \u003cp\u003e67.8 (57.4\u0026ndash;76.0)\u003c/p\u003e\n \u003cp\u003e40.3 (29.8\u0026ndash;54.8)\u003c/p\u003e\n \u003cp\u003e1068.0 (386.1\u0026ndash;1529.0)\u003c/p\u003e\n \u003cp\u003e1222.0 (657.5\u0026ndash;2064.0)\u003c/p\u003e\n \u003cp\u003e0.9 (0.5\u0026ndash;0.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eStimulation\u003c/p\u003e\n \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;20)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRRinterval (ms)\u003c/p\u003e\n \u003cp\u003epNN50 (%)\u003c/p\u003e\n \u003cp\u003eSDNN (ms)\u003c/p\u003e\n \u003cp\u003eRMSSD (ms)\u003c/p\u003e\n \u003cp\u003eLF (ms\u003csup\u003e2\u003c/sup\u003e)\u003c/p\u003e\n \u003cp\u003eHF (ms\u003csup\u003e2\u003c/sup\u003e)\u003c/p\u003e\n \u003cp\u003eLF/HF\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e753.0 (668.4\u0026ndash;857.6)\u003c/p\u003e\n \u003cp\u003e11.1 (3.0\u0026ndash;13.3)\u003c/p\u003e\n \u003cp\u003e48.7 (32.5\u0026ndash;55.0)\u003c/p\u003e\n \u003cp\u003e38.8 (22.1\u0026ndash;48.6)\u003c/p\u003e\n \u003cp\u003e477.5 (201.6\u0026ndash;785.6)\u003c/p\u003e\n \u003cp\u003e422.3 (245.1\u0026ndash;1010.0)\u003c/p\u003e\n \u003cp\u003e1.1 (0.5\u0026ndash;1.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e648.0 (556.5\u0026ndash;682.1)\u003c/p\u003e\n \u003cp\u003e4.3 (1.3\u0026ndash;8.1)\u003c/p\u003e\n \u003cp\u003e56.8 (44.7\u0026ndash;65.7)\u003c/p\u003e\n \u003cp\u003e34.0 (20.8\u0026ndash;51.2)\u003c/p\u003e\n \u003cp\u003e663.0 (385.8\u0026ndash;1244.0)\u003c/p\u003e\n \u003cp\u003e1105.0 (774.5\u0026ndash;1620.0)\u003c/p\u003e\n \u003cp\u003e0.6 (0.5\u0026ndash;1.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e745.0 (645.1\u0026ndash;802.2)\u003c/p\u003e\n \u003cp\u003e8.7 (4.2\u0026ndash;11.7)\u003c/p\u003e\n \u003cp\u003e63.9 (46.2\u0026ndash;89.2)\u003c/p\u003e\n \u003cp\u003e36.7 (28.0\u0026ndash;53.3)\u003c/p\u003e\n \u003cp\u003e597.3 (241.3\u0026ndash;872.1)\u003c/p\u003e\n \u003cp\u003e512.1 (400.7\u0026ndash;993.4)\u003c/p\u003e\n \u003cp\u003e1.1 (0.5\u0026ndash;1.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eRRinterval Analysis Across Experimental Phases\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eDuring the stress phase, a pronounced decrease in RRinterval was observed in all groups, indicating a shift toward sympathetic dominance under acute stress conditions, with the stimulation group showing the most pronounced recovery post-stress. In the stimulation group, the RRinterval dropped from 753 ms (pre-stress) to 648 ms (stress), followed by a notable recovery to 745 ms post-stress. This considerable change suggests that taVNS may enhance vagal reactivation and facilitate faster cardiac recovery following stress exposure. The sham group exhibited a similar pattern with RRinterval decreasing from 742 ms to 620 ms, then partially recovering to 712 ms post-stress, implying a limited recovery, possibly due to placebo effects or non-specific factors. In contrast, the control group showed the sharpest drop (from 731 ms to 575 ms), with only partial recovery to 710 ms, reflecting minimal autonomic restoration in the absence of any stimulation.\u003c/p\u003e\n\u003cp\u003eThese findings support the hypothesis that taVNS modulates cardiac autonomic function, primarily by promoting parasympathetic re-engagement after sympathetic activation.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003epNN50 Analysis Across Experimental Phases\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe pNN50 parameter, representing the percentage of successive normal heartbeats that differ by more than 50 milliseconds, is a well-established marker of parasympathetic (vagal) activity. Across all groups, pNN50 values demonstrated phase-dependent variation, with the most prominent changes occurring in the stimulation group (Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e\n\u003cp\u003eIn the stimulation group, the baseline pNN50 was relatively high (11.1%) during the pre-stress phase, which is consistent with elevated vagal tone. During the stress phase, pNN50 dropped significantly to 4.3%, indicating sympathetic dominance and vagal withdrawal under acute stress. Following stimulation, pNN50 rebounded to 8.7%, which might suggest that taVNS\u003c/p\u003e\n\u003cp\u003epromoted parasympathetic reactivation and cardiac recovery. The sham group also showed a decline in pNN50 from 10.6\u0026ndash;6.9% during stress, followed by a moderate increase to 8.4% post-stress. While this suggests some recovery, the absence of real vagal stimulation limits the extent of parasympathetic engagement. In contrast, the control group maintained consistently low pNN50 values across all phases (3.7%, 3.4%, and 5.2%, respectively), indicating minimal vagal responsiveness and no meaningful autonomic recovery. Overall, these results highlight pNN50 as a sensitive indicator of taVNS efficacy, reflecting both the stress-induced vagal suppression and the subsequent restoration of parasympathetic activity.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSDNN Analysis Across Experimental Phases\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSDNN (Standard Deviation of NN intervals) reflects overall HRV and is influenced by both sympathetic and parasympathetic branches of the ANS. Across all groups, SDNN values increased progressively from pre-stress to post-stress, reflecting dynamic autonomic adaptations to stress and recovery.\u003c/p\u003e\n\u003cp\u003eIn the sham group, SDNN showed the most pronounced rise, from 50.3 ms (pre-stress) to 65.0 ms (stress), peaking at 67.8 ms (post-stress). This pattern suggests that even without active stimulation, anticipation, or placebo-related factors may contribute to increased variability. The stimulation group also exhibited a steady increase from 48.7 ms (pre-stress) to 56.8 ms (stress), reaching 63.9 ms (post-stress), supporting the idea that taVNS enhances overall autonomic flexibility during the recovery phase. In the control group, SDNN increased from 44.7 ms (pre-stress) to 66.9 ms (post-stress), indicating a delayed but robust autonomic response. However, without vagal stimulation, the mechanisms driving this increase may reflect non-specific stress adaptation rather than targeted modulation.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eRMSSD Analysis Across Experimental Phases\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eRMSSD (Root Mean Square of Successive Differences) is a more specific time-domain metric reflecting short-term vagal (parasympathetic) activity. The parameter was particularly informative for assessing the effects of taVNS on parasympathetic rebound. In the stimulation group, RMSSD declined from 38.8 ms (pre-stress) to 34.0 ms (stress), followed by a partial recovery to 36.7 ms (post-stress). This pattern aligns with parasympathetic withdrawal under stress and partial reactivation with taVNS, although the recovery was not complete. Similarly, the sham group showed a slight reduction from 41.7 ms (pre-stress) to 39.7 ms (stress), then stabilization at 40.3 ms (post-stress), suggesting modest vagal fluctuations, possibly due to psychological or environmental effects rather than physiological stimulation. The control group remained relatively stable across all phases, namely 27.5 ms (pre-stress), 26.4 ms (stress), and 30.7 ms (post-stress), indicating limited autonomic responsiveness in the absence of intervention.\u003c/p\u003e\n\u003cp\u003eThese findings demonstrate that RMSSD, as a parasympathetic-specific indicator, is sensitive to both stress-induced vagal suppression and stimulation-driven recovery, particularly when interpreted alongside pNN50, and are consistent with previous findings in the literature and align with expectations based on earlier studies [\u003cspan class=\"CitationRef\"\u003e14\u003c/span\u003e\u0026ndash;\u003cspan class=\"CitationRef\"\u003e17\u003c/span\u003e].\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eLF Analysis Across Experimental Phases\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe LF (Low Frequency) band oscillations are reported to be in the range of 0.04\u0026ndash;0.15 Hz and generate the highest classification rate compared to the other statistical features. This metric is associated with both sympathetic and parasympathetic activity, usually considered as a marker of how active the sympathetic system is. LF power increased in the control group from 557 ms\u003csup\u003e2\u003c/sup\u003e to 773 ms\u003csup\u003e2\u003c/sup\u003e during stress, then slightly decreased to 644 ms\u003csup\u003e2\u003c/sup\u003e post-stress, indicating typical sympathetic activation with limited recovery. The sham group showed a strong LF increase from 561 ms\u003csup\u003e2\u003c/sup\u003e to 1020 ms\u003csup\u003e2\u003c/sup\u003e during stress and further to 1068 ms\u003csup\u003e2\u003c/sup\u003e after, suggesting prolonged sympathetic arousal, possibly linked to anticipatory effects. In contrast, the stimulation group had a milder LF rise (477.5 ms\u003csup\u003e2\u003c/sup\u003e \u0026rarr; 663 ms\u003csup\u003e2\u003c/sup\u003e) and a post-stress drop to 597.3 ms\u003csup\u003e2\u003c/sup\u003e, suggesting that taVNS dampened the sympathetic response and aided autonomic recovery. The control and sham groups faced a significant increase in LF metric between pre and stress phases, \u0026ldquo;sympathetic activation,\u0026rdquo; which was expected. Compared with the stimulation group, which does not show this increase, these patterns support the role of Vagus nerve stimulation in promoting better autonomic regulation under stress.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eHF Analysis Across Experimental Phases\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eHF (High Frequency), another metric of the frequency domain, may be a direct measure of vagal tone and is typically associated with respiratory sinus arrhythmia. HF band oscillations are reported to be in the range of 0.15\u0026ndash;0.4 Hz. Contrary to theoretical expectations, our results presented no decreased HF during stress, widely associated with vagal withdrawal [\u003cspan class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e19\u003c/span\u003e]. In the control group, HF increased from 722 ms\u003csup\u003e2\u003c/sup\u003e at baseline to 1076 ms\u003csup\u003e2\u003c/sup\u003e during stress, followed by a moderate decline to 855 ms\u003csup\u003e2\u003c/sup\u003e post-stress. This unusual stress-phase increase may suggest compensatory vagal activation or interindividual variability. The sham group showed a dramatic HF rise from 618 ms\u003csup\u003e2\u003c/sup\u003e to 1780 ms\u003csup\u003e2\u003c/sup\u003e during stress, with a drop to 1222 ms\u003csup\u003e2\u003c/sup\u003e post-stress. This exaggerated parasympathetic pattern may reflect a placebo-related overcompensation or stress-related misinterpretation. In contrast, the stimulation group started with a low HF (422 ms\u003csup\u003e2\u003c/sup\u003e), increased to 1105 ms\u003csup\u003e2\u003c/sup\u003e during stress, and slightly declined to 512 ms\u003csup\u003e2\u003c/sup\u003e post-stress. This sharp rise and partial retention suggest effective vagal engagement under stress and a more stable autonomic shift. Overall, these findings indicate that taVNS may support parasympathetic modulation, though the complex HF responses across groups suggest further investigation is needed into context-dependent vagal dynamics.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eLF/HF Analysis Across Experimental Phases\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe Low Frequency/High Frequency ratio represents the ANS balance\u0026mdash;where elevated values suggest sympathetic dominance, and lower values indicate stronger parasympathetic influence. The statistical significance of the stress phase (p\u0026thinsp;=\u0026thinsp;0.038) in the sham group indicates a placebo effect, which we could see in the change of values between 0.9 (pre-stress) and the highly drop of 0.6 (stress), then rebound to 0.9 (post-stress). This pattern may indicate some form of temporary vagal activation or reduction in sympathetic tone during the stress task, perhaps because of some anticipatory effects or participant expectations. The sham and control groups show relatively stable values in LF/HF post return close to baseline, suggesting autonomic rebalancing after the stressor. In the stimulation group, the variation between phases\u0026rsquo; values was indicated by 1.1 (pre-stress), 0.6 (stress), and 1.1 (post-stress This suggests that the effect of stimulation may facilitate autonomic recovery and modulate sympathetic-parasympathetic balance, promoting faster return to baseline homeostasis.\u003c/p\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eThis study investigated the effects of bilateral transcutaneous auricular Vagus Nerve Stimulation (taVNS) on cardiac autonomic regulation in healthy individuals, under conditions of real-time stress. Participants were randomly assigned to control, sham, or stimulation groups and underwent three experimental phases: pre-stress, stress, and post-stress. Heart Rate Variability (HRV) was evaluated using time-domain indices to characterize shifts in autonomic balance across phases. Among the time domain HRV parameters, pNN50 and RMSSD are well-established indicators of parasympathetic modulation, while SDNN reflects overall HRV, influenced by both branches of the autonomic nervous system [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. In line with previous findings, this study observed significant fluctuations in HRV variables across time. Notably, pNN50 levels in the stimulation group decreased sharply during the stress phase and rebounded during the post-stress period, indicating a parasympathetic recovery facilitated by taVNS. In contrast, the control group showed minimal variation, and the sham group exhibited only partial recovery, suggesting that the observed effects are likely due to real vagal stimulation rather than placebo or expectation. The RMSSD values showed similar trends, although changes were less pronounced and not statistically significant between groups. As RMSSD reflects rapid, short-term vagal fluctuations [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e], the pattern still suggests some degree of taVNS-induced parasympathetic engagement. SDNN increased significantly in the stimulation group, with median values rising steadily from pre-stress to post-stress phases. Since SDNN represents broader autonomic variability, its enhancement may reflect a global autonomic adaptability reinforced by vagal stimulation. The participants with higher baseline SDNN values tended to exhibit stronger autonomic flexibility across phases.\u003c/p\u003e\u003cp\u003eThe frequency domain variables ratio, LF/HF showed no significant change in the stimulation group against the control group. Median values decreased during the stress phase in both the sham and stimulation groups, contrary to the expected increase in the control group. This suggests that the participants of the sham group could have induced sensations similar to those in the stimulation group. Upon further inspection of the data, the overall distribution shifted downward irreversibly for both the sham and stimulation groups compared to that of the control. This indicates that individuals with a high LF/HF baseline value (indicative of an imbalanced ANS) experienced a decrease in LF/HF during stimulation, maintaining the distribution range in the post phase, leading to a more balanced system. Independently, LF showed no significant change in the stimulation group during stress, confirming the effect of stimulation and its role in regulating sympathetic dominance.\u003c/p\u003e\u003cp\u003eThe relationship between HF and the parasympathetic system is complex (as illustrated in this study); HF (the respiratory band) provides a different understanding of what should decrease during stress. Variations in study design and taVNS protocols contribute to the heterogeneity across studies, making it essential to identify potential moderator and mediator variables. The change in HF between group phases does not necessarily indicate improved vagal tone; if this increases under stress, it may suggest over-activation of the parasympathetic system and suppressed heart rate variability [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. Additionally, HF power may be sensitive to breathing frequency, which differentiates this distribution in the HF range [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. Evaluating this parameter in this study suggests that HF reflects the HRV distributions, representing parasympathetic and sympathetic activity together. This suggests that baseline HRV may serve as a predictor of resilience, echoing findings from other work that link autonomic variability to both physiological adaptability and cognitive-emotional processing under pressure. In summary, the results support the conclusion that taVNS facilitates parasympathetic recovery following acute stress, with effects most evident in pNN50, SDNN, LF, HF, and LF/HF indices. While further research is needed to explore individual variability, long-term stimulation effects, and underlying neural mechanisms, these findings contribute to the growing evidence base for non-invasive vagal stimulation as a tool for autonomic regulation.\u003c/p\u003e\u003cp\u003eThe mechanisms underlying the observed parasympathetic reactivation are still not entirely understood. One possible explanation is offered by homeostatic adaptation theories, which suggest that controlled or transient stress may promote physiological resilience, enabling individuals to return to baseline or even an enhanced autonomic state [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. From a neurobiological perspective, it has also been proposed that stress-related neuromodulators may influence large-scale neuronal dynamics, altering functional patterns across brain regions involved in autonomic control [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. Within this framework, taVNS may act as a neuromodulatory tool, reinforcing adaptive brain-heart communication and supporting physiological recovery under stress.\u003c/p\u003e"},{"header":"CONCLUSION","content":"\u003cp\u003eIn this study, we examined how bilateral taVNS influences cardiac autonomic regulation before, during, and after acute stress. The findings suggest that taVNS may support the reactivation of parasympathetic activity in the recovery period, particularly reflected in the pNN50 and SDNN measures. Participants who received active stimulation showed clearer signs of autonomic rebound compared to those in the sham and control groups. Although some parameters, such as RMSSD, did not show statistically significant differences between groups, the overall pattern was consistent with enhanced vagal modulation, whereas frequency-domain outcomes provide additional context to the autonomic patterns observed in the time-domain measures. The LF values remained relatively stable across phases in the stimulation group, in contrast to the significant increases seen in the sham and control groups\u0026mdash;an effect that likely reflects reduced sympathetic activation due to taVNS. While HF power unexpectedly peaked during the stress phase across all groups, only the stimulation group showed a sharp decline in the post-stress period, suggesting a distinct recovery trajectory. The LF/HF ratio further supports this interpretation, as the stimulation group maintained a more balanced profile across phases, whereas the sham group showed a transient disruption during stress. These results offer additional support for the potential use of taVNS in modulating stress responses, especially in contexts where autonomic flexibility plays a key role. Further research is needed to clarify the underlying mechanisms and determine how individual baseline differences may shape the physiological response to stimulation.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003ch2\u003eAUTHOR CONTRIBUTIONS STATEMENT\u003c/h2\u003e\u003cp\u003eAmani Alrikabi: Conceptualization, Methodology, Investigation, Data curation, Formal analysis, Visualization, Writing \u0026ndash; original draft; Asst. Prof. Hakan Solmaz: Supervision, Validation, Writing \u0026ndash; review \u0026amp; editing.\u003c/p\u003e\u003c/p\u003e\u003ch2\u003e\u003cb\u003eADDITIONAL INFORMATION\u003c/b\u003e\u003c/h2\u003e\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003cp\u003eThe author(s) declare no competing interests.\u003c/p\u003e\u003c/p\u003e\u003ch2\u003eFUNDING\u003c/h2\u003e\u003cp\u003eThis research received no external funding.\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eAmani Alrikabi: Conceptualization, Methodology, Investigation, Data curation, Formal analysis, Visualization, Writing \u0026ndash; original draft; Asst. Prof. Hakan Solmaz: Supervision, Validation, Writing \u0026ndash; review \u0026amp; editing.\u003c/p\u003e\u003ch2\u003eAcknowledgement\u003c/h2\u003e\u003cp\u003eThe authors would like to thank Prof. Dr. Abdulameer Nasser Ghaloub, Prof. Dr. Lamyaa Yaseen Zghair, Dr. Ali Veysel \u0026Ouml;zden, and Dr. Mehmet Ozansoy for their valuable guidance and insightful suggestions throughout the development of this research.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eThe datasets generated and analysed during the current study, including HRV time and frequency domain, are not publicly available due to participant privacy and confidentiality requirements. However, anonymized datasets are available from the corresponding author upon reasonable request, provided that the request is compliant with ethical approval and institutional data-sharing policies.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eHon, E. 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Sci.\u003c/em\u003e \u003cb\u003e9\u003c/b\u003e, 878962. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.3389/fvets.2022.878962\u003c/span\u003e\u003cspan address=\"10.3389/fvets.2022.878962\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2022).\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Transcutaneous Auricular Vagus Nerve Stimulation (taVNS), Heart Rate Variability (HRV), Psychological Stress, Parasympathetic Activity, Time-Domain Analysis, Frequency-Domain Analysis","lastPublishedDoi":"10.21203/rs.3.rs-7386946/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7386946/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eTranscutaneous auricular Vagus Nerve Stimulation (taVNS) has emerged as a promising non-invasive method for modulating the Autonomic Nervous System (ANS). However, its impact on cardiac autonomic regulation during acute stress remains underexplored. This study investigates taVNS effects on Heart Rate Variability (HRV) indices in response to psychological stress in healthy individuals across time and frequency domains. Sixty participants were randomly assigned to three groups: control, sham, and stimulation. Each underwent a three-phase experimental protocol: pre-stress, stress induction, and post-stress. Time domain (RR interval, pNN50, SDNN, RMSSD), frequency domain (HF, LF, LF/HF) were computed from ECG signals and analyzed using repeated-measures comparisons. Results revealed that stimulation group exhibited a sharper drop in RR intervals (753 ms pre-stress, 648 ms stress, and 745 ms post-stress), pNN50 (11.1% → 4.3% → 8.7%), and LF/HF rose from (0.6) under stress to (1.1) in recovery, suggesting enhanced vagal reactivation. While the sham group showed limited improvement, the control group demonstrated minimal restoration in pNN50. SDNN values for the stimulation group increased steadily (48.7 ms → 56.8 ms → 63.9 ms), indicating broader autonomic adaptability. These results indicate a targeted influence of taVNS on cardiac vagal tone and overall autonomic regulation, potentially promoting parasympathetic engagement under stress.\u003c/p\u003e","manuscriptTitle":"Neuro-Cardiac Interactions of Transcutaneous Auricular Vagus Nerve Stimulation: A Focus on Stress Effects","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-09-11 10:13:11","doi":"10.21203/rs.3.rs-7386946/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"2d126731-a985-4526-be48-a8528b9ae037","owner":[],"postedDate":"September 11th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":54528772,"name":"Health sciences/Cardiology"},{"id":54528773,"name":"Biological sciences/Neuroscience"},{"id":54528774,"name":"Biological sciences/Physiology"}],"tags":[],"updatedAt":"2025-10-07T07:39:00+00:00","versionOfRecord":[],"versionCreatedAt":"2025-09-11 10:13:11","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7386946","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7386946","identity":"rs-7386946","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}