==== Front Sci Rep Sci Rep Scientific Reports 2045-2322 Nature Publishing Group UK London 78722 10.1038/s41598-020-78722-3 Article Reduced vagal modulations of heart rate during overwintering in Antarctica Maggioni Martina A. martina.maggioni@charite.de 12 Merati Giampiero 34 Castiglioni Paolo 3 Mendt Stefan 1 Gunga Hanns-Christian 1 Stahn Alexander C. astahn@pennmedicine.upenn.edu 15 1 Charité – Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Institute of Physiology, Center for Space Medicine and Extreme Environments Berlin, 10117 Berlin, Germany 2 grid.4708.b0000 0004 1757 2822Department of Biomedical Sciences for Health, Università degli Studi di Milano, 20133 Milan, Italy 3 IRCCS Fondazione Don Carlo Gnocchi, 20148 Milan, Italy 4 grid.18147.3b0000000121724807Department of Biotechnology and Life Sciences (DBSV), University of Insubria, 21100 Varese, Italy 5 grid.25879.310000 0004 1936 8972Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, 1016 Blockley Hall, 423 Guardian Drive, Philadelphia, PA 19004 USA 11 12 2020 11 12 2020 2020 10 218103 9 2020 27 11 2020 © The Author(s) 2020Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.Long-duration Antarctic expeditions are characterized by isolation, confinement, and extreme environments. Here we describe the time course of cardiac autonomic modulation assessed by heart rate variability (HRV) during 14-month expeditions at the German Neumayer III station in Antarctica. Heart rate recordings were acquired in supine position in the morning at rest once before the expedition (baseline) and monthly during the expedition from February to October. The total set comprised twenty-five healthy crewmembers (n = 15 men, 38 ± 6 yrs, n = 10 women, 32 ± 6 yrs, mean ± SD). High frequency (HF) power and the ratio of low to high frequency power (LF/HF) were used as indices of vagal modulation and sympathovagal balance. HF power adjusted for baseline differences decreased significantly during the expedition, indicating a gradual reduction in vagal tone. LF/HF powers ratio progressively shifted toward a sympathetic predominance reaching statistical significance in the final trimester (August to October) relative to the first trimester (February to April). This effect  was particularly pronounced in women. The depression of cardio-vagal tone and the shift toward a sympathetic predominance observed throughout the overwintering suggest a long-term cardiac autonomic modulation in response to isolation and confinement during Antartic overwintering. Subject terms PhysiologyMedical researchhttp://dx.doi.org/10.13039/501100002946Deutsches Zentrum für Luft- und Raumfahrt50WB133050WB133050WB152550W1915Gunga Hanns-Christian Stahn Alexander C. Projekt DEALOpen Access funding enabled and organized by Projekt DEAL. issue-copyright-statement© The Author(s) 2020 ==== Body Introduction Antarctic expeditions have a long history for studying the physiological and psychological effects of isolation, confinement, and extreme environments (ICE)1. Except for unprecedented polar traverses in dangerous terrain during the winter, harsh environmental conditions are typically of less concern for modern day expeditions due to significant advances in technology and travel. In contrast, social isolation and confinement associated with Antarctic overwintering can pose considerable psycho-physiological challenges. Prolonged stays in Antarctica have shown to alter circadian2–4, immunological5, hormonal6,7, and neurobehavioral responses including mood disturbances1,8 and brain changes9. Isolation and confinement are also considered critical stressors during future long-duration spaceflight missions (LDSM) that could put human health and mission success at risk10. LDSM and Antarctic expeditions share significant similarities of the psychosocial environment11. These include altered day/night cycles, reduced sensory stimulation, sensory monotony, isolation from the outside world, separation from friends and family, absence of privacy, overlap between work and leisure, and exposure to the same small group in both of these settings1. Antarctic overwintering has therefore been considered a high-fidelity spaceflight analog for investigating the behavioral risks of isolation and confinement. The neurobehavioral impact of isolation and confinement may vary between and within individuals12, depending on previous expedition experience, crew cohesion, professional and social group roles, coping strategies, and sources of social support. Tools for unobtrusively and non-invasively monitoring physiological responses could add to the usefulness of self-reported measures to better understand these phenotypic differences, and support the early detection of any adverse behavioral conditions. Heart rate variability (HRV) is a measure of cardiac autonomic modulation that has been suggested as a reliable tool to quantify the physiological13,14 and neurobehavioral effects of human adaptation to different stressors15,16. Greater social integration was shown to be associated with increased high frequency (HF) power of HRV in humans17. Data from prairie voles demonstrated significant disruptions of HRV and behavior after isolation from their partner, and these changes were reversed following re-pairing or environmental enrichment18. We are aware of only one study that identified the time course of HRV during an Antarctic expedition19. This study reported decreases in low frequency (LF) power and in the ratio of LF to HF power at the end of the expedition. However, the small sample (n = 6 men), the limitation of two data collections during the austral summer, and the short study period (about 40 days) warrant a cautious interpretation of the findings. Accordingly, the long-term effects of isolation and confinement on autonomic balance in healthy humans remain to be established. Here, we investigated the time course of short-term HRV during overwintering at the German Neumayer III station in Antarctica. It is the first study that reports findings of the time course during overwintering in Antarctica in both men and women. Results Demographic and pre-mission HRV characteristics by sex are shown in Table 1. Women tended to have higher resting HR (P = 0.069) and HF power (P = 0.070); they also had significantly lower LF/HF ratio than men (P = 0.025). At Neumayer III station we acquired a total of 225 RR series. Thirteen of these recordings were discarded because of an excessive number of edited beats. Further, an additional eight recordings were identified as outliers and excluded from the final data set (see Statistical analysis). HR in both women and men remained unchanged and did not show trends during the whole period (see Supplementary Table S1). Results from the mixed model analyses are provided in Table 2, showing a significant effect of the expedition on log LF/HF (P = 0.02), LFnu (P = 0.024), and HFnu (P = 0.023). The adjusted means and standard errors for each month and sex are provided in Supplementary Tables S1 and S2. Our pre-defined contrasts revealed a significant effect of the expedition on log HF (P < 0.01), which was characterized by a linear decrease in both men and women (linear trend: P = 0.033 and P = 0.048 for women and men) (Fig. 1a). Visual inspection of the data suggested a slight increase of log HF towards the end of the mission. Nonetheless, neither non-linear trends nor the comparison between trimesters (i.e., T1: Feb to April; T2: May to July; T3: August to October) could confirm such a pattern. As indicated in Fig. 1b, log HF was considerably lower during trimester 2 and 3, and this temporal profile was similar for men and women, suggesting a decrease in vagal activity throughout the mission (see also Table 5). In contrast, log LF showed a different time course between men and women that was qualified by a nonlinear trajectory in women compared to men (cubic trend: P = 0.012 for women, and P = 0.699 for men; interaction: P = 0.089; see also Table 3). As for log LF/HF, the significant shift toward sympathetic predominance during the overwintering was largely driven by women (Fig. 1c, d). Polynomial contrasts confirmed significant linear (LFnu, HFnu, log LF/HF), and significant cubic (log LF/HF) trends for women, but not men (Table 3 and 4). Likewise, log LF/HF was significantly higher at T3 compared to T1 in women (Table 5). We acknowledge that the differences in error probabilities do not imply statistical differences, but raise the point towards potential sex-specific differences, which is also supported by the nearly significant interactions between sex and time for the linear and cubic trends observed for log LF/HF (P = 0.069 and P = 0.067). Table 1 General characteristics of the enrolled subjects at baseline. Variable Women (N = 10) Men (N = 15) P Age (yrs) 31.8 (5.7) 38.4 (8.9) 0.050 Body Mass Index (kg/m2) 24.7 (3.6) 26.9 (3.5) 0.143 HR (bpm) 70.3 (6.3) 64.2 (8.5) 0.069 log LF/HF 0.004 (0.379) 0.334 (0.239) 0.025 log HF (ms2) 2.824 (0.393) 2.534 (0.266) 0.070 Note: mean (SD); HRV, heart rate variability; P values refer to unpaired Student’s t-tests comparing men and women. Table 2 Mixed models investigating the effects of expedition duration and sex on heart rate and indices of cardiac autonomic modulation. Variable Fixed Effect df1 df2 F P HR Time 8.00 167.27 0.71 0.682 Sex 1.00 21.96 0.35 0.561 Time × Sex 8.00 167.27 0.54 0.827 log HF Time 8.00 167.33 1.70 0.102 Sex 1.00 21.81 0.06 0.804 Time × Sex 8.00 167.33 0.39 0.927 log LF Time 8.00 167.51 1.85 0.072 Sex 1.00 21.98 2.25 0.148 Time × Sex 8.00 167.50 1.49 0.164 log LF/HF Time 8.00 167.28 2.35 0.020 Sex 1.00 21.30 2.53 0.127 Time × Sex 8.00 167.28 0.97 0.464 LFnu Time 8.00 167.23 2.28 0.024 Sex 1.00 21.24 1.83 0.191 Time × Sex 8.00 167.23 0.90 0.518 HFnu Time 8.00 167.23 2.29 0.023 Sex 1.00 21.24 1.81 0.192 Time × Sex 8.00 167.23 0.91 0.512 Note: Mixed models were run with time and sex as fixed effects, baseline as a covariate, and participants as a random factor (random intercept only); df1, numerator degrees of freedom; df2, denominator degrees of freedom; F, F-statistic; P, p value. Figure 1 Temporal profiles of log HF (a) and log LF/HF (c) during Antarctica overwintering in men (blue) and women (red). Data are adjusted means and standard errors. Contrasts show mean effects and 95% CI for linear and cubic trends in men and women and their differences. Detailed polynomial contrast analyses are provided in Table 3. Panel (b) and (d) show changes between trimesters T1, T2, and T3 for men (blue) and women (red), which were defined as T1: Feb to April; T2: May to July; and T3: Aug to Oct. Contrasts indicate interactions between trimesters and sex, i.e., mean differences between men and women relative to changes in log HF and Log LF/HF from T1 to T2, T2 and T3, and T1 and T3, respectively. Detailed contrasts analyses are reported in Table 5. Table 3 Contrasts for assessing linear, quadratic, and cubic trends of expedition on heart rate and indices of cardiac autonomic modulation in men and women. Variable Contrast Estimate SE df t P HR Linear Women 9.33 14.33 167.2 0.65 0.516 Men 15.41 11.95 167.2 1.29 0.199 Difference 6.08 18.66 167.2 0.33 0.745 Quadratic Women 47.33 95.59 167.0 0.50 0.621 Men  − 8.95 83.32 167.3  − 0.11 0.915 Difference  − 56.28 126.81 167.1  − 0.44 0.658 Cubic Women  − 8.00 59.21 167.3  − 0.14 0.893 Men 79.24 48.63 167.6 1.63 0.105 Difference 87.24 76.62 167.4 1.14 0.257 log HF Linear Women  − 1.33 0.62 167.2  − 2.15 0.033 Men  − 1.03 0.51 167.3  − 1.99 0.048 Difference 0.30 0.80 167.2 0.37 0.708 Quadratic Women 2.44 4.12 167.0 0.59 0.554 Men 0.92 3.59 167.4 0.26 0.798 Difference  − 1.52 5.46 167.2  − 0.28 0.781 Cubic Women 1.36 2.55 167.3 0.54 0.593 Men 0.20 2.09 167.8 0.10 0.923 Difference  − 1.16 3.30 167.5  − 0.35 0.725 log LF Linear Women 0.47 0.57 167.4 0.82 0.415 Men  − 0.72 0.48 167.4  − 1.51 0.134 Difference  − 1.19 0.75 167.4  − 1.59 0.113 Quadratic Women 5.72 3.82 167.1 1.50 0.136 Men 3.19 3.33 167.5 0.96 0.339 Difference  − 2.53 5.07 167.3  − 0.50 0.618 Cubic Women  − 5.99 2.37 167.5  − 2.53 0.012 Men  − 0.75 1.94 168.0  − 0.39 0.699 Difference 5.24 3.06 167.7 1.71 0.089 log LF/HF Linear Women 1.65 0.56 167.1 2.94  < 0.01 Men 0.31 0.47 167.2 0.67 0.504 Difference  − 1.33 0.73 167.1  − 1.83 0.069 Quadratic Women 2.64 3.74 166.7 0.71 0.481 Men 2.38 3.26 167.3 0.73 0.466 Difference  − 0.26 4.96 167.0  − 0.05 0.958 Cubic Women  − 6.38 2.31 167.3  − 2.76  < 0.01 Men  − 0.87 1.90 168.1  − 0.46 0.648 Difference 5.51 2.99 167.6 1.84 0.067 Note: SE, standard error; df, degrees of freedom, t, t-statistic for parameter estimate; P, p value.Table 4 Contrasts for assessing linear, quadratic, and cubic trends of expedition on normalized units indices of cardiac autonomic modulation in men and women. Variable Contrast Estimate SE df t P LFnu Linear Women 74.68 26.77 167.0 2.79  < 0.01 Men 8.65 22.33 167.1 0.39 0.699 Difference  − 66.03 34.86 167.1  − 1.89 0.060 Quadratic Women 136.29 178.66 166.7 0.76 0.447 Men 103.71 155.65 167.3 0.67 0.506 Difference  − 32.58 236.95 167.0  − 0.14 0.891 Cubic Women  − 276.03 110.62 167.2  − 2.50 0.014 Men  − 52.68 90.78 168.0  − 0.58 0.563 Difference 223.36 143.10 167.5 1.56 0.120 HFnu Linear Women  − 74.99 26.74 167.0  − 2.80  < 0.01 Men  − 8.55 22.31 167.1  − 0.38 0.702 Difference 66.44 34.82 167.1 1.91 0.058 Quadratic Women  − 137.89 178.49 166.7  − 0.77 0.441 Men  − 104.67 155.50 167.3  − 0.67 0.502 Difference 33.22 236.72 167.0 0.14 0.889 Cubic Women 277.24 110.51 167.2 2.51 0.013 Men 52.71 90.69 168.0 0.58 0.562 Difference  − 224.53 142.96 167.5  − 1.57 0.118 Note: SE, standard error; df, degrees of freedom, t, t-statistic for parameter estimate; P, p value. Table 5 Contrasts assessing changes between trimesters.Note: SE, standard error; df, degrees of freedom, t, t-statistic for parameter estimate; P, p value. Variable Contrast Estimate SE df t P log HF T1–T2 Women 0.31 0.19 167.0 1.61 0.108 Men 0.26 0.16 167.3 1.60 0.112 Difference 0.04 0.255 167.178 0.16 0.867 T2–T3 Women 0.05 0.19 167.2 0.27 0.784 Men 0.03 0.16 167.1 0.20 0.839 Difference 0.02 0.25 167.2 0.08 0.936 T1–T3 Women 0.36 0.20 167.4 1.82 0.070 Men 0.30 0.16 167.2 1.86 0.064 Difference 0.06 0.25 167.3 0.24 0.806 log LF/HF T1–T2 Women  − 0.22 0.17 166.7  − 1.29 0.197 Men 0.05 0.15 167.3 0.35 0.723 Difference  − 0.28 0.23 167.0  − 1.21 0.228 T2–T3 Women  − 0.35 0.17 167.1  − 1.95 0.053 Men  − 0.14 0.15 167.0  − 0.94 0.345 Difference  − 0.20 0.23 167.1  − 0.89 0.374 T1–T3 Women  − 0.57 0.18 167.4  − 3.17  < 0.01 Men  − 0.08 0.14 167.0  − 0.60 0.549 Difference  − 0.48 0.23 167.2  − 2.09 0.038 Discussion We investigated the time course of cardiac autonomic modulation using HRV during overwintering at the German Neumayer III station in Antarctica. We found a significant gradual decrease in parasympathetic tone that is somewhat plateauing after about two thirds of the mission, and a concomitant shift towards sympathetic predominance. These results seem to contradict previous data demonstrating a reduced day-time sympathovagal balance at the end of a 40-day stay on the Italian Zucchelli station at Terra Nova Bay19. The two data sets vary significantly with respect to their study design and sample size: (1) the group size residing at the station comprised at total of n = 75 persons at Zucchelli vs. n = 9 crewmembers at Neumayer III station; (2) the present study investigated the time course of HRV over 9 months compared to two measurements at Zucchelli station collected within less than two months during the austral summer; the expedition duration comprised 14 months at Neumayer III station vs. about 1.5 months at Zucchelli station. (3) Finally, data at Zucchelli station were collected in n = 6 men compared to a total of n = 25 (n = 10 women) at Neumayer III station. Our data suggest distinct differences in sympathovagal balance (LF/HF ratio), which has also been shown in recent meta-analyses20 . Nonetheless, it is too simplistic to attribute the discrepancy of the findings to sex-specific differences because the gradual linear decrease in cardiac vagal drive throughout the expedition was consistent for men and women. For instance, data from isolation studies targeted at small crews and longer study periods, i.e., 105 days and 520 days of isolation also showed an increase of parasympathetic activity during wakefulness (HFnu increased), and diminished parasympathetic activity during sleep periods (HFnu decreased)21,22. The authors speculated that the diminished circadian rhythm of the autonomic cardiac modulation could be related to a variety of factors including monotony and boredom and a lack of daylight exposure during isolation and confinement22. Light is the primary external cue for entraining the circadian system, and plays a key role for regulating the sleep–wake rhythms of the autonomic nervous system23. Recent research shows that solar activity also affects HRV. It was shown that solar radio flux was positively associated with HF power24. The role of solar activity is somewhat supported by the time course of log HF in women in the present study. The time course of log HF in women was characterized by a significant cubic trend (P = 0.012). Following a relatively stable profile during the first four months, log HF power linearly decreased between May and July, and then increased between July and September concomitant with considerable changes in sunshine duration at Neumayer III station25. The slight reduction in log HF power during the final data recording in October remains speculative. A growing body of research highlights the role of cardiac vagal control in regulating emotional and stress responses26. It is possible that the crew is starting their preparation for the austral summer, which is characterized by a considerable increase in operational and logistical activities, and external researchers and staff visiting the station. Likewise, the marked decrease in log LF/HF in March could reflect the psycho-physiological response to the end of the demanding summer period characterized by extensive working hours, reduced privacy due to the increased number of staff and researchers, and the pressure to successfully take over the station and expectations to function as a team in an unknown operational environment. Strengths and limitations According to the authors’ best knowledge, this is the first study investigating the time course during long-duration overwintering in Antarctica. We collected monthly recordings of HRV in the morning at rest over a series of three overwintering campaigns, resulting in a total sample size of 25 participants comprising men and women. However, we also acknowledge several limitations. First, our analysis focused on short-term recordings of HRV acquired in the morning, because they were reported to be representative of the autonomic modulations of HR27. Thus, we cannot verify any differences in autonomic modulation during different daily activities and sleep and circadian changes in response to long-duration Antarctic overwintering. Second, we did not control our analyses for addtional factors that have also been shown to affect HRV such as changes in hydration status or body weight, sleep quality, or environmental factors such as the sunshine duration, geomagnetic activity, and cosmic radiation24. Third, we did not directly record the respiratory frequency. Changes in respiratory rate over time could potentially contribute to the observed changes in the HF power. Given that Neumayer III station is located at sea level we may safely exclude respiratory effects observed in response to high altitude exposure. Moreover, to mitigate the possible effects of different respiratory patterns we standardized the data collections (lying position, same time of the day for all sessions), and removed HF-power outliers from the final data set (see Statistical analysis). We are confident that these procedures minimized confounding effects associated with irregular breathing patterns. In line with that, the frequency of the highest spectral peak in the HF band (see Supplementary Table S3), providing  indirect evidence of the central respiratory frequency, was in the physiological range for healthy adults, and remarkably stable in men and women during the entire expedition. Furthermore, we did not quantify behavioral responses as self-reported measures of social isolation, emotional deprivation, and stress levels, which would highly valuable to better understand phenotypic differences in HRV responses relative to coping strategies15. Likewise, we cannot infer the physiologic mechanisms responsible for our findings because we did not correlate our data with neuroimmunologic and hormonal responses. Finally, our data revealed characteristic differences in the time course of HRV indices between men and women that require further studies to elucidiate potential sex-related differences in HRV responses to prolonged isolation and confinement. Taken together, this study found a phenomenon of cardiac autonomic modulation that has not been observed in other ICC and ICE analogs: a persistent vagal modulation depression throughout the expedition that is particularly marked during the second trimester of the expedition. This finding is particularly striking as it contrasts previous research investigating shorter stays in Antarctica19 and long-duration isolation studies in ICCs21,22. Visual inspection of the data suggested that the change in autonomic cardiac modulation was more pronounced in women. Larger studies collecting 24-h ECG recordings throughout the entire expedition are needed to detect sex-specific differences and determine the circadian and circannual rhythms of the autonomous nervous system during long-duration Antarctic overwintering. Combining HRV recordings with a set of behavioral and environmental measures will allow for an integrative understanding of the effects of social isolation, group size and dynamics, and sunshine duration and geomagnetic activity on HRV. Such approaches will help to verify the use of HRV as a non-invasive tool to assess individual differences in self-regulatory coping strategies in response to isolation and confinement associated with exploratory class spaceflight missions or conditions of large-scale social restrictions such as during the COVID-19 pandemic. Methods Participants Participants were recruited from three consecutive winter-over expedition crews (each n = 9) staying at the German Neumayer III station for 14 months. A total of twenty-five healthy participants (men: n = 15, 38 ± 6 yrs, 87 ± 10 kg, 180 ± 6 cm; women: n = 10, 32 ± 6 yrs, 68 ± 6 kg, 166 ± 6 cm; mean ± SD) were enrolled in the study (Mission 1, n = 9, Mission 2, n = 7, and Mission 3, n = 9). Each expedition was preceded by a 4.5-month extensive operational training program including general education and training about running and living on Neumayer III station, and specific professional training related to different operational responsibilities. Following the training program the crews departed to Antarctica in December, and the station was handed over from the previous crew, which then returned to Europe typically around the end of January/beginning of February. A detailed description of Neumayer III station and operational characteristics is provided elsewhere9. Subjects provided written informed consent to participate in the study, which was approved by the local Ethic Committee of the Charité – Universitätsmedizin Berlin, Berlin, Germany. All experimental sessions were performed in full accordance with the principles of the Declaration of Helsinki28. Experimental procedures Data were collected in the morning between 9.00 and 12.00 a.m. in supine position at rest using a mobile heart rate (HR) monitor (Polar S810, Polar Electro Oy, Kempele, Finland) that provides beat-by-beat time series of RR intervals with resolution of 1 ms29. A baseline recording was performed about two months before the departure to Antarctica at Charité – Universitätsmedizin Berlin, including a 12-lead resting electrocardiogram (ECG) to check sinus rhythm and exclude arrhythmias. The baseline session was followed by a training session on how to operate the HR monitor and perform the recording according to a strict procedure. All data were collected in supine position for 10 min, and participants were instructed to refrain from caffeine consumption for at least three hours before the measurement and limiting any strenuous exercise 24 h prior to the data recording. In-mission data were collected monthly from February to October, resulting in a total of 250 h recordings. HRV data pre-processing and analysis Normal-to-normal (NN) interval series were obtained by visual inspection of each RR series, removing possible premature beats and artefacts14. The entire series was discarded if the number of artefacts or ectopic beats exceeded 5% of all RR intervals. HRV was quantified by indices in frequency domain14. The power spectrum of NN intervals was calculated from the Welch periodogram, deriving spectral powers in the low-frequency (LF, from 0.04 to 0.15 Hz) and high-frequency (HF, from 0.15 to 0.40 Hz) bands14. The HF power comprises respiratory oscillations mediated by the cardiac vagal drive, whereas the LF/HF powers ratio is an index of cardiac sympathovagal balance14,30,31. Furthermore LF/HF ratio is an HRV index sensitive to ongoing stress, as previously reported32,33. HF, LF and LF/HF indices were log transformed for further analyses. LF and HF were also expressed as normalized units (nu) as follows: HFnu = HF/(total power—VLF) × 100 and LFnu = LF/(total power—VLF) × 100, were the VLF is the spectral power in the very low-frequency band (0–0.04 Hz). The LFnu is considered an index of sympathovagal balance, the HFnu an index of vago/sympathetic balance. The indices were calculated with the software Kubios HRV ver. 2.2 (Kuopio, Finland)34. Statistical analysis Anthropometric, HR, log HF and log LF/HF differences between men and women at baseline were assessed using unpaired Student’s t tests, before the expedition. None of the baseline recordings was discarded because of premature beats or artifacts, while 13 out of 225 recordings performed in Antarctica were discarded because of an excessive number of edited beats. Eight additionally monthly recordings were excluded because identified as outliers. Unlike pre-mission recordings, obtained in a controlled laboratory under supervision, recordings in Antarctica were performed by the volunteers themselves. Thus we checked these recordings for the possible presence of outliers before applying any statistical test. Considering that the vagal tone is particularly sensitive to external perturbations, changes in breathing patterns, or lack of steady-state conditions, outliers were identified with Tukey’s method35 applied on the index of vagal HR modulations, log HF. For each volunteer we considered the distribution of 9 monthly estimates in Antarctica of log HF, calculated the first and third quartiles (Q1 and Q3) of the distribution, and identified values of log HF as outliers, if they were smaller than Q1─1.5 × (Q3–Q1) or larger than Q3 + 1.5 × (Q3–Q1). When a log HF estimate was identified as an outlier, we discarded the corresponding HR recording. To analyze the time courses of HRV we first formulated mixed models with subject as a random factor, time and sex as fixed factors, and baseline data (data collected before the expedition) as a covariate. Variance components were estimated using restricted maximum likelihood (REML) approach using the R package lme436. Normality and homogeneity were checked by visual inspection of plots of residuals against fitted values (Q–Q plots). Next, the adjusted means (estimated marginal means) were used to assess the linear, quadratic, cubic trends for each sex, and determined their interaction using pre-planned polynomial contrasts. We also defined custom contrasts averaging the data across trimesters (T1, T2, and T3) and compared the changes in HRV between trimesters (T1–T2, T2–T3, and T1–T3) to further elucidate sex differences. No corrections of the level of significance were applied37. We acknowledge that this increased the chance of Type I errors. However, given the exploratory nature of the study, we were also cautious about false negatives38. As a compromise we limited the tests to a small set of pre-planned contrasts and kept the level of significance at α = 0.05 (two-sided) for all testing. Note that whereas we also provide P-values for the fixed effects of the mixed models using Satterthwaite’s approximation for denominator degrees of freedom39, our primary hypotheses focus on the estimates related to our a priori defined linear, quadratic, cubic40 . All statistical analyses were carried out using the software package R41. Supplementary information Supplementary Information. Publisher's note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. Supplementary information The online version contains supplementary material available at 10.1038/s41598-020-78722-3. Acknowledgements This investigation was supported by the DLR grants, 50WB1030, 50WB1330, 50WB1525, and 50WB1915. We thank the crews who participated in the study and the Alfred-Wegener-Institut, Helmholtz-Zentrum für Polar- und Meeresforschung. Author contributions A.C.S. conceived, designed, planned, and supervised the study. M.A.M. and A.C.S. wrote the paper. M.A.M. and S.M. supported the data collection. M.A.M. processed and analyzed HRV data with support of G.M. and P.C.. A.C.S. performed statistical analyses and prepared the figures. G.M., P.C. and H.C.G. provided critical feedback and contributed to the interpretation of the results. All authors contributed and approved the final manuscript. Funding Open Access funding enabled and organized by Projekt DEAL. Data availability The data that support the findings of this study are openly available in figshare at. https://doi.org/10.6084/m9.figshare.12901682 Competing interests The authors declare no competing interests. ==== Refs References 1. Palinkas LA Suedfeld P Psychological effects of polar expeditions Lancet 2008 371 153 163 10.1016/S0140-6736(07)61056-3 17655924 2. Steinach M Sleep quality changes during overwintering at the german antarctic stations Neumayer II and III: The Gender Factor PLoS ONE 2016 11 e0150099 10.1371/journal.pone.0150099 26918440 3. Broadway JW Arendt J Seasonal and bright light changes of the phase position of the human melatonin rhythm in Antarctica Arctic Med. Res. 1988 47 Suppl 1 201 203 3272606 4. Kennaway DJ Van Dorp CF Free-running rhythms of melatonin, cortisol, electrolytes, and sleep in humans in Antarctica Am. J. Physiol. Integr. Comp. Physiol. 1991 260 R1137 R1144 10.1152/ajpregu.1991.260.6.R1137 5. Strewe C Sex differences in stress and immune responses during confinement in Antarctica Biol. Sex Differ. 2019 10 20 10.1186/s13293-019-0231-0 30992051 6. Steinach M Changes of 25-OH-Vitamin D during overwintering at the german antarctic stations Neumayer II and III PLoS ONE 2015 10 e0144130 10.1371/journal.pone.0144130 26641669 7. Farrace S Endocrine and psychophysiological aspects of human adaptation to the extreme Physiol. Behav. 1999 66 613 620 10.1016/S0031-9384(98)00341-2 10386905 8. Shea, C., Slack, K. J., Keeton, K. E., Palinkas, L. A. & Leveton, L. B. Antarctica Meta-analysis : Psychosocial Factors Related to Long-duration Isolation and Confinement. NASA Behavioral Health and Performance Element (2011). 9. Stahn AC Brain changes in response to long antarctic expeditions N. Engl. J. Med. 2019 381 2273 2275 10.1056/NEJMc1904905 31800997 10. Vessel, E. A. & Russo, S. Effects of Reduced Sensory Stimulation and Assessment of Countermeasures for Sensory Stimulation Augmentation. NASA Rep. (NASA/TM-2015–218576 Available at: http//ston.jsc.nasa.gov/collections/TRS) (2015). 11. Stuster J Bold Endeavors: Lessons from Polar and Space Exploration 2011 Annapolis Naval Institute Press 12. Basner M Psychological and behavioral changes during confinement in a 520-Day simulated interplanetary mission to Mars PLoS ONE 2014 9 e93298 10.1371/journal.pone.0093298 24675720 13. Buchheit M Monitoring training status with HR measures: Do all roads lead to Rome? Front. Physiol. 2014 5 1 19 10.3389/fphys.2014.00073 24478714 14. Task Force of the European Society of Cardiology and the North American Society of Pacing Electrophysiology Heart rate variability standards of measurement, physiological interpretation, and clinical use Circulation 1996 93 1043 1065 10.1161/01.CIR.93.5.1043 8598068 15. Carnevali L Koenig J Sgoifo A Ottaviani C Autonomic and brain morphological predictors of stress resilience Front. Neurosci. 2018 12 228 10.3389/fnins.2018.00228 29681793 16. Thayer JF Ahs F Fredrikson M Sollers JJ Wager TD A meta-analysis of heart rate variability and neuroimaging studies: Implications for heart rate variability as a marker of stress and health Neurosci. Biobehav. Rev. 2012 36 747 756 10.1016/j.neubiorev.2011.11.009 22178086 17. Gouin J-P Zhou B Fitzpatrick S Social integration prospectively predicts changes in heart rate variability among individuals undergoing migration stress Ann. Behav. Med. 2015 49 230 238 10.1007/s12160-014-9650-7 25212509 18. Grippo AJ Cardiac and behavioral effects of social isolation and experimental manipulation of autonomic balance Auton. Neurosci. 2018 214 1 8 10.1016/j.autneu.2018.08.002 30177218 19. Farrace S Reduced sympathetic outflow and adrenal secretory activity during a 40-day stay in the Antarctic Int. J. Psychophysiol. 2003 49 17 27 10.1016/S0167-8760(03)00074-6 12853127 20. Koenig J Thayer JF Sex differences in healthy human heart rate variability: A meta-analysis Neurosci. Biobehav. Rev. 2016 64 288 310 10.1016/j.neubiorev.2016.03.007 26964804 21. Vigo DE Sleep-wake differences in heart rate variability during a 105-Day simulated mission to mars Aviat. Space. Environ. Med. 2012 83 125 130 10.3357/ASEM.3120.2012 22303591 22. Vigo DE Circadian rhythm of autonomic cardiovascular control during Mars500 simulated mission to mars Aviat. Space. Environ. Med. 2013 84 1023 1028 10.3357/ASEM.3612.2013 24261053 23. Legates TA Fernandez DC Hattar S Light as a central modulator of circadian rhythms, sleep and affect Nat. Rev. Neurosci. 2014 15 443 54 10.1038/nrn3743 24917305 24. Alabdulgader A Long-term study of heart rate variability responses to changes in the solar and geomagnetic environment Sci. Rep. 2018 8 2663 10.1038/s41598-018-20932-x 29422633 25. PANGAEA Data Publisher for Earth & Environmental Science. Available at: https://www.pangaea.de. 26. Balzarotti S Biassoni F Colombo B Ciceri MR Cardiac vagal control as a marker of emotion regulation in healthy adults: A review Biol. Psychol. 2017 130 54 66 10.1016/j.biopsycho.2017.10.008 29079304 27. McNarry MA Lewis MJ Interaction between age and aerobic fitness in determining heart rate dynamics Physiol. Meas. 2012 33 901 914 10.1088/0967-3334/33/6/901 22551657 28. World Medical Association Declaration of Helsinki World Medical Association Declaration of Helsinki: Ethical principles for medical research involving human subjects JAMA 2013 310 2191 2124 10.1001/jama.2013.281053 24141714 29. Gamelin FX Berthoin S Bosquet L Validity of the polar S810 Heart rate monitor to measure R–R intervals at rest Med. Sci. Sports Exerc. 2006 38 887 893 10.1249/01.mss.0000218135.79476.9c 16672842 30. Montano N Power spectrum analysis of heart rate variability to assess the changes in sympathovagal balance during graded orthostatic tilt Circulation 1994 90 1826 1831 10.1161/01.CIR.90.4.1826 7923668 31. Malliani A Lombardi F Pagani M Power spectrum analysis of heart rate variability: A tool to explore neural regulatory mechanisms Br. Heart J. 1994 71 1 2 10.1136/hrt.71.1.1 32. Järvelin-Pasanen S Sinikallio S Tarvainen MP Heart rate variability and occupational stress-systematic review Ind. Health 2018 56 500 511 10.2486/indhealth.2017-0190 29910218 33. Zaffalon Júnior JR Viana A de Melo G De Angelis K The impact of sedentarism on heart rate variability (HRV) at rest and in response to mental stress in young women Physiol. Rep. 2018 6 e13873 10.14814/phy2.13873 30238692 34. Tarvainen MP Niskanen J-P Lipponen JA Ranta-aho PO Karjalainen PA Kubios HRV—Heart rate variability analysis software Comput. Methods Programs Biomed. 2014 113 210 220 10.1016/j.cmpb.2013.07.024 24054542 35. Tuckey JW Exploratory Data Analysis 1977 Boston Addison-Wesely 36. Bates, D., Maechler, M., Bolker, B. & Walker, S. lme4: Linear mixed-effects models using Eigen and S4. R package version 1.1-7, http://CRAN.R-project.org/package=lme4. R Packag. version (2014). 37. Perneger TV What’s wrong with Bonferroni adjustments BMJ 1998 316 1236 1238 10.1136/bmj.316.7139.1236 9553006 38. Fiedler K Kutzner F Krueger JI The long way from α-error control to validity proper Perspect. Psychol. Sci. 2012 7 661 669 10.1177/1745691612462587 26168128 39. Kuznetsova, A., Brockhoff, P. B. & Christensen, R. H. B. lmerTest: Tests for random and fixed effects for linear mixed effect models. R package version (2016). 40. Maxwell SE Delaney HD Kelley K Designing experiments and analyzing data: A model comparison perspective 2018 New York Routledge 41. R Foundation for Statistical Computing. R: a Language and Environment for Statistical Computing. http://www.R-project.org/ (2018).