Respiratory synchrony and individual differences causally influence dyadic interpersonal coordination

1 2 Human interpersonal coordination can yield synchronization at multiple timescales, including 3 behavioral (auditory-motor) and physiological (respiratory and cardiac) levels; yet the causal 4 relationship among these levels is poorly understood. By comparing dyadic melody perception 5 and production, we demonstrate that physiological synchrony is not merely a byproduct of 6 shared perception, as it increases significantly during joint production relative to joint perception 7 or to silence. Perturbing dyads' behavior or respiration revealed distinct causal effects: 8 respiratory perturbations impaired both dyadic respiratory and behavioral synchrony, whereas 9 auditory-motor perturbations disrupted only dyadic behavioral synchrony. Individual differences 10 further shaped synchrony: partners who shared similar spontaneous rates achieved better 11 behavioral synchrony, and partners with more similar resting heart rates exhibited stronger 12 cardiac synchrony in joint production. These findings disentangle the relationships among levels 13 of human synchrony, reveal directional entrainment processes between respiratory and 14 behavioral synchrony, and highlight the pivotal role of individual differences in interpersonal 15 coordination. 16 was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. The copyright holder for this preprint (whichthis version posted May 8, 2025. ; https://doi.org/10.1101/2025.05.02.651958doi: bioRxiv preprint 1. INTRODUCTION 1 2 Human interpersonal coordination often incorporates both intentional and spontaneous 3 (unintentional) synchronization of individuals' actions. Synchrony is considered to be a 4 fundamental, evolutionarily based mechanism that facilitates social cohesion and bonding among 5 people1–6. In addition to behavioral synchrony, physiological synchrony between individuals, 6 such as alignments in their respiratory and cardiac patterns, can coincide with group cohesion 7 and shared intentions7–16. Increased physiological synchrony has been observed among members 8 of musical groups, including choral singers17, string quartet musicians18, and drumming 9 groups10,19, when music performance is compared with a silent baseline. Despite these findings, 10 causal relationships among behavioral and physiological synchrony that arise in interpersonal 11 interactions among individuals are not well-understood. 12 Studies of interpersonal coordination often assume that respiratory or cardiac alignment 13 between individuals emerges when they perform a similar task together; how behavioral 14 synchrony facilitates that physiological synchrony is unclear20,21. Some research suggests that 15 stronger cardiac or respiratory synchrony occurs between individuals who perform a behavioral 16 synchronization task together, compared with a baseline condition17,19,22. However, these findings 17 did not establish a causal link between the behavioral and physiological variables, as the 18 directional influence of one variable on the other was not manipulated23,24. One study directly 19 examined the causal role of auditory-motor synchrony in cardiac synchrony by comparing 20 drummer trios who synchronized their beats with either predictable or unpredictable acoustic 21 cues. Drummers exhibited greater behavioral asynchronies when presented with unpredictable 22 auditory cues, but their cardiac synchrony remained unchanged across the acoustic conditions10. 23 These mixed findings raise a critical question: Whether physiological synchrony that sometimes 24 was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. The copyright holder for this preprint (whichthis version posted May 8, 2025. ; https://doi.org/10.1101/2025.05.02.651958doi: bioRxiv preprint arises between individuals is a byproduct of their shared perceptual experience (i.e., participants 1 are experiencing similar events in shared environments20,25) or is instead the result of direct 2 behavioral interactions between participants. 3 Another unsolved issue is whether physiological synchrony is necessary to facilitate 4 interpersonal coordination. It is well-established that physiological rhythms can modulate human 5 cognitive processes26–28. For example, different phases of respiratory activity can impact 6 behavior: the inhalation phase has been shown to enhance memory retrieval29, visuospatial 7 accuracy30, and auditory discrimination abilities31 relative to the exhalation phase. As well, the 8 cardiac systole phase (heart muscle contraction) is often accompanied by baroreceptor noise that 9 can inhibit visual and auditory perception while simultaneously enhancing motor excitability26. 10 Conversely, the diastole phase (heart muscle relaxation) is associated with reduced motor 11 activity but enhanced sensory evaluation26,27,32,33. These findings raise important questions about 12 whether and how physiological rhythms influence joint behavior among individuals. The current 13 study manipulated groups’ respiratory synchrony as an independent variable to test its causal 14 influence on groups’ behavioral synchrony, and vice versa. 15 Both behavioral and physiological rhythms show large and consistent differences across 16 individuals21,34–38. For example, humans tend to produce reliable and characteristic differences 17 in movement rates when talking, walking, performing music, or singing20. These optimal 18 movement frequencies, shown to require the least energy expenditure, have been modeled as the 19 natural frequencies of oscillators that represent preferred coordination states within a system, 20 known as the Spontaneous Production Rate (SPR)35,39–42. Partners with similar SPRs perform 21 more synchronously in joint tasks36, a finding that aligns with the predictions of coupled 22 oscillators with different natural frequencies; during entrainment in joint actions, oscillators with 23 was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. The copyright holder for this preprint (whichthis version posted May 8, 2025. ; https://doi.org/10.1101/2025.05.02.651958doi: bioRxiv preprint similar frequencies will synchronize more43. Similarly, individual differences in resting heart 1 rates have been observed that remain consistent over time44, but can differ across individuals by 2 as much as 70 beats per minute. If a dynamic entrainment process occurs between oscillations 3 with different natural frequencies, then dyad members with similar physiological baselines (such 4 as resting heart rates) may synchronize more than those with different physiological baselines. 5 We investigated causal relationships between behavioral and physiological synchrony in two-6 person productions of melodies, while unpredictable perturbations disturbed their auditory-motor 7 and respiratory rhythms. Amateur musicians were randomly paired to perform a musical 8 synchronization task (Figure 1A). Both respiratory and cardiac rhythms were measured, as 9 individual respiratory rhythms are known to be coupled with cardiac rhythms in a range of tasks, 10 including rest, sleep, and physical activity45–47. Participants first completed a standardized 11 individual melody production task35,36,39–41 to quantify their SPRs as a measure of behavioral 12 individual differences. Next, participants sat quietly together for a silent Baseline measurement 13 of their resting heart rates and breathing rates. Then participants completed a Perception task, 14 during which they heard the same auditory sequences they would later produce. Finally, 15 participants performed the Production task, beginning with the Normal condition, in which they 16 synchronized their melody production with their partner (Figure 1B). Sounded perturbations 17 occurred at unpredictable stimulus locations in two conditions: In the Auditory condition, a 18 sounded cue signaled that partners should restart the melody production immediately. In the 19 Respiratory condition, the same sounded cue signaled that partners should take a rapid deep 20 breath, thereby resetting their respiration rhythms. A final Normal condition was collected last. 21 We predicted that the Production task, in which both partners contributed to the shared 22 synchronization goal, would yield higher levels of respiratory/cardiac synchrony than the 23 was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. The copyright holder for this preprint (whichthis version posted May 8, 2025. ; https://doi.org/10.1101/2025.05.02.651958doi: bioRxiv preprint Baseline and Perception tasks. The Normal Production condition (with no perturbations) was 1 expected to yield the greatest behavioral and respiratory/cardiac synchrony. The Auditory 2 Production condition (auditory-motor perturbations) was anticipated to disrupt behavioral 3 synchrony and to cause reduced respiratory/cardiac synchrony between partners. Finally, the 4 Respiratory Production condition (respiratory perturbations) was expected to reduce both 5 behavioral and respiratory synchrony, compared with the Normal and Auditory conditions. 6 2. RESULTS 7 2.1 Auditory-motor synchronization in tone onsets 8 2.1.1 Perturbation effects on auditory-motor synchronization 9 Dyadic behavioral synchronization was measured by the absolute asynchronies between the 10 partners' tone onsets (intended as simultaneous). There were no significant differences in 11 absolute asynchronies between the first and last Normal conditions (t(30) = -0.003, p = 0.998), 12 and the two conditions were combined. The repeated measures ANOVA on the absolute 13 asynchronies by Task revealed a significant main effect (Figure 2A, B), F(2,60) = 14.08, p < .001, 14 η ² = 0.319. Post-hoc comparisons showed that absolute asynchronies in the Normal condition 15 were significantly smaller than those in the Auditory condition, t(30) = -2.505, pholm = 0.018, d = 16 -0.274, and the Respiratory condition, t(30)= -4.602, pholm < .001, d = -0.870. Additionally, 17 asynchronies in the Auditory condition were significantly smaller than those in the Respiratory 18 condition, t(30) = -3.113, pholm = .008, d = -0.596. Thus, participants synchronized their auditory-19 motor behaviors highest in the Normal condition, followed by the Auditory condition, with the 20 lowest synchronization in the Respiratory condition. The mean inter-tap intervals showed that 21 participants produced the melodies significantly slower in the respiratory condition than in the 22 Normal and Auditory conditions (See SI.1). 23 was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. The copyright holder for this preprint (whichthis version posted May 8, 2025. ; https://doi.org/10.1101/2025.05.02.651958doi: bioRxiv preprint To determine whether the perturbation effects were short-lived (i.e., only affecting tone 1 synchronization immediately after the perturbation cue), we removed the first and second 2 asynchronies following each cued location from the data. The same significant findings were 3 obtained, with asynchronies following the same pattern (See SI.2). Together, these findings 4 suggest that both auditory and respiration perturbations negatively impacted partners' behavioral 5 synchronization, with respiratory disruptions yielding the largest reduction. 6 2.1.2 Individual differences in auditory-motor synchronization 7 We examined the dyads' asynchronies in terms of each partner's Spontaneous Production 8 Rates (SPR) observed while producing a familiar melody, to quantify individual differences. 9 Each participant’s mean inter-tap interval (ITI) per trial from the SPR Measurement task 10 demonstrated consistent inter-individual rate differences (Figure 2C). We then tested whether the 11 dyad partners' differences in spontaneous production rate (SPR) predicted their dyadic behavioral 12 synchronization Following established procedures in previous studies39,41,48, we calculated signed 13 asynchronies in tone onsets within each dyad (Participant 1 - Participant 2) and correlated them 14 with the signed SPR differences between dyad members (Participant 1 - Participant 2) in the 15 Normal (nonperturbed) condition. The partners' signed asynchronies correlated positively with 16 their signed SPR differences, Pearson’s r = 0.38, p = 0.03 (Figure 2D). The dyad partner with the 17 faster spontaneous rate tended to precede in tone asynchronies the partner with the slower 18 spontaneous rate. Consistent with previous results41,48, the larger the partners' differences in 19 spontaneous rates, the larger their tone asynchronies were in the direction predicted by the SPR 20 values. 21 22 23 was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. The copyright holder for this preprint (whichthis version posted May 8, 2025. ; https://doi.org/10.1101/2025.05.02.651958doi: bioRxiv preprint 2.2 Perturbation effects on physiological synchronization 1 Respiratory and cardiac synchrony between the two dyad members was quantified using 2 Phase Locking V alues (PL V), which range from 0 to 1, with 1 indicating perfect phase 3 synchronization49,50. Respiratory and cardiac PLVs showed no significant differences between 4 the first and last Normal conditions (see SI.3) or between the Perception-Normal (without 5 perturbation cue) and Perception-Perturbation (with perturbation cues) conditions (see SI.4). 6 Therefore, we averaged the two Normal conditions and the two Perception conditions into a 7 single Normal and Perception task, respectively. The Production task conditions (including 8 Normal, Auditory, and Respiratory conditions) were contrasted with the Baseline and Perception 9 tasks to examine physiological differences across the tasks. Finally, we analyzed differences 10 among the Normal, Auditory, and Respiratory conditions within the Production task to assess the 11 effects of perturbations on physiological activities. 12 2.2.1 Respiratory synchronization 13 We assessed respiratory synchrony between dyad members using Phase Locking Value (PL V) 14 computed on normalized respiration amplitudes by Task. There were significant differences 15 among the Baseline, Perception, and Production tasks, F(2,60) = 3.251, p = 0.046, η ² = 0.098. 16 Linear contrasts were applied to test the hypothesized lower Baseline PLV values than in the 17 other conditions; as expected, the Baseline PLV was significantly lower than the Production PLV , 18 (t(30) = -2.144, p = 0.04, d = -0.385). The difference between Baseline and Perception PLVs 19 was not significant (t(30) = -1.658, p = 0.108). There were no significant differences between the 20 Perception and Production conditions (t(30) = 1.060, p = 0.30). 21 We next analyzed the PLV values in the three Production conditions (Normal, Auditory, 22 Respiratory), which also indicated a significant main effect, F(2,60) = 18.619, pholm < .001, η ² = 23 was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. The copyright holder for this preprint (whichthis version posted May 8, 2025. ; https://doi.org/10.1101/2025.05.02.651958doi: bioRxiv preprint 0.383. As expected, the Respiratory condition had the lowest PL V compared to the Normal (t(30) 1 = 5.183, pholm < .001, d = 0.955) and Auditory (t(30) = 4.53, pholm < .001, d = 1.00) conditions 2 (Figure 3A). There was no significant difference between the Normal and Auditory conditions 3 (t(30) = -0.318, pholm = 0.753). Surrogate analyses demonstrated that the observed dyads showed 4 significantly higher PLV compared to randomly reassigned dyads (p < 0.0042) or to randomly 5 reassigned conditions (p < 0.001, see SI.5), confirming that respiratory synchrony emerged in 6 interpersonal coordination and was manipulated by the specific conditions (Normal, Auditory, 7 Respiratory). 8 In sum, these findings confirm that the respiratory perturbation manipulation significantly 9 disrupted respiratory synchronization in interpersonal coordination. The non-significant 10 respiration PLV differences between the Normal and Auditory conditions suggest that perturbing 11 the dyads' behavioral synchronization did not affect their respiratory synchronization. 12 2.2.2 Cardiac synchronization 13 Phase Locking Values (PL V) on heart rates were analyzed next to measure cardiac 14 synchronization between dyad members. The repeated-measures ANOV A by task indicated 15 significant differences in cardiac PLVs (F(2, 60) = 3.509, p = 0.036, η ² = 0.105). The PL Vs were 16 highest in the Production task compared to the Perception task (t(30) = -2.471, p = 0.01, d = -17 0.483) and Baseline task (t(30) = -2.737, p = 0.01, d = -0.585). There was no significant 18 difference between the Perception and Baseline tasks (t(30) = -0.354, p = 0.725). Thus, joint 19 melody production enhanced cardiac synchronization, and this effect was not driven by 20 perception alone, as Perception and Baseline PLVs did not differ. 21 The same analysis was performed on the PL V values from the Normal, Auditory, and 22 Respiratory conditions. Results showed significant differences between the three Production 23 conditions, F(2, 60) = 7.688, p = 0.001, η ² = 0.204 (Figure 3B). The PLVs in the Normal 24 was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. The copyright holder for this preprint (whichthis version posted May 8, 2025. ; https://doi.org/10.1101/2025.05.02.651958doi: bioRxiv preprint condition were significantly lower than in both the Auditory (t(30) = -3.166, pholm = 0.007, d = -1 0.52) and Respiratory (t(30) = -3.712, pholm = 0.003, d = -0.816) conditions. There was no 2 significant difference between Auditory and Respiratory perturbation conditions (t(30) = -1.230, 3 pholm = 0.228). Surrogate and Monte-Carlo analyses showed that the observed dyads’ cardiac 4 synchronies were significantly higher than randomly assigned dyads (p = 0.019) or re-assigned 5 conditions (p < 0.001), suggesting that the observed synchrony was not attributable to chance or 6 solely depend on shared responses to external stimuli, but instead reflected genuine interpersonal 7 coordination shaped by specific dyadic interactions or task context. (See SI.5 for details). 8 2.2.3 Individual differences in cardiac synchronization 9 To examine whether individual differences influence cardiac synchrony, we assessed the 10 correlation between the absolute difference in partners' resting heart rates measured during 11 Baseline and their PL Vs in the Normal synchronization condition. Similar to previous findings44, 12 the mean resting heart rates (in R-R intervals) showed large but consistent inter-individual 13 differences (Figure 3C). A Spearman correlation was conducted (the Shapiro-Wilk test indicated 14 violation of the normality assumption); the absolute difference in partners' resting heart rates 15 (measured as mean R-R interval differences) was negatively correlated with the dyad's cardiac 16 PL V in the Production task (Spearman rho = -0.41, p = 0.022, Figure 3D). Thus, greater 17 similarity in dyad members' resting heart rates was associated with stronger cardiac synchrony 18 during Production. The correlations between the same measures in the Baseline and Perception 19 tasks were not significant, suggesting that the partners' joint actions, rather than shared 20 perception facilitated cardiac entrainment between individuals (see SI.6 for details). 21 In sum, the dyad's joint action facilitated respiratory and cardiac synchrony10,17,18, and 22 perturbations demonstrated that resetting either behavioral or respiratory synchronization 23 was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. The copyright holder for this preprint (whichthis version posted May 8, 2025. ; https://doi.org/10.1101/2025.05.02.651958doi: bioRxiv preprint promoted cardiac synchrony. These findings suggest that dyadic cardiac synchronization can be 1 independent of both auditory-motor and respiratory synchronization. 2 2.3 Correspondences between dyadic behavioral, respiratory, and cardiac synchrony 3 We tested correspondences between the behavioral and physiological synchronization 4 measures in the Production task. Dyadic auditory-motor asynchronies were negatively correlated 5 with dyadic respiratory PL V measures in the Normal condition (Pearson r = -0.48, p = 0.006), 6 indicating that dyads with greater respiratory phase-locking showed higher behavioral 7 synchronies. Importantly, this relationship persisted even when respiratory synchronization was 8 perturbed (Respiratory condition: Pearson r = -0.50, p = 0.005, Figure 4A), but disappeared 9 when behavioral synchronization was perturbed (Auditory condition: Pearson r = -0.161, p = 10 0.387). These findings further support the previous main effect that disrupting respiration 11 impacts behavioral synchrony, whereas disrupting behavioral synchrony does not significantly 12 alter respiration. When dyads breathed in synchrony, they were more likely to align their 13 behavior more precisely. 14 Dyadic tone onset asynchronies did not correlate significantly with the dyads' cardiac PL V in 15 the Normal synchronization condition or the Auditory or Respiratory (perturbation) conditions 16 (see SI.7). In addition, no significant correlations were observed between the dyads' cardiac and 17 respiratory PLVs in any of the Production tasks (see SI.8). 18 2.4 Individual physiological rhythms and cardiorespiratory coupling 19 To investigate whether cardiac and respiratory coupling were linked within individuals in the 20 Production task. Considering the large frequency difference between cardiac and respiratory 21 signals, we quantified individuals' cardiac–respiratory phase synchrony using the n:m phase-22 locking value, where m was fixed at 1, and n was determined by rounding the ratio of cardiac to 23 was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. The copyright holder for this preprint (whichthis version posted May 8, 2025. ; https://doi.org/10.1101/2025.05.02.651958doi: bioRxiv preprint respiratory frequency to the nearest integer for every trial45,47,50 (see Methods). Repeated-1 measures ANOVA on the PLVs revealed a significant effect of Production condition (F(2, 60) = 2 14.18, p < 0.001, η ² = 0.321, Figure 4B). Post hoc comparisons showed that individuals’ 3 cardiorespiratory PLVs were significantly lower in the Respiratory condition compared to both 4 the Normal condition (t(30) = 3.35, pholm = 0.004, d = 0.623) and the Auditory condition (t(30) = 5 5.50, pholm < 0.001, d = 1.031). No significant difference was observed between the Normal and 6 Auditory conditions (t(30) = –1.94, pholm = 0.062). To confirm that individual cardiorespiratory 7 PL Vs reflected genuine within-individual coupling, we conducted a surrogate analysis in which 8 each participant’s cardiac time series was reassigned to the respiration time series of another 9 individual within each Production condition. A Monte Carlo simulation revealed that PLVs were 10 significantly higher in the observed individuals' cardiorespiratory pairings compared to the 11 surrogate pairings (p < 0.001; see SI.9 for details), indicating reliable phase coupling within 12 individuals’ cardiorespiratory systems. 13 In sum, individual-level physiological dynamics indicated that respiratory perturbations led 14 to a decoupling of cardiac and respiratory rhythms. In contrast, auditory-motor perturbations did 15 not significantly alter individual physiological dynamics. 16 3. Discussion 17 Human interpersonal synchronization occurs at multiple levels; the present study reported a 18 directional relationship between behavioral and physiological synchronization in dyads while 19 they performed a joint task in a novel perturbation paradigm. We replicated previous findings17–20 19,51,52 that joint group activity promotes dyadic cardiac and respiratory synchronization 21 compared to a quiet baseline. Critically, the dyads' increased physiological synchronization was 22 not simply due to shared perceptual experiences; no significant change or causal relationship was 23 was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. The copyright holder for this preprint (whichthis version posted May 8, 2025. ; https://doi.org/10.1101/2025.05.02.651958doi: bioRxiv preprint observed in the Perception task, which required the dyads to perceive and respond to the same 1 auditory stimuli as they heard during joint production. Furthermore, we reported the first causal 2 evidence linking respiratory synchrony to auditory-motor synchrony; when dyads breathed more 3 synchronously, they synchronized their auditory-motor behavior more accurately. The study also 4 provided evidence that the dyads' individual differences influenced interpersonal synchronization 5 at physiological levels. Dyads with smaller individual differences in Spontaneous Production 6 Rate achieved better behavioral synchrony in the Production tasks40,41,48. Similarly, dyads with 7 smaller differences in resting heart rate exhibited higher cardiac synchrony in joint production. 8 Together, these findings provide new insights into the dynamic entrainment processes underlying 9 person-to-person synchronization at both behavioral and physiological levels, which we review 10 next. 11 First, we demonstrated a causal, unidirectional influence of respiratory synchrony on 12 auditory–motor synchrony (Fig. 4C). Disruptions to respiratory synchrony during the Respiratory 13 condition significantly reduced the dyads' auditory–motor synchronization, whereas disruptions 14 to auditory–motor synchrony during the Auditory condition had no measurable effect on dyads' 15 respiratory synchrony. This asymmetry supports a directional influence from respiratory to 16 behavioral synchrony. Follow-up correlation analyses further indicated the critical role of 17 respiratory synchrony in interpersonal coordination: a significant negative correlation between 18 dyads’ respiratory PLVs and auditory-motor asynchronies was observed in the Normal condition, 19 and this relationship persisted in the Respiratory condition, despite direct perturbation of 20 breathing patterns. These findings reveal a millisecond-level correspondence between temporal 21 behavioral and physiological coordination, extrapolating beyond prior evidence that compared 22 synchrony in joint action with baseline conditions only17,18. 23 was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. The copyright holder for this preprint (whichthis version posted May 8, 2025. ; https://doi.org/10.1101/2025.05.02.651958doi: bioRxiv preprint Second, heightened cardiac synchrony between dyad members was observed in all 1 perturbation conditions, despite the dyads' increased auditory-motor asynchronies in those 2 conditions. Cardiac synchrony appeared to be independent of the dyads' auditory-motor 3 synchrony, similar to previous studies of group drumming10. Instead, the elevated cardiac 4 synchrony may have been driven by the resetting demands imposed by the perturbation cues. We 5 propose that the perturbation cues may have modulated the dyads' dynamic attending processes, 6 leading to shared fluctuations in attention and arousal throughout the trial53. This interpretation is 7 supported by findings that group cardiac synchrony decreases in distracted-listening conditions 8 compared to attentive-listening conditions during audiovisual narratives54. Although increased 9 cardiac synchrony is often interpreted as an index of shared positive affect and group 10 cohesion7,9,10,15,55, our findings suggest that cardiac synchrony can also reflect negative outcomes, 11 such as the dyads' increased behavioral asynchronies. Research findings on mother-infant 12 interactions indicate that cardiac synchrony can arise during shared stress responses or stressful 13 social interactions56. Rather than an index of shared positive affective valence among group 14 members, cardiac synchrony is more likely a general physiological marker of shared attentional 15 fluctuations. 16 Previous findings have focused on individual cardiorespiratory coupling and how that 17 coupling changes in individual psychophysiological states and tasks45,46,57. In the current study, 18 individuals' cardiorespiratory phase coupling was reliably maintained in the Normal and 19 Auditory conditions but significantly reduced under Respiratory perturbations, reflecting some 20 cardiorespiratory dissociation when breathing conditions were altered. This within-individual 21 reduction coincided with decreased dyadic respiratory synchrony and elevated dyadic cardiac 22 synchrony relative to the Normal condition. Consistent with previous findings, this demonstrates 23 was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. The copyright holder for this preprint (whichthis version posted May 8, 2025. ; https://doi.org/10.1101/2025.05.02.651958doi: bioRxiv preprint that dyadic heart rate synchronization is always not driven by the dyads' synchronous breathing54 1 and indicates distinct mechanisms driving cardiac and respiratory synchrony on a group level: 2 dyadic respiratory synchrony was closely linked to auditory–motor coordination, while dyadic 3 cardiac synchrony may have arisen independently of overt behavioral synchrony. 4 Finally, individual differences observed in the randomly paired dyad members shaped the 5 dyad's auditory-motor and cardiac synchrony in the Production tasks. Previous studies have 6 demonstrated that partners with similar Spontaneous Production Rates exhibited increased 7 auditory-motor synchronization48,58. The current study replicated this finding and extended it to 8 the physiological level: Dyadic members with similar baseline heart rates exhibited greater 9 cardiac synchronization during joint production. An important step in understanding how 10 intrinsic frequencies influence physiology, a dynamical systems perspective suggests that two 11 hearts may function as coupled oscillators whose similar intrinsic frequencies require less 12 external energy to adapt and maintain synchrony, as frequency-matched systems naturally fall 13 into stable phase relationships with less external forcing43,59,60. Thus, individuals with closely 14 matched intrinsic frequencies behaviorally or physiologically likely synchronize more efficiently 15 due to lower energy costs in adapting to each other’s biological rhythms. 16 Dyadic analysis of behavioral and physiological synchrony requires different design 17 considerations to permit comparable interpersonal synchronization measures. First, a data 18 collection interface that enables the capture of low-latency, high-precision auditory sequences is 19 necessary to ensure millisecond-level accuracy in measuring multiple participants’ temporal 20 coordination61. Second, a perturbation paradigm must be implemented to ensure consistency 21 across dyad members; both participants perceived or produced identical rhythmic sequences in 22 all tasks, controlling for the possible role of perception in facilitating physiological synchrony. 23 was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. The copyright holder for this preprint (whichthis version posted May 8, 2025. ; https://doi.org/10.1101/2025.05.02.651958doi: bioRxiv preprint Third, the same perturbation cues must be presented to both participants to allow for direct 1 comparison across perturbation conditions. Finally, causal analyses within each dependent 2 variable (behavioral asynchronies, respiratory and cardiac measures) minimize the need for data 3 interpolation when comparing time series based on different temporal resolution. These dyadic 4 adjustments permit us to make robust causal inference between different types of distinct 5 physiological and behavioral signals. Future studies may extend these design issues to larger 6 groups of interpersonal coordination60. 7 In sum, by integrating behavioral and physiological measures within a controlled 8 experimental framework, this study provides novel insights into how auditory-motor, respiratory, 9 and cardiac synchrony interact and dynamically emerge within and between individuals. These 10 findings offer a comprehensive perspective on physiological synchronization in dyads, and hold 11 promise for future measurement of interpersonal coordination in real-world settings. For instance, 12 strategically modulating breathing patterns or pairing individuals with compatible physiological 13 rhythms could optimize synchrony in collaborative tasks such as musical ensembles, therapeutic 14 interactions, or team-based activities requiring high coordination. Additionally, these insights 15 may inform interventions for individuals with social communication challenges by maximizing 16 physiological entrainment strategies to improve social attunement and group cohesion. 17 4. Methods 18 4.1 Participants 19 A total of 62 participants (14 males, 48 females, and 2 nonbinary; age range: 18–34 years; M 20 = 22.55, SD = 4.20) were recruited in the Montreal community and randomly assigned to 31 21 pairs to perform the dyadic tasks. The sample size of 31 dyads was determined a priori using 22 G*Power, with an estimated medium effect size of /g1858 = 0.25 and power of 0.85 to detect 23 was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. The copyright holder for this preprint (whichthis version posted May 8, 2025. ; https://doi.org/10.1101/2025.05.02.651958doi: bioRxiv preprint significant differences across the three conditions. All participants had at least six years of 1 individual music instruction and had never performed music with each other before the study (M 2 = 11.87 years, SD = 4.06) and provided informed consent before beginning the experiment. The 3 study was approved by McGill University’s Research Ethics Board. Participants received either 4 course credit or a small honorarium upon completing the experiment which lasted approximately 5 90 minutes 6 4.2 Materials 7 The auditory sequences used in the Perception and Production tasks featured repeating 16-8 note binary meter pattern, each containing a total of 16 beats (one beat = 500 ms): presented with 9 a classic piano timbre preset on a Roland Studio Canvas SD-50 tone generator. One pattern 10 contained five ascending tones (G4, A4, B4, C5, D5), three beats of silence, five descending 11 tones (D5, C5, B4, A4, G4), and three more beats of silence. A second auditory pattern, presented 12 one octave higher than the first pattern, was designed to be discriminable when both patterns 13 were produced simultaneously in the Production conditions. Trials in the Production condition 14 began with eight metronome beats at 500 ms intervals to establish the indicated rate, presented at 15 a high-hat drum timbre on the SD-50 tone generator. Perturbation cues occurred eight times in 16 each Production trial and were placed pseudo-randomly within 500-1000 ms after the first silent 17 beat in each auditory pattern. 18 Participants completed two questionnaires: A customized musical background questionnaire 19 and Goldsmith’s Musical Sophistication Questionnaire62 at the start of the experiment to 20 determine their past experience with music and level of expertise (results see SI.12). Additionally, 21 participants completed a Social Interaction Questionnaire63 after each Production condition to 22 was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. The copyright holder for this preprint (whichthis version posted May 8, 2025. ; https://doi.org/10.1101/2025.05.02.651958doi: bioRxiv preprint assess their subjective judgments about their partner interaction during the experiment on a 7-1 point Likert scale (results see SI. Part II). 2 4.3 Equipment 3 To ensure precise sequence production timing, Arduino-based force-sensitive tapping pads 4 were used connected to a Toshiba Linux computer via MIDI64. Each tap on the force sensor 5 triggered the next tone in the stimulus melody, generated by a Roland Studio Canvas SD-50 and 6 delivered to the participant through Sennheiser HD650 headphones. Timing values were 7 recorded with 1-millisecond resolution using FTAP61. 8 Physiological data were recorded using Biopoint sensors (Quebec, Canada) and Vernier 9 GDX-RB respiration belts (Oregon, USA). The Biopoint sensors, placed on the non-dominant 10 wrist, captured bipolar ECG data at 500 Hz, with sensor leads positioned on the underside of the 11 wrist and a ground electrode attached to the dominant-side waist. The respiration belts, secured 12 around the chest near the diaphragm, recorded inhalation and exhalation motion at 10 Hz. All 13 data streams were synchronized using custom Python scripts on a Linux computer. 14 4.4 Design and Procedure 15 The within-subject design consisted of four separate tasks performed in the following order: 16 Individual differences measurement, Baseline measurement, Perception task, and Production task 17 (Figure 1B). 18 After participants provided consent, they completed the two music background 19 questionnaires. Then the participants completed a standardized individual Spontaneous Rate 20 (SPR) measurement task individually, to determine the rate of their spontaneous productions of a 21 familiar melody35,36,41,48. Participants first confirmed their familiarity with the melody “Twinkle 22 Twinkle Little Star”, an isochronous rhythm used in previous studies to measure participants’ 23 was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. The copyright holder for this preprint (whichthis version posted May 8, 2025. ; https://doi.org/10.1101/2025.05.02.651958doi: bioRxiv preprint natural frequencies35,41,48. Participants produced the melody by tapping on the force-sensitive pad 1 with their index finger at a steady and consistent rate, where each tap produced the next tone in 2 the sequence, heard over headphones in a marimba timbre (GM2, patch 13, bank #0) produced 3 on a SD-50 tone generator at a fixed loudness level. They were instructed to tap the melody for 4 three iterations without any pauses on each trial and they completed 3 trials. Each participant's 5 spontaneous rate was calculated from the middle two complete repetitions of the melody to 6 capture maximally stable rhythmic behavior (excluding the initial 16 and final 32 tones)35,36. The 7 mean and standard error of the intertap intervals (ITI) of the produced melodies on each trial 8 were computed as each participants' Spontaneous rate. 9 Next, the participants were brought to the same testing room to complete the rest of the tasks. 10 First, a ninety-second-long silent Baseline measurement was conducted to assess participants’ 11 resting heart rate and respiratory patterns during which, participants were asked to sit quietly and 12 remain still. 13 The Perception task was conducted to assess physiological responses during melody 14 perception and to ensure that participants could reliably detect both melodies when presented 15 simultaneously and the perturbation cues. During the Normal Perception trial, participants 16 listened to the melody without perturbation cues; during the Perturbation Perception trial, 17 perturbation cues were embedded at the same locations as in the Production task. Participants 18 were told that some trials would contain high-pitched cues and they were instructed to count the 19 number of cues on each trial. There was a total of three trials. Participants were required to report 20 the correct number of cues to continue in the study. 21 Next, the Production task was conducted; participants were instructed to produce the 22 melody on the force sensor pads while they were seated face-to-face, with a visual barrier 23 was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. The copyright holder for this preprint (whichthis version posted May 8, 2025. ; https://doi.org/10.1101/2025.05.02.651958doi: bioRxiv preprint preventing them from seeing each other's hands (Figure 1A). They were asked to synchronize 1 their melody with their partner as accurately as possible after the initial metronome cue ended, 2 while maintaining the metronome's rate. The Production task consisted of three conditions: 3 Normal, Auditory, and Respiratory. The Normal condition was conducted twice (at the beginning 4 and end of the Production task), and the order of the Auditory and Respiratory conditions was 5 counterbalanced across pairs. Each condition included practice trials for participants to 6 familiarize themselves with the task. 7 During the Normal trials, participants were instructed to produce the melody in synchrony 8 with their partner. During the Respiratory trials, participants were instructed to perform the same 9 melody, and that during unpredictable silent beats, a high-pitched sound would signal both 10 participants to take a quick, deep breath. During the Auditory condition, participants were 11 instructed to perform the same melody, and that during unpredictable silent beats, a high-pitched 12 sound would signal both participants to immediately restart the melody on the next beat, starting 13 with the first melody tone. 14 4.5 Data Analyses 15 4.5.1 Behavioral data analysis 16 The melody production data was processed using a Python script that extracted tone onsets 17 from each force sensor. Each participant's inter-tap intervals (ITIs), defined as the time intervals 18 between consecutive taps (in ms), and the dyad's absolute asynchronies (defined as the absolute 19 value of Participant 1's tone onsets - Participant 2's tone onsets) for tones intended as 20 simultaneous (ie, from the same serial position in the melodies) were computed. Trials 21 containing three or more ITIs exceeding 1000 ms (i.e., longer than two reference beats) or 22 was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. The copyright holder for this preprint (whichthis version posted May 8, 2025. ; https://doi.org/10.1101/2025.05.02.651958doi: bioRxiv preprint asynchronies exceeding 1000 ms were excluded from the analysis. In total, 14 trials (3.8% of all 1 trials) and 43 asynchronies (0.1% of all asynchrony data) were excluded. 2 4.5.2 Physiological data analysis 3 Both respiratory and cardiac data were preprocessed and cleaned using NeuroKit2 in 4 Python 3.8 following established procedures65. Cardiac data quality was first assessed using an 5 automated algorithm66, and only the signals classified as high-quality were included in the 6 analyses. No trials were excluded based on this assessment. The raw ECG signals were then 7 preprocessed using a fifth-order, 0.5 Hz high-pass Butterworth filter, followed by powerline 8 filtering65. R-R intervals were extracted using the NeuroKit algorithm and corrected for potential 9 artifacts67. To ensure data length consistency between participants7,18, R-R intervals were 10 resampled to 0.2-second intervals BPM data68. 11 Respiratory data were normalized, detrended, and filtered using a second-order Butterworth 12 bandpass filter (0.05–3 Hz)69,70. Then the respiration peak detection was performed by the 13 NeuroKit2 software; Inhale-to-inhale intervals were then extracted from the cleaned respiration 14 signals69. To confirm compliance with the deep breathing instructions in the Respiratory 15 condition, we visually inspected the alignment between breathing cycles and perturbation cue 16 locations. Trials were excluded if fewer than six of the eight expected deep breaths were detected 17 as prominent respiration cycles. Based on this criterion, 8 trials (2.1% of the total trials) were 18 removed from the dataset. 19 Physiological synchronization was assessed using Phase Locking Value (PLV) in a Python 20 3.8 script; PL V is a measure that quantifies the consistency of phase differences between two 21 time series49,50, and has been widely applied to two periodic time series to quantify the level of 22 synchronization in their relative phase12,47,49,50,71,72. PL V provides a normalized value ranging 23 was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. The copyright holder for this preprint (whichthis version posted May 8, 2025. ; https://doi.org/10.1101/2025.05.02.651958doi: bioRxiv preprint from 0 (no synchronization) to 1 (perfect synchronization), indicating the stability of the phase 1 relationship over time and, consequently, the strength of synchronization. 2 We applied the Hilbert transform to extract the instantaneous phase of each participant’s time 3 series at each time point. For dyadic cardiac and respiratory PLV analyses, the phase difference 4 between the two pre-processed time series (Participant 1’s heart rate/respiration – Participant 2’s 5 heart rate/respiration) was computed at each time point as Δ/i2 (k). For within-individual 6 cardiorespiratory PLV analyses, to account for frequency and sampling rate differences between 7 cardiac and respiratory signals, the R peaks timing was extracted from ECG signals, and mapped 8 with respiratory signals, n:m (n = cardiac frequency, m = respiratory frequency) phase difference 9 was calculated as: Δ/g2038 /g4666 /g1863 /g4667 /g3404/g1866/g1668/g2038 /g3045/g3032/g3046/g3043/g4666 /g1863 /g4667 /g3398/g1865/g1668/g2038 /g3032/g3030/g3034/g4666 /g1863 /g4667 . Following established procedures45,47, 10 m was fixed at 1, and n was determined by rounding the ratio of cardiac to respiratory frequency 11 to the nearest integer for every trial . PLV for each trial was calculated using the following 12 equation: 13 PLV /g3404 /g3629 1 /g1840 /g3533/g1857 /g3036/g2940/g3109/g4666/g3038/g4667 /g3015 /g3038/g2880/g2869 /g3629 ( 1 ) 14 where N is the number of time points in the trial. The magnitude of the mean resultant vector 15 reflects the consistency of phase differences within one trial, with higher PLV values indicating 16 stronger phase-locking between signals. 17 4.5.3 Statistical analysis 18 All statistical analyses were conducted in R (RStudio 2024.10) using ANOV A with repeated 19 measures for comparisons across Baseline, Perception, and Production conditions. A second set 20 of ANOV As compared differences across the 3 Production conditions (Normal, Auditory, 21 was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. The copyright holder for this preprint (whichthis version posted May 8, 2025. ; https://doi.org/10.1101/2025.05.02.651958doi: bioRxiv preprint Respiratory). When a significant main effect was observed (α = 0.05), Holm–Bonferroni–1 corrected post hoc tests were applied to adjust for multiple pairwise comparisons. To examine 2 relationships within and between behavioral and physiological measures, Pearson correlation 3 analyses were performed; Spearman rho was performed when data did not meet normality 4 assumptions. Outliers—defined as data points exceeding three standard deviations from the 5 mean—were excluded from the correlation analysis (only one data point got removed). PL V 6 values were computed separately for each trial in the Normal, Auditory, and Respiratory 7 conditions to assess how experimental manipulations influenced cardiac and respiratory 8 synchronization. A repeated-measures analysis of variance (ANOV A) was conducted to compare 9 PL V values across conditions, testing whether task demands and perturbation cues modulated 10 physiological coupling between participants. 11 12 was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. The copyright holder for this preprint (whichthis version posted May 8, 2025. ; https://doi.org/10.1101/2025.05.02.651958doi: bioRxiv preprint Acknowledgments 1 The authors acknowledge the assistance of Elizabeth Harrigan, Kai Mikkelsen, and Joshua 2 Samuels in data collection and technical assistance. This work was partially funded by grants 3 from the Natural Sciences and Engineering Research Council of Canada—Create Graduate 4 Fellowship to W.Y ., and from the Natural Sciences and Engineering Research Council of Canada 5 (Discovery Grant 298173) and Canada Research Chair to C.P. 6 7 8 9 10 11 12 13 was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. The copyright holder for this preprint (whichthis version posted May 8, 2025. ; https://doi.org/10.1101/2025.05.02.651958doi: bioRxiv preprint 1 2 Figure 1. Experimental paradigm. 3 A) Two participants sat face-to-face with a visual barrier occluding finger movements. Each 4 participant produced an auditory sequence, with possible perturbation cue locations indicated. 5 B) Overview of the experimental procedure, including individual tasks (questionnaires, 6 spontaneous production rate measurement), baseline task while seated together (90 s of silence), 7 perception tasks while seated together (listening to the Normal melody without cues and the 8 Perturbation melody with cues), and production tasks. Production conditions included: Normal 9 (melody without cues), Auditory (melody with auditory cues prompting participants to reset to 10 the start), and Respiratory (melody with auditory cues prompting participants to inhale deeply 11 and quickly to reset respiration). The Normal condition was repeated, and the order of Auditory 12 and Respiratory conditions was counterbalanced across dyads. 13 C) Data analysis pipeline. Physiological (ECG and respiration) and Behavioral (tone onset) data 14 were recorded from each participant. Data pre-processing procedures were applied to ECG, 15 respiratory, and behavioral signals (see Methods for details). 16 17 was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. The copyright holder for this preprint (whichthis version posted May 8, 2025. ; https://doi.org/10.1101/2025.05.02.651958doi: bioRxiv preprint 1 2 Figure 2. Behavioral measures from Spontaneous Production Rate and Production task. 3 A) Example trials from one dyad showing auditory-motor synchronization across Production 4 conditions (Normal, Auditory, Respiratory). Absolute asynchronies were computed as the 5 absolute difference between tone onsets from Participant 1 and Participant 2. Dashed lines 6 indicate perturbation cue locations; gaps denote silent beats (rests) within a trial. 7 B) Mean absolute asynchronies across dyads in the three Production conditions. Box plots 8 display medians (horizontal lines) and means (circles in boxes). Significance markers: p < 0.05 9 (*), p < 0.01 (**), p < 0.001 (***). 10 C) Mean intertap intervals (ms) from the Spontaneous Production Rate (SPR) task, ranked from 11 fastest to slowest across participants. Error bars indicate the standard error of the mean. 12 D) Correlation between mean signed asynchrony (Participant 1’s higher-pitched tone onsets -13 Participant 2’s lower-pitched tone onsets, in ms) and the dyad’s SPR difference (Participant 1 -14 Participant 2, in ms). A significant positive correlation was observed (Pearson r = 0.38, p = 15 0.033); the regression line is shown. 16 17 18 was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. The copyright holder for this preprint (whichthis version posted May 8, 2025. ; https://doi.org/10.1101/2025.05.02.651958doi: bioRxiv preprint 1 2 Figure 3. Respiratory and Cardiac measures from Production task. 3 A) Mean respiratory phase-locking values (PL Vs) between dyad members across Production 4 tasks (Normal, Auditory, Respiratory). Box plots show medians (horizontal lines) and means 5 (circles in boxes). Significance markers: p < 0.05 (*), p < 0.01 (**), p < 0.001 (***). 6 B) Mean cardiac PLVs across Production tasks (Normal, Auditory, Respiratory). Box plots 7 indicate medians (horizontal lines) and means (circles in boxes), significance markers: p < 0.05 8 (*), p < 0.01 (**), p < 0.001 (***). 9 C) Individual mean resting heart rates (mean R–R interval, in ms) recorded during the Baseline 10 task, ranked from fastest (shortest interval) to slowest rate (longest interval). 11 D) Correlation between absolute differences in the ranks of resting heart rate between dyad 12 members (Participant 1 – Participant 2 in R–R interval, ms) and the rank of their mean cardiac 13 PL V in the Normal condition. A significant negative correlation was observed (Spearman’s rho = 14 –0.41, p = 0.022); the regression line is shown. 15 16 = was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. The copyright holder for this preprint (whichthis version posted May 8, 2025. ; https://doi.org/10.1101/2025.05.02.651958doi: bioRxiv preprint 1 2 Figure 4. Dyadic Respiratory and Individual Cardiorespiratory measures in Production 3 task. 4 A) Negative correlations between participants’ mean absolute asynchronies and their respiratory 5 PLVs in both the Normal (Pearson r = –0.48, p = 0.006) and Respiratory (Pearson r = –0.50, p = 6 0.005) conditions, indicating a tight link between respiratory synchrony and coordinated 7 behavior. 8 B) Mean cardiorespiratory PLVs within individuals across Production conditions. Box plots 9 show medians (horizontal lines) and means (circles in boxes). Significance markers: p < 0.05 (*), 10 p < 0.01 (**), p < 0.001 (***). 11 C) Schematic summary of observed relationships between auditory–motor, cardiac, and 12 respiratory Dyadic synchrony (middle, black), and individual differences in rates and 13 cardiorespiratory measures. Solid arrows indicate observed directional influences. 14 15 16 17 18 ), was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. The copyright holder for this preprint (whichthis version posted May 8, 2025. ; https://doi.org/10.1101/2025.05.02.651958doi: bioRxiv preprint

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