Respiratory and Cardiac Phase Coupling With Voluntary Actions Across Motor Tasks

Respiratory and Cardiac Phase Coupling With Voluntary Actions Across Motor Tasks | Authorea try { document.documentElement.classList.add('js'); } catch (e) { } var _gaq = _gaq || []; _gaq.push(['_setAccount', 'G-8VDV14Y67G']); _gaq.push(['_trackPageview']); (function() { var ga = document.createElement('script'); ga.type = 'text/javascript'; ga.async = true; ga.src = ('https:' == document.location.protocol ? 'https://ssl' : 'http://www') + '.google-analytics.com/ga.js'; var s = document.getElementsByTagName('script')[0]; s.parentNode.insertBefore(ga, s); })(); Skip to main content Preprints Collections Wiley Open Research IET Open Research Ecological Society of Japan All Collections About About Authorea FAQs Contact Us Quick Search anywhere Search for preprint articles, keywords, etc. Search Search ADVANCED SEARCH SCROLL Psychophysiology This is a preprint and has not been peer reviewed. Data may be preliminary. 27 June 2025 V1 Latest version Share on Respiratory and Cardiac Phase Coupling With Voluntary Actions Across Motor Tasks Authors : Hiroshi Shibata 0009-0002-4507-5092 [email protected] and Hideki Ohira Authors Info & Affiliations https://doi.org/10.22541/au.175102585.59392045/v1 Published Psychophysiology Version of record Peer review timeline 351 views 185 downloads Contents Abstract Supplementary Material Information & Authors Metrics & Citations View Options References Figures Tables Media Share Abstract Interoceptive signals such as breathing and heartbeat constitute the internal bodily rhythms that influence perception and motor processes. Recent studies have indicated that breathing phases, particularly exhalation, synchronize with voluntary actions, reflecting a general influence on motor intention; however, this effect can also be explained by the alignment with specific motor schemas. This study aimed to investigate (i) respiratory synchronization across different voluntary motor tasks, (ii) the interaction between the respiratory synchronization of stimulus presentation and voluntary actions, and (iii) cardiac synchronization with voluntary actions. A total of 32 healthy participants performed two voluntary motor tasks: a modified Libet clock task and an elbow flexion–extension task. In the Libet clock task, the participants either pressed a key at a spontaneously chosen time (key-press condition) or spontaneously released the key after holding it pressed (key-release condition). In the elbow flexion–extension task, the participants spontaneously pushed (elbow extension) or pulled (elbow flexion) a joystick. The results demonstrated that the voluntary actions across different effectors (finger extension, finger flexion, elbow extension, and elbow flexion) were consistently synchronized with exhalation. Furthermore, stimulus presentation was correlated with the breathing phases, influencing subsequent action timing. Finally, we observed weak but consistent diastole synchronization with voluntary actions. Collectively, these findings revealed the diverse interoceptive synchronization mechanisms underlying voluntary action timing. jabbrv-ltwa-all.ldf jabbrv-ltwa-en.ldf Respiratory and Cardiac Phase Coupling With Voluntary Actions Across Motor Tasks Hiroshi Shibata 1* , Hideki Ohira 1 1 Department of Informatics, Nagoya University, Nagoya, Aichi, Japan, 464-8601 * Corresponding author: Hiroshi Shibata Department of Informatics, Nagoya University, Furo-cho, Chikusa-ku, Nagoya, Aichi, Japan, 464-8601 E-mail: [email protected] , [email protected] Abstract Interoceptive signals such as breathing and heartbeat constitute the internal bodily rhythms that influence perception and motor processes. Recent studies have indicated that breathing phases, particularly exhalation, synchronize with voluntary actions, reflecting a general influence on motor intention; however, this effect can also be explained by the alignment with specific motor schemas. This study aimed to investigate (i) respiratory synchronization across different voluntary motor tasks, (ii) the interaction between the respiratory synchronization of stimulus presentation and voluntary actions, and (iii) cardiac synchronization with voluntary actions. A total of 32 healthy participants performed two voluntary motor tasks: a modified Libet clock task and an elbow flexion–extension task. In the Libet clock task, the participants either pressed a key at a spontaneously chosen time (key-press condition) or spontaneously released the key after holding it pressed (key-release condition). In the elbow flexion–extension task, the participants spontaneously pushed (elbow extension) or pulled (elbow flexion) a joystick. The results demonstrated that the voluntary actions across different effectors (finger extension, finger flexion, elbow extension, and elbow flexion) were consistently synchronized with exhalation. Furthermore, stimulus presentation was correlated with the breathing phases, influencing subsequent action timing. Finally, we observed weak but consistent diastole synchronization with voluntary actions. Collectively, these findings revealed the diverse interoceptive synchronization mechanisms underlying voluntary action timing. Keywords: respiration, heartbeat, voluntary action, interoception, sensorimotor synchronization 1 Introduction Breathing is an internal body rhythm that modulates perception and behavior. In recent years, a growing body of research has demonstrated that interoception—our representation of bodily states derived from physiological signals (Chen et al., 2021)—influences various aspects of our lives, including emotion and cognition (Critchley & Garfinkel, 2017, 2018). Although early studies primarily focused on the cardiac domain (Garfinkel et al., 2014; Tsakiris et al., 2011), accumulating evidence indicates that the respiratory phases, particularly inhalation and exhalation, systematically modulate perception, cognition, and emotional processing (Mizuhara & Nittono, 2023; Perl et al., 2019; Zelano et al., 2016). For instance, intracranial electroencephalogram studies have provided neurophysiological evidence for such respiratory influences, demonstrating that nasal inhalation enhances cortical oscillations and, consequently, improves sensory and memory processes (Zelano et al., 2016). Besides modulating sensory processes, respiratory phases also affect and synchronize motor processes. Behavioral studies have reported that response times are modulated by breathing phases and that response timing is synchronized with breathing (Harting et al., 2025; Johannknecht & Kayser, 2022). Similar respiratory synchronization is evident in motor control; for instance, eye movements systematically align with respiratory phases during sleep (Rittweger & Pöpel, 1998) and wakefulness (Rassler & Raabe, 2003). Arm extension and flexion are synchronized with respiration when guided by visual stimuli (Krupnik et al., 2015). Furthermore, rhythmic movements such as walking and tapping are also known to synchronize with breathing (Bechbache & Duffin, 1977; Ebert et al., 2002; Wilke et al., 2013). These findings demonstrate a robust and widespread relationship between the respiratory phases and motor processes. Voluntary action initiation shows a marked bias toward the exhalation phase. Park et al. (2020) demonstrated that self-initiated key presses preferentially occur during late exhalation. This timing coincides with oscillations in readiness potential (RP) amplitudes, suggesting the respiratory modulation of voluntary action initiation. Subsequent research extended these findings to cognitive tasks, such as motor and visual imagery, showing similar respiratory biases and RP coupling patterns (Park et al., 2022). By contrast, Perl et al. (2019) observed voluntary task initiation locked to the inhalation phase, which likely resulted from optimization for subsequent cognitive tasks, indicating task-specific respiratory alignment strategies. Further evidence indicates that motor responses occur predominantly during exhalation (Harting et al., 2025; Johannknecht & Kayser, 2022). This synchronization between respiration and voluntary actions may involve higher-order cortical regions, reflecting the integrative processing of respiratory and motor signals. However, studies predominantly focused on a single effector type (finger flexion). Research on muscular physiology indicates that respiratory modulation varies depending on movement characteristics. For instance, the maximal finger flexor force significantly increases during exhalation (Li & Laskin, 2006), and the elbow extension torque is similarly facilitated during exhalation; however, elbow flexion remains unaffected (Ikeda et al., 2009). Additionally, respiratory phases differentially affect motor precision depending on the effector type. For example, finger flexion accuracy deteriorates during exhalation, whereas finger extension accuracy decreases during inhalation (Rassler, 2000). Collectively, these biomechanical data suggest a potential match–mismatch mechanism between motor schemas and respiratory phases. Thus, it remains unclear whether the previously observed exhalation-linked preference (Harting et al., 2025; Johannknecht & Kayser, 2022; Park et al., 2020) generalizes to proximal limb movements, such as elbow flexion and extension, or movements involving opposite kinematic characteristics, such as finger extension. Moreover, two critical issues remain unresolved. First, although recent studies have suggested that stimulus presentations can be synchronized with breathing (Harting et al., 2025; Johannknecht & Kayser, 2022), the potential influence of this stimulus synchronization on voluntary action timing has been largely overlooked. For instance, the commonly used Libet clock task (Libet et al., 1983; Park et al., 2020) incorporates stimulus presentations that potentially align with breathing, possibly confounding action synchronization. Therefore, whether stimulus- and action-locked respiratory synchronizations represent distinct or shared mechanisms remains unknown (Harting et al., 2025). Second, the evidence for cardiac synchronization in voluntary actions remains inconsistent. While Park et al. (2020) found no systematic cardiac phase bias during voluntary key presses, Mussini et al. (2024) showed that participants refrained from action initiation during systole, supporting the baroreceptor-mediated inhibitory theories (Makowski et al., 2020; Rae et al., 2018). Kunzendorf et al. (2019) and Palser et al. (2021) similarly reported the systolic alignment of voluntary action initiation. These mixed findings may stem from methodological or task-based differences. To address this inconsistency, we adopted the Libet clock task, matching the approach used by Park et al. (2020), and conducted circular and biphasic analyses. Therefore, the present study aimed to investigate (i) whether voluntary actions involving distinct effectors (finger flexion, finger extension, elbow flexion, and elbow extension) exhibit a consistent exhalation-phase bias; (ii) whether respiratory phases simultaneously modulate stimulus presentation and action initiation; and (iii) whether voluntary actions synchronize with cardiac cycles, addressing the discrepancies in previous findings. Additionally, we explored the individual physiological factors that could explain the variability in respiratory–action synchronization. By comprehensively addressing these questions, we aimed to clarify the contradictions in the literature and refine the theoretical models of the respiratory-driven temporal organization of perception and motor behavior in humans. 2 Methods 2.1 Participants The participants were 32 healthy Japanese students (17 female; 27 right-handed; mean age: 21.87 ± 2.42 years) attending Nagoya University in Japan. The sample size was determined based on an a priori power analysis. A medium effect size ( d = 0.5) was assumed, with an alpha level of 0.05 and desired power of 0.80. The analysis indicated that a minimum of 27 participants were required to detect a statistically significant effect. We recruited 32 participants to account for potential dropouts. In the Libet clock task, data from four participants were excluded because they did not understand the instructions, resulting in a final sample size of 28. The Ethics Committee of the Department of Psychology at Nagoya University approved this study (No. NUPSY-220729-G-01). All participants provided written informed consent before participating in the study and were compensated for their participation. 2.2 Physiological Recording Continuous respiration data were recorded using an MP160 acquisition system with an RSP100C respiratory amplifier and SKT100C thermal airflow amplifier (Biopac System Inc.) at a sampling rate of 200 Hz. Respiratory movements were measured using a respiration belt transducer (TSD201; Biopac Systems, Inc.) placed around each participant’s abdomen. Simultaneously, nasal airflow was monitored using a thermal transducer (TSD202A; Biopac Systems, Inc.) positioned just below the right nostril and secured within a mask to ensure accurate detection of the airflow temperature changes associated with breathing. Electrocardiogram (ECG) data were recorded using an MP160 system with an ECG100C amplifier (Biopac System Inc.) at a sampling rate of 200 Hz. Disposable ECG electrodes were placed below each clavicle (right and left) and on the lower left side of the abdomen. All physiological data were recorded using Acqknowledge-NDT software (Biopac Systems Inc.). The participants were instructed to maintain natural nasal breathing throughout the experiment. 2.3 Tasks To comprehensively examine whether the respiratory synchronization effects generalize across different effectors, we implemented two distinct motor tasks: the Libet clock task (key press or release using finger movements) and elbow flexion–extension task (joystick push or pull involving elbow flexion and extension). 2.3.1 Libet clock task Each trial commenced when a black dot appeared at a random position on the clock face (radius: 2° visual angle), rotating at a rate of 2,560 ms per cycle (Figure 1). For the key-press condition, the procedures aligned with those described by Park et al. (2020). The participants were instructed to allow the dot to complete at least one full rotation before freely pressing the key at their chosen moment using their right index finger. Immediately after the key press, the rotating dot disappeared. Each subsequent trial began after a randomized inter-trial interval of 4–8 s. In the key-release condition, the participants initially pressed and held the button as soon as the rotating dot appeared. They were instructed to allow the dot to complete at least one full rotation before releasing the key at their chosen moment. Similar to the key-press condition, the rotating dot disappeared immediately upon key release, and the following trial commenced after a randomized inter-trial interval of 4–8 s. Consistent with prior research (Libet et al., 1983; Park et al., 2020), the participants were explicitly instructed to avoid preselecting the dot’s location for pressing or releasing the key, refrain from maintaining identical intervals between trials, and respond spontaneously. The key-press and key-release conditions were applied in a block design in a counterbalanced order. Each condition comprised 40 experimental trials, preceded by 5 practice trials. The participants were offered rest periods after every 20 trials. The timings of dot appearance, key press, and key release were recorded and transmitted to the AcqKnowledge software as trigger signals. Figure 1. Libet clock task (key-press and key-release conditions). The participants viewed a rotating dot (cycle duration: 2,560 ms) on the clock face. In the key-press condition, they spontaneously pressed a key at their chosen moment after at least one full rotation. In the key-release condition, the participants initially pressed and held a key, spontaneously releasing it after at least one full rotation. Following each action, the rotating dot disappeared, and the participants reported the perceived position of the dot at the moment of their action. 2.3.2 Elbow flexion–extension task The experimental session consisted of a single block lasting 8 min. In the push condition, the participants voluntarily pushed a joystick (Extreme 3D Pro, Logitech) using their right arm. Conversely, in the pull condition, they voluntarily pulled the joystick with their right arm. The other procedures closely followed the Kornhuber task (Kornhuber & Deecke, 1965; Park et al., 2020). The participants were instructed to perform one voluntary joystick movement approximately every 8–12 s, corresponding to approximately three respiration cycles. They were explicitly asked to avoid counting seconds, prevent rhythmic or regular joystick movements, and rely solely on spontaneous timing. The participants practiced pushing and pulling the joystick using elbow flexion and extension before each condition. Prior to the main recording, they completed a brief training session lasting 1 min, during which the experimenter provided feedback on movement timing and regularity, allowing them to adjust their performance accordingly. Throughout the experiment, the participants were acoustically isolated by being made to listen to continuous white noise via insert headphones and were instructed to keep their eyes closed. The push and pull conditions were determined using a counterbalanced block design. The timings of the pull and push movements were detected using a predefined threshold and transmitted to the AcqKnowledge software via a trigger signal. 2.4 Procedure The participants were seated comfortably in front of a computer monitor (EV2495-BK, EIZO), positioned 57 cm away. Stimulus presentation and response collection were controlled using PsychoPy (version 2022.10). After setting up the physiological recording equipment (respiration belt, thermal transducer, and ECG electrodes), the participants completed the Libet clock task (key press or release conditions), followed by the elbow flexion–extension task (joystick push or pull conditions). After completing the tasks, they received a debriefing regarding the study’s aims and procedures and answered post-experiment questionnaires assessing task experience and compliance with instructions. The entire experimental session lasted approximately 90 min. 2.5 Data Analysis 2.5.1 Exclusion criteria for behavioral data In the Libet clock task, trials were excluded when participants in the key-press condition responded before the rotating dot completed one full rotation (2,560 ms). In the key-release condition, trials were excluded when the initial key press occurred more than 1 s after dot onset or when the participants released the key before completion of the one rotation (2,560 ms). Participants who had fewer than 20 valid trials per condition were excluded from subsequent analyses. In the elbow flexion–extension task, trials with inter-movement intervals shorter than 5 s or longer than 30 s were excluded from the analysis. jabbrv-ltwa-all.ldf jabbrv-ltwa-en.ldf 2.5.2 Pre-processing for physiological data Respiration data were band-pass filtered between 0.1 Hz (high-pass) and 3 Hz (low-pass). Because of the temporal delay introduced by the thermal airflow measurement, the airflow data were corrected to align with the respiration belt data. Specifically, the thermal airflow signal was inverted in phase, and a cross-correlation analysis with the respiration belt data was conducted to identify the optimal temporal shift that yielded the maximum correlation (Supplementary Figure 1). All subsequent analyses were performed using the corrected airflow data. To determine instantaneous respiratory phases, we applied the Hilbert transform to the corrected airflow data. Peaks and troughs were identified from the instantaneous respiratory phase, defining the inhalation phases from trough to peak and exhalation phases from peak to trough (Supplementary Figure 2). Respiratory cycles with abnormal durations were excluded based on participant-specific criteria, specifically cycles with total cycle, inhalation, or exhalation durations outside the range defined by Q1 – 2.5 × interquartile range (IQR) and Q3 + 2.5 × IQR. Finally, the respiratory phases at the time of the behavioral events (dot onset, key press or release, and joystick push or pull) were extracted for further analyses. We band-pass filtered ECG signals between 0.5 Hz (high-pass) and 40 Hz (low-pass). R-peak detection was performed, and instantaneous cardiac phases were calculated based on the detected R-peaks, consistent with the procedure described by Park et al. (2020) (Supplementary Figure 3). Abnormal R-R intervals, which were defined as intervals falling outside the range from Q1 − 2.0 × IQR to Q3 + 2.0 × IQR, were identified and excluded for each participant. Subsequently, the cardiac phases at the time of the behavioral events were extracted for further analyses. The physiological data were preprocessed using MATLAB (R2024a). 2.5.3 Statistical analysis 2.5.3.1 Circular analysis We investigated the synchronization between voluntary movements and physiological signals (respiratory and cardiac phases) using the methods established by Park et al. (2020). The Hodges–Ajne (omnibus) test was used to determine whether the phase distribution of voluntary movements deviated significantly from uniformity (Ajne, 1968). Given that exhalation typically lasts longer than inhalation, random events tend to cluster during exhalation. To control for this bias, we generated 1,000 surrogate datasets by randomly shifting the respiratory phase data for each participant, allowing the empirical determination of chance-level distributions. The observed statistical value (M), defined as the minimum number of data points falling within any half-circle, was compared with these surrogate distributions. Lower M values indicated greater deviation from uniformity, and significant departures from the null hypothesis (uniform distribution) were evaluated using two-tailed permutation t -tests. All p -values were corrected for multiple comparisons using the false discovery rate (FDR) method. Circular statistical analyses were performed using MATLAB (R2024a) and the Circular Statistics Toolbox (Berens, 2009). Differences in the mean phase across conditions were analyzed following the procedures described by Grund et al. (2022). We applied a randomized version of Moore’s paired circular test (Moore, 1980) to evaluate the mean phase differences between the conditions. This involved 10,000 random permutations for each comparison. To account for multiple comparisons, we corrected all resulting p -values using the FDR procedure. jabbrv-ltwa-all.ldf jabbrv-ltwa-en.ldf 2.5.3.2 Physiological state analysis Analyses were conducted by dividing the data according to specific physiological states. For the respiration-based analyses, the phases were classified into inhalation (first half of the respiratory cycle) and exhalation (second half of the respiratory cycle). Cardiac state analyses were conducted by dividing the cardiac cycle into two equal phases using the proportion of events occurring in the second half of the cycle (corresponding primarily to diastole). For each respiratory and cardiac state, the frequency of events was calculated and expressed as proportions. Because the inhalation ratio is directly complementary to the exhalation ratio (i.e., inhalation ratio = 1 – exhalation ratio), we used only the exhalation and systole ratios in subsequent analyses. The baseline proportions of the respiratory and cardiac states were computed for each participant as the average proportion across trials for each condition. An analysis of variance (ANOVA) was conducted with condition and timing as independent variables and exhalation and systole ratios as dependent variables. Subsequent individual t -tests comparing each condition to its baseline were performed, with p -values corrected for multiple comparisons using the FDR method. All analyses were conducted using the R software (version 4.3.1). jabbrv-ltwa-all.ldf jabbrv-ltwa-en.ldf 2.5.3.3 Breathing rate changes We examined whether voluntary movements significantly affected respiratory and heart rates. Respiratory intervals were measured during each movement and one interval before and after the movement, resulting in three intervals per movement. Cardiac intervals were measured during each movement and three intervals before and after each movement, resulting in seven intervals. A two-way ANOVA (condition × timing) was conducted for these intervals. 2.5.3.4 Trial-by-trial respiratory phase coupling between stimulus presentation and voluntary action (Libet clock task) To clarify whether the respiratory phases temporally couple stimulus presentation and voluntary action initiation within trials, we calculated the circular correlations between the respiratory phases at dot onset (stimulus) and key press or release (action). Additionally, we examined the correlations between the voluntary action in one trial and stimulus presentation timing in a subsequent trial to assess potential trial-by-trial respiratory influences. To control for the possible confounding effects of stimulus–action intervals, correlations were computed using the residual phases obtained after regressing out these intervals. The resulting correlation coefficients for each participant were converted to Fisher’s z -values, and one-sample t -tests were performed to determine whether the group-level mean z -values significantly exceeded 0. jabbrv-ltwa-all.ldf jabbrv-ltwa-en.ldf 2.5.3.5 Individual difference analysis for respiration To characterize individual variability in the respiratory synchronization of spontaneous voluntary movements (Libet clock and elbow flexion–extension tasks), we examined the physiological factors influencing the respiratory phases immediately preceding voluntary movements. We computed two measures: phase difference (event phase minus baseline phase) and phase-locking strength (baseline phase variability minus event phase variability). Because lower variability indicates stronger phase-locking, we multiplied this difference by –1 so that larger (positive) values reflect greater phase-locking strength. To assess the consistency of the synchronization effects within each participant, we examined the correlations of these measures between different voluntary action types and stimulus presentation timings. Furthermore, we explored the correlations between phase-locking strength and other physiological factors, such as cardiac activity, to identify the potential sources of individual differences. 3 Results 3.1 Libet clock task 3.1.1 Basic measurements The average inhalation, exhalation, and total breathing cycle durations were 1.781 s (standard deviation [ SD ] = 0.422), 2.173 s ( SD = 0.603), and 3.969 s ( SD = 1.007), respectively. The correlation between the respiration belt and thermal airflow signals after alignment was 0.780 ( SD = 0.125), with a thermal airflow delay of 382.5 ms ( SD = 160.5). Approximately 5.511% ( SD = 2.888) of the respiratory cycles were excluded as outliers. Regarding the ECG, the average R-R interval was 0.800 s ( SD = 0.100), with 2.227% ( SD = 2.526) of R-R intervals excluded as outliers. The ECG data from one participant were excluded because of measurement issues. Approximately 7.730% of the trials were excluded owing to predefined criteria, and four participants’ data were excluded because they misunderstood the instructions. The mean waiting time was 4.332 s ( SD = 1.753) in the key-press condition and 4.033 s ( SD = 1.619) in the key-release condition (Supplementary Figure 4). The mean reaction time from dot presentation to key press under the key-release condition was 0.414 s ( SD = 0.105). 3.1.2 Breathing synchronization 3.1.2.1 Circular analysis We tested whether voluntary actions and stimulus presentation systematically aligned with the spontaneous breathing phases (Figure 2). In the key-press condition, significant respiratory synchronization was observed at the dot presentation ( p = .032) and key-press ( p = .032) timings. By contrast, in the key-release condition, synchronization was significant only at the key-release timing ( p = .005) but not at the dot presentation or key-press timings ( p = .647). All p -values were corrected using the FDR method. Moore’s paired tests with FDR correction confirmed that in the key-press condition, the mean respiratory phase at key-press onset ( R = 1.84, p < .001) and dot presentation ( R = 1.69, p < .001) differed significantly from baseline, occurring earlier in the exhalation phase. In the key-release condition, no significant differences were observed between the key-release and baseline phases ( R = 0.85, p = .17). Additionally, there was no significant correlation between the respiratory phases at key-release and key-press timings ( R = 0.72, p = .23). Figure 2. Respiratory synchronization and phase distributions during stimulus presentation and voluntary actions in the Libet clock task. Each horizontal row corresponds to a specific event type and experimental condition: (a, b) dot presentation in the key-press condition; (c, d) dot presentation in the key-release condition; (e, f) key press in the key-press condition; (g, h) key press in the key-release condition; and (i, j) key release in the key-release condition. The left panels (a, c, e, g, i) show the surrogate data distributions of the summed statistics (M) as gray histograms, with the observed values indicated by vertical blue lines. The observed values shifted significantly to the left, indicating stronger synchronization than that expected by chance (associated p -values are shown). The right panels (b, d, f, h, j) display circular histograms illustrating the respiratory phase distributions of event timings across the trials. The black dots represent individual participants’ mean respiratory phases, and the red dots indicate the overall group-level mean phases. 3.1.2.2 State analysis A two-way ANOVA (condition × timing) revealed a significant main effect of timing ( F (2, 54) = 7.96, p < .001, ges = .083), indicating differences in respiratory state across event timings (Figure 3). Neither the main effect of the condition ( F (1, 27) = 1.77, p = .194, ges = .006) nor the interaction between the condition and timing ( F (2, 54) = 1.39, p = .258, ges = .009) was significant. Follow-up pairwise comparisons (FDR-corrected) revealed that, compared with the baseline, the proportion of events occurring during exhalation significantly increased at key press in the key-press condition ( t (30) = 3.04, p = .010, d = 0.546) but not at dot presentation ( t (30) = 1.95, p = .060, d = 0.351). In the key-release condition, a similar significant increase was observed at key release ( t (28) = 2.97, p = .012, d = 0.551), but no difference was found at dot presentation ( t (28) = 0.19, p = .849, d = 0.036). Overall, these results indicated that voluntary key presses and releases occurred preferentially during exhalation relative to baseline. Figure 3. Exhalation ratios at different event timings in the Libet clock task. Mean exhalation ratios for baseline, dot presentation, and key-press or key-release timings in the key-press and key-release conditions. Individual participant data points are represented as dots, and the error bars indicate standard errors of the mean (SEM). Asterisks (*) denote significant differences (FDR-corrected pairwise comparisons; * p < .05). 3.1.2.3 Breathing rate changes Repeated-measures ANOVAs were used to examine the breathing intervals around stimulus presentations and voluntary actions (Supplementary Figure 5). Breathing intervals were significantly lengthened during dot presentations compared with the intervals immediately before or after (main effect of timing: F (1, 26) = 7.765, p = .010, ges = .004), without significant effects of condition or interaction. Pairwise t -tests confirmed that the intervals during dot presentation were significantly longer than those preceding stimulus onset (Before1) in the key-press condition ( t (29) = −3.767, p = .002, d = 0.688) but not in the key-release condition ( t (27) = −2.011, p = .054, d = 0.380). By contrast, the breathing intervals around voluntary actions showed no significant effects or interactions ( p > .375). These findings indicated an efferent regulatory effect on breathing specific to stimulus presentations but not voluntary actions. 3.1.2.4 Trial-by-trial respiratory phase coupling between stimulus presentation and voluntary action We examined the trial-by-trial relationships between respiratory phases at stimulus (dot) presentation and subsequent voluntary actions using circular correlation analyses. The results revealed a significant correlation between the respiratory phases at dot presentation and the subsequent voluntary action timings ( t (27) = 2.62, p = .014, d = 0.495) (Figure 4). However, the respiratory phases during voluntary actions (key press or release) did not significantly predict the respiratory phases at dot presentation in the following trial ( t (27) = 1.275, p = .213, d = 0.241). Figure 4. Circular correlations (Fisher’s z -transformed) between respiratory phases at dot presentation and subsequent voluntary actions. The conditions are shown on the horizontal axis: key press and key release. Individual participant data points are indicated by dots. The boxes represent the IQR. The horizontal lines within the boxes indicate the medians, and the whiskers extend to 1.5 × IQR. 3.1.2.5 Individual differences in respiratory synchronization We examined individual differences in respiratory synchronization across the conditions. No significant correlation was observed between the key-press and key-release conditions in terms of the mean phase difference from baseline ( r = .33, p = .091). However, the phase-locking strength was significantly correlated between the two conditions ( r = .38, p = .049). This suggests that participants consistently exhibited similar patterns of synchronization strength across different voluntary actions. Within the key-press condition, individual differences in phase difference and phase-locking strength were not significantly correlated between the dot presentation and key-press timings (| r | .56). The exploratory analyses examining the correlations between individual differences in phase-locking strength and physiological factors are presented in Supplementary Table 1. 3.1.3 Heart synchronization 3.1.3.1 Circular analysis We examined whether voluntary movements systematically aligned with the cardiac phases (Figure 5). The circular analyses (Hodges–Ajne tests with FDR correction) revealed no significant phase biases for timing or condition ( p > .23). A paired Moore’s test with randomization indicated no significant difference between the cardiac phases at the key-press timing in the key-press condition and key-release timing in the key-release condition ( R = 0.82, p = .146). These findings suggest that voluntary action timings were not significantly associated with specific cardiac phases. Figure 5. Cardiac synchronization and phase distributions during stimulus presentation and voluntary actions in the Libet clock task. The panels follow the same layout as in Figure 2 but depict cardiac (instead of respiratory) synchronization. The surrogate distributions and observed values of summed statistics (M) for cardiac phase synchronization are shown in the left panels with their associated p -values. The circular histograms (right panels) show the individual participants’ mean cardiac phases (black dots) and group-level mean phases (red dots) at the event timings. jabbrv-ltwa-all.ldf jabbrv-ltwa-en.ldf 3.1.3.2 State analysis A two-way ANOVA (condition × timing) on cardiac phase ratios (proportion of events in the second half of the cardiac cycle) revealed a significant main effect of condition ( F (1, 26) = 4.81, p = .037, ges = .036) but not timing ( F (2, 52) = 1.04, p = .360, ges = .011) or interaction ( F (2, 52) = 2.68, p = .078, ges = .040) (Figure 6). Pairwise comparisons indicated a significant decrease from baseline at action timing in the key-release condition ( t (27) = 3.32, p = .005, d = 0.627). No significant differences from baseline were observed at the dot presentation timing or in the key-press condition. All p -values were corrected using the FDR method. Figure 6. Cardiac phase ratio across conditions. The mean proportion of events occurring in the second half of the cardiac cycle (phase 2 ratio). The dots indicate individual participant data. The error bars represent SEM. * p < .05, FDR corrected. 3.2 Elbow flexion–extension task 3.2.1 Basic measurements In the pull condition, the average inhalation, exhalation, and total breathing cycle durations were 1.852 s ( SD = 0.621), 2.285 s ( SD = 0.791), and 4.168 s ( SD = 1.426), respectively. In the push condition, the averages were 1.786 s ( SD = 0.607), 2.172 s ( SD = 0.593), and 3.964 s ( SD = 1.180), respectively. The correlation between the respiration belt and airflow signals after alignment was 0.709 ( SD = 0.196), with an airflow delay of 455.1 ms ( SD = 208.8). Approximately 5.220% ( SD = 2.937) and 5.476% ( SD = 3.839%) of the respiratory cycles were excluded in the pull and push conditions, respectively. Behaviorally, 6.21% of the trials were excluded. The mean waiting times were similar for the pull (10.611 s, SD = 3.035) and push (10.586 s, SD = 3.053) actions (Supplementary Figure 6). 3.2.2 Breathing synchronization 3.2.2.1 Circular analysis We examined whether voluntary elbow movements were synchronized with the respiratory phases (Figure 7). The Hodges–Ajne test revealed significant respiratory phase biases at movement onset for the pull and push conditions ( p = .001, FDR-corrected). Moore’s paired test showed that the respiratory phase at push onset differed significantly from baseline ( R = 1.138, p = .047). However, pull onset was not significantly different ( R = 0.926, p = .086). No significant phase difference was observed directly between the pull and push movements ( R = 0.595, p = .362). Figure 7. Respiratory synchronization and phase distributions during stimulus presentation and voluntary actions in the elbow flexion–extension task. Each horizontal row corresponds to a specific event type and experimental condition: (a, b) pull condition and (c, d) push condition. The left panels (a, c) show the surrogate data distributions of the summed statistics (M) as gray histograms, with the observed values indicated by vertical blue lines. The observed values shifted significantly to the left, indicating stronger synchronization than that expected by chance (associated p -values are shown). The right panels (b, d) display circular histograms illustrating the respiratory phase distributions of event timings across trials. The black dots represent individual participants’ mean respiratory phases, and the red dots indicate the overall group-level mean phases. 3.2.2.2 State analysis A two-way ANOVA (condition × timing) revealed a significant main effect of timing ( F (1, 31) = 5.54, p = .025, ges = .042) but no significant main effect of condition ( F (1, 27) = 0.04, p = .849, ges < .001) or a significant interaction ( F (1, 31) < 0.01, p = .975, ges < .001) (Figure 8). Pairwise comparisons showed that exhalation ratios at movement onset did not significantly differ from baseline for the pull ( t (31) = 1.76, p = .089, d = 0.310) or push ( t (31) = 1.95, p = .060, d = 0.345) conditions. These findings indicated a general trend toward increased exhalation at movement onset, accompanied by notable individual differences. Figure 8. Exhalation ratios at different event timings in the elbow flexion–extension task. The mean exhalation ratios for baseline and pull or push timing. Individual participant data points are represented as dots, and the error bars indicate standard errors of the mean. 3.2.2.3 Breathing rate changes We used repeated-measures ANOVAs to examine the breathing intervals surrounding voluntary movements (Supplementary Figure 7). For the breathing intervals around voluntary movements, a two-way repeated-measures ANOVA revealed no significant main effect of timing ( F (2, 60) = 0.363, p = .697, ges < 0.001) or condition ( F (1, 30) = 3.153, p = .086, ges = 0.008) nor a significant interaction ( F (2, 60) = 0.214, p = .808, ges < 0.001). 3.2.2.4 Individual differences We analyzed the individual differences in respiratory synchronization between the pull and push conditions. The mean phase difference ( r = .18, p = .323) and phase-locking strength ( r = .22, p = .244) were not significantly correlated across conditions. The exploratory analyses showed positive correlations between breathing variability (rmssd) and phase-locking strength in both the pull ( r = .53, p = .002) and push ( r = .43, p = .017) conditions (Supplementary Figure 8), suggesting that participants with higher breathing variability exhibited stronger synchronization. Additional correlations are presented in Supplementary Table 2. 3.2.2.5 Technical considerations Post-experimental verification was conducted by repeating the measurements for six participants. Results indicated average measurement delays of 201.1 ms ( SD = 93.1) in the pull condition and 218.7 ms ( SD = 83.8) in the push condition. These delays reflect technical limitations associated with the threshold-based detection method used to identify precise action onset timings. 4 Discussion This study examined whether respiratory and cardiac signals are coupled with multiple voluntary actions and stimulus presentations. We found (i) voluntary actions synchronizing with exhalation across different effectors, (ii) dissociation and interaction between the stimulus and action-locked coupling with breathing, and (iii) a weak tendency for the cardiac-phase coupling of actions. 4.1 Exhalation Dominance Across Effectors The results demonstrated a robust exhalation-phase bias for the initiation of voluntary actions, regardless of the effector (finger flexion and finger extension) or joint (elbow flexion and elbow extension). All four movements peaked during mid- to late-exhalation relative to a participant-specific respiratory baseline, although the time-forced condition did not show a systematic phase preference, replicating and extending earlier findings (Park et al., 2020). Psychological and neuroscientific evidence supports the notion that voluntary actions are preferentially initiated during exhalation. Psychologically, inhalation is an active, resource-demanding phase, which involves diaphragmatic contraction and thoracic expansion. The accompanying surge of afferent signals from pulmonary stretch receptors, baroreceptors, and the olfactory epithelium compete for central processing resources. By contrast, exhalation is largely passive and energetically inexpensive, liberating the attentional capacity for movement preparation. To minimize the competition between respiratory afference and motor planning, the motor system biases action onset toward mid- to late-exhalation. From a neuroscientific perspective, studies have indicated that cortical states vary systematically with respiratory phases, reflecting the respiration-driven entrainment of cortical oscillatory networks across multiple frequency bands (Tort et al., 2018, 2025). Specifically, inhalation suppresses α-band activity, resulting in enhanced perceptual sensitivity, particularly in vision (Kluger et al., 2021; Perl et al., 2019), and memory (Zelano et al., 2016). As α-band oscillations broadly reflect cortical excitability and are associated with various cognitive tasks (Samaha et al., 2020), their modulation by respiratory phases can extensively influence perception and behavior. Moreover, in the motor domain, event-related potentials associated with voluntary action preparation, such as the readiness potential, co-vary systematically with respiratory phases, particularly aligning with the synchronization between exhalation and voluntary actions (Park et al, 2020, 2022). Collectively, these findings highlight the clearly differentiated psychophysiological roles of inhalation and exhalation: inhalation enhances sensory sensitivity, whereas exhalation facilitates the initiation of voluntary actions. A purely biomechanical account, in which movements align with breathing phases optimized for energetic efficiency, cannot adequately explain the observed results. Early isometric studies demonstrated that finger flexor force peaks during late exhalation (Li & Laskin, 2006); however, elbow extension torque peaks during exhalation, and elbow flexion torque shows no clear respiratory phase dependency (Ikeda et al., 2009). Similarly, studies on finger-tracking movements indicate differing respiratory influences on flexion and extension movements (Rassler, 2000). If respiratory coupling is primarily driven by biomechanical optimization, distinct effectors should display distinct respiratory couplings; however, this pattern was not observed. Instead, the consistent alignment of various voluntary actions with exhalation supports the notion that respiration functions as a temporal cue at the level of action intention, preceding effector-specific motor planning and execution. Notably, individual participant traits may influence respiratory–action synchronization. Despite the general trend toward exhalation alignment, considerable individual variability was observed. For instance, in the elbow flexion–extension task, some participants exhibited robust synchronization with inhalation rather than exhalation. Such variability suggests that individual learning processes, potentially shaped by previous motor experiences such as sports training, may influence respiratory–action synchronization patterns. Additionally, we identified a positive correlation of the phase-locking bias between the key-press and key-release conditions in the Libet clock task. This finding indicated that participants might possess stable, individual-specific tendencies, potentially reflecting broader psychophysiological traits such as interoceptive sensitivity. Physiological factors were also correlated with phase-locking strength. Breathing variability was positively correlated with synchronization strength in the pull and push conditions of the elbow flexion–extension task. Higher breathing flexibility may broaden the temporal window for respiratory synchronization, providing individuals with enhanced opportunities to align their actions with respiratory phases. Clarifying these individual-specific relationships by using questionnaires and other trait measures is a promising direction for future research. 4.2 Respiratory Phase as a Shared Clock for Stimulus and Action Our data demonstrated that stimulus presentations and voluntary actions shared the same mid- to late-exhalation phase window, suggesting that respiration serves as a common temporal reference within each trial. The circular correlation analyses confirmed significant trial-by-trial coupling between the respiratory phase at stimulus onset and subsequent voluntary action timing; however, no carry-over was observed between voluntary actions and subsequent stimulus presentations. Thus, stimulus onset likely resets the respiratory cycle, establishing a respiratory-based internal clock that aligns sensory and motor events. Although stimulus- and action-locked couplings share the same respiratory phase, the underlying control processes appear to be distinct. Stimulus-locked synchronization is primarily efferent, as indicated by prolonged breathing intervals around stimulus onset, suggesting that participants actively lengthen their exhalations until stimuli appear. By contrast, action-locked coupling is predominantly afferent; breathing intervals remain unchanged around voluntary actions, implying that actions align passively with ongoing respiratory rhythms rather than actively altering them. Notably, such respiratory phase resetting around stimulus onset was absent in the key-release condition, in which immediate motor responses likely increased sympathetic activation and prevented exhalation prolongation. Moreover, individual differences in stimulus- and action-locked synchronization were uncorrelated, supporting the idea of distinct underlying pathways for these processes. Additionally, the direction of stimulus synchronization depends on the task characteristics. Johannknecht and Kayser (2022) reported stimulus alignment with inhalation in memory tasks, reflecting active respiratory adjustments to optimize cognitive performance (Zelano et al., 2016). By contrast, stimulus synchronization in our Libet clock task, which lacked task-relevant stimulus information, predominantly occurred during exhalation, likely representing passive entrainment facilitated by a flexible exhalation duration. Thus, even randomized inter-trial intervals ranging from 4 to 8 s, commonly assumed to prevent rhythmic entrainment, can unintentionally overlap with the participants’ breathing cycles, posing potential experimental confounders. To isolate pure voluntary action timing from such stimulus-induced respiratory synchronization, paradigms without external stimuli, such as the Kornhuber task (Kornhuber & Deecke, 1965), should be considered. 4.3 Cardiac Phase Coupling on Voluntary Action Evidence for the cardiac synchronization of voluntary action initiation remains inconsistent, likely owing to methodological and task-based differences. While Park et al. (2020), using the Libet clock task, found no systematic cardiac-phase bias during self-paced actions, Mussini et al. (2024) reported that participants tended to refrain from initiating voluntary responses during systole, instead favoring diastole. This finding is consistent with the baroreceptor-mediated inhibitory theories (Makowski et al., 2020; Rae et al., 2018). Conversely, other studies have reported the opposite bias, where voluntary actions were more frequent during systole than during diastole (Kunzendorf et al., 2019; Palser et al., 2021). However, these discrepancies may stem from fundamental differences in experimental paradigms. Kunzendorf et al. (2019) examined voluntary action initiation influenced by subsequent visual stimuli, whereas Palser et al. (2021) investigated action offset timing instead of initiation. Employing the Libet clock task, consistent with Park et al. (2020), we observed no statistically significant cardiac phase bias across conditions, although a weak yet consistent trend emerged: voluntary actions occurred slightly more frequently during diastole (Phase 2) than during systole (Phase 1). This subtle cardiac phase effect aligns with the findings of Mussini et al. (2024), suggesting a potential inhibitory influence of systole on voluntary action initiation. This effect was observed specifically in the key-release condition, likely reflecting higher physiological arousal and task engagement requirements (Yang et al., 2023). Participants were required to maintain active engagement by holding the key, possibly heightening baroreceptor sensitivity and accentuating subtle cardiac-related effects. Taken together, these findings support the hypothesis that cardiac phase influences on voluntary actions, although weaker than respiratory effects, significantly depend on task characteristics and associated physiological arousal levels. jabbrv-ltwa-all.ldf jabbrv-ltwa-en.ldf 4.4 Limitations and Conclusion First, the timing of measurement in the elbow flexion–extension task made it difficult to infer precise action onset timings because we relied on threshold-based detection of the participants’ movements. Post-experimental verification indicated delays of approximately 200 ms for six participants who were measured again. As the respiratory cycles range from 3,000 to 5,000 ms, these delays are unlikely to substantially affect respiratory-related conclusions. However, owing to the higher temporal sensitivity of the cardiac phases, we could not reliably analyze cardiac synchronization data from the elbow flexion–extension task. Second, subjective individual measures, such as sports experience and interoceptive sensitivity, were absent; without these data, we could not determine how such factors influence individual variability in phase-locking strength. Moreover, investigating subjective experiences such as feelings of action initiation or a sense of agency across different breathing phases could further elucidate individual differences. Finally, we did not examine other types of voluntary actions that require varying degrees of power or precision. Given that different motor demands may yield divergent synchronization patterns, future studies should systematically explore these variations. In conclusion, the current study advances our understanding of respiratory influences on perception and behavior by demonstrating (i) general exhalation–action coupling across various effectors, (ii) the dissociation and integration of stimulus- and action-related phase couplings, and (iii) a weak but consistent cardiac influence. Author Contributions jabbrv-ltwa-all.ldf jabbrv-ltwa-en.ldf Hiroshi Shibata: conceptualization, methodology, data curation, formal analysis, investigation, writing – original draft, writing – review and editing, visualization. Hideki Ohira: conceptualization, methodology, supervision, writing – review and editing. Data and Code Availability Statement The data that support the findings of this study are available from the corresponding author upon request. 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The Journal of Neuroscience: The Official Journal of the Society for Neuroscience , 36 (49), 12448–12467. https://doi.org/10.1523/JNEUROSCI.2586-16.2016 Supplementary Material File (image1.emf) Download 1.41 MB File (image2.emf) Download 1.31 MB File (image5.emf) Download 5.30 MB File (image7.emf) Download 2.13 MB Information & Authors Information Version history V1 Version 1 27 June 2025 Peer review timeline Published Psychophysiology Version of Record 18 Feb 2026 Published Copyright This work is licensed under a Non Exclusive No Reuse License. Collection Psychophysiology Authors Affiliations Hiroshi Shibata 0009-0002-4507-5092 [email protected] Nagoya Daigaku Daigakuin Johogaku Kenkyuka Shinri Ninchi Kagaku Senko View all articles by this author Hideki Ohira Nagoya Daigaku Daigakuin Johogaku Kenkyuka Shinri Ninchi Kagaku Senko View all articles by this author Metrics & Citations Metrics Article Usage 351 views 185 downloads .FvxKWukQNSOunydq8rnd { width: 100px; } Citations Download citation Hiroshi Shibata, Hideki Ohira. Respiratory and Cardiac Phase Coupling With Voluntary Actions Across Motor Tasks. Authorea . 27 June 2025. DOI: https://doi.org/10.22541/au.175102585.59392045/v1 If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download. For more information or tips please see 'Downloading to a citation manager' in the Help menu . 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