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. 2020 May 21;10(1):8484.
doi: 10.1038/s41598-020-65670-1.

Physiological and Behavioral Synchrony Predict Group Cohesion and Performance

Ilanit Gordon  1   2 , Avi Gilboa  3 , Shai Cohen  3 , Nir Milstein  4 , Nir Haimovich  4 , Shay Pinhasi  5 , Shahar Siegman  6
Affiliations

Physiological and Behavioral Synchrony Predict Group Cohesion and Performance

Ilanit Gordon et al. Sci Rep. .

Abstract

Interpersonal synchrony contributes to social functioning in dyads, but it remains unknown how synchrony shapes group experiences and performance. To this end, we designed a novel group drumming task in which participants matched their drumming to either predictable or unpredictable tempos. Fifty-one three-person groups were randomly assigned to one of two conditions: synchronized or asynchronized drumming. Outcome measures included electrocardiograms and self-reports of group cohesion and synchrony. The drumming task elicited an increase in physiological synchrony between group members (specifically their hearts' interbeat intervals). We also found that physiological synchronization and behavioral synchronization predicted individuals' experience of group cohesion. Physiological synchrony also predicted performance in a subsequent group task that involved freely drumming together. The findings suggest that the behavioral and physiological consequences of synchronization contribute to the formation of group bonds and coordination. They also confirm that insights from translational social neuroscience can inform our knowledge of the development of cohesive and efficacious groups.

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Conflict of interest statement

The authors declare no competing interests.

Figures

Figure 1
Figure 1
An outline of the study’s procedure. Before the music task, we assessed each group member’s demographic information, affect, prior familiarity with each other, and prior musical knowledge in self-reported questionnaires. Next, we recorded each participant’s ECG during a 5-minute baseline in which they were instructed to sit together and relax. The ECGs were monitored continuously from the first baseline until the end of the study. Following the 1st baseline measurement, the drumming task began and lasted 4 minutes. After the drumming task, the participants completed manipulation check questions that assessed perceived drumming synchrony, the main outcome measure of group cohesion, and affect surveys. Next, a second 5-minute baseline period that was identical to the first one began. Then, the participants were instructed to freely play together on the drums for 4 minutes, which allowed us to derive an objective group performance measure of coordination in a new improvisation task. Affect was then reported via self-reports for a final time in the study. Figure credits: [“Yuii]/Shutterstock.com”; “[flatvector]/Shutterstock.com”; “[NadzeyaShanchuk]/Shutterstock.com”.
Figure 2
Figure 2
(A,B). In panel A, we present changes in the group-level physiological synchrony (y-axis) from the baseline (in which group members were asked to sit together and relax for 5 minutes) to the drumming task. There was a significant increase in IBI synchrony from the baseline in all groups during the drumming task, which was unrelated to the drumming condition (t(47) = −5.37, p = 0.0001, 95% CI = −0.2–0.09.). In panel B, we present a frequency distribution showing the percentage of dyads (y-axis) that had any given IBI correlation score (x-axis). In blue, we show the real interacting dyads from the same group, and in orange, we show all possible randomly created dyads from different groups. These two samples are significantly different from each other with higher-level synchrony scores in real dyads. In combination, both panels show that IBI physiological synchrony in the drumming task was higher than baseline synchrony in the same groups and was not spurious due to similar task conditions across groups. ***p < 0.0001.
Figure 3
Figure 3
In panels (A,B), we present the time series of the interbeat intervals (IBIs) of the heart from all dyads within the sample groups participating in the drumming task. Each group includes three dyads, which are presented separately. We present the IBI time series for every dyad in the group so that the level of dyadic correlations comprising the groups’ average can be viewed. In panel A, we present dyads from a group with a high level of physiological synchrony. In panel B, we present dyads from a group with a low level of physiological synchrony. The IBI time series was derived from the ECG signal for each group member throughout the duration of the drumming task. The y-axis represents standardized IBI (Z-scores of intervals in seconds), and the X-axis represents the time elapsed from the beginning of the drumming task in seconds. As shown, there is a higher level of convergence and covariation for dyads on the left panels than for dyads on the right panels.
Figure 4
Figure 4
This figures shows the results of cross-correlation function (CCF) analyses performed on the IBI time series of all possible dyads from the two sample groups presented in Fig. 3 during the drumming task. The y-axis is the level of correlation. The x-axis is the temporal lag of 3 seconds (from −6 to +6 data lags) of the CCF. The two horizontal blue lines in each graph represent the 95% confidence interval. Correlations that extend vertically beyond the blue lines are significant. Panel A presents an example of three CCF analyses in dyads from a group with a high level of IBI synchrony. Panel B presents an example of three CCF analyses in dyads from a group in which there was a low level of IBI synchrony. This figure shows that dyads from groups with high IBI synchrony have higher and more significant CCF scores than those from groups with low IBI synchrony.
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