Body sway reflects leadership in joint music performance

Abstract

The cultural and technological achievements of the human species depend on complex social interactions. Nonverbal interpersonal coordination, or joint action, is a crucial element of social interaction, but the dynamics of nonverbal information flow among people are not well understood. We used joint music making in string quartets, a complex, naturalistic nonverbal behavior, as a model system. Using motion capture, we recorded body sway simultaneously in four musicians, which reflected real-time interpersonal information sharing. We used Granger causality to analyze predictive relationships among the motion time series of the players to determine the magnitude and direction of information flow among the players. We experimentally manipulated which musician was the leader (followers were not informed who was leading) and whether they could see each other, to investigate how these variables affect information flow. We found that assigned leaders exerted significantly greater influence on others and were less influenced by others compared with followers. This effect was present, whether or not they could see each other, but was enhanced with visual information, indicating that visual as well as auditory information is used in musical coordination. Importantly, performers' ratings of the "goodness" of their performances were positively correlated with the overall degree of body sway coupling, indicating that communication through body sway reflects perceived performance success. These results confirm that information sharing in a nonverbal joint action task occurs through both auditory and visual cues and that the dynamics of information flow are affected by changing group relationships.leadership | joint action | music performance | body sway | Granger causality C oordinating actions with others in time and space-joint action-is essential for daily life. From opening a door for someone to conducting an orchestra, periods of attentional and physical synchrony are required to achieve a shared goal. Humans have been shaped by evolution to engage in a high level of social interaction, reflected in high perceptual sensitivity to communicative features in voices and faces, the ability to understand the thoughts and beliefs of others, sensitivity to joint attention, and the ability to coordinate goal-directed actions with others (1-3). The social importance of joint action is demonstrated in that simply moving in synchrony with another increases interpersonal affiliation, trust, and/or cooperative behavior in infants and adults (e.g., refs. 4-9). The temporal predictability of music provides an ideal framework for achieving such synchronous movement, and it has been hypothesized that musical behavior evolved and remains adaptive today because it promotes cooperative social interaction and joint action (10-12). Indeed music is used in important situations where the goal is for people to feel a social bond, such as at religious ceremonies, weddings, funerals, parties, sporting events, political rallies, and in the military...

Hyperbrain network properties of guitarists playing in quartet

“…investigated brain‐to‐brain synchrony in the classroom and showed that synchronous EEG activity across students predicts student class engagement and social dynamics. Chang et al . also reported body‐sway synchrony (recorded with motion capture) in string quartets, with a greater influence of the leader on the others.…”

“…15,16 Very recently, Dikker et al 17 investigated brain-to-brain synchrony in the classroom and showed that synchronous EEG activity across students predicts student class engagement and social dynamics. Chang et al 18 also reported body-sway synchrony (recorded with motion capture) in string quartets, with a greater influence of the leader on the others. Critically, we focused on hyperbrain network properties and hyperbrain network architecture based on community structures and their changes across frequency and time.…”

Social motor coordination during adult–child interactions

“…Early measurements of SMC, through the synchrony field, involved either intensive behavioral coding 26 or behavioral ratings 27 or explicitly manipulating study conditions to promote a narrow definition of synchrony, such as a dyad bouncing or swinging at the same time to a beat. 11,28 Mathematical applications to applied sciences now allow researchers to quantify SMC using both linear (cross-correlations) 5,22,[29][30][31] and nonlinear (i.e., coherence, relative phase, and cross-wavelet analyses) 1,2,6,32 approaches using a variety of different methods for capturing movement activity, including motion sensors, 9 accelerometers, 33,34 and musical instrument digital interface (MIDI)/audio recordings (e.g., to capture moments of contact during a drum hit). 15,35 SMC has also been measured through the timeseries analysis of movement obtained from the frame-difference method (FDM), 29,36,37 which measures the difference in luminance of grayscale pixels between consecutive video frames.…”

The Evolution of Rhythm Cognition: Timing in Music and Speech

“…The relationship between rhythm and sociality has seen a steady increase in research and has probably been the most investigated topic over the last 2 years (Large and Gray, 2015;Yu and Tomonaga, 2015;Ellamil et al, 2016;Gebauer et al, 2016;Greenfield et al, 2016;Moore et al, 2016;Reddish et al, 2016;Rennung and Göritz, 2016;Schirmer et al, 2016;Tunçgenç and Cohen, 2016;Wallot et al, 2016;Bishop and Goebl, 2017;Chang et al, 2017;Cirelli et al, 2017;Hannon et al, 2017;Knight et al, 2017;Mogan et al, 2017;Murphy and Schul, 2017;Rorato et al, 2017;Myers et al). Common foci are the relationship between synchronization and prosociality (Gebauer et al, 2016;Reddish et al, 2016;Rennung and Göritz, 2016;Tunçgenç and Cohen, 2016;Cirelli et al, 2017), and different forms of rhythmic behaviors in interaction (Large and Gray, 2015;Ravignani, 2015;Yu and Tomonaga, 2015;Ellamil et al, 2016;Gebauer et al, 2016;Greenfield et al, 2016;Moore et al, 2016;Schirmer et al, 2016;Wallot et al, 2016;Murphy and Schul, 2017).…”