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Hyper-Frequency Network Topology Changes During Choral Singing.

Viktor Müller¹, Julia A M Delius¹, Ulman Lindenberger^1,2,3

¹Center for Lifespan Psychology, Max Planck Institute for Human Development, Berlin, Germany.

Frontiers in Physiology

|March 23, 2019

Summary

Choral singing reveals complex network dynamics. Network topology measures, like clustering coefficients, are higher when singing in parts versus unison, indicating enhanced social interaction and coordination.

Keywords:

cardiac and respiratory autonomic responses cross-frequency coupling graph-theoretic approach heart rate variability interpersonal action coordination social networks within-frequency coupling

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Area of Science:

Neuroscience
Systems Biology
Music Psychology

Background:

Choral singing involves intricate coordination of physiological systems within and between individuals.
Previous research suggested a choir functions as a superordinate system influencing individual singer dynamics.
Network topography analysis using within- and cross-frequency couplings (WFC and CFC) revealed differences in choir singing.

Purpose of the Study:

To investigate hyper-frequency network (HFN) topology structures during choral singing using graph theory.
To analyze phase coupling (WFC and CFC) between respiratory, cardiac, and vocalizing subsystems.
To explore the relationship between network topology and physiological arousal indicators.

Main Methods:

Calculated WFC and CFC between respiratory, cardiac, and vocalizing subsystems across ten frequencies.
Constructed HFNs with nodes representing frequency components and subsystems.
Applied graph-theoretical measures including clustering coefficients (CCs), local/global efficiency, and characteristic path lengths.

Main Results:

Network topology measures (CCs, efficiency) were highest and path lengths shortest when singing in canon versus unison.
These metrics correlated significantly with individual heart rate and the LF/HF ratio (sympathetic/parasympathetic balance).
CCs and local efficiency were higher in groups singing the same canon part compared to random groups.

Conclusions:

Network topology dynamics are critical determinants of group behavior in choral singing.
Hyper-frequency network topology may serve as a biomarker for social interaction.
The findings highlight the complex interplay between physiological synchrony and group performance.