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Hyper-Frequency Network Topology Changes During Choral Singing
Open accessAbstract
Choral singing requires the coordination of physiological subsystems within and across individuals. Previously, we suggested that the choir functions as a superordinate system that imposes boundary conditions on the dynamic features of the individual singers and found reliable differences in the network topography by analyzing within- and cross-frequency couplings (WFC and CFC, respectively). Here, we further refine our analyses to investigate hyper-frequency network (HFN) topology structures (i.e., the layout or arrangement of connections) using a graph-theoretical approach. In a sample of eleven singers and one conductor engaged in choral singing (aged between 23 and 56 years, and including five men and seven women), we calculated phase coupling (WFC and CFC) between respiratory, cardiac, and vocalizing subsystems across ten frequencies of interest. All these couplings were used for construction of HFN with nodes being a combination of frequency components and subsystems across choir participants. With regard to the network topology measures, we found that clustering coefficients as well as local and global efficiency were highest and characteristic path lengths, correspondingly, were shortest when the choir sang a canon in parts as compared to singing it in unison. Furthermore, these metrics revealed a significant relationship to individual heart rate, as an indicator of arousal, and to an index of heart rate variability indicated by the LF/HF ratio (low and high frequency, respectively) and reflecting the balance between sympathetic and parasympathetic activity. In addition, we found that the clustering coefficient and local efficiency for groups singing the same canon part were higher than for groups of singers constructed randomly post hoc, indicating stronger neighbor–neighbor connections in the former. We conclude that network topology dynamics are a crucial determinant of group behavior and may represent a potent biomarker for social interaction.
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Müller et al. (2019) identified negative correlations between heart rate, LF/HF ratio and CFC measures during canon singing.
“Müller et al. (2019) identified negative correlations between HR, LF/HF ratio and CFC measures during canon singing.”
From Mapping the Neurophysiological Link Between Voice and Autonomic Function: A Scoping Review (2025) · cites this paper as [30]
In the unison condition, both heart rate and LF/HF decreased with stronger CFC, whereas in the multipart condition, LF/HF decreased with increasing CFC input, indicating distinct autonomic patterns across singing modes.
“In the unison condition, both HR and LF/HF decreased with stronger CFC, whereas in the multipart condition, LF/HF decreased with increasing CFC input, indicating distinct autonomic patterns across singing modes [30].”
From Mapping the Neurophysiological Link Between Voice and Autonomic Function: A Scoping Review (2025) · cites this paper as [30]
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References 35 · Cited by 22
Research works printed but not linked: 30
- Bassett, 2017, A network engineering perspective on probing and perturbing cognition with neurofeedback., Ann. N. Y. Acad. Sci., 1396, 126, 10.1111/nyas.13338 · DOI
- Bettermann, 2002, Effects of speech therapy with poetry on heart rate rhythmicity and cardiorespiratory coordination., Int. J. Cardiol., 84, 77, 10.1016/S0167-5273(02)00137-7 · DOI
- Cysarz, 2004, Oscillations of heart rate and respiration synchronize during poetry recitation., Am. J. Physiol. Heart Circ. Physiol., 287, H579, 10.1152/ajpheart.01131.2003 · DOI · Paper page
- Detrain, 2006, Self-organized structures in a superorganism: do ants “behave” like molecules?, Phys. Life Rev., 3, 162, 10.1016/j.plrev.2006.07.001 · DOI
- Emerson, 1939, Social coordination and the superorganism., Am. Midl. Nat., 21, 182, 10.2307/2420380 · DOI
- Fagiolo, 2007, Clustering in complex directed networks., Phys. Rev. E, 76, 10.1103/PhysRevE.76.026107 · DOI
- Harmat, 2010, Heart rate variability during singing and flute playing., Music Med., 2, 10, 10.1177/1943862109354598 · DOI
- Hasson, 2016, Mirroring and beyond: coupled dynamics as a generalized framework for modelling social interactions., Philos. Trans. R. Soc. Lond. B Biol. Sci., 371, 10.1098/rstb.2015.0366 · DOI · Paper page
- Keller, 2014, Rhythm in joint action: psychological and neurophysiological mechanisms for real-time interpersonal coordination., Philos. Trans. R. Soc. B Biol. Sci., 369, 10.1098/rstb.2013.0394 · DOI · Paper page
- Koban, 2019, Why do we fall into sync with others? Interpersonal synchronization and the brain’s optimization principle., Soc. Neurosci., 14, 1, 10.1080/17470919.2017.1400463 · DOI · Paper page
- Latora, 2001, Efficient behavior of small-world networks., Phys. Rev. Lett., 87, 10.1103/PhysRevLett.87.198701 · DOI · Paper page
- Liao, 2017, Small-world human brain networks: perspectives and challenges., Neurosci. Biobehav. Rev., 77, 286, 10.1016/j.neubiorev.2017.03.018 · DOI
- Malik, 1996, Heart rate variability: standards of measurement, physiological interpretation, and clinical use., Eur. Heart J., 17, 354, 10.1161/01.CIR.93.5.1043 · DOI · Paper page
- Marti, 2012, Wirkungen des Chorsingens auf die cardiorespiratorische Koordination und das subjektive Befinden bei Erwachsenen., RoSE Res. Steiner Educ., 3, 146
- Mazzucco, 2017, Mechanical ventilatory modes and cardioventilatory phase synchronization in acute respiratory failure patients., Physiol. Meas., 38, 895, 10.1088/1361-6579/aa56ae · DOI
- Müller, Complex networks emerging during choir singing., Ann. N. Y. Acad. Sci., 1431, 85, 10.1111/nyas13940 · DOI
- Müller, Hyperbrain network properties of guitarists playing in quartet., Ann. N. Y. Acad. Sci., 1423, 198, 10.1111/nyas.13656 · DOI
- Müller, 2011, Cardiac and respiratory patterns synchronize between persons during choir singing., PLoS One, 6, 10.1371/journal.pone.0024893 · DOI · Paper page
- Müller, 2014, Hyper-brain networks support romantic kissing in humans., PLoS One, 9, 10.1371/journal.pone.0112080 · DOI
- Müller, 2016, Structure and topology dynamics of hyper-frequency networks during rest and auditory oddball performance., Front. Comput. Neurosci., 10, 10.3389/fncom.2016.00108 · DOI
- Müller, 2013, Intra- and inter-brain synchronization during musical improvisation on the guitar., PLoS One, 8, 10.1371/journal.pone.0073852 · DOI
- Noble, 2012, A theory of biological relativity: no privileged level of causation., Interface Focus, 2, 55, 10.1098/rsfs.2011.0067 · DOI · Paper page
- Olsson, 2013, Heart rate variability during choral singing., Music Med., 5, 52, 10.1177/1943862112471399 · DOI
- Pollard, 2007, Do blood pressure and heart rate responses to perceived stress vary according to endogenous estrogen level in women?, Am. J. Phys. Antropol., 132, 151, 10.1002/ajpa.20468 · DOI
- Sänger, 2011, Interactive brains, social minds., Commun. Integr. Biol., 4, 655, 10.4161/cib.4.6.17934 · DOI
- Sänger, 2012, Intra- and interbrain synchronization and network properties when playing guitar in duets., Front. Hum. Neurosci., 6, 10.3389/fnhum.2012.00312 · DOI
- Stewart, 2016, It’s better together: the psychological benefits of singing in a choir., Psychol. Music, 44, 1240, 10.1177/0305735615624976 · DOI
- von Rosenberg, 2017, Resolving ambiguities in the LF/HF ratio: LF-HF scatter plots for the categorization of mental and physical stress from HRV., Front. Physiol., 8, 10.3389/fphys.2017.00360 · DOI
- Watts, 1998, Collective dynamics of “small-world” networks., Nature, 393, 440, 10.1038/30918 · DOI · Paper page
- Wheeler, 1926, Emergent evolution and the social., Science, 64, 433, 10.1126/science.64.1662.433 · DOI
Metadata
- Authors
- Müller, V., Delius, J. A. M., & Lindenberger, U.
- Affiliations
- Max Planck Institute for Human Development (DE)
- Corresponding author
- Müller, Viktor
- Lindenberger, Ulman
- Venue
- Frontiers in Physiology
- Publisher
- Frontiers Media SA
- Published
- 2019-03-06
- Volume
- 10
- Pages
- 207-207
- ISSN
- 1664-042X (ISSN-L)
- PMC
- PMC6416178
- OpenAlex
- W2921929556
- Cited by
- 22
- References
- 35
- Citations by year
- 2026: 4 · 2025: 2 · 2024: 2 · 2023: 2 · 2022: 5 · 2021: 6 · 2019: 1
- FWCI
- 2.17
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Frontiers in Physiology (publishedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- MPG.PuRe (Max Planck Society) (submittedVersion, other-oa)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Funders
- Max-Planck-Gesellschaft
- Topics
- Health Sciences › Medicine › Cardiology and Cardiovascular Medicine › Heart Rate Variability and Autonomic Control
- Social Sciences › Psychology › Social Psychology › Action Observation and Synchronization
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neural dynamics and brain function
- Keywords
- choral singing, cross-frequency coupling, heart rate, heart rate variability, LF/HF ratio, clustering coefficient, local efficiency, global efficiency, path length, group behavior, choral conductors
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