Zum Hauptinhalt springen

Intra- and interbrain synchrony and hyperbrain network dynamics of a guitarist quartet and its audience during a concert.

Müller, V ; Lindenberger, U
In: Annals of the New York Academy of Sciences, Jg. 1523 (2023-05-01), Heft 1, S. 74-90
Online academicJournal

Titel:
Intra- and interbrain synchrony and hyperbrain network dynamics of a guitarist quartet and its audience during a concert.
Autor/in / Beteiligte Person: Müller, V ; Lindenberger, U
Link:
Zeitschrift: Annals of the New York Academy of Sciences, Jg. 1523 (2023-05-01), Heft 1, S. 74-90
Veröffentlichung: 2006- : New York, NY : Malden, MA : New York Academy of Sciences ; Blackwell ; <i>Original Publication</i>: New York, The Academy., 2023
Medientyp: academicJournal
ISSN: 1749-6632 (electronic)
DOI: 10.1111/nyas.14987
Schlagwort:
  • Humans
  • Brain Mapping
  • Diencephalon
  • Brain
  • Electroencephalography
Sonstiges:
  • Nachgewiesen in: MEDLINE
  • Sprachen: English
  • Publication Type: Journal Article; Research Support, Non-U.S. Gov't
  • Language: English
  • [Ann N Y Acad Sci] 2023 May; Vol. 1523 (1), pp. 74-90. <i>Date of Electronic Publication: </i>2023 Mar 27.
  • MeSH Terms: Brain* ; Electroencephalography* ; Humans ; Brain Mapping ; Diencephalon
  • References: Nozaradan, S., Peretz, I., & Keller, P. E. (2016). Individual differences in rhythmic cortical entrainment correlate with predictive behavior in sensorimotor synchronization. Scientific Reports, 6, 20612. ; Keller, P. E., Novembre, G., & Hove, M. J. (2014). Rhythm in joint action: Psychological and neurophysiological mechanisms for real-time interpersonal coordination. Philosophical Transactions of the Royal Society B, 369, 20130394. ; D'Ausilio, A., Novembre, G., Fadiga, L., & Keller, P. E. (2015). What can music tell us about social interaction? Trends in Cognitive Sciences, 19, 111-114. ; Badino, L., D'ausilio, A., Glowinski, D., Camurri, A., & Fadiga, L. (2014). Sensorimotor communication in professional quartets. Neuropsychologia, 55, 98-104. ; Keller, P. E., Novembre, G., & Loehr, J. (2016). Musical ensemble performance: Representing self, other, and joint action outcomes. In E. Cross & O. Sukhvinder (Eds.), Shared representations: Sensorimotor foundations of social life (pp. 280-310). Cambridge: Cambridge University Press. ; Acquadro, M. A. S., Congedo, M., & De Riddeer, D. (2016). Music performance as an experimental approach to hyperscanning studies. Frontiers in Human Neuroscience, 10, 242. ; Sänger, J., Müller, V., & Lindenberger, U. (2013). Directionality in hyperbrain networks discriminates between leaders and followers in guitar duets. Frontiers in Human Neuroscience, 7, 234. ; Gugnowska, K., Novembre, G., Kohler, N., Villringer, A., Keller, P. E., & Sammler, D. (2022). Endogenous sources of interbrain synchrony in duetting pianists. Cerebral Cortex, 32, 4110-4127. ; Lindenberger, U., Li, S.-C., Gruber, W., & Müller, V. (2009). Brains swinging in concert: Cortical phase synchronization while playing guitar. BMC Neuroscience [Electronic Resource], 10, 22. ; Müller, V., & Lindenberger, U. (2022). Probing associations between interbrain synchronization and interpersonal action coordination during guitar playing. Annals of the New York Academy of Sciences, 1507, 146-161. ; Müller, V., & Lindenberger, U. (2019). Dynamic orchestration of brains and instruments during free guitar improvisation. Frontiers in Integrative Neuroscience, 13, 50. ; Müller, V., Sänger, J., & Lindenberger, U. (2013). Intra- and inter-brain synchronization during musical improvisation on the guitar. PLoS ONE, 8, e73852. ; Müller, V., Sänger, J., & Lindenberger, U. (2018). Hyperbrain network properties of guitarists playing in quartet. Annals of the New York Academy of Sciences, 1423, 198-210. ; Sänger, J., Lindenberger, U., & Müller, V. (2011). Interactive brains, social minds. Communicative & Integrative Biology, 4, 655-663. ; Sänger, J., Müller, V., & Lindenberger, U. (2012). Intra- and interbrain synchronization and network properties when playing guitar in duets. Frontiers in Human Neuroscience, 6, 312. ; Czeszumski, A., Eustergerling, S., Lang, A., Menrath, D., Gerstenberger, M., Schuberth, S., Schreiber, F., Rendon, Z. Z., & König, P. (2020). Hyperscanning: A valid method to study neural inter-brain underpinnings of social interaction. Frontiers in Human Neuroscience, 14, 39. ; Frith, C. D., & Frith, U. (2007). Social cognition in humans. Current Biology, 17, R724-R732. ; Hari, R., & Kujala, M. V. (2009). Brain basis of human social interaction: From concepts to brain imaging. Physiological Reviews, 89, 453-479. ; Müller, V. (2022). Neural synchrony and network dynamics in social interaction: A hyper-brain cell assembly hypothesis. Frontiers in Human Neuroscience, 16, 848026. ; Müller, V., Ohström, K.-R. P., & Lindenberger, U. (2021). Interactive brains, social minds: Neural and physiological mechanisms of interpersonal action coordination. Neuroscience and Biobehavioral Reviews, 128, 661-677. ; Thompson, E., & Varela, F. J. (2001). Radical embodiment: Neural dynamics and consciousness. Trends in Cognitive Sciences, 5, 418-425. ; Chabin, T., Gabriel, D., Comte, A., Haffen, E., Moulin, T., & Pazart, L. (2022). Interbrain emotional connection during music performances is driven by physical proximity and individual traits. Annals of the New York Academy of Sciences, 1508, 178-195. ; Chabin, T., Gabriel, D., Comte, A., & Pazart, L. (2022). Audience interbrain synchrony during live music is shaped by both the number of people sharing pleasure and the strength of this pleasure. Frontiers in Human Neuroscience, 16, 855778. ; Néda, Z., Ravasz, E., Brechet, Y., Vicsek, T., & Barabási, A.-L. (2000). The sound of many hands clapping. Nature, 403, 849-850. ; Néda, Z., Ravasz, E., Vicsek, T., Brechet, Y., & Barabási, A. L. (2000). Physics of the rhythmic applause. Physical Review E, 61, 6987-6992. ; Zamm, A., Debener, S., Bauer, A.-K. R., Bleichner, M. G., Demos, A. P., & Palmer, C. (2018). Amplitude envelope correlations measure synchronous cortical oscillations in performing musicians. Annals of the New York Academy of Sciences, 1423, 251-263. ; Müller, M. (2021). Fundamentals of music processing. Springer International Publishing. ; Vigário, R. N. (1997). Extraction of ocular artefacts from EEG using independent component analysis. Electroencephalography and Clinical Neurophysiology, 103, 395-404. ; Müller, V., Perdikis, D., Von Oertzen, T., Sleimen-Malkoun, R., Jirsa, V., & Lindenberger, U. (2016). Structure and topology dynamics of hyper-frequency networks during rest and auditory oddball performance. Frontiers in Computational Neuroscience, 10, 108. ; Newman, M. E. J. (2004). Analysis of weighted networks. Physical Review E, 70, 1-9. ; Newman, M. E. J. (2006). Finding community structure in networks using the eigenvectors of matrices. Physical Review E, 74, 036104. ; Rubinov, M., & Sporns, O. (2010). Complex network measures of brain connectivity: Uses and interpretations. Neuroimage, 52, 1059-1069. ; Strehl, A., & Ghosh, J. (2003). Cluster ensembles - A knowledge reuse framework for combining multiple partitions. Journal of Machine Learning Research, 3, 583-617. ; Vinh, N. X., Epps, J., & Bailey, J. (2010). Information theoretic measures for clusterings comparison: Variants, properties, normalization and correction for chance. Journal of Machine Learning Research, 11, 2837-2854. ; Achard, S., Salvador, R., Whitcher, B., Suckling, J., & Bullmore, E. (2006). A resilient, low-frequency, small-world human brain functional network with highly connected association cortical hubs. Journal of Neuroscience, 26, 63-72. ; Bassett, D. S., & Bullmore, E. (2006). Small-world brain networks. Neuroscience, 12, 512-523. ; Telesford, Q. K., Joyce, K. E., Hayasaka, S., Burdette, J. H., & Laurienti, P. J. (2011). The ubiquity of small-world networks. Brain Connectivity, 1, 367-375. ; Watts, D. J., & Strogatz, S. H. (1998). Collective dynamics of “small-world” networks. Nature, 393, 440-442. ; Buzsáki, G. (2006). Rhythms of the brain. Oxford: Oxford University Press. ; Haken, H. (1983). Synergetics: An introduction: Nonequilibrium phase transitions and self-organization in physics, chemistry. Berlin: Springer-Verlag. ; Blood, A. J., & Zatorre, R. J. (2001). Intensely pleasurable responses to music correlate with activity in brain regions implicated in reward and emotion. Proceedings of the National Academy of Sciences of the United States of America, 98, 11818-11823. ; Ferreri, L., Mas-Herrero, E., Zatorre, R. J., Ripollés, P., Gomez-Andres, A., Alicart, H., Olivé, G., Marco-Pallarés, J., Antonijoan, R. M., Valle, M., Riba, J., & Rodriguez-Fornells, A. (2019). Dopamine modulates the reward experiences elicited by music. Proceedings of the National Academy of Sciences of the United States of America, 116, 3793-3798. ; Salimpoor, V. N., Benovoy, M., Larcher, K., Dagher, A., & Zatorre, R. J. (2011). Anatomically distinct dopamine release during anticipation and experience of peak emotion to music. Nature Neuroscience, 14, 257-262. ; Buzsáki, G. (2010). Neural syntax: Cell assemblies, synapsembles, and readers. Neuron, 68, 362-385. ; Buzsáki, G. (2019). The brain from inside out. New York: Oxford University Press. ; Hasson, U., & Frith, C. D. (2016). Mirroring and beyond: Coupled dynamics as a generalized framework for modelling social interactions. Philosophical Transactions of the Royal Society B, 371, 20150366. ; Jirsa, V., & Müller, V. (2013). Cross-frequency coupling in real and virtual brain networks. Frontiers in Computational Neuroscience, 7, 78. ; Müller, V., & Lindenberger, U. (2014). Hyper-brain networks support romantic kissing in humans. PLoS ONE, 9, e112080.
  • Contributed Indexing: Keywords: EEG hyperscanning; graph-theoretical approach; hyperbrain networks; intra- and interbrain coupling; phase synchronization; social interaction
  • Entry Date(s): Date Created: 20230328 Date Completed: 20230515 Latest Revision: 20230524
  • Update Code: 20240513

Klicken Sie ein Format an und speichern Sie dann die Daten oder geben Sie eine Empfänger-Adresse ein und lassen Sie sich per Email zusenden.

oder
oder

Wählen Sie das für Sie passende Zitationsformat und kopieren Sie es dann in die Zwischenablage, lassen es sich per Mail zusenden oder speichern es als PDF-Datei.

oder
oder

Bitte prüfen Sie, ob die Zitation formal korrekt ist, bevor Sie sie in einer Arbeit verwenden. Benutzen Sie gegebenenfalls den "Exportieren"-Dialog, wenn Sie ein Literaturverwaltungsprogramm verwenden und die Zitat-Angaben selbst formatieren wollen.

xs 0 - 576
sm 576 - 768
md 768 - 992
lg 992 - 1200
xl 1200 - 1366
xxl 1366 -