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Origins of 1/f noise in human music performance from short-range autocorrelations related to rhythmic structures

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  • Ian D Colley
  • Roger T Dean

Abstract

1/f fluctuations have been described in numerous physical and biological processes. This noise structure describes an inverse relationship between the intensity and frequency of events in a time series (for example reflected in power spectra), and is believed to indicate long-range dependence, whereby events at one time point influence events many observations later. 1/f has been identified in rhythmic behaviors, such as music, and is typically attributed to long-range correlations. However short-range dependence in musical performance is a well-established finding and past research has suggested that 1/f can arise from multiple continuing short-range processes. We tested this possibility using simulations and time-series modeling, complemented by traditional analyses using power spectra and detrended fluctuation analysis (as often adopted more recently). Our results show that 1/f-type fluctuations in musical contexts may be explained by short-range models involving multiple time lags, and the temporal ranges in which rhythmic hierarchies are expressed are apt to create these fluctuations through such short-range autocorrelations. We also analyzed gait, heartbeat, and resting-state EEG data, demonstrating the coexistence of multiple short-range processes and 1/f fluctuation in a variety of phenomena. This suggests that 1/f fluctuation might not indicate long-range correlations, and points to its likely origins in musical rhythm and related structures.

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  • Ian D Colley & Roger T Dean, 2019. "Origins of 1/f noise in human music performance from short-range autocorrelations related to rhythmic structures," PLOS ONE, Public Library of Science, vol. 14(5), pages 1-15, May.
  • Handle: RePEc:plo:pone00:0216088
    DOI: 10.1371/journal.pone.0216088
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    1. Marina Fortes & Didier Deligniéres & Grégory Ninot, 2004. "The Dynamics of Self-Esteem and Physical Self: Between Preservation and Adaptation," Quality & Quantity: International Journal of Methodology, Springer, vol. 38(6), pages 735-751, December.
    2. Marietta Kirchner & Patric Schubert & Magnus Liebherr & Christian T Haas, 2014. "Detrended Fluctuation Analysis and Adaptive Fractal Analysis of Stride Time Data in Parkinson's Disease: Stitching Together Short Gait Trials," PLOS ONE, Public Library of Science, vol. 9(1), pages 1-6, January.
    3. Teresa Blázquez, M. & Anguiano, Marta & de Saavedra, Fernando Arias & Lallena, Antonio M. & Carpena, Pedro, 2009. "Study of the human postural control system during quiet standing using detrended fluctuation analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(9), pages 1857-1866.
    4. Cheolwoo Park & F�lix Hernández-Campos & Long Le & J. S. Marron & Juhyun Park & Vladas Pipiras & F. D. Smith & Richard L. Smith & Michele Trovero & Zhengyuan Zhu, 2011. "Long-range dependence analysis of Internet traffic," Journal of Applied Statistics, Taylor & Francis Journals, vol. 38(7), pages 1407-1433, June.
    5. Esa Räsänen & Otto Pulkkinen & Tuomas Virtanen & Manfred Zollner & Holger Hennig, 2015. "Fluctuations of Hi-Hat Timing and Dynamics in a Virtuoso Drum Track of a Popular Music Recording," PLOS ONE, Public Library of Science, vol. 10(6), pages 1-16, June.
    6. Leon Glass, 2001. "Synchronization and rhythmic processes in physiology," Nature, Nature, vol. 410(6825), pages 277-284, March.
    7. Granger, C. W. J., 1980. "Long memory relationships and the aggregation of dynamic models," Journal of Econometrics, Elsevier, vol. 14(2), pages 227-238, October.
    8. Kantelhardt, Jan W & Koscielny-Bunde, Eva & Rego, Henio H.A & Havlin, Shlomo & Bunde, Armin, 2001. "Detecting long-range correlations with detrended fluctuation analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 295(3), pages 441-454.
    9. Plamen Ch. Ivanov & Luís A. Nunes Amaral & Ary L. Goldberger & Shlomo Havlin & Michael G. Rosenblum & Zbigniew R. Struzik & H. Eugene Stanley, 1999. "Multifractality in human heartbeat dynamics," Nature, Nature, vol. 399(6735), pages 461-465, June.
    10. Daniel Liu Bowling & Janani Sundararajan & Shui'er Han & Dale Purves, 2012. "Expression of Emotion in Eastern and Western Music Mirrors Vocalization," PLOS ONE, Public Library of Science, vol. 7(3), pages 1-8, March.
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    2. Ferreira, Paulo & Quintino, Derick & Wundervald, Bruna & Dionísio, Andreia & Aslam, Faheem & Cantarinha, Ana, 2021. "Is Brazilian music getting more predictable? A statistical physics approach for different music genres," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 583(C).

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