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Windowed detrended cross-correlation analysis of synchronization processes

Author

Listed:
  • Roume, C.
  • Almurad, Z.M.H.
  • Scotti, M.
  • Ezzina, S.
  • Blain, H.
  • Delignières, D.

Abstract

The aim of this paper was to propose a formal approach of the Windowed Detrended Cross-Correlation (WDCC) analysis, a method designed for identifying the processes that underlie intra- and interpersonal synchronization. We present the three main theoretical frameworks that have been proposed for accounting for synchronization processes, (1) the information-processing approach, (2) the coupled oscillators model and (3) the complexity matching effect. We formally derive the WDCC results that could be expected from each model. We show by simulation that each model allows generating series that fit the expected results. We also analyze experimental data sets collected in situations that were supposed to selectively elicit the synchronization processes depicted in the three theoretical frameworks. Our results show that the information-processing and the complexity matching processes are both present in each situation, but with a clear dominance of one of these processes on the other. Finally our results lead us to cast some doubts about the relevance of the coupled oscillators model in interpersonal synchronization.

Suggested Citation

  • Roume, C. & Almurad, Z.M.H. & Scotti, M. & Ezzina, S. & Blain, H. & Delignières, D., 2018. "Windowed detrended cross-correlation analysis of synchronization processes," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 503(C), pages 1131-1150.
    • Handle: RePEc:eee:phsmap:v:503:y:2018:i:c:p:1131-1150
    DOI: 10.1016/j.physa.2018.08.074
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    References listed on IDEAS

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    1. Stephen, Damian G. & Dixon, James A., 2011. "Strong anticipation: Multifractal cascade dynamics modulate scaling in synchronization behaviors," Chaos, Solitons & Fractals, Elsevier, vol. 44(1), pages 160-168.
    2. Delignières, Didier & Marmelat, Vivien, 2014. "Strong anticipation and long-range cross-correlation: Application of detrended cross-correlation analysis to human behavioral data," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 394(C), pages 47-60.
    3. Vivien Marmelat & Kjerstin Torre & Peter J Beek & Andreas Daffertshofer, 2014. "Persistent Fluctuations in Stride Intervals under Fractal Auditory Stimulation," PLOS ONE, Public Library of Science, vol. 9(3), pages 1-9, March.
    4. B. Podobnik & I. Grosse & D. Horvatić & S. Ilic & P. Ch. Ivanov & H. E. Stanley, 2009. "Quantifying cross-correlations using local and global detrending approaches," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 71(2), pages 243-250, September.
    5. Zebende, G.F., 2011. "DCCA cross-correlation coefficient: Quantifying level of cross-correlation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(4), pages 614-618.
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    Cited by:

    1. Iran R Roman & Auriel Washburn & Edward W Large & Chris Chafe & Takako Fujioka, 2019. "Delayed feedback embedded in perception-action coordination cycles results in anticipation behavior during synchronized rhythmic action: A dynamical systems approach," PLOS Computational Biology, Public Library of Science, vol. 15(10), pages 1-32, October.
    2. Okano, Masahiro & Kurebayashi, Wataru & Shinya, Masahiro & Kudo, Kazutoshi, 2019. "Hybrid dynamics in a paired rhythmic synchronization–continuation task," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 524(C), pages 625-638.

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