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Translational Recurrences pp 173–186Cite as

Recurrence Quantification as an Analysis of Temporal Coordination with Complex Signals

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Part of the book series: Springer Proceedings in Mathematics & Statistics ((PROMS,volume 103))

Abstract

Ample past research demonstrates that human rhythmic behavior and rhythmic coordination reveal complex dynamics. More recently, researchers have begun to examine the dynamics of coordination with complex, fractal signals. Here, we present preliminary research investigating how recurrence quantification techniques might be applied to study temporal coordination with complex signals. Participants attempted to synchronize their rhythmic finger tapping behavior with metronomes with varying fractal scaling properties. The results demonstrated that coordination, as assessed by recurrence analyses, differed with the fractal scaling of the metronome stimulus. Overall, these results suggest that recurrence analyses may aid in understanding temporal coordination between complex systems.

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Notes

  1. 1.

    There are ample resources available for those readers interested in the details of fractal analyses [1, 10, 11] and the current theoretical debates [12–14].

  2. 2.

    These two fractal analyses are frequently used in studies of human behavioral data, but there are also maximum-likelihood techniques that are superior for verifying actual power-law scaling (see [18, 19]).

  3. 3.

    The primary difference between the two analyses is that, although both indicate the ITI series of participants synchronized with blue metronomes to be near-random on average (\(\upalpha \) \(\approx \) 0), PSD estimated \(\upalpha \) in the remaining conditions to be substantially greater than DFA (\(\upalpha \) \(\approx \) 0.7 versus 0.5). This difference, however, likely has little bearing on the further analyses described below.

  4. 4.

    Preliminary examination of the new ITI series suggested that the same parameter settings for delay (25), embedding dimension (3), and radius (10 % of the mean distance). Every series was also Z-scored prior to CRQA to ensure both series were on a standard scale.

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Acknowledgments

Thanks to Justin Hasselbrock for help with data collection. This research was supported by the National Institutes of Health (R01GM105045). The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.

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Authors and Affiliations

  1. Department of Psychology, University of Cincinnati, Cincinnati, OH, USA

    Charles A. Coey, Auriel Washburn & Michael J. Richardson

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  1. Charles A. Coey
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  2. Auriel Washburn
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  3. Michael J. Richardson
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Correspondence to Charles A. Coey .

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Editors and Affiliations

  1. Potsdam Institute for Climate Impact Res, Potsdam, Germany

    Norbert Marwan

  2. Dept. of Psychology, University of Cincinnati, Cincinnati, Ohio, USA

    Michael Riley

  3. Istituto Superiore di Sanita, Rome, Italy

    Alessandro Giuliani

  4. Loyola University Chicago, Stritch School of Medicine, Health Sciences Division,Dept. of Cell and Molecular Physiology, Maywood, Illinois, USA

    Charles L. Webber, Jr.

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Coey, C.A., Washburn, A., Richardson, M.J. (2014). Recurrence Quantification as an Analysis of Temporal Coordination with Complex Signals. In: Marwan, N., Riley, M., Giuliani, A., Webber, Jr., C. (eds) Translational Recurrences. Springer Proceedings in Mathematics & Statistics, vol 103. Springer, Cham. https://doi.org/10.1007/978-3-319-09531-8_11

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