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 tap** 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
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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.
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Preliminary examination of the new ITI series suggested that the same parameter settings for delay (25), embedding dimension (3), and radius (10Â % 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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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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DOI: https://doi.org/10.1007/978-3-319-09531-8_11
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