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Interpersonal Couplings in Human Interactions

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Book cover Recurrence Quantification Analysis

Part of the book series: Understanding Complex Systems ((UCS))

Abstract

As inherently social beings people routinely interact with others. Interpersonal activities such as dancing, conversation, or team sports require people to coordinate at several different levels, ranging from the coordination of physical movements and physiological states of the body to the coordination of mental states and cognitive or linguistic activity. One of the challenges confronted by researchers in this interdisciplinary field has been to find ways to objectively quantify interpersonal coupling on the basis of brief, noisy, nonstationary, and complex time series of human behavioral sequences. Given their robustness to these challenges, recurrence-based strategies have played a very important role in the development of this field of research. This chapter provides a review of current behavioral, cognitive, and physiological research that has used recurrence methods to quantify interpersonal coupling.

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Acknowledgments

This chapter is dedicated to Guy Van Orden (1952–2012) who foresaw the exceptional utility of recurrence-based methods for studying interpersonal coordination and encouraged our pursuit of these methods in behavioral research. We would also like to thank the American Psychological Association (APA) for sponsoring our Advanced Training Institute on Nonlinear Methods each summer since 2006 (taught at the University of Cincinnati in conjunction with John [Jay] Holden, Rick Dale, and Michael J. Richardson). APA’s support, particularly the support of Nicolle Singer and Howard Kurtzman, has allowed us to share our knowledge of recurrence-based and other nonlinear methods with a greater number and variety of researchers than we could have hoped for. This work was supported by National Science Foundation grant: BCS-0926662.

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Shockley, K., Riley, M.A. (2015). Interpersonal Couplings in Human Interactions. In: Webber, Jr., C., Marwan, N. (eds) Recurrence Quantification Analysis. Understanding Complex Systems. Springer, Cham. https://doi.org/10.1007/978-3-319-07155-8_14

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