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Social Coordination, from the Perspective of Coordination Dynamics

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Encyclopedia of Complexity and Systems Science

Definition of the Subject

Social Coordination Dynamics(SCD)explores, at both behavioral and neural levels, the mechanisms mediating the formation and dissolution of bonds between individuals. SCD applies theconcepts, methods and tools of informationally coupled self‐organizing systems (coordination dynamics) to quantify real time social processes. Justas coordination dynamics deals with how the parts of complex systems work together in a meaningful way to achieve goals, so SCD aims to understandthe interplay of forces operating at both individual and collective levels to produce effective social behavior. SCD offers a novel perspective andnew metrics to explore systematically a fundamental form of human bonding (or lack thereof), and the self‐organizing processes that underlieits persistence and change over space and time. SCD therefore complements recent developments in several fields such as sociology, social cognitiveneuroscience, behavioral...

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Abbreviations

Self‐organization :

Self‐organization lies behind all structure and pattern formation in nature's complex systems, including the human brain. Self‐organization is a principle governing a system where no agent-like entity is ordering the elements, telling them where and what to do. In self‐organizing systems, low‐dimensional dynamics are revealed by changing one (or more) control parameter(s) whose role is simply to move the system through a series of state changes without prescribing its behavioral patterns.

Coordination dynamics:

Coordination dynamics seeks the laws, principles and mechanisms underlying the coordinated behavior of different kinds of components at multiple levels of description (molecules, cells, circuits, etc). It is an overarching conceptual framework that describes, explains and predicts how patterns of coordination form and change at multiple levels of brain and behavior. The brain, mind and behavior are linked by virtue of sharing a common underlying coordination dynamics.

Information exchange :

A remarkable fact is that in contrast to classical dynamics that deal with fundamental quantities such as mass, length and time and their relations, coordination dynamics is informational in nature, dealing with informational quantities of a relational kind that couple different parts of a system or different systems.

Phase transitions :

Phase transitions are the true illustration that a system is self‐organizing. They are spontaneous qualitative pattern changes occurring as parameters are changed quantitatively. When they occur, abrupt switches from one coordinated pattern to another are observed and the dynamics of the entire self‐organizing system is dominated by one or a few collective variables: the order parameters.

Stability :

Stability is a key concept in coordination dynamics. Here the stability is of coordination or collective variables. The (loss of) stability of a self‐organizing system indicates whether a phase transition is to occur. In order to evaluate the stability of a system, one can perturb it and measure the time it takes for the system to return to its initial state, i. e. its relaxation time. A number of other converging measures have been used to measure stability in coordination dynamics such as switching time (the time it takes for the system to switch from one pattern to another when phase transitions occur) and critical fluctuations (the increase of variability of the collective variable in the vicinity of the phase transition).

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Acknowledgments

The authors wish to thank their collaborators at the Human Brain andBehavior Laboratory (Center for Complex Systems and Brain Sciences) who co‐authored the articles on social coordination dynamics reportedin this article: Drs. Gonzalo C. de Guzman (Florida Atlantic University), Kelly J. Jantzen (Washington Western University), Julien Lagarde (Université de Montpellier I), Cyrille Magne(Middle Tenesse State University) and Emmanuelle Tognoli (Florida AtlanticUniversity). Amélie L. and Audrey O. should also be thanked for letting the authors use their beautiful hands and eyes in all figures. Wewish to thank the following institutions for supporting our research and the writing of this article. The US National Institutes ofHealth (NIMH Innovation Grant MH 42900 and MH080838), the Pierre de Fermat Chair of the Région Midi-Pyrénées (France) to J.A.S.K,and the Centre National de la Recherche Scientifique (Programme CNRS Neuroinformatique to O.O.). Correspondence should beaddressed to: Olivier Oullier (olivier@oullier.fr) or J. A. Scott Kelso (kelso@ccs.fau.edu).

For additional information pleasevisit the following websites: www.oullier.fr and www.ccs.fau.edu/section_links/HBBLv2/index.html

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  1. Laboratoire de Neurobiologie Humaine (UMR 6149), Aix-Marseille Université, Marseille, France

    Olivier Oullier

  2. Human Brain and Behavior Laboratory, Center for Complex Systems and Brain Sciences, Florida Atlantic University, Boca Raton, USA

    Olivier Oullier & James A. S. Kelso

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  1. Olivier Oullier
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  1. RAMTECH LIMITED, 122 Escalle Lane, Larkspur, CA, 94939, USA

    Robert A. Meyers Ph. D. (Editor-in-Chief) (Editor-in-Chief)

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Oullier, O., Kelso, J.A.S. (2009). Social Coordination, from the Perspective of Coordination Dynamics. In: Meyers, R. (eds) Encyclopedia of Complexity and Systems Science. Springer, New York, NY. https://doi.org/10.1007/978-0-387-30440-3_486

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