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multiSyncPy: A Python package for assessing multivariate coordination dynamics.

Dan Hudson1,2, Travis J Wiltshire3, Martin Atzmueller4

  • 1Semantic Information Systems Group, Institute of Computer Science, Osnabrück University, P.O. Box 4469, 49069, Osnabrueck, Germany. daniel.dominic.hudson@uni-osnabrueck.de.

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|May 5, 2022
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Summary
This summary is machine-generated.

We introduce multiSyncPy, an open-source Python package for analyzing multivariate synchrony in groups and individuals. This tool enhances the study of complex coordination dynamics in real-world scenarios.

Keywords:
CoordinationDynamicsInteractionMultivariate methodsSynchrony

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Area of Science:

  • Psychology
  • Neuroscience
  • Data Science

Background:

  • Intra- and interpersonal synchrony research is expanding.
  • Quantifying group coordination and individual multimodal synchronization is complex.
  • Existing methods often lack the capacity for complex, real-world study designs.

Purpose of the Study:

  • To introduce multiSyncPy, an open-source Python package.
  • To support advanced research in multivariate synchrony.
  • To enable the analysis of complex coordination dynamics in larger, more ecologically valid study designs.

Main Methods:

  • Includes state-of-the-art multivariate methods: symbolic entropy, multidimensional recurrence quantification analysis, coherence, cluster-phase 'Rho' metric, and Kuramoto order parameter.
  • Provides functions for surrogation techniques to assess statistical significance.
  • Offers a windowing function for time-varying coordination analysis.

Main Results:

  • The multiSyncPy package offers a comprehensive suite of tools for multivariate synchrony analysis.
  • It facilitates the application of advanced methods to complex datasets.
  • The package supports both synthetic and empirical data analysis with practical examples and guidance.

Conclusions:

  • multiSyncPy makes the study of interpersonal synchronization and coordination dynamics more accessible for complex study designs.
  • The software provides researchers with powerful tools to analyze group and individual synchrony.
  • It advances the field by enabling more ecologically valid research into coordination.