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Searching for structure in collective systems.

Colin R Twomey1, Andrew T Hartnett2, Matthew M G Sosna3

  • 1Department of Biology, University of Pennsylvania, Philadelphia, PA, USA. crtwomey@sas.upenn.edu.

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|March 25, 2020
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Summary
This summary is machine-generated.

Researchers developed a universal measure for quantifying collective behavior coordination across diverse systems, from fish schools to neural networks. This new approach enables cross-system comparisons and reveals internal organizational structures within these complex systems.

Keywords:
Collective behaviorCoordinationGroup structureInformation theory

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Area of Science:

  • Collective behavior
  • Systems biology
  • Information theory

Background:

  • Collective systems, such as fish schools and neural networks, exhibit coordinated behavior through local interactions.
  • Current measures of large-scale coordination are system-specific, hindering broad comparisons.
  • A universal, quantitative scale for coordination is lacking.

Purpose of the Study:

  • To develop a system-independent measure of coordination for collective behavior.
  • To enable quantitative comparisons across diverse collective systems.
  • To identify and analyze the most coordinated components within systems.

Main Methods:

  • Utilized an information-theoretic measure of multivariate dependence.
  • Developed a novel, system-independent coordination metric.
  • Applied the metric to analyze classic and well-studied collective systems.

Main Results:

  • Introduced a universal measure applicable to various collective systems.
  • Provided a new perspective on well-established collective phenomena.
  • Demonstrated a method for identifying highly coordinated subsystems.

Conclusions:

  • The developed measure offers a unified framework for studying collective coordination.
  • This approach facilitates cross-disciplinary research in collective behavior.
  • Reveals underlying organizational principles in natural and artificial systems.