Connecting empirical phenomena and theoretical models of biological coordination across scales

Mengsen Zhang, Christopher Beetle, J.A. Scott Kelso, Emmanuelle Tognoli

Research output: Contribution to journalArticlepeer-review

31 Citations (Scopus)
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Abstract

Coordination in living systems—from cells to people—must be understood at multiple levels of description. Analyses and modelling of empirically observed patterns of biological coordination often focus either on ensemble-level statistics in large-scale systems with many components, or on detailed dynamics in small-scale systems with few components. The two approaches have proceeded largely independent of each other. To bridge this gap between levels and scales, we have recently conducted a human experiment of mid-scale social coordination specifically designed to reveal coordination at multiple levels (ensemble, subgroups and dyads) simultaneously. Based on this experiment, the present work shows that, surprisingly, a single system of equations captures key observations at all relevant levels. It also connects empirically validated models of large- and small-scale biological coordination—the Kuramoto and extended Haken–Kelso–Bunz (HKB) models—and the hallmark phenomena that each is known to capture. For example, it exhibits both multistability and metastability observed in small-scale empirical research (via the second-order coupling and symmetry breaking in extended HKB) and the growth of biological complexity as a function of scale (via the scalability of the Kuramoto model). Only by incorporating both of these features simultaneously can we reproduce the essential coordination behaviour observed in our experiment.
Original languageEnglish
Article number20190360
Number of pages11
JournalJournal of The Royal Society Interface
Volume16
Issue number157
Early online date14 Aug 2019
DOIs
Publication statusPublished (in print/issue) - 30 Aug 2019

Keywords

  • complexity
  • complex systems
  • coordination dynamics
  • nonlinear dynamics
  • statistical mechanics
  • social
  • Bioengineering
  • Biomedical Engineering
  • Biotechnology
  • Biochemistry
  • Biophysics
  • Biomaterials

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