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Two classes of functional connectivity in dynamical processes in networks.

Venetia Voutsa1, Demian Battaglia2,3, Louise J Bracken4

  • 1Department of Life Sciences and Chemistry, Jacobs University Bremen, 28759 Bremen, Germany.

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|October 19, 2021
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Summary

This study distinguishes two types of functional connectivity (FC) based on node activity: simultaneous (co-activity) and sequential. This framework helps organize observations relating complex network structure and dynamics across various scientific fields.

Keywords:
chaotic oscillatorsexcitable dynamicsmodular graphsrandom graphsscale-free graphssynchronisation

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Area of Science:

  • Complex Systems Theory
  • Network Science
  • Dynamical Systems

Background:

  • The relationship between network structure (structural connectivity, SC) and dynamics (functional connectivity, FC) is a key problem in complex systems.
  • Understanding SC/FC correlations is crucial across diverse fields like neuroscience, ecology, and geomorphology.

Purpose of the Study:

  • To differentiate between two classes of functional connectivity: co-activity (simultaneous) and sequential activity.
  • To explore the implications of these two FC classes for understanding SC/FC relationships in various dynamical processes.

Main Methods:

  • Distinguishing functional connectivity into co-activity and sequential activity classes.
  • Analyzing these classes across different dynamical processes, including excitations and regular/chaotic oscillators.
  • Providing conceptual examples of SC and FC for diverse application scenarios.

Main Results:

  • Demonstrated that functional connectivity can be categorized based on simultaneous (co-activity) versus sequential node activity.
  • Illustrated SC/FC correlations for both FC classes within models of excitations and oscillators.
  • Expanded the theoretical framework for SC/FC relationships with practical examples.

Conclusions:

  • Classifying network dynamics as either co-activity or sequential activity provides a framework to organize structure-function observations.
  • This approach offers a way to bring order to the complex interplay between network structure and function in various systems.