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Dynamic information routing in complex networks

Author

Listed:
  • Christoph Kirst

    (Network Dynamics, Max Planck Institute for Dynamics and Self-Organization (MPIDS)
    Nonlinear Dynamics, Max Planck Institute for Dynamics and Self-Organization (MPIDS)
    Institute for Nonlinear Dynamics, Georg-August University Göttingen
    Bernstein Center for Computational Neuroscience (BCCN))

  • Marc Timme

    (Network Dynamics, Max Planck Institute for Dynamics and Self-Organization (MPIDS)
    Institute for Nonlinear Dynamics, Georg-August University Göttingen
    Bernstein Center for Computational Neuroscience (BCCN))

  • Demian Battaglia

    (Université Aix-Marseille, INSERM UMR 1106, Institut de Neurosciences des Systémes)

Abstract

Flexible information routing fundamentally underlies the function of many biological and artificial networks. Yet, how such systems may specifically communicate and dynamically route information is not well understood. Here we identify a generic mechanism to route information on top of collective dynamical reference states in complex networks. Switching between collective dynamics induces flexible reorganization of information sharing and routing patterns, as quantified by delayed mutual information and transfer entropy measures between activities of a network’s units. We demonstrate the power of this mechanism specifically for oscillatory dynamics and analyse how individual unit properties, the network topology and external inputs co-act to systematically organize information routing. For multi-scale, modular architectures, we resolve routing patterns at all levels. Interestingly, local interventions within one sub-network may remotely determine nonlocal network-wide communication. These results help understanding and designing information routing patterns across systems where collective dynamics co-occurs with a communication function.

Suggested Citation

  • Christoph Kirst & Marc Timme & Demian Battaglia, 2016. "Dynamic information routing in complex networks," Nature Communications, Nature, vol. 7(1), pages 1-9, April.
    • Handle: RePEc:nat:natcom:v:7:y:2016:i:1:d:10.1038_ncomms11061
    DOI: 10.1038/ncomms11061
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    Cited by:

    1. Benedict J Lünsmann & Christoph Kirst & Marc Timme, 2017. "Transition to reconstructibility in weakly coupled networks," PLOS ONE, Public Library of Science, vol. 12(10), pages 1-12, October.
    2. Yoon, Jisung & Park, Jinseo & Yun, Jinhyuk & Jung, Woo-Sung, 2023. "Quantifying knowledge synchronization with the network-driven approach," Journal of Informetrics, Elsevier, vol. 17(4).
    3. Janina Hesse & Jan-Hendrik Schleimer & Nikolaus Maier & Dietmar Schmitz & Susanne Schreiber, 2022. "Temperature elevations can induce switches to homoclinic action potentials that alter neural encoding and synchronization," Nature Communications, Nature, vol. 13(1), pages 1-12, December.
    4. Samy Castro & Wael El-Deredy & Demian Battaglia & Patricio Orio, 2020. "Cortical ignition dynamics is tightly linked to the core organisation of the human connectome," PLOS Computational Biology, Public Library of Science, vol. 16(7), pages 1-23, July.
    5. Tommaso Menara & Giacomo Baggio & Dani Bassett & Fabio Pasqualetti, 2022. "Functional control of oscillator networks," Nature Communications, Nature, vol. 13(1), pages 1-13, December.
    6. Xiaoge Bao & Qitong Hu & Peng Ji & Wei Lin & Jürgen Kurths & Jan Nagler, 2022. "Impact of basic network motifs on the collective response to perturbations," Nature Communications, Nature, vol. 13(1), pages 1-8, December.

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