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Examining Local Network Processing using Multi-contact Laminar Electrode Recording
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Control of Multilayer Networks.

Giulia Menichetti1, Luca Dall'Asta2,3, Ginestra Bianconi4

  • 1Department of Physics and Astronomy and INFN Sez. Bologna, Bologna University, Viale B. Pichat 6/2 40127 Bologna, Italy.

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|February 13, 2016
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Summary
This summary is machine-generated.

This study introduces a new framework for analyzing network controllability in multilayer networks. Correlating signals across layers can decrease robustness, but multilayer networks can stabilize controllability even when individual layers cannot.

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Area of Science:

  • Network Science
  • Theoretical Physics
  • Systems Biology
  • Financial Mathematics

Background:

  • Network controllability is crucial in diverse fields like finance and neuroscience.
  • Previous research focused on single, isolated networks, neglecting the prevalence of multilayer systems.
  • Complex systems are predominantly structured as interconnected, multilayer networks.

Purpose of the Study:

  • To develop a theoretical framework for the linear controllability of multilayer networks.
  • To investigate how signal correlation across layers impacts network robustness and controllability.
  • To explore the stabilizing effect of multilayer structures on network controllability.

Main Methods:

  • Developed a theoretical framework by mapping multilayer network controllability to a combinatorial matching problem.
  • Analyzed the effects of correlating external signals across different network layers.
  • Investigated phase transitions in interacting Poisson networks to understand robustness changes.

Main Results:

  • Correlating external signals across layers significantly reduces multilayer network robustness to node removal.
  • Observed a hybrid phase transition in interacting Poisson networks linked to reduced robustness.
  • Multilayer networks can stabilize fully controllable configurations, even if individual layers are not stable.

Conclusions:

  • The proposed framework provides new insights into the controllability of complex multilayer systems.
  • Signal correlation is a critical factor influencing the robustness and stability of multilayer networks.
  • Multilayer architectures offer a mechanism to enhance overall network controllability and stability.