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Network structure and time delays shape synchronization patterns in brain network models.

Iain Pinder1, Martin R Nelson1, Jonathan J Crofts1

  • 1School of Science and Technology, Department of Physics and Mathematics, Nottingham Trent University, Nottingham NG11 8NS, United Kingdom.

Chaos (Woodbury, N.Y.)
|December 3, 2024
PubMed
Summary
This summary is machine-generated.

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This study explores how time delays and network structure impact brain region synchronization. Delays can regulate chaotic dynamics and suppress spreading, crucial for complex information processing.

Area of Science:

  • Computational Neuroscience
  • Systems Neuroscience
  • Network Science

Background:

  • Brain function relies on synchronized activity across regions.
  • Understanding information processing requires modeling communication delays and network topology.

Purpose of the Study:

  • Investigate synchronization and coherence in delayed Wilson-Cowan networks.
  • Analyze the impact of intra-nodal and inter-nodal delays on network dynamics.
  • Examine how network topology, coupling strength, and delays shape global brain dynamics.

Main Methods:

  • Simulated a network of delayed Wilson-Cowan nodes.
  • Incorporated distinct intra-nodal and inter-nodal delays.
  • Studied various network topologies, including Macaque monkey cortical structure.

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Main Results:

  • Identified parameter regions with transverse instabilities in synchronized states.
  • Observed diverse dynamics dependent on network architecture, coupling, and delays.
  • Cortical networks showed unique time-dependent behaviors like phase cluster dynamics, unlike simpler networks.

Conclusions:

  • Time delays and network topology significantly influence brain network dynamics.
  • Delays are crucial for orchestrating complex information processing and behavior.
  • Delays can regulate chaotic dynamics and potentially suppress pathological spreading.