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Area of Science:

  • Computational Neuroscience
  • Complex Systems

Background:

  • Neuronal networks exhibit complex dynamics influenced by delays.
  • FitzHugh-Nagumo models are crucial for simulating neuron behavior.

Purpose of the Study:

  • Investigate the locking phenomenon in ring-structured neuronal networks.
  • Analyze the impact of distance-dependent delays on network dynamics.
  • Characterize emergent spatiotemporal patterns.

Main Methods:

  • Utilized FitzHugh-Nagumo neuron models.
  • Simulated ring-structured networks with varying element time delays.
  • Analyzed interspike intervals and mean time lags.
  • Examined network size and coupling strength effects.

Main Results:

  • Observed distinct spatiotemporal patterns as time delay increased.
  • Identified patterns as lockings between spiking periods and distance-dependent delays.
  • Found network size has negligible impact; coupling strength critically affects pattern clarity and existence.
  • Demonstrated predictability of locking order for pattern emergence.

Conclusions:

  • Distance-dependent delays induce predictable locking phenomena in neuronal networks.
  • Coupling strength is a key parameter for controlling emergent network patterns.
  • The findings offer insights into the self-organization principles in neural systems.