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Related Experiment Video

Updated: Oct 29, 2025

Real-time Electrophysiology: Using Closed-loop Protocols to Probe Neuronal Dynamics and Beyond
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Transient dynamics and multistability in two electrically interacting FitzHugh-Nagumo neurons.

Luana Santana1, Rafael M da Silva2, Holokx A Albuquerque1

  • 1Departamento de Física, Universidade do Estado de Santa Catarina, 89219-710 Joinville, Santa Catarina, Brazil.

Chaos (Woodbury, N.Y.)
|July 9, 2021
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Summary

This study reveals self-organized periodic structures within chaotic dynamics in coupled FitzHugh-Nagumo neurons. It also demonstrates transient chaos and multistability, offering insights for complex neural network models.

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Area of Science:

  • Computational neuroscience
  • Nonlinear dynamics
  • Complex systems

Background:

  • The FitzHugh-Nagumo (FHN) model is a simplified representation of neuron dynamics, crucial for understanding neural network behavior.
  • Interactions between neurons can lead to complex dynamics, including chaos and multistability, which are challenging to analyze.
  • Understanding these dynamics is essential for modeling brain function and neurological disorders.

Purpose of the Study:

  • To investigate the parameter space of two electrically coupled FHN neurons for chaotic and regular dynamics.
  • To analyze the phenomenon of transient chaos and multistability in these coupled systems.
  • To explore the influence of coupling strength and asymmetry on neural dynamics.

Main Methods:

  • Extensive numerical simulations were employed to map the parameter space.
  • Analysis focused on identifying periodic and chaotic domains, transient chaos, and multistable regions.
  • Numerical experiments were conducted with varying coupling strengths and asymmetries between identical FHN neurons.

Main Results:

  • Self-organized periodic structures were found within chaotic regions of the parameter space.
  • Transient chaos was identified as a cause for extended chaotic behavior preceding periodic dynamics.
  • Multiple domains of multistability with numerous attractors were observed.
  • Chaos, transient chaos, and multistability were confirmed to persist even with varying coupling strengths.

Conclusions:

  • The findings demonstrate complex self-organization and diverse dynamical behaviors in coupled FHN neurons.
  • Transient chaos and multistability are significant phenomena in these neural models.
  • The results are applicable to more complex, high-dimensional neuron models, aiding experimental parameter setting.