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Generic two-variable model of excitability.

A C Ventura1, G B Mindlin, S Ponce Dawson

  • 1Departamento de Física, FCEN, UBA Ciudad Universitaria, Pabellón I (1428), Buenos Aires, Argentina.

Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics
|May 15, 2002
PubMed
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We developed a versatile model for excitable systems, capable of classifying different regimes. This model algorithmically fits experimental data, accurately determining the excitability class of various systems.

Area of Science:

  • Computational Neuroscience
  • Dynamical Systems Theory
  • Biophysics

Background:

  • Excitable systems exhibit threshold dynamics, crucial for phenomena like neuronal firing.
  • Characterizing diverse excitable regimes remains a challenge in nonlinear dynamics.
  • Existing models may not universally capture all classes of excitable behavior.

Purpose of the Study:

  • To introduce a unified, simple model for all classes of two-dimensional excitable regimes.
  • To demonstrate the model's capability in classifying system excitability.
  • To provide a method for algorithmic fitting to experimental and simulated data.

Main Methods:

  • Development of a novel, simple two-dimensional model.
  • Utilizing a

Related Experiment Videos

  • standard
  • vector field representation for broad applicability.
  • Algorithmic fitting of the model to spike data using membrane potential recordings and established models (FitzHugh-Nagumo, Eguía et al.).

    • Main Results:

    • The model successfully displays all classes of two-dimensional excitable regimes.
    • One model variable exhibits characteristic spikes, analogous to real-world excitable systems.
    • Successful algorithmic fitting and classification of excitability for leech neuron data, FitzHugh-Nagumo, and Eguía et al. models were achieved.

    Conclusions:

    • The presented model offers a unified framework for analyzing diverse excitable systems.
    • Its algorithmic fitting capability allows for robust classification of excitability from various data sources.
    • This work simplifies the quantitative analysis and comparison of different excitable phenomena.