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Related Experiment Videos

Coherence and stochastic resonance in a two-state system

Lindner1, Schimansky-Geier

  • 1Humboldt-University at Berlin, Invalidenstrasse 110, D-10115 Berlin, Germany.

Physical Review. E, Statistical Physics, Plasmas, Fluids, and Related Interdisciplinary Topics
|November 23, 2000
PubMed
Summary

This study analyzes a two-state system with noise and a harmonic signal, revealing resonance phenomena in bistable, excitable, and oscillatory behaviors for improved signal detection.

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Model Studies of Phytochrome Photochromism: Protein-Mediated Photoisomerization of a Linear Tetrapyrrole in the Absence of Covalent Bonding This work is part of the PhD thesis of I. Lindner, Max-Planck-Institut für Strahlenchemie, Mülheim an der Ruhr, and Gerhard-Mercator-Universität, Duisburg, 2000. We thank Tanja Berndsen, Gül Koç, and Helene Steffen for technical assistance.

Angewandte Chemie (International ed. in English)·2000

Area of Science:

  • Nonlinear dynamics
  • Statistical physics
  • Computational neuroscience

Background:

  • The study investigates a piecewise linear FitzHugh-Nagumo model, a simplified neural model.
  • The system exhibits bistable, excitable, or oscillatory behaviors depending on parameters.
  • Focus is on two-state dynamics under Gaussian white noise and a weak harmonic signal.

Purpose of the Study:

  • To characterize coherence resonance in bistable and excitable regimes.
  • To quantify non-adiabatic resonances with respect to an external signal.
  • To analyze output spectra and spectral power amplification for arbitrary noise and frequency.

Main Methods:

  • Analysis of a piecewise linear FitzHugh-Nagumo model with perfect time scale separation.
  • Calculation of output spectra and spectral power amplification.

Related Experiment Videos

  • Investigation of system dynamics driven by Gaussian white noise and a harmonic signal.

    • Main Results:

    • The system's behavior (bistable, excitable, oscillatory) is dependent on noise and signal parameters.
    • Coherence resonance is characterized in specific regimes.
    • Non-adiabatic resonances are quantified across all regimes.

    Conclusions:

    • The study provides a comprehensive analysis of resonance phenomena in a simplified neural model.
    • Understanding these resonances is crucial for signal processing in noisy biological systems.
    • The framework allows for arbitrary noise strengths and frequencies, offering broad applicability.