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Soft threshold stochastic resonance.

Priscilla E Greenwood1, Ursula U Müller, Lawrence M Ward

  • 1Department of Mathematics and Statistics, Arizona State University, Tempe, AZ 85287-1804, USA. pgreenw@math.asu.edu

Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics
|December 17, 2004
PubMed
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Soft thresholds in biological systems are key to neural function. This study shows Fisher information, not steepness, is crucial for stochastic resonance in neural networks, offering new insights into information processing.

Area of Science:

  • Computational Neuroscience
  • Information Theory
  • Biophysics

Background:

  • Soft thresholds are fundamental in biological systems, particularly in neuronal mechanisms and neural networks like sensory systems.
  • Understanding which soft threshold functions induce stochastic resonance is an ongoing research question.

Purpose of the Study:

  • To investigate the role of different information measures in characterizing stochastic resonance across soft thresholds.
  • To determine the critical properties of soft threshold functions that facilitate stochastic resonance.

Main Methods:

  • Analysis of information transmission across soft threshold functions using Fisher information and signal-to-noise ratio.
  • Examination of how signal characteristics influence information patterns as they traverse soft thresholds.

Related Experiment Videos

  • Evaluation of the impact of threshold function properties, such as noninvertibility and steepness, on stochastic resonance.

    • Main Results:

    • Fisher information is proposed as a suitable measure for information transmission across soft thresholds.
    • The pattern of information transmission can be similar when using Fisher information or signal-to-noise ratio for certain signals.
    • Noninvertibility of the threshold function is identified as a key factor for stochastic resonance, more so than its steepness.

    Conclusions:

    • The study highlights the importance of Fisher information in understanding information processing in systems with soft thresholds.
    • Noninvertibility of soft threshold functions plays a critical role in achieving stochastic resonance, providing a new perspective on neural information transmission.