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Recurrence Resonance" in Three-Neuron Motifs.

Patrick Krauss1,2, Karin Prebeck2, Achim Schilling1,2

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Summary

Noise can enhance information flow in recurrent neural networks, a phenomenon termed Recurrence Resonance (RR). This finding suggests that neural noise may be a resource for optimizing brain information processing.

Keywords:
coherence resonanceentropymotifsmutual informationnoiserecurrent neural networksstochastic resonance

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Area of Science:

  • Computational Neuroscience
  • Non-linear Dynamics
  • Information Theory

Background:

  • Stochastic Resonance (SR) and Coherence Resonance (CR) are known non-linear phenomena where noise optimizes specific functions.
  • SR enhances weak signal detection, while CR improves the coherence of oscillations.
  • The role of noise in complex systems, particularly neural networks, remains an active area of research.

Purpose of the Study:

  • To investigate the effect of noise on information processing in recurrent neural networks.
  • To introduce and demonstrate a novel phenomenon, Recurrence Resonance (RR).
  • To explore how noise can potentially improve information flux within neural circuits.

Main Methods:

  • Theoretical analysis and simulation of three-neuron motifs with ternary connection strengths.
  • Introduction of controlled noise to neuron inputs.
  • Quantification of information flux using mutual information between successive network states.

Main Results:

  • Demonstrated that adding an optimal amount of noise maximizes mutual information in recurrent neural networks.
  • Identified this noise-optimized information processing as Recurrence Resonance (RR).
  • Showcased that RR is analogous to SR and CR but focuses on information flux.

Conclusions:

  • Noise is not merely detrimental but can be a crucial resource for neural computation.
  • Recurrence Resonance (RR) highlights a mechanism by which the brain may dynamically regulate noise to optimize information processing.
  • Findings suggest a paradigm shift in understanding neural noise from a hindrance to a functional component.