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Controlling Chaotic Resonance using External Feedback Signals in Neural Systems.

Sou Nobukawa1, Natsusaku Shibata2

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Chaotic resonance, a phenomenon enhancing signal response with chaos, was induced in a neural system. This study demonstrates its potential for signal processing applications, unlike prior stochastic resonance applications.

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Area of Science:

  • Non-linear dynamics
  • Computational neuroscience
  • Signal processing

Background:

  • Stochastic resonance enhances signal response using noise, with proposed applications in tactile sensitivity.
  • Chaotic resonance, induced by deterministic chaos, offers higher sensitivity but lacks reported applications due to parameter adjustment difficulties, especially in biological systems.

Purpose of the Study:

  • To induce chaotic resonance in a neural system using a novel method.
  • To investigate the frequency dependency of chaotic resonance with weak input signals.
  • To explore the dual effects of external noise (diminishing and enhancing) on chaotic resonance.

Main Methods:

  • Application of the reduced region of orbit method.
  • Modeling a neural system composed of excitatory and inhibitory neurons.
  • Analysis of signal response under weak input signals and external noise.

Main Results:

  • Successful induction of chaotic resonance in the neural system.
  • Demonstration of signal frequency dependency in chaotic resonance.
  • Observation of both diminishing and enhancing effects of external noise on signal response.

Conclusions:

  • The study successfully induced chaotic resonance in a neural system, overcoming previous application barriers.
  • The findings highlight the potential of chaotic resonance for signal processing, offering tunable responses.
  • This research may pave the way for developing novel devices that leverage chaotic resonance mechanisms.