Stochastic multiresonance in the coupled relaxation oscillators.

Area of Science:

• Computational neuroscience
• Nonlinear dynamics
• Physical chemistry

Background:

• Excitable systems, like those modeled by the FitzHugh-Nagumo equations, exhibit complex dynamics.
• Noise is often considered a disruptive factor in biological and physical systems.
• Understanding signal processing in coupled oscillatory networks is crucial for various scientific fields.

Purpose of the Study:

• To investigate noise-dependent dynamics in a chain of coupled excitable oscillators.
• To demonstrate frequency- and noise-selective signal acceptance.
• To elucidate the underlying mechanisms of noise-supported stochastic attractors.

Main Methods:

• Simulations of a chain of four stiff FitzHugh-Nagumo oscillators.
• Analysis of local coupling via inhibitor diffusion.
• Investigation of noise effects on system dynamics and signal acceptance.
• Characterization of noise-supported stochastic attractors and their properties.

Main Results:

• Demonstrated frequency- and noise-selective signal acceptance.
• Identified several noise-supported stochastic attractors with distinct average periods.
• Observed various phase relations between coupled excitable elements.
• Established a correspondence between stochastic attractors and resonance peaks in linear response curves.

Conclusions:

• Noise can facilitate selective signal processing in coupled excitable systems.
• Stochastic attractors arising from slow variable diffusion are key to this phenomenon.
• The findings explain resonance phenomena in terms of noise-supported dynamics.