Optimizing charge-balanced pulse stimulation for desynchronization

Area of Science:

• Complex systems
• Nonlinear dynamics
• Statistical physics

Background:

• Collective synchronization is prevalent in natural and engineered systems, with applications in neuroscience.
• Controlling synchronization levels is crucial, necessitating effective techniques for both enhancement and suppression.

Purpose of the Study:

• To investigate pulsatile control strategies for modulating collective synchronization in large populations.
• To develop a theoretical framework for optimizing pulse profiles and stimulation phases to control synchrony levels.

Main Methods:

• Utilizing the noisy Kuramoto-Winfree model to analyze synchronization dynamics.
• Deriving an analytical expression for the change in phase distribution entropy due to pulsatile stimuli.
• Investigating the influence of individual unit properties (natural frequencies, phase response curves) and population state.

Main Results:

• A method was derived to quantify the impact of pulsatile control on the entropy of phase distribution, serving as a measure of synchrony.
• The study identified optimal pulse profiles and stimulation phases for either increasing or decreasing synchrony.
• Theoretical predictions were validated through numerical simulations on a two-frequency population model.

Conclusions:

• Pulsatile control offers a viable method for managing collective synchronization in complex systems.
• The derived theoretical framework provides a foundation for designing targeted control strategies in systems like neural networks.
• The findings highlight the importance of pulse characteristics and population properties in achieving desired synchronization outcomes.