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Magnitude-constrained optimal chaotic desynchronization of neural populations
Michael Zimet1, Faranak Rajabi2, Jeff Moehlis1,2
1Interdepartmental Graduate Program in Dynamical Neuroscience, University of California, Santa Barbara, Santa Barbara, CA, United States.
Frontiers in Network Physiology
|November 6, 2025
Summary
We developed optimal stimuli to desynchronize neuron populations, balancing Lyapunov exponent maximization with energy minimization. This approach is crucial for deep brain stimulation under current constraints.
Area of Science:
- Computational Neuroscience
- Biophysics
- Neural Engineering
Background:
- Neuronal populations exhibit synchronized activity, which can be associated with various neurological disorders.
- Deep brain stimulation (DBS) is a therapeutic intervention that modulates neuronal activity.
- Current limitations in DBS hardware and biological tolerance necessitate energy-efficient stimulation strategies.
Purpose of the Study:
- To derive magnitude-constrained optimal stimuli for neuronal desynchronization.
- To investigate the trade-off between desynchronization efficacy (Lyapunov exponent) and energy consumption.
- To provide a theoretical framework for designing effective DBS protocols under current constraints.
Main Methods:
- Calculating magnitude-constrained optimal stimuli by maximizing the Lyapunov exponent for neuronal phase differences.
- Minimizing energy expenditure during stimulation.
- Analyzing the impact of varying constraint magnitudes on stimulation outcomes using parameter sweeps.
- Validating the approach with a computational model of neuronal populations.
Main Results:
- Optimal stimuli were derived that effectively desynchronize neuronal populations while respecting magnitude constraints.
- A clear relationship was established between the constraint magnitude, Lyapunov exponent, and energy usage.
- The study demonstrated that increased constraints lead to a trade-off between desynchronization efficiency and energy cost.
- Event-triggered optimal inputs showed efficacy in a computational model.
Conclusions:
- Magnitude-constrained optimal stimuli offer a viable strategy for neuronal desynchronization in DBS.
- The findings provide valuable insights for optimizing DBS protocols considering energy and current limitations.
- This theoretical framework can guide the development of more targeted and efficient neuromodulation therapies.
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