Bayesian adaptive dual control of deep brain stimulation in a computational model of Parkinson’s disease
Fig 8
Bayesian ADC optimizing stimulus phase trigger.
Example 1D optimization of stimulus phase trigger. The simulation was run for 25 iterations in which Bayesian optimization was used to select the stimulus phase trigger while holding stimulus amplitude and power threshold constant (2.37 mA, -28.6 dB). (top) Gaussian process built from observations. (bottom) Power as a function of iteration, and minimum value found. The color of each dot represents the iteration at which each parameter setting was visited during the simulation.