Bayesian adaptive dual control of deep brain stimulation in a computational model of Parkinson’s disease
Fig 4
Adaptive dual controller (ADC) for DBS.
The ADC has dual goals (exploitation and exploration), and is composed of two loops: an inner parameterized stimulator and an outer parameter adjustment loop. The inner loop may incorporate feedback from the patient to alter stimulation. The outer loop is composed of an estimator and a design block, and is given a specification. The estimator builds a model of the relationship between stimulation parameters and some measure of patient outcome, which it passes on to the design block. The design block then incorporates this information with the specification to select new parameters for the inner loop. The inner loop operates on a much shorter timescale than the outer loop.