A data-driven algorithm finds the ‘sweet spot’ parameters that optimize outcomes in Parkinson’s disease


  • A novel data-driven model can suggest deep brain stimulation parameters leading to optimal motor improvement while minimizing side effects in people with Parkinson’s disease.

Why this matters?

  • Finding the optimal deep brain stimulation parameters for people with Parkinson’s disease is time consuming and requires highly trained medical personnel.

  • This study used a novel approach to predict outcome based on simulations of estimates of the electric field surrounding the electrodes. In the future, this approach could help to guide deep brain stimulation programming in clinical practice.