  Deep brain stimulation(DBS)has become an effective intervention for advanced
Parkinson's disease, but the exact mechanism of DBS is still unclear. In this
review, we discuss the history of DBS, the anatomy and internal architecture of
the basal ganglia(BG), the abnormal pathological changes of the BG in
Parkinson's disease, and how computational models can help understand and
advance DBS. We also describe two types of models:mathematical theoretical
models and clinical predictive models. Mathematical theoretical models simulate
neurons or neural networks of BG to shed light on the mechanistic principle
underlying DBS, while clinical predictive models focus more on patients'
outcomes, helping to adapt treatment plans for each patient and advance novel
electrode designs. Finally, we provide insights and an outlook on future
technologies.
