Circuit approach could improve deep brain stimulation for Parkinson’s disease

Guided by optogenetics and machine learning, Terésa A. Spix and colleagues have developed a method of deep brain stimulation (DBS) that focuses on specific neural circuits and produces long-lasting effects in a mouse model of Parkinson’s Disease. With more testing, their results could help improve DBS treatment of Parkinson’s, especially since their method can be delivered through commonly used DBS implants and at FDA-approved stimulus frequencies. DBS is sometimes used to treat Parkinson’s symptoms, but its effects diminish rapidly after the stimulation is turned off. DBS is also applied to a larger part of the brain than might be necessary during treatment, since it has been difficult to zero in on the specific neural circuits affected by the disease. In mouse models of Parkinson’s, Spix et al. used optogenetics to figure out how to stimulate two key neuron populations—inhibiting one group and exciting the other—simultaneously to produce long-lasting effects. They then used a machine learning method to determine the optimal type of electrical stimulation to these neural circuits. The resulting method of brief “bursts” of DBS in the mouse brain offered therapeutic effects that lasted on average 4.5-fold longer than those of conventional DBS, the researchers found. Carola Haas discusses their findings in a related Perspective.