Adaptive brain pacemaker may reduce Parkinson’s symptoms

This method, known as adaptive deep brain stimulation (aDBS), improves on traditional deep brain stimulation (DBS) that has been used for years to treat PD and other neurological disorders. The study revealed that aDBS provides better control of PD symptoms compared to conventional deep brain stimulation (DBS).

DBS involves placing small electrodes in specific areas of the brain to send electrical signals that reduce symptoms of disorders like PD. Traditional DBS provides constant stimulation, which can sometimes cause side effects because the brain doesn’t always need the same amount of stimulation. In contrast, aDBS uses real-time feedback from the brain, coupled with machine learning algorithms, to dynamically adjust the intensity of stimulation in response to the patient’s changing needs.

In the study, four participants who were already receiving conventional DBS were asked to identify their most troublesome symptom, which typically involved involuntary movements or difficulty initiating movement. The aDBS system was then set up to target these specific symptoms. After several months of algorithm training, the participants were sent home, where the effectiveness of aDBS was compared to their existing treatment. The study employed a crossover design, with participants alternating between aDBS and conventional DBS every two to seven days.

Results showed that aDBS improved the most bothersome symptoms by approximately 50% compared to conventional DBS. Interestingly, even though the participants were not informed about which treatment they were receiving at any given time, three out of the four were able to identify when they were using aDBS due to noticeable improvements in their symptoms.

This study builds on years of research led by Philip Starr, M.D., PhD, and his team at the University of California, San Francisco. In 2018, they introduced an early version of the aDBS system, which adjusted its operation based on feedback from brain activity – a system known as “closed-loop” DBS. Further developments in 2021 enabled the recording of brain activity during normal daily activities. The current study combines these advancements, utilising brain activity data recorded during daily life to inform the operation of the aDBS system. However, they found that DBS itself changes brain activity so much that the expected signal was hard to detect. So, they used a data-driven approach to find a new signal in the brains of people with PD who were receiving DBS.

Parkinson’s disease is often treated with the drug levodopa, which compensates for dopamine loss in the brain. However, the drug's effectiveness fluctuates, peaking shortly after administration and gradually diminishing as it is metabolised. aDBS could help smooth out these fluctuations by increasing stimulation when drug levels are high and reducing it when they’re low, making it a good option for people who need high doses of levodopa.

Although these findings are promising, there are still challenges to making aDBS more widely available. The initial setup of the device demands extensive input from specialised clinicians. But researchers hope that, in the future, the device could manage itself more, reducing the need for frequent clinic visits to adjust settings. This kind of automation is important for more people to be able to use aDBS in a clinical setting.

Addressing the challenges of accessibility and training for DBS is important because the therapy requires specialised expertise that is not widely available. Automating aDBS could make this treatment easier to access for more patients.