Deep brain stimulators for Parkinson’s and dystonia currently deliver a constant, unvarying electrical pulse—wasting battery life and causing unnecessary side effects. Researchers will record brain signals directly from the tip of the stimulation electrode to identify which patterns of neural activity are causally linked to specific symptoms. They will then use those signals as biomarkers to create a “smart” stimulator that adjusts its output in real time, delivering stimulation only when and where it is needed. This matters because existing therapy forces patients to undergo repeated surgery to replace depleted batteries, and the fixed stimulation can worsen side effects without improving symptom control. The team will also test whether stimulation patterns tailored to each individual patient work better than the current one-size-fits-all approach. If successful, smart stimulation could extend battery life, reduce side effects, and improve symptom control for people with Parkinson’s and dystonia. The same biomarker-driven approach might later be adapted for other neurological disorders that do not respond well to drugs.
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Parkinson?s disease and dystonia are two of the most common neurological disorders of movement. Recently there has been immense interest in the neurosurgical treatment of these disabling disorders through electrical deep brain stimulation. However, the cost of deep brain stimulation, its partial usefulness and its side-effects mean that there is still a pressing need to improve current therapy. One major problem is that existing brain stimulators only provide continuous and fixed stimulation which increases side effects, while reducing battery life. As a result batteries have to be surgically replaced at periodic intervals. Our growing understanding of how different patterns of brain activity are associated with different symptoms raises the possibility of improving therapy using ?smart? stimulation. Smart stimulators modify their electrical output according to the level of a particularly informative brain signal known as a biomarker. In this way the smart stimulator can determine when and how much stimulation is necessary, thereby improving the clinical result and extending battery life. In this research program we will study the brain signals that can be recorded from the tip of deep brain electrodes so as to clarify their nature and determine which may provide biomarkers suitable for smart stimulation in Parkinson?s disease and dystonia. In particular, we will establish which biomarkers are causally linked to symptoms. The latter is a crucial step in both understanding disease processes and in identifying the best biomarkers for smart stimulation. In addition, we will define how deep brain stimulation interacts with each patient?s own brain signals. This will help us identify the most effective stimulation pattern in individual patients, rather than use the same pattern for all patients regardless of their particular symptoms. Finally, we will develop and test smart stimulation, comparing it to existing stimulation therapy. The understanding gained in this research program will lay the foundation for improved therapies involving brain stimulation in disorders of movement, and in other neurological disorders which can be resistant to available drug treatments.
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