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Scientists Hacked an Old Brain-Zapping Treatment for Parkinson’s

Deep brain stimulation can be more efficient, and safer, by using the computer-generated pattern, the study showed.
Image: Val Altounian / Science Translational Medicine (2017)

Zapping the deepest corners of the brain with high frequency electrical pulses has been used to treat advanced Parkinson's disease for years. Scientists just figured out how to make it better.

Deep brain stimulation (DBS) is very effective at relieving some of the worst symptoms of the hard-to-treat disease, such as tremors, but there are some drawbacks to the treatment, including frequent surgeries to replace the device delivering the electric pulses. That's why researchers at Duke University recently used a computer model to hack deep brain stimulation, making it more efficient and safer, according to a study published in Science Translational Medicine this week.


DBS requires electrodes to be implanted in the brain through a small opening in the skull, and connected by an insulated wire to a small, battery-operated device called a neurostimulator. The neurostimulator looks a bit like a pacemaker and is implanted under the skin, usually near the collarbone, and controlled using a handheld remote. The neurostimulator delivers a constant stream of high-frequency pulses, typically 130- to 185-Hz. Early research found that lower frequency pulses weren't effective (and could even make symptoms worse), and randomly alternating pulses also had no effect.

But constantly barraging the brain with high-frequency pulses has side effects, including headaches and confusion. It also quickly drains the DBS device's battery—individuals using DBS need to have their batteries changed every two to five years, and swapping out batteries requires surgery, which comes with a risk of infection.

A team of researchers at Duke Medical led by David Brocker have come up with a possible improvement to DBS: alternating the frequency of the electrical pulses, not in a random way, but using a pattern generated by an advanced computer model. They created the model to calculate a pattern that would reduce the average frequency and use less energy, without losing the overall effect.

Brocker and his team then tested that pattern in devices implanted in mice with Parkinson's and in eight patients with Parkinson's, with promising results. The patients were tasked with performing a finger-tapping exercise to measure their symptoms, and the computer-generated pattern of electrical pulses was just as effective as the standard, constant-blast approach.

And it did so while using less energy: the researchers estimated patients would get an additional 3.9 years of battery life using the computer's pattern versus the typical, constant stream approach. They also suggested the model could be used to customize patterns to target specific symptoms in individuals, giving each patient their own personal pattern that suits their brain best.

It's an exciting example of how combining different disciplines can solve some of the trickiest problems when treating complex diseases like Parkinson's.