When a person has Parkinson’s disease, their brain sends out signals that cause tremors, stiffness, and trouble with movement.
Scientists around the world are trying to better understand what happens in the brain to cause these symptoms.
One powerful method they use is based on a treatment already common in hospitals: deep brain stimulation.
Deep brain stimulation involves placing tiny electrodes inside the brain. These electrodes send gentle electrical pulses to reduce symptoms.
But these electrodes can also record brain activity in areas that scientists normally can’t reach in living people. This gives researchers a rare look into how the brain functions in Parkinson’s disease and may help develop better treatments.
In a major European research effort, scientists from the Max Planck Institute worked closely with experts from hospitals in Berlin, Düsseldorf, London, and Oxford. They focused on brain waves called “beta waves,” which repeat about 20 times per second.
These waves have been linked to the severity of Parkinson’s movement problems. However, earlier studies from different labs had shown mixed results. The researchers wanted to know why.
To find the answer, they collected brain data from over 100 patients across the different hospitals—much more than most earlier studies had used. They also created a single method to analyze the data, rather than each hospital using its own system.
The result: beta waves were indeed linked to movement symptoms, but the effect was weaker than expected. Only when the team looked at data from a large group of patients did the connection become clear. This shows that small studies may not provide accurate results.
Another reason past studies may have missed the mark is how they analyzed brain signals. Many did not separate the clear, steady rhythms in the brain from the noisier, more chaotic signals.
This is important because the brain works like a concert hall—sometimes musicians (neurons) play together in rhythm, and sometimes they play randomly. If you only measure how loud the music is, you miss whether it’s rhythmic or just noise.
By using new methods to separate rhythmic and non-rhythmic signals, the team found that rhythmic beta waves matched up better with patients’ symptoms.
Even more exciting, the rhythmic signals came from the exact spot where deep brain stimulation was most effective. This could help doctors choose the best location to place the electrode in the future—automatically, instead of relying on guesswork.
The team also faced another challenge: patients were very different in age, disease severity, and symptoms. And since deep brain stimulation is only used in severe cases, they had no healthy people to compare with. So the scientists got creative.
Parkinson’s often affects one side of the body more than the other. This allowed them to compare brain activity on the more-affected side to the less-affected side in the same person. Each patient became their own control group.
They found that the more-affected side had more non-rhythmic, noisy brain activity. This could mean the neurons on that side are firing too much—a result seen before in animal studies.
This newly discovered signal could change how deep brain stimulation is used. Right now, the device sends out pulses all the time. But with this new information, it may be possible to make the device “smart”—only sending signals when abnormal brain activity is detected.
These so-called “adaptive” stimulators already exist, and future research will test how well they work using this new approach.
This breakthrough could lead to more accurate and effective treatment for Parkinson’s disease, helping patients move more freely and improving their quality of life.
If you care about Parkinson’s disease, please read studies These common drugs may increase risk of Parkinson’s disease and Researchers find an important cause of Parkinson’s disease.
If you care about Parkinson’s disease, please read studies This type of exercise may help reverse Parkinson’s disease and Supplements for Parkinson’s: Can they work?
The study is published in eBioMedicine.
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