In a large follow-up study, Swann said she hopes to combine scalp EEG measurements with detailed medical histories and self-reports of how patients are feeling on each day of testing. Eventually, it is hoped the approach could help detect changes in the disease in individuals over time.
Current treatment involves surgery to permanently implant an electric stimulator or a pharmacological approach in which dosage titration is difficult and often results in frustrating cycling of effectiveness, said study co-author Bradley Voytek, a neuroscientist at UC San Diego, in whose lab Cole, who has since earned his doctorate, had worked.
"If there were real-time measures of how effective treatments are at reducing the negative symptoms of Parkinson's disease, treatments could be adjusted in real-time," Voytek said. "In the case of an invasive brain stimulator, this might mean only applying electric stimulation when it's needed. In the case of pharmacology, it would mean adjusting a drug's dose much like continuous glucose monitoring done by an implant can signal a pump to adjust insulin levels as needed."
Ideally, Swann said, if the approach proves to provide robust information, EEG testing could be remotely done by Parkinson's patients wearing a hat fitted with electrodes. Results could be sent to their neurologists and used to quickly and easily adjust treatments.
A challenge, Voytek said, is that real-time measures of brain activity are often noisy and can cloud the ability to capture the correct signals.
"A lot of the tools we have for measuring them take a lot of processing power, so they can't easily be applied in real-time," he said.
The study's first author was Nick Jackson, a lab technician in Swann's UO lab who is now pursuing a doctoral degree at the University of Texas at Austin.
This work was supported by grants from the National Science Foundation, Whitehall Foundation and Sloan Foundation to Cole and Voytek.
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