Artificial Intelligence: AI May Improve Brain Stimulation Devices, E.g. For Parkinson’s
The Mayo Clinic and Google Research Brain Team have developed a new AI Algorithm to better direct brain stimulation.
Patients suffering a movement disorder like Parkinson’s disease, in many cases, opt for deep brain stimulation (DBS) to improve their motor reflexes and reduce medicines intake. DBS involves implanting electrodes within certain areas of the brain to regulate abnormal impulses. An AI algorithm developed by the Mayo Clinic and the Google Research Brain Team can help to potentially better direct DBS. (Parkinson’s News Today)
“Our findings show that this new type of algorithm may help us understand which brain regions directly interact with one another, which in turn may help guide placement of electrodes for stimulating devices to treat network brain diseases,” Kai Miller, MD, PhD, a neurosurgeon at Mayo Clinic and the first author of the study, said in a statement.
Effective placement of electrodes
According to Klaus-Robert Mueller, PhD, member of the Google Research Brain Team and study co-author, neurological data is extremely challenging to model and interpret. To resolve this, the researchers at Mayo and Google created a new type of AI algorithm called “basis profile curve identification.”
They placed an array of electrodes in a patient with a brain tumor to collect data on brain seizures and the functioning of the brain prior to surgery for removal of the tumor. The algorithm was fed the thousands of readings from these electrodes.
“Each of these readings allows the creation of basis profile curves — sets of characteristic responses — that can be mapped back to the brain anatomy, helping to quantify the projection strength of each stimulated site,” the researchers said.
The AI then generated a more straightforward interpretation of the data from the patient’s brain. In future, this could help neurologists place their electrodes more strategically for maximum stimulation benefit for a Parkinson’s patient.
The results were published in the study, “Basis profile curve identification to understand electrical stimulation effects in human brain networks,” in PLOS Computational Biology.
Patients suffering epilepsy, and psychiatric illnesses like obsessive compulsive disorder and depression may also benefit from the new AI technology.
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