New AI Algorithm Improves Brain Disease Treatment

A set of paradigms, or viewpoints, that simplifies comparisons between effects of electrical stimulation on the brain is developed by Mayo Clinic researchers to record complex brain signals. Electrical stimulation of the brain is used in the treatment of epilepsy and movement disorders such as Parkinson's disease. In the future, electrical stimulation may help people with psychiatric illness and direct brain injuries, such as stroke.

Brain networks can be explored by delivering brief pulses of electrical current in one area of a patient's brain while measuring voltage responses in other areas.

Research team collaborated with an international expert in artificial intelligence (AI) algorithms to develop a new type of algorithm called "basis profile curve identification”, that characterizes how assemblies of inputs converge in human brain regions did not exist in the scientific literature.

Every electrode interaction in a patient with a brain tumor resulted in hundreds to thousands of time points to be studied using the new algorithm. The study findings are published in PLOS Computational Biology.

"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," says Kai Miller, M.D., Ph.D., a Mayo Clinic neurosurgeon and first author of the study.

In the study, researchers also provided a downloadable code package so that others may explore the technique. Sharing this developed code is a core part of researcher’s efforts to help reproducibility of research.

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Source-Medindia