“This elegantly simple test allows us to glimpse into the brain as it is working,” Apostolos P. Georgopoulos said. “We were able to classify, with 100 percent accuracy, the various disease groups represented in the group of research subjects.”
Researchers from the University of Minnesota Medical School and Brain Sciences Center at the Minneapolis VA Medical Center have identified a way to diagnose Alzheimer’s and other brain diseases. Using magnetoencephalography (MEG) and various mathematic algorithms, the researchers were able to identify and classify the brain disease in 142 research subjects that had been previously diagnosed. Magnetoencephalography is a non-invasive measurement of magnetic fields in the brain and the tests last between 45-60 seconds.
This study should be of particular interest to anyone that is genetically predisposed to Alzherimer’s and other forms of Dementia.
Currently, brain diseases are diagnosed with behavioral exams, psychiatric interviews, and neuropsychological testing.
U of M Researchers Discover Noninvasive Diagnostic Tool for Brain Diseases
Researchers from the University of Minnesota Medical School and Brain Sciences Center at the Minneapolis VA Medical Center have identified a noninvasive and painless way to diagnose complex brain diseases. And it’s as simple as staring at a point of light.
The research offers promise for a less-stressful, painless, and objective diagnosis for brain diseases, as well as a way to measure the effectiveness of different treatments for these diseases.
Using magnetoencephalography (MEG) to record tiny magnetic fields in the brain, the researchers recorded brain cells communicating with each other while research subjects stared at a point of light.
After applying various mathematic algorithms, the researchers were able to classify the 142 research subjects by diagnosis. Study participants fell into one of six categories, including people with Alzheimer’s disease, chronic alcoholism, schizophrenia, multiple sclerosis or Sjogren’s syndrome, as well as healthy controls.
The research, led by Apostolos P. Georgopoulos, M.D., Ph.D., professor of neuroscience, neurology, and psychiatry, will be published in the Aug. 27, 2007 issue of the Journal of Neural Engineering.
“This elegantly simple test allows us to glimpse into the brain as it is working,” Georgopoulos said. “We were able to classify, with 100 percent accuracy, the various disease groups represented in the group of research subjects.”
There are no good tests that measure the brain as it functions. Several tests exist to assess brain structure, but they reveal little of how the brain interacts. Currently, brain-related diseases are diagnosed with a combination of behavioral exams, psychiatric interviews, and neuropsychological testing, all which take time and can be hard on the patient, Georgopoulos said.
“This discovery gives scientists and physicians another tool to assess people’s disease progression,” he said. “In the future it could be applied when studying the effect of new treatments or drug therapies.”
All behavior and cognition in the brain involves networks of nerves continuously interacting-these interactions occur on a millisecond by millisecond basis. The MEG has 248 sensors that record the interactions in the brain on a millisecond by millisecond basis, much faster than current methods of evaluation such as the functional magnetic resonance imaging (fMRI), which takes seconds to record. The measurements the MEG records represent the workings of tens of thousands of brain cells.
Georgopoulos and his team were inspired to try to use the MEG as a diagnostic tool after discovering that neural interactions across human subjects were very similar. The team published on this novel way to assess the dynamic interactions of brain networks acting in synchrony in a 2006 issue of the Proceedings of the National Academy of Sciences.
Now the team will continue to collect more data on the six disease groups, as well as begin to analyze research subjects with other brain diseases, including depression, post-traumatic stress disorder, autism, and Parkinson’s disease, to see if the same technique can be applied.
The research is supported by the Department of Veterans Affairs, American Legion Brain Sciences Chair and grants from the following sources: Academic Health Center, University of Minnesota; Minnesota Medical Foundation; University of Minnesota Graduate School; Department of Veterans Affairs Clinical Science Research Division; National Institute of Mental Health; and the National Institutes of Health.
Editor’s note: Georgopoulos and the University of Minnesota have a financial interest in the technology described in the journal article.