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.
“This elegantly simple test allows us to glimpse into the brain as it is working,” Apostolos P. Georgopoulos, M.D., Ph.D., professor of neuroscience, neurology, and psychiatry at the University of Minnesota said. “We were able to classify, with 100 percent accuracy, the various disease groups represented in the group of research subjects.”
Currently, brain-related diseases are diagnosed with a combination of behavioural exams, psychiatric interviews, and neuropsychological testing, all which take time and can be hard on the patient, Georgopoulos said. All behaviour 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 these interactions in the brain. The measurements they recorded 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.
COMPAMED.de; Source: University of Minnesota