Brain signals that anticipate the Alzheimer’s before

They identify a biomarker from electrical signals of the brain that could be used to predict whether mild cognitive deterioration will become Alzheimer’s disease. They have done it researchers from the Carney Institute for the Science of the brain of the Brown University (United States) have identified

“We have detected a pattern in the electrical signals of the brain activity that predicts which patients are more likely to develop the disease within a period of two and a half years,” said the professor of neuroscience Stephanie Jones in the center that has led this discovery.

According to ‘Imaging Neuroscience’, the research team, in which the Complutense University of Madrid (UCM)analyzed recordings of the brain activity of 85 patients diagnosed with mild cognitive impairment and monitored the evolution of the disease during the following years.

To record the recordings, they used a non -invasive technique called Magnetoenphaography (MEG) while patients were at rest with closed eyes. Most of the methods to study MEG recordings compress and averaged the detected activity, which hinders their interpretation at the neuronal level, but Brown researchers promoted a computational tool called ‘Spectral Events Toolbox’, which reveals neuronal activity as discreet events, showing exactly when and how often they occur, their duration and intensity.

Using this tool in which the equipment is a pioneer, they analyzed the brain activity events in Patients with mild cognitive impairment That are produced in the Beta frequency band, a frequency involved in the processing of memory, which discovered clear differences in the beta events of the participants who developed Alzheimer’s within a period of two and a half years, compared to those who did not.

“Two and a half years before Alzheimer’s diagnosis, patients had beta events with less frequently, shorter duration and less power,” as detailed the first author of the study, Danylyna Shpakivska.

From these findings, scientists are confident that the ‘Spectral Events Toolbox’ tool can be used to Diagnose Alzheimer’s disease before progress. “Once our finding is replicated, health professionals can use our tools for early diagnosis and also to check if their interventions are working,” said Jones.

Meanwhile, the team will go to a new research phase to study generation mechanisms through tools for Neuronal modeling Computerl. “If we manage to recreate the brain failure that generates that signal, we can collaborate to try therapies that could correct the problem,” the specialist concluded.