Scientists at Brown University have identified a subtle brain activity pattern that can forecast Alzheimer's disease in people with mild cognitive impairment up to two and a half years in advance. Using magnetoencephalography and a custom analysis tool, the researchers detected changes in neuronal electrical signals linked to memory processing. This noninvasive approach offers a potential new biomarker for early detection.
Researchers from Brown University, in collaboration with the Complutense University of Madrid, have uncovered a brain-based biomarker that signals the progression from mild cognitive impairment to Alzheimer's disease. The study, published in the journal Imaging Neuroscience in 2025, analyzed brain activity in 85 participants diagnosed with mild cognitive impairment, tracking their conditions over several years.
Brain activity was captured using magnetoencephalography (MEG), a noninvasive technique that records electrical signals from neurons while participants rested with eyes closed. To analyze the data precisely, the team employed the Spectral Events Toolbox, a computational method developed at Brown that identifies distinct events in brain signals, including their timing, frequency, duration, and strength. This tool avoids the blurring effect of traditional averaging methods and has been cited in over 300 studies.
Focusing on the beta frequency band (12–30 Hz), which is associated with memory processes, the researchers found significant differences. Participants who developed Alzheimer's within two and a half years exhibited beta events that occurred at a lower rate, lasted shorter durations, and had weaker power compared to those whose impairment remained stable.
"We've detected a pattern in electrical signals of brain activity that predicts which patients are most likely to develop the disease within two and a half years," said Stephanie Jones, a neuroscience professor at Brown's Carney Institute for Brain Science and co-leader of the research. The first author, Danylyna Shpakivska from Madrid, added, "Two and a half years prior to their Alzheimer's disease diagnosis, patients were producing beta events at a lower rate, shorter in duration and at a weaker power. To our knowledge, this is the first time scientists have looked at beta events in relation to Alzheimer's disease."
Unlike current biomarkers in spinal fluid or blood that detect amyloid plaques and tau tangles, this method directly observes neuronal responses to brain damage. David Zhou, a postdoctoral researcher in Jones's lab, noted its potential for revealing how brain cells function under stress.
The findings could enable earlier diagnosis and treatment monitoring. Jones explained, "The signal we've discovered can aid early detection. Once our finding is replicated, clinicians could use our toolkit for early diagnosis and also to check whether their interventions are working."
Funded by the National Institutes of Health's BRAIN Initiative and Spanish agencies, the team now plans to model the signal's mechanisms and test therapeutics, supported by a Zimmerman Innovation Award from the Carney Institute.
