Published on: Aug 01, 2025
Using a custom-built tool to analyze neuron-level electrical activity, researchers at Brown University have identified a brain-based biomarker that may predict whether mild cognitive impairment (MCI) will progress to Alzheimer’s disease.
“We’ve detected a specific pattern in brain electrical signals that can indicate which patients are most likely to develop Alzheimer’s within two and a half years,” said Stephanie Jones, professor of neuroscience at Brown’s Carney Institute for Brain Science and co-lead of the study. “This is the first time we can noninvasively observe an early marker of Alzheimer’s progression directly in the brain, which is a very exciting step.”
The findings, published in Imaging Neuroscience, emerged from a collaboration with the Complutense University of Madrid. The team analyzed magnetoencephalography (MEG) recordings — a noninvasive method for measuring brain electrical activity — from 85 MCI patients, tracking their cognitive status over several years. During the recordings, participants rested quietly with their eyes closed.
Traditional MEG analysis compresses and averages brain activity, making it hard to interpret at the neuronal level. Jones and colleagues at Brown developed the Spectral Events Toolbox, a computational method that identifies neuronal activity as discrete events, revealing their timing, frequency, duration, and strength. Widely adopted and cited in over 300 academic papers, this tool allowed the researchers to focus on beta-frequency brain activity, which plays a role in memory processing and is linked to Alzheimer’s disease.
The analysis revealed that patients who went on to develop Alzheimer’s within 2.5 years showed beta events that were less frequent, shorter, and weaker than those who remained stable. “To our knowledge, this is the first time beta events have been examined in the context of Alzheimer’s disease,” said first author Danylyna Shpakivska from Madrid.
While spinal fluid and blood tests can detect amyloid plaques and tau tangles — hallmark proteins of Alzheimer’s — this brain-based biomarker offers a more direct measure of how neurons are affected. “By measuring neural activity changes directly, we gain valuable insight into how the brain responds to these toxic proteins,” said David Zhou, a postdoctoral researcher in Jones’ lab who will lead the next research phase.
Jones envisions that the Spectral Events Toolbox could help clinicians diagnose Alzheimer’s earlier and monitor treatment effectiveness. “The signal we’ve discovered could aid early detection,” she said. “Once replicated, clinicians could use this approach for diagnosis and to track whether interventions are working.
The next stage of research, supported by a Zimmerman Innovation Award in Brain Science from the Carney Institute, will explore the mechanisms behind these beta-event changes. “If we can model what’s going wrong in the brain to create this signal, we can work with collaborators to test therapies aimed at correcting it,” Jones said.
Source: https://www.brown.edu/news/2025-08-01/alzheimers-biomarker
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