New Research identifies brain Activity Pattern as Potential Early Alzheimer’s Marker
Researchers have identified a distinct pattern of brain activity that may serve as an early, noninvasive marker for Alzheimer’s disease progression. The findings,published in Imaging Neuroscience,represent a meaningful step towards earlier diagnosis and potential intervention strategies.
The study, a collaboration between Brown University and the complutense University of Madrid, analyzed magnetoencephalography (MEG) recordings from 85 patients with mild cognitive impairment. MEG is a technique that measures electrical activity in the brain without requiring invasive procedures, while patients rested with their eyes closed. Researchers monitored the participants over several years to track disease progression.
A key to the discovery was the Spectral Events Toolbox, a computational tool developed at Brown University. Unlike traditional MEG analysis methods that average brain activity, this toolbox reveals neuronal activity as individual events, detailing their timing, duration, and strength. The toolbox has gained widespread recognition within the scientific community, being cited in over 300 academic studies.Applying the Spectral Events Toolbox, the team focused on brain activity within the beta frequency band - a frequency known to be involved in memory processing and therefore relevant to Alzheimer’s disease. They found that individuals who afterward developed Alzheimer’s disease within two and a half years exhibited substantially different beta event patterns compared to those who did not.Specifically, these future Alzheimer’s patients displayed beta events that occurred at a lower rate, were shorter in duration, and had weaker intensity.
“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,” explained Danylyna Shpakivska, the Madrid-based first author of the study. Researchers believe this is the first time beta events have been linked to Alzheimer’s disease.
This brain activity-based biomarker offers a more direct assessment of neuronal response to the toxic effects of beta amyloid plaques and tau tangles – proteins associated with alzheimer’s – than existing methods like spinal fluid or blood tests.
According to researcher David Jones, the discovery holds promise for clinical submission. “The signal we’ve discovered can aid early detection,” she stated, adding that replication of the findings could lead to the use of the Spectral Events Toolbox for early diagnosis and monitoring the effectiveness of potential treatments.The research team, now funded by a Zimmerman Innovation Award in Brain Science, is moving into a new phase focused on understanding the underlying mechanisms generating these beta event patterns through computational neural modeling. The ultimate goal is to identify potential therapeutic interventions to correct the observed brain activity abnormalities.
The research was supported by the National Institutes of Health, including the BRAIN Initiative, and funding agencies in Spain.
