New Brain Signal May Predict Alzheimer’s Progression Years Before Diagnosis

The research was led by scientists at the Carney Institute for Brain Science at Brown University, in collaboration with researchers from the Complutense University of Madrid.

Scientists at Brown University have identified a distinct pattern in brain electrical activity that may predict the progression of Alzheimer’s disease years before a formal diagnosis, according to findings published in Imaging Neuroscience.

The study shows that changes in neural signals can distinguish patients with mild cognitive impairment (MCI) who later develop Alzheimer’s disease from those whose condition remains stable.

The signal appears as early as two and a half years before an Alzheimer’s diagnosis, offering a potential new approach to tracking disease progression directly from brain activity.

The research was led by scientists at the Carney Institute for Brain Science at Brown University, in collaboration with researchers from the Complutense University of Madrid. The team analyzed brain activity data from 85 individuals diagnosed with MCI, following them over several years to observe clinical outcomes.

Brain activity was recorded using magnetoencephalography (MEG), a noninvasive technique that measures the electrical signals generated by neurons. Participants underwent MEG scans while resting with their eyes closed, allowing researchers to capture baseline neural activity.

To analyze the data, the team used a computational method known as the Spectral Events Toolbox, developed at Brown. Unlike conventional techniques that smooth and average neural signals, this approach breaks brain activity into discrete events, enabling precise measurement of when signals occur, how often they appear, how long they last, and how strong they are.

Using this method, researchers focused on beta-frequency brain activity, which is linked to memory and cognitive processing. The analysis revealed consistent differences in beta activity between patients who progressed to Alzheimer’s disease and those who did not. Patients who later developed Alzheimer’s produced beta events at a lower rate, with shorter duration and weaker signal strength, more than two years before diagnosis.

The findings suggest that brain-based electrical signals could serve as an early biomarker for Alzheimer’s progression, complementing existing blood and spinal fluid markers that detect amyloid and tau pathology. Researchers noted that neural activity biomarkers may provide a more direct measure of how neurons respond to underlying disease processes.

The team plans to further validate the findings and investigate the mechanisms behind the altered brain signals using computational modeling. Future research will explore whether the identified signal can be used to monitor treatment response or guide early intervention strategies.

The study was supported by funding from the U.S. National Institutes of Health, including the BRAIN Initiative, along with research agencies in Spain.

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