Scientists have developed a innovative headband that has the ability to detect early signs of Alzheimer’s disease while the wearer is asleep. This device, which has been dubbed as a “Fitbit for the brain,” is equipped with small sensors that monitor brainwaves. By analyzing changes in the brain region responsible for memory reactivation, the headband can identify the presence of different proteins associated with Alzheimer’s disease. In a groundbreaking study, over 200 patients in their 70s wore the headband six nights a week for two years. The results of this study offer the potential for affordable wearable EEG devices that can monitor brain health, detect preclinical Alzheimer’s disease, and assess treatment response.
Alzheimer’s disease is a progressive neurodegenerative condition characterized by the accumulation of abnormal proteins that cause the death of nerve cells. This results in disrupted communication between brain cells and shrinkage of the brain. In the United States alone, more than 5 million people are affected by this disease, making it the sixth leading cause of death.
The headband was developed by scientists from the University of Colorado Anschutz Medical Campus and Washington University in St. Louis. They have found a way to evaluate brain activity during sleep, specifically targeting the early stages of Alzheimer’s disease that can occur long before symptoms of dementia manifest. Brice McConnell, the lead scientist of the study, referred to this device as a “digital biomarker” that can transform any simple EEG headband into a brain health fitness tracker. This advancement in catching and mitigating Alzheimer’s disease at its early stages is a significant breakthrough.
All participants in the study were either cognitively unimpaired or mildly cognitively impaired, with one participant being mildly impaired. The researchers hypothesized that the headband could identify potential biomarkers associated with memory reactivation during sleep. These biomarkers include theta bursts (TB) that improve depression, sleep spindles (SP) associated with non-rapid eye movement, and slow waves (SW) that represent the deepest level of sleep lasting up to 40 minutes in each cycle. The team believes that changes in the coupling of these events may indicate the early pathogenesis of Alzheimer’s disease.
Using the headband, the researchers mapped the coupling precision of SW-TB and SW-SP neural circuits to amyloid positivity, cognitive impairment, and cerebrospinal fluid biomarkers for Alzheimer’s disease. The collection of data revealed a correlation between cognitive impairment and lower TB concentrations in SW-TB coupling. Additionally, cognitively unimpaired individuals exhibited lower precision in SW-TB and SW-SP coupling. These abnormal protein levels, which were detected in brainwave patterns before the onset of symptoms, serve as early biomarkers for Alzheimer’s disease. Identifying these biomarkers in asymptomatic adults can help develop preventive or mitigating strategies to slow or halt the progression of the disease.
This research also signifies a significant step toward using wearable devices as digital biomarkers for disease detection. Brice McConnell expresses his enthusiasm for the future of monitoring brain health through affordable and user-friendly devices. The potential for turning brainwaves during sleep into a digital biomarker is just the beginning, and the next phase involves perfecting this process.
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