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Boston, MA – A groundbreaking study conducted by researchers at Mass General Brigham has revealed that brain wave activity during sleep can predict cognitive impairment years before symptoms appear. Using artificial intelligence (AI) to analyze electroencephalography (EEG) data, the study suggests that wearable EEG devices could become an early-warning system for dementia risk.
Published in the Journal of Alzheimer’s Disease, the research focused on a group of women aged 65 and older who were tracked over five years. The AI tool, developed by scientists at Massachusetts General Hospital and Harvard Medical School, identified subtle changes in brain wave patterns—particularly in gamma band frequencies during deep sleep—that were predictive of future cognitive decline.
Key Findings:
- The study examined sleep study data from 281 cognitively healthy women at the start of the research period.
- Five years later, 96 of these women had developed cognitive impairment.
- The AI model successfully identified 85% of individuals who later developed cognitive issues, achieving an overall accuracy rate of 77%.
The ability to detect cognitive decline years before symptoms emerge could revolutionize dementia prevention and treatment. “Using advanced AI and information theory tools, we can detect subtle changes in brain waves during sleep that indicate future cognitive impairment, creating an opportunity for early intervention,” said lead author Dr. Shahab Haghayegh of Massachusetts General Hospital.
The study relied on data originally collected for a separate trial on fracture risk in women. Participants underwent an overnight sleep study using EEG, followed by cognitive assessments both at the start of the study and five years later. Researchers applied AI-driven analysis techniques to identify brainwave patterns linked to cognitive impairment.
Despite the promising results, the authors acknowledge limitations, including the reliance on a single night of EEG data. However, senior author Dr. Kun Hu of Brigham and Women’s Hospital and Harvard Medical School noted that analyzing EEG data over multiple nights could yield even more accurate predictions.
Implications for Early Detection and Intervention The findings suggest that non-invasive EEG monitoring could be integrated into routine healthcare for early dementia detection. This is particularly significant given that new FDA-approved treatments for Alzheimer’s disease are most effective in the early stages of the condition.
Researchers are now exploring whether manipulating brain electrical activity during sleep could slow cognitive decline. “This research paves the way for a future where wearable EEG technology helps identify those at risk and allows for earlier medical and lifestyle interventions,” said Haghayegh.
Disclaimer:
This study is an early-stage investigation, and further research is needed to validate the findings across diverse populations, including men and individuals from different racial and ethnic backgrounds. The results should not be considered definitive for diagnosing or predicting dementia in clinical settings without further validation. Always consult a healthcare professional for personalized medical advice.
