Catalyst Awardee

Project Description

Enhancing Sleep in Older Adults Using Auditory Stimulation: A Machine Learning Approach

Stephanie Buss, MD | Beth Israel Deaconess Medical Center, Harvard Medical School; Brandon Westover, MD, PhD; Wolfgang Ganglberger, PhD; Mouhsin Shafi, MD, PhD; Lorella Battelli, PhD
Competition Sponsor: National Academy of Medicine
Awardee Year: 2024

Older adults face a risk of cognitive decline which increases with each decade of life, and are at risk of Alzheimer’s disease and related dementias. New treatments are needed to maintain healthy cognition and delay onset of dementia during aging. Slow wave sleep declines with increasing age and is strongly linked with learning and memory. Prior studies using auditory stimulation during sleep to increase slow waves have shown promising yet inconsistent results. The optimal parameters for increasing slow wave sleep with auditory stimulation likely vary over the lifespan, between individuals, over time, and at different depths of sleep. This project will use machine learning to account for this variability and boost the effectiveness of auditory stimulation. Our study aims to enhance slow wave sleep in 15 older adults with normal cognition using auditory stimulation compared to Sham stimulation during separate daytime naps. We will use a novel closed-loop control algorithm, fine-tuned using machine learning, to personalize auditory stimulation parameters for each individual and adjust stimulation at different depths of sleep. We anticipate that this novel auditory stimulation technique will improve slow wave sleep in older adults, and that improvements in slow wave sleep will be linked to better performance on tests of memory and thinking. We expect the results of this study will set the stage for future clinical trials utilizing novel at-home auditory stimulation techniques to enhance slow wave sleep and promote healthy cognitive aging in older adults and patients at risk of Alzheimer’s dementia.

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