A Large-Scale, Quantitative EEG Analysis of Chronic Insomnia

Explore a comprehensive conference talk examining how large-scale quantitative EEG analysis reveals objective biomarkers for chronic insomnia using Julia programming. Discover findings from a post-hoc analysis across three EEG datasets involving thousands of individuals, revealing that those with insomnia demonstrate higher likelihood of waking from all sleep stages, increased wake-like brain activity measured through WESI (an aggregate data-driven arousal measure), elevated alpha and theta power during wake periods, and altered sleep spindle characteristics. Learn how treatment with dual orexin receptor antagonists (DORA) partially reverses these insomnia-linked EEG differences by reducing wake-to-wake transitions, increasing transitions into sleep stages, reducing wake-like brain activity measures, and modifying power spectral characteristics across different sleep stages. Understand the technical challenges and successes of performing large-scale neurophysiological analyses, including strategies for managing massive heterogeneous datasets at Beacon Biosignals. Gain insights into Julia's strengths as a platform for scalable data ingest, feature extraction, and model fitting in neuroscience applications, while also learning about ecosystem limitations and integration approaches with existing tools from other programming languages.