Our lab is interested in understanding sleep. With sleep deprivation, there are a number of deleterious health consequences that individuals can feel, such as sleepiness and brain fog, and those to which we are blind, such as higher rates of Type II diabetes and cardiovascular problems. Individuals have different sleep needs. To understand sleep and the consequences of sleep deprivation, our lab uses two different systems:
Biomarkers of sleepiness in humans: We have developed a novel algorithm, the Wasserstein Algorithm for Classifying Sleep And Wakefulness (WACSAW), that converts activity data into sleep and wakefulness data. We can use this approach to understand sleep outside of the lab in a natural setting. Even under routine conditions, individuals still experience sleep loss. These nights of inadequate sleep can lead to performance decrements and errors. We are interested in developing biomarkers that can help identify cognitive and health impacts of sleep loss.
To that end, we are using WACSAW, and the metrics it provides, to understand the sleep patterns that lead to decreased cognitive performance and health.
Supported by the Department of Defense.
Molecular consequences of sleep loss: We have modeled sleep and wakefulness transitions in the model organism, Drosophila melanogaster. We are able to bin flies into predicted short- and long-lived flies based on their sleep patterns. We can then evaluate molecular changes that are associated with the differences in sleep that related to differences in sleep.
Supported by National Institute of General Medical Sciences.