Abstract
The conserved nature of sleep in Drosophila has allowed the fruit fly to emerge in the last decade as a powerful model organism in which to study sleep. Recent sleep studies in Drosophila have focused on the discovery and characterization of hyposomnolent mutants. One common feature of these animals is a change in sleep architecture: sleep bout count tends to be greater, and sleep bout length lower, in hyposomnolent mutants. I propose a mathematical model, produced by least-squares nonlinear regression to fit the form Y = aX∧b, which can explain sleep behavior in the healthy animal as well as previously-reported changes in total sleep and sleep architecture in hyposomnolent mutants. This model, fit to sleep data, yields coefficient of determination R squared, which describes goodness of fit. R squared is lower, as compared to control, in hyposomnolent mutants insomniac and fumin. My findings raise the possibility that low R squared is a feature of all hyposomnolent mutants, not just insomniac and fumin. If this were the case, R squared could emerge as a novel means by which sleep researchers might assess sleep dysfunction.
Highlights
Sleep in Drosophila exhibits many characteristics that are seen in mammalian sleep, including extended periods of quiescence and increased arousal threshold (Cirelli & Bushey, 2008)
These findings suggest that increased cAMP activity may
Sleep behavior in control is normal quantitatively (Fig. 1) and qualitatively (Fig. 2). This indicates that my sleep system is in good working order
Summary
Sleep in Drosophila exhibits many characteristics that are seen in mammalian sleep, including extended periods of quiescence and increased arousal threshold (Cirelli & Bushey, 2008). Caffeine, which is a somnolytic agent in humans, reduces Drosophila sleep length in a dose-dependent fashion (Hendricks et al, 2000) These findings suggest that increased cAMP activity may. Sleep is poorly consolidated: bout length is reduced as compared to control (Koh et al, 2008; Stavropoulos & Young, 2011; Foltenyi, Greenspan & Newport, 2007; Pfeiffenberger & Allada, 2012; Ueno et al, 2012). These techniques could be used on higher animals, including humans
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