bioRxivAnimal Behavior & CognitionPreprint
Using a Homeogram to Detect Sleep in Free-living Animals
M. Gaidica, E. Studd, A. E. Wishart, W. Gonzalez, J. Lane, A. G. McAdam, S. Boutin, B. Dantzer
Abstract
O_LISleep is appreciated as a behavior critical to homeostasis, performance, and fitness. Yet, most of what we know about sleep comes from humans or controlled laboratory experiments. Assessing sleep in wild animals is challenging, as it is often hidden from view, and electrophysiological recordings that define sleep states are difficult to obtain. Accelerometers have offered great insight regarding gross movement, although ambiguous quiescent states like sleep have been largely ignored, limiting our understanding of this ubiquitous behavior. C_LIO_LIWe developed a broadly applicable sleep detection method called a homeogram that can be applied to accelerometer data collected from wild animals. We applied our methodology to detect sleep in free-ranging North American red squirrels (Tamiasciurus hudsonicus) in a region that experiences drastic seasonal shifts in light, temperature, and behavioral demands. C_LIO_LIOur method characterized sleep in a manner consistent with limited existing studies and expanded those observations to provide evidence that red squirrels apply unique sleep strategies to cope with changing environments. C_LIO_LIApplying our analytical strategy to accelerometer data from other species may open new possibilities to investigate sleep patterns for researchers studying wild animals. C_LI
- organism: mouse
- organism: rat
- organism: zebrafish
- assay: imaging
- assay: behavioral assay
- research focus: cell type annotation
- research focus: clustering
- research focus: trajectory inference
- research focus: differential expression
- approach: deep learning
- approach: statistical model
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