The basic functions of sleep are still unknown. Abnormal sleep patterns can manifest as a variety of disorders- sleep apnea, parasomnias, REM (rapid eye movement sleep) behavioral disorder (RBD), narcolepsy-many of which are influenced by heredity. There is an increasing focus on characterizing mouse behaviors for genetic and drug studies. However, discovering the genes responsible for sleep and related disorders requires time- consuming large-scale behavioral screening of phenotypes to correlate observed traits with genetics. Behavioral monitoring of mice is usually limited to actigraphic measurements such as video tracking, wheel-running, and photoelectric beam-breaking. Although many of these methods are noninvasive and have potential for high- throughput (HT) application, they monitor mainly locomotor activity without providing information about sleep-wake state and sleep architecture, which are important for investigating sleep disorders. While EEG can be used to accurately determine sleep-wake state, it is invasive and resource-intensive (surgery, recovery, etc.), which limits its application in large-scale genetic studies wih rodents. Signal Solutions, LLC, has developed a sensor cage environment for noninvasive behavioral monitoring that is being used by prominent research groups to identify genes responsible for different traits related to sleep and circadian rhythms.
The specific aims of this work are to further improve the capabilities of the piezo system to noninvasively: 1. Discriminate sleep-wake state (sleep/wake, REM/NREM) and behavior within wake (e.g., quiet vs. active, high activity, feeding, grooming) to a level comparable to EEG/EMG by classifying piezo signal features with added low-cost video features; 2. Incorporate real-time feedback stimulation for behavior modification, 3. Integrate electronics and with new multimodal sensing into a compact system for testing in research laboratories, 4. Develop low-cost device for automatic animal welfare monitoring. The envisioned end product is a sensor cage and software interface for HT monitoring of sleep-wake state and behavior in small animals to identify genetic factors responsible for sleep/circadian disorders as well as behavioral effects of pharmacological manipulation, sensory stimulation, or neural injury (e.g., traumatic brain injury, epilepsy). This system will be particularly advantageous for prescreening potentially interesting phenotypes, and reserving invasive EEG analysis for further confirmation. Medical targets of interest are sleep/circadian disorders, sleep apnea, obesity/diabetes, REM/NREM sleep deprivation, and stress, among others. Potential clients include academic research labs as well as industrial labs interested in behavioral monitoring on a large scale (e.g., drug screening).
Discovery of genes that play a role in sleep and circadian rhythm disorders requires extensive screening of behavior, usually in mice, preferably with invasive and resource-intensive brain signal (EEG) recordings to score sleep stage (REM, NREM) and wake behavior. The goal of this research is to develop and validate a methodology for using a noninvasive, pressure-sensitive piezoelectric ('piezo') sensor platform to distinguish different stages of sleep and behavior without the need for EEG making large-scale behavioral screening feasible and limit the need for EEG verification to only the most interesting phenotypes thus identified.
| Yaghouby, Farid; Donohue, Kevin D; O'Hara, Bruce F et al. (2016) Noninvasive dissection of mouse sleep using a piezoelectric motion sensor. J Neurosci Methods 259:90-100 |
| Yaghouby, Farid; Sunderam, Sridhar (2016) SegWay: A simple framework for unsupervised sleep segmentation in experimental EEG recordings. MethodsX 3:144-55 |
| Yaghouby, Farid; Sunderam, Sridhar (2015) Quasi-supervised scoring of human sleep in polysomnograms using augmented input variables. Comput Biol Med 59:54-63 |
| Yaghouby, Farid; Schildt, Christopher J; Donohue, Kevin D et al. (2014) Validation of a closed-loop sensory stimulation technique for selective sleep restriction in mice. Conf Proc IEEE Eng Med Biol Soc 2014:3771-4 |
