SYSTEM FOR AUTOMATED NONINVASIVE MONITORING OF MOUSE SLEEP AND BEHAVIOR

描述（由申请人提供）：睡眠的基本功能尚不清楚。异常的睡眠模式可以表现为各种各样的障碍——睡眠呼吸暂停、睡眠异常、REM（快速眼动睡眠）行为障碍（RBD）、嗜睡症——其中许多都受遗传影响。在基因和药物研究中，越来越多的人关注小鼠行为的特征。然而，发现负责睡眠和相关疾病的基因需要耗时的大规模行为筛选，以将观察到的特征与遗传学联系起来。对小鼠的行为监测通常限于活动测量，如视频跟踪、滚轮运行和光电束破断。尽管这些方法大多是非侵入性的，具有高通量（HT）应用的潜力，但它们主要监测运动活动，而不能提供睡眠-觉醒状态和睡眠结构的信息，而这些信息对研究睡眠障碍很重要。目前哺乳动物睡眠分析的金标准是脑电图（EEG）和肌电图（EMG）。脑电图虽然可以准确判断睡眠-觉醒状态，但具有侵入性和资源密集型（手术、恢复等），限制了其大范围应用

DESCRIPTION (provided by applicant): 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. The current gold standard for sleep analysis in mammals is electroencephalography (EEG) with electromyography (EMG). 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 with rodents. EEG is therefore a critical barrier to the discovery of genes that promote sleep disorders. Signal Solutions, LLC, has developed a sensor cage environment for noninvasive, HT behavioral monitoring that is being used by many prominent research groups to identify genes responsible for different traits related to sleep and circadian rhythms. The system is based on analysis of the signal generated by a pressure- sensitive piezoelectric sensor attached to the cage floor, and can already discriminate sleep from wakefulness with high accuracy and track changes in respiratory effort when the animal is relatively inactive. The Sunderam Lab at the University of Kentucky has used Signal Solutions' "piezo" system to develop techniques and obtain preliminary data suggesting that pressure changes associated with respiratory effort may distinguish REM and non-REM (NREM) stages of sleep as verified by simultaneous EEG/EMG recordings. The specific aims of this application are to determine whether the piezo system can noninvasively: 1. Discriminate sleep-wake state (sleep/wake, REM/NREM) and behavior within wake (e.g., quiet vs. active, high activity, feeding, grooming) at a level comparable to EEG/EMG by classifying piezo signal features; 2. Identify outliers in a cohort and differentiate strains of mice with known sleep differences on the basis of specific sleep traits (percent time in each state, mean bout frequency and duration, sleep-onset REM); and 3. Develop the capability to apply and quantify responses to sensory stimulation for selective sleep restriction and startle reflex measurement. The purpose of this investigation is to integrate and test these additional capabilities in the piezo system. The envisioned end product is a sensor cage and software interface for high-throughput monitoring of sleep- wake state and behavior in small animals (e.g., KO mice, QTL analyses) 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. The current system for classifying sleep vs. wake is essentially as good as EEG/EMG; REM/NREM would be extremely valuable as a first pass screen. 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), and upgrades to existing users.