课题基金 / 基金详情

SYSTEM FOR AUTOMATED NONINVASIVE MONITORING OF MOUSE SLEEP AND BEHAVIOR

SYSTEM FOR AUTOMATED NONINVASIVE MONITORING OF MOUSE SLEEP AND BEHAVIOR
自动无创监测小鼠睡眠和行为的系统
批准号:
9112029
负责人:
Michael E Lhamon
金额:
$49.15万
依托单位:
依托单位国家:
美国
项目类别:
财政年份:
2013
资助国家:
美国
项目状态:
已结题
起止时间:
2013-04-01 至 2018-04-30
关键词:
AffectAlgorithmsAmplifiersAnimal ExperimentationAnimal HousingAnimal WelfareAnimalsBehaviorBehavior DisordersBehavior TherapyBehavior monitoringBehavioralBehavioral AssayBehavioral GeneticsBehavioral ResearchBrainCircadian Rhythm Sleep DisordersCircadian RhythmsClientCodeComputer InterfaceComputer softwareDataDecision TreesDevelopmentDevicesDiabetes MellitusDiscriminationDiseaseElectroencephalographyElectronicsEnvironmentEpilepsyEvaluationEventFeedbackFilmFloorGenesGeneticGenetic ScreeningGenetic studyGoalsGovernmentGrantGroomingHealthHeredityHome environmentImplantInterventionKentuckyKnockout MiceLabelLaboratory ResearchLettersMeasurementMedicalMethodologyMethodsModificationMonitorMotor ActivityMusNarcolepsyNoiseObesityOperative Surgical ProceduresOutcomePatternPersonsPharmaceutical PreparationsPhasePhenotypePhysiologic pulsePlayPolysomnographyPower SourcesPreclinical Drug EvaluationQuantitative Trait LociREM SleepREM Sleep ParasomniasRecoveryResearchResourcesRodentRoleRunningSensorySignal TransductionSleepSleep Apnea SyndromesSleep ArchitectureSleep DeprivationSleep DisordersSleep StagesStressStructureSystemSystems IntegrationTechniquesTestingTimeTraumatic Brain InjuryUniversitiesWakefulnessWorkactigraphyawakebasebrain researchcommercializationcostfeedingfield studyflexibilityfootgene discoveryhigh throughput analysisimprovedinterestmeetingsnerve injurynervous system disordernovelpressureprototyperespiratoryresponsescreeningsensorsignal processingsomatosensorysuccesstooltraittrend

项目摘要

项目成果

Michael E Lhamon的其他基金

相似基金

相关文献

中文摘要
翻译
 描述(由申请人提供):睡眠的基本功能仍然未知。异常的睡眠模式可以表现为多种疾病-睡眠呼吸暂停、异态睡眠、REM(快速眼动睡眠)行为障碍(RBD)、发作性睡病-其中许多受遗传影响。有越来越多的关注表征遗传和药物研究的小鼠行为。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表型,以将观察到的性状与遗传学相关联。小鼠的行为监测通常仅限于活动记录测量,如视频跟踪、轮跑和光电光束中断。尽管这些方法中的许多是非侵入性的并且具有高通量(HT)应用的潜力,但是它们主要监测运动活动,而不提供关于睡眠-觉醒状态和睡眠结构的信息,这对于研究睡眠障碍是重要的。虽然EEG可用于准确地确定睡眠-觉醒状态,但它是侵入性的和资源密集型的(手术、恢复等),这限制了其在啮齿动物的大规模遗传研究中的应用。Signal Solutions,LLC开发了一种用于非侵入性行为监测的传感器笼环境,该环境正被著名的研究小组用于识别负责与睡眠和昼夜节律相关的不同特征的基因。这项工作的具体目标是进一步提高压电系统的能力,以非侵入性:1。区分睡眠-觉醒状态(睡眠/觉醒,REM/NREM)和觉醒内的行为(例如,安静与活跃、高活动、进食、梳理)通过对具有添加的低成本视频特征的压电信号特征进行分类而达到与EEG/EMG相当的水平; 2.结合实时反馈刺激行为修正,3。将电子设备和新的多模态传感集成到一个紧凑的系统中,用于研究实验室的测试,4.开发低成本的动物福利自动监测设备。设想的最终产品是用于HT监测小动物的睡眠-觉醒状态和行为的传感器笼和软件接口,以识别导致睡眠/昼夜节律紊乱的遗传因素以及药理学操纵、感觉刺激或神经损伤(例如,创伤性脑损伤、癫痫)。该系统将特别有利于预筛选潜在的感兴趣的表型,并保留侵入性EEG分析进一步确认。感兴趣的医学目标是睡眠/昼夜节律紊乱、睡眠呼吸暂停、肥胖/糖尿病、REM/NREM睡眠剥夺和压力等。潜在客户包括学术研究实验室以及对大规模行为监测感兴趣的工业实验室(例如,药物筛选)。
英文摘要
 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. 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).
期刊论文(0)
专著(0)
科研奖励(0)
会议论文
SYSTEM FOR AUTOMATED NONINVASIVE MONITORING OF MOUSE SLEEP AND BEHAVIOR
  • 批准号:
    8981814
  • 项目类别:
  • 资助金额:
    $50.32万
  • 财政年份:
    2013
  • 负责人:
    Michael E Lhamon
  • 依托单位:
海外基金