Quantitative evaluation of 3D mouse behaviors in the open field using markerless
Quantitative evaluation of 3D mouse behaviors in the open field using markerless
批准号:
8318070
负责人:
D M Basso
金额:
$19.06万
依托单位:
依托单位国家:
美国
项目类别:
财政年份:
2011
资助国家:
美国
项目状态:
已结题
起止时间:
2011-08-15 至 2015-07-31
关键词:
Advanced DevelopmentAlgorithmsAmyotrophic Lateral SclerosisAnimal DiseasesAnimalsAreaBehaviorBehavioralCharacteristicsColorDataData AnalysesDevelopmentDiseaseEnvironmentEvaluationExperimental ModelsForelimbFosteringFunctional disorderGoalsHandHeightHindlimbHumanHuman ResourcesHuntington DiseaseLeadLegLengthLimb structureLocomotionMeasurementMeasuresMethodsMissionMotionMotorMovementMultiple SclerosisMusMuscleMusculoskeletal EquilibriumNeuromuscular DiseasesOutcomeParalysedParkinson DiseasePatternPerformancePhasePositioning AttributePublic HealthQuantitative EvaluationsRattusResearchResearch PersonnelRodentRodent ModelScientistSeveritiesSeverity of illnessSpeedSpinal cord injuryStrokeTechniquesTestingTextureTimeTreatment EffectivenessUnited States National Institutes of HealthVariantWeightbaseburden of illnessclinically relevantcomputerized data processingdisabilityfootinjuredinnovationkinematicsmeetingsmethod developmentmotor deficitmotor impairmentmusculoskeletal injurynerve injuryopen field behaviorreconstructionrelating to nervous systemtherapy development
中文摘要
描述(由申请人提供):数千名科学家致力于确定细胞机制,这些机制可以导致在开发用于使人衰弱的神经和肌肉疾病(如脊髓损伤、中风、帕金森病、亨廷顿病、ALS和多发性硬化症)的改善治疗方面取得突破。大多数研究使用啮齿动物模型来检验假设,这些研究都受到评估动物运动功能的方法的限制。为了继续在开发用于这些衰弱病症的治疗方面取得进展,迫切需要更灵敏、可重复和时间有效的方法来量化开放场地环境中的功能运动。该项目的目标是通过开发一种方法来满足这一关键需求,该方法可以自动量化和分类多个动物同时在开放领域中的总3D运动和步进运动学,而无需在动物上放置标记或需要手动数字化。最先进的3D体积重建技术将用于测量和分类未受伤和受伤小鼠的特征运动,解剖标志跟踪算法将量化步进协调。运动性能的开放领域评估允许同时分析和测试多种动物的各种行为,这将显著减少评估所需的时间。将通过对小鼠脊髓损伤(SCI)严重程度进行分类来开发和测试无标记测量和运动功能评估技术。这些动物表现出极具挑战性的运动功能障碍,范围从完全瘫痪到正常运动。对小鼠SCI有效的评估方法可能会推广到更大的啮齿动物,如大鼠和其他运动缺陷不太严重的疾病状态。为了使研究人员能够使用该方法,将最大限度地减少准确量化和分类旷场行为所需的相机数量、数据捕获率和试验长度。该提案将通过实现以下具体目标来开发、改进和优化这种用于评估运动功能的无标记方法:(1)使用体积测量中心自动识别开放场中的临床相关3D运动,其反映不同严重程度的运动损伤,并且可以同时测量多个动物。(2)将疾病的严重程度与开放场地中的前肢和后肢协调模式联系起来。这种方法是创新的,因为它将主要为人类开发的无标记运动跟踪算法应用于与鼠标运动功能相关的问题。这将使研究人员能够获得以前从未有过的动物运动的定量测量。这种方法可以在行为运动评估中产生显著和根本的变化,因为它将联合收割机结合当前最先进的运动功能评估的所有最强大的特征。其结果将是一种自动化的方法,产生准确,灵敏,可重复的测量开放领域的运动,用于定量评估电机性能。
英文摘要
DESCRIPTION (provided by applicant): Thousands of scientists strive to identify cellular mechanisms that can lead to breakthroughs in the development of ameliorative treatments for debilitating neural and muscular conditions such as spinal cord injury, stroke, Parkinson's disease, Huntingtons disease, ALS and Multiple Sclerosis. Most studies use rodent models to test hypotheses, and these studies are all limited by the methods available to evaluate animal motor function. To continue to make advancements in developing treatments for these debilitating conditions, there is a critical need for more sensitive, repeatable, and time efficient methods for quantifying functional movements in an open field environment. The goal of this project is to fill this critical need by developing a method to automatically quantify and classify gross 3D movements and stepping kinematics in the open field for multiple animals simultaneously, without placing markers on the animals or requiring hand digitization. State of the art 3D volumetric reconstruction techniques will be used to measure and classify characteristic movements of uninjured and injured mice, and anatomical landmark tracking algorithms will quantify stepping coordination. Open field evaluations of motor performance allow a wide variety of behaviors to be analyzed and testing of multiple animals simultaneously, which will significantly reduce the time needed for evaluation. The markerless measurement and motor function evaluation technique will be developed and tested by classifying spinal cord injury (SCI) severity in mice. These animals display extremely challenging motor dysfunction that ranges from complete paralysis to normal locomotion. Assessment methods which are effective for murine SCI would likely generalize to larger rodents like rats and to other disease states where motor deficits are less severe. To make the method accessible to researchers, the number of cameras, data capture rates and trial lengths needed to accurately quantify and classify open field behavior will be minimized. This proposal will develop, refine and optimize this markerless approach for evaluating motor function by accomplishing the following specific aims: (1) Automatically identify clinically relevant 3D movements in the open field which reflect motor impairments of different severities using center of volume measurements and can be measured for multiple animals simultaneously. (2) Relate disease severity to patterns of fore- and hindlimb coordination in the open field. This approach is innovative because it will apply markerless motion tracking algorithms, which have been primarily developed for humans, to questions related to mouse motor function. This will give researchers access to quantitative measures of animal motion that have never been possible before. This approach can produce significant and fundamental changes in behavioral movement assessments since it will combine all of the most powerful features of current state-of-the art motor function assessments. The result would be an automated method that produces accurate, sensitive, repeatable measurements of open-field movements for use in quantitative evaluations of motor performance.
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会议论文
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Behavioral and cellular determinants of treadmill training and recovery after SCI
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SPARING AND EXERCISE TRAINING PROMOTE RECOVERY IN SCI
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SPARING AND EXERCISE TRAINING PROMOTE RECOVERY IN SCI
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SPARING AND EXERCISE TRAINING PROMOTE RECOVERY IN SCI
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资助金额:$25.3万
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SPARING AND EXERCISE TRAINING PROMOTE RECOVERY IN SCI
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依托单位:
海外基金