DIGITAL VIDEO ANALYSIS SYSTEM FOR HOME CAGE BEHAVIOR

用于家笼行为的数字视频分析系统

• 批准号: 2868124
• 负责人: YIQING LIANG
• 金额: $ 11.79万
• 依托单位: CLEVER SYSTEMS, INC.
• 依托单位国家: 美国
• 财政年份: 1999
• 资助国家: 美国
• 起止时间: 1999-07-01 至 2000-01-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/2868124
• 关键词: bioimaging /biomedical imaging; biomedical equipment development; computer data analysis; computer program /software; computer system design /evaluation; digital imaging; ethology; image processing; laboratory mouse; mathematics; video recording system; videotape /videodisc

The development of transgenic and knock-out mouse models of human disorders, particularly psychiatric disorders has led to the need for sensitive automated methods for detecting behavioral abnormalities in mice. We propose to develop novel mathematical and computer algorithms that will be able to automatically track mouse and identify mouse normal behaviors such as locamotor movements and in home cage and even recognize deviations from their normal behaviors, including complex animal behaviors such as forelimb reaching (in Phase II). The purpose is to use these sophisticated digital video analysis algorithms to allow computer interpretation of behavior. Once the complete home-cage behavioral repertoire is codified, it will be possible to produce a normal profile of behavior across the daily cycle for commonly used inbred strains of mice of different ages and genders. This will enable investigators to detect deviations from the normative pattern of behaviors, either in the types, amount, or daily rhythms of individual behaviors. Having identified deviations, video clips of the deviant behaviors could be presented by the system to the investigator for interpretation of the meaning of the deviation. Digital video algorithms will also allow non linear access to desired animal behavior scenes effectively and efficiently. PROPOSED COMMERCIAL APPLICATION: This proposed research will not only create enormous benefits for the neuroscience and behavior research community including medical research institutes, universities, pharmaceutical companies, and hospitals and clinics who are conducting behavior study and analysis, but also find applications in the entire area of biology which will be interested in this system to help them conduct research in such areas as genetic research, cancel research, HIV research, etc. I can be applied to human-computer interface and surveillance and monitoring areas.

人类疾病，特别是精神疾病的转基因和基因敲除小鼠模型的发展导致需要灵敏的自动化方法来检测小鼠的行为异常。我们建议开发新颖的数学和计算机算法，能够自动跟踪小鼠并识别小鼠的正常行为，例如自主运动和在笼子里的运动，甚至识别其正常行为的偏差，包括复杂的动物行为，例如前肢伸展（第二阶段）。目的是使用这些复杂的数字视频分析算法来允许计算机解释行为。一旦完整的家笼行为库被编码，就可以为不同年龄和性别的常用近交系小鼠在日常周期中产生正常的行为特征。这将使调查人员能够发现与规范行为模式的偏差，无论是个人行为的类型、数量还是日常节奏。识别出偏差后，系统可以将异常行为的视频片段呈现给调查人员，以解释偏差的含义。数字视频算法还将允许有效且高效地非线性访问所需的动物行为场景。拟议的商业应用：这项拟议的研究不仅将为神经科学和行为研究界创造巨大的利益，包括进行行为研究和分析的医学研究机构、大学、制药公司、医院和诊所，而且还会在整个生物学领域找到应用，对这个系统感兴趣的人可以帮助他们在遗传研究、取消研究、艾滋病毒研究等领域进行研究。我可以应用于人机界面和监视和 监控区域。