Automated tracking of monkey groups: recognition of social structure and behavior

自动跟踪猴群：识别社会结构和行为

• 批准号: 8999764
• 负责人: Tucker Balch
• 金额: $ 65.59万
• 依托单位: EMORY UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-04-15 至 2020-01-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8999764
• 关键词: Accidents; Address; Adult; Aggressive behavior; Animals; Area; Behavior; Behavioral; Characteristics; Clip; Code; Collection; Complex; Computer software; Data; Development; Diagnostic; Event; Female; Funding; Goals; Grooming; Group Structure; Health; Housing; Human; Individual; Infant; Intervention; Investigation; Letters; Life; Location; Macaca mulatta; Maternal Behavior; Monitor; Monkeys; Mothers; Movement; National Institute of Child Health and Human Development; National Institute of Drug Abuse; National Institute of Mental Health; Pathway Analysis; Pattern; Pharmaceutical Preparations; Primates; Records; Reporting; Reproductive Behavior; Research; Resolution; Running; Sex Behavior; Social Behavior; Social Development; Social Hierarchy; Social Impacts; Social Interaction; Social Network; Software Tools; Structure; Support Groups; System; Technology; Time; Translational Research; Video Recording; Visual; Work; animal resource; density; design; detector; improved; innovation; instrument; male; member; men' s group; new technology; programs; prototype; public health relevance; radio frequency; relating to nervous system; social; social group; software development; software systems; surveillance data; tool

 DESCRIPTION (provided by applicant): Delineating patterns of social affiliation and hierarchical relations in group living rhesus monkeys is very labor intensive. We propose to develop and implement innovative new software and hardware technology that will automate the continuous collection of social interaction data in a complex species-typical rhesus monkey social group. The proposed system will continuously and simultaneously track the precise 3D locations of multiple individuals in a large social group of monkeys in their half acre living area Individual identification will come from comfortable collars, we will design and build, that contai active RFID tags that continuously broadcast each animal's unique code. RFID detectors within and around the compound's periphery allow triangulating each animal's precise location to within 25cm as well as their direction and velocity of movement. We will track the adult males and females that make up the core of the social hierarchy (45 individuals in total). Distance between individuals is a key diagnostic for inferring social affiliation as monkeys are rarely withn 25cm of each other by accident. Thus knowing the amount of time spent at that distance allows inferring affiliative relations. The patterns of affiliation, avoidance, and time in close proximit will allow inferring the social hierarchy of the group. In combination with social network analysis, we will identify patterns of group association and social instability. In addition, we will develop an deploy (in years 3 and 4) a RFID-guided camera system that automatically records high resolution video of predetermined target subjects without human intervention, allowing significantly increased efficiency for later human behavioral coding from these video snippets. Three software systems will be developed under this project: 1) behavioral inference software that infers affiliative, hierarchical, aggressive, and sexual behavior from the automated tracking data; 2) social network analysis software to identify social instabilities; 3) video recognition software that will automate the coding of social behavior from the video snippets collected with the RFID-guided cameras. Together this combined hardware and software will provide an enhanced animal resource making possible easy investigation of the social impact of a variety of manipulations, from drugs to neural insult. In addition, this system can be used to monitor group health and identify individual sickness behavior. This animal resource would facilitate research funded by NIMH, NIDA, or NICHD, and support and enhance primate colony management.

 描述（由申请人提供）：在群体生活的恒河猴中描绘社会隶属关系和等级关系的模式是非常劳动密集的。我们建议开发和实施创新的新的软件和硬件技术，将自动化的社会互动数据的连续收集在一个复杂的物种典型的恒河猴社会群体。拟议的系统将连续和同时跟踪多个人的精确3D位置在一个大型社会群体的猴子在他们的半英亩的生活区个人识别将来自舒适的衣领，我们将设计和建造，contai主动RFID标签，不断广播每个动物的唯一代码。大院内部和周围的RFID检测器可以对每只动物的精确位置进行三角测量，误差在25厘米以内，以及它们的运动方向和速度。我们将追踪构成社会等级核心的成年男性和女性（共45人）。个体之间的距离是推断社会关系的一个关键诊断，因为猴子很少偶然在25厘米以内。因此，知道在那个距离上花费的时间量允许推断从属关系。从属关系，回避和时间的模式将允许推断该群体的社会等级。结合社会网络分析，我们将识别群体关联和社会不稳定的模式。此外，我们将开发一个部署（在第3年和第4年）RFID引导的摄像头系统，该系统可以自动记录预定目标对象的高分辨率视频，而无需人工干预，从而大大提高了从这些视频片段进行后期人类行为编码的效率。该项目将开发三个软件系统：1）行为推理软件，从自动跟踪数据中推断亲和，分层，攻击性和性行为; 2）社交网络分析软件，以识别社会不稳定性; 3）视频识别软件，将从RFID引导的摄像头收集的视频片段中自动编码社会行为。这种结合的硬件和软件将提供一种增强的动物资源，使得从药物到神经损伤的各种操纵的社会影响的容易调查成为可能。此外，该系统还可用于监测群体健康和识别个体疾病行为。这种动物资源将促进由NIMH，NIDA或NICHD资助的研究，并支持和加强灵长类动物群体的管理。