CRCNS: Modeling Pathfinding and Target Recognition in the Olfactory System

CRCNS：嗅觉系统中的寻路和目标识别建模

• 批准号: 0218521
• 负责人: David Lin
• 金额: $ 100万
• 依托单位: Cornell Univ - State: AWDS MADE PRIOR MAY 2010
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2002
• 资助国家: 美国
• 起止时间: 2002-10-01 至 2006-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0218521&HistoricalAwards=false
• 关键词: CRCNS; Modeling; Pathfinding; Target; Recognition

EIA-0218521Lin, DavidCornell University-StateCRCNS: Modeling Pathfinding and Target Recognition in the Olfactory SystemStatement for public consumptionThe proper development of the nervous system is essential to the f unction of any organism. The nervous system integrates sensory input, coordinates motor output, controls autonomic functions, and shapes memory and cognition. To accomplish these tasks, the nervous system employs billions of neurons that will form trillions of connections with their appropriate targets. For example, in the olfactory system, odorant in the environment are detected by olfactory sensory neurons (OSNs) located in the nose. In order for odorant information to be properly transmitted to the brain, however, these neurons must be connected, or "wired together," with their appropriate partners in the brain. How this critical feat of pathfinding and target recognition is accomplished is still largely unknown. In one model, this process is mediated b cues located at various points within the brain that would interact with and guide neurons to their target. These cues would form, in essence, a "roadmap", that would help guide neurons to their target.In this proposal, we will combine bioinformatics, statistical methods, and genomics to begin to determine the shape of this map. As a model system, we will study the ability of olfactory sensory neurons (OSNs) to identify their targets in the olfactory bulb.

EIA-0218521 Lin，DavidCornell University-StateCRCNS：嗅觉系统中的寻路和目标识别建模供公众消费的声明神经系统的正常发育对任何生物体的功能都是必不可少的。神经系统整合感觉输入，协调运动输出，控制自主功能，并塑造记忆和认知。为了完成这些任务，神经系统使用了数十亿个神经元，这些神经元将与其相应的目标形成数万亿个连接。 例如，在嗅觉系统中，环境中的气味由位于鼻子中的嗅觉感觉神经元（OSN）检测。然而，为了将气味信息正确地传递到大脑，这些神经元必须与大脑中相应的伙伴连接，或“连接在一起”。这一关键的寻路和目标识别技术是如何完成的，在很大程度上仍然是未知的。 在一个模型中，这个过程是由位于大脑内不同点的B线索介导的，这些线索将与神经元相互作用并引导神经元到达它们的目标。 这些线索将形成，在本质上，一个“路线图”，这将有助于引导神经元到他们的目标。在这个建议中，我们将联合收割机生物信息学，统计学方法和基因组学结合起来，开始确定这个地图的形状。作为一个模型系统，我们将研究嗅感觉神经元（OSNs）识别其目标的能力在嗅球。