Collaborative Research: Dendritic Processing of Topographic Information in a Collision Detecting Neuron

合作研究：碰撞检测神经元中地形信息的树突状处理

• 批准号: 1122455
• 负责人: Steven Cox
• 金额: $ 27.56万
• 依托单位: William Marsh Rice University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2011
• 资助国家: 美国
• 起止时间: 2011-10-01 至 2017-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1122455&HistoricalAwards=false
• 关键词: Collaborative; Research; Dendritic; Processing; Topographic

The brain regions devoted to the processing of sensory information are remarkable for their two-dimensional map-like (topographic) organization. Recent evidence suggests that this property can be maintained down to the subcellular level, in the form of topographically organized inputs onto the extended arborizations (dendrites) of single cells (neurons). The goal of this project is to identify the key principles underlying the processing of such topographic inputs in the dendrites of a prototypical neuron. The project focuses on a nerve cell that is most sensitive to objects approaching on a collision course with the animal and that is implicated in generating collision avoidance behaviors. The investigators use tools developed to study partial differential equations to determine the detailed dendritic distribution of the cell's ion channels. Next, techniques designed to reduce the complexity of mathematical models are used, as well as to simultaneously respect the topography of inputs, to extract a simplified representation of the neuron?s signal processing characteristics. This allows the investigators to characterize the role played by the neuron's dendrites in generating the responses of the neuron to objects approaching on a collision course. Particular focus is on understanding the invariance of responses to objects approaching from different directions.The survival of all animals, including humans, critically depends on the neuronal processing of impending dangers. This project sheds light on how the brain accomplishes this feat in a particular model system ideally suited for this purpose. Mathematical tools are generated and are made available to other researchers to analyze neurons with similar properties in other contexts. Additionally, the project contributes to our basic understanding of brain function that may eventually lead to better cures for diseases affecting sensory perception. Finally, the results of this project could potentially find applications in the design of autonomous robots.

致力于处理感官信息的大脑区域对于其二维地图（地形）组织而言是显着的。最近的证据表明，该特性可以保持到亚细胞水平，形式是在单个细胞（神经元）的延伸树皮（树突）上的形状组织的输入形式。该项目的目的是确定原型神经元树突中此类地形输入处理的关键原则。 该项目的重点是对与动物碰撞过程中接近的物体最敏感的神经细胞，这与产生造成碰撞行为有关。 研究人员使用开发的工具来研究部分微分方程，以确定细胞离子通道的详细树突分布。 接下来，使用旨在减少数学模型复杂性的技术，并同时尊重输入的地形，以提取神经元信号处理特性的简化表示。 这使研究人员可以表征神经元的树突在产生神经元对碰撞过程中接近对象的反应中所扮演的角色。 特别的重点是理解从不同方向接近物体的反应的不变性。包括人类在内的所有动物的生存在很大程度上取决于即时危险的神经元处理。该项目阐明了大脑如何在适合此目的的特定模型系统中实现这一壮举。 生成数学工具，并可以向其他研究人员使用，以分析在其他情况下具有相似特性的神经元。 此外，该项目有助于我们对大脑功能的基本理解，最终可能会为影响感官感知的疾病提供更好的治疗方法。 最后，该项目的结果可能有可能在自主机器人设计中找到应用。