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.

致力于处理感觉信息的大脑区域以其二维地图状（地形）组织而闻名。最近的证据表明，这种特性可以维持到亚细胞水平，以地形组织输入的形式进入单个细胞（神经元）的扩展树突（树突）。这个项目的目标是确定在一个原型神经元的树突中处理这种地形输入的关键原理。该项目关注的是一种神经细胞，这种细胞对接近与动物发生碰撞的物体最敏感，并与产生避碰行为有关。研究人员使用研究偏微分方程的工具来确定细胞离子通道的详细树突分布。接下来，使用旨在降低数学模型复杂性的技术，并同时尊重输入的地形，以提取神经元的简化表示。S信号处理特性。这使得研究人员能够描述神经元树突在产生神经元对接近碰撞过程的物体的反应时所起的作用。特别关注的是理解对从不同方向接近的物体的反应的不变性。包括人类在内的所有动物的生存，都严重依赖于神经元对即将到来的危险的处理。这个项目揭示了大脑是如何在一个非常适合这个目的的特定模型系统中完成这一壮举的。由此产生的数学工具可供其他研究人员使用，以分析在其他情况下具有类似性质的神经元。此外，该项目有助于我们对大脑功能的基本了解，最终可能导致更好地治疗影响感官知觉的疾病。最后，这个项目的结果可能会在自主机器人的设计中找到应用。