RCN: The Pyloric Model Group: Functional Analysis of a Complex, Distributed Biological Neural Network

RCN：幽门模型组：复杂的分布式生物神经网络的功能分析

• 批准号: 0090250
• 负责人: Scott Hooper
• 金额: $ 43.61万
• 依托单位: Ohio University
• 依托单位国家: 美国
• 项目类别: Continuing grant
• 财政年份: 2001
• 资助国家: 美国
• 起止时间: 2001-05-15 至 2006-04-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0090250&HistoricalAwards=false
• 关键词: RCN; Pyloric; Model; Group; Functional

Complex, distributed systems are those in which the components are highly interconnected and individually non-linear in operation. We have little understanding of how such systems operate. Nervous systems are highly complex and non-linear, and this lack of understanding is an impediment to understanding nervous system function, and to designing computational devices that can mimic nervous system capabilities. Experimental and computational studies of advantageous animal models have led to some useful advances. This proposal describes such an approach using a small network of nerve cells (neurons) called the pyloric neural network, part of a larger complex called the stomatogastric ganglion, which generates rhythmic activity in the gut of crustaceans. This network generates a suite of behaviors and is small, extremely well understood, and very amenable to experiment and computational modeling. These investigations have been done in many different laboratories, with a far broader scope than any one or two labs could approach, and this Research Coordination Network is established to coordinate their efforts. The Pyloric Model Group is set up to construct a computational model of the pyloric network, to supervise a postdoctoral fellow who will help fill critical gaps and construct the model, to sponsor annual meetings to share the knowledge of the pool of labs that conduct stomatogastric ganglion research, and to share the results of the collaboration with the broader scientific community by Web and CD distribution. This project will have an impact on the fundamental understanding of the neurobiological basis of behavior, will provide insights into the function of complex distributed systems in general, will promote cross-disciplinary collaborations including small colleges with major universities, and will broaden the experience of students in a cross-disciplinary environment.

复杂的分布式系统是那些组件高度互连且在操作中单独非线性的系统。 我们对这些系统的运作方式知之甚少。 神经系统是高度复杂和非线性的，这种缺乏理解是理解神经系统功能和设计可以模拟神经系统能力的计算设备的障碍。 对有利的动物模型的实验和计算研究已经取得了一些有益的进展。 该提案描述了一种使用称为幽门神经网络的神经细胞（神经元）的小网络的方法，该网络是称为口胃神经节的更大复合体的一部分，该复合体在甲壳类动物的肠道中产生有节奏的活动。 这个网络生成一系列行为，并且很小，非常容易理解，并且非常适合实验和计算建模。 这些研究已在许多不同的实验室进行，其范围比任何一两个实验室所能达到的范围要广泛得多，而这个研究协调网络的建立是为了协调他们的工作。 幽门模型组的成立是为了构建幽门网络的计算模型，监督一名博士后研究员，他将帮助填补关键空白并构建模型，赞助年度会议，以分享进行口胃神经节研究的实验室池的知识，并通过网络和CD分发与更广泛的科学界分享合作成果。 该项目将对行为的神经生物学基础的基本理解产生影响，将提供对复杂分布式系统功能的见解，将促进跨学科合作，包括小型学院与主要大学，并将拓宽学生在跨学科环境中的经验。