Collaborative Research: NSF-FO: Ground-Truth Analysis and Modeling of Entire Individual C. elegans Nervous Systems

合作研究：NSF-FO：整个线虫个体神经系统的真实分析和建模

• 批准号: 1734821
• 负责人: Albert-Laszlo Barabasi
• 金额: $ 23.75万
• 依托单位: Northeastern University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-09-01 至 2019-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1734821&HistoricalAwards=false
• 关键词: Collaborative; Research; NSF; FO; Ground

How does the brain compute? Understanding this process could lead to many advances in science and technology. The Boyden, Flavell, Barabasi, and Tegmark groups propose to examine how the cells within the brain of a simple animal work together to generate the computations that underlie behavior. The teams will study C. elegans, a small worm with just a few hundred neurons, yet capable of learning and adaptive behavior in complex real-world environments.  The teams will apply new technologies to measure and control the neural circuits of C. elegans, in order to investigate how they works. The project will also generate new mathematical tools to analyze the data that is collected - tools that could help analyze how the brain goes wrong in disorders such as Parkinson's or Alzheimer's. Using the data acquired, the project will reveal how brain circuits compute, which could inspire new algorithms for machine learning and computer information processing. These in turn could have broad impact on economic prosperity as well as in advancing human quality of life. The Boyden, Flavell, Barabasi, and Tegmark groups will launch a novel integrative endeavor to reveal how entire nervous systems - from sensory input neurons, to motor output neurons, and including the networks that underlie learning, decision making, and other processes - work together as emergent wholes to generate the computations that underlie behavior. They will utilize C. elegans, with just 302 neurons, yet capable of learning and adaptive behavior in complex real-world environments.  They will optimize and deploy novel technologies, including a new fluorescent voltage indicator for C. elegans, and a method for 3-D visualization of entire nervous systems with molecular information via physical expansion by up to 10,000 fold in volume. They will record neural and behavioral dynamics, imaging the activity of neurons throughout entire brains and even entire nervous systems of freely moving as well as fictively behaving C. elegans engaged in complex decision-making tasks, or forming new memories. They will then use expansion microscopy to map the structure and molecular profiles of entire individual nervous systems. They will analyze the resultant network structures to determine how individual variation in these features connect to details of an individual's behavior, and make mathematical models of the relevant neural circuits capable of predicting how the nervous system would respond in complex contexts. The outcome of their work will yield radical new theories of how nervous systems operate, as well as a diversity of tools for the neuroscience and computational communities.This project is funded by Integrative Strategies for Understanding Neural and Cognitive Systems (NSF-NCS), a multidisciplinary program jointly supported by the Directorates for Computer and Information Science and Engineering (CISE), Education and Human Resources (EHR), Engineering (ENG), and Social, Behavioral, and Economic Sciences (SBE).

大脑如何计算？了解这一过程可能会导致科学技术的许多进步。 Boyden，Flavell，Barabasi和Tegmark小组提出了研究简单动物大脑中的细胞如何共同起作用以产生构成行为的计算。团队将研究秀丽隐杆线虫，这是一个只有几百个神经元的小蠕虫，但能够在复杂的现实世界环境中学习和适应性行为。这些团队将采用新技术来测量和控制秀丽隐杆线虫的神经回路，以研究它们的工作原理。该项目还将生成新的数学工具来分析收集的数据 - 可以帮助分析大脑在帕金森氏症或阿尔茨海默氏症等疾病中如何出错的工具。使用获取的数据，该项目将揭示大脑电路如何计算，这可能会激发用于机器学习和计算机信息处理的新算法。这些反过来又可能对经济繁荣以及提高人类生活质量产生广泛的影响。 Boyden，Flavell，Barabasi和Tegmark小组将发起一项新颖的集成努力，以揭示整个神经系统如何从感觉输入神经元到运动输出神经元，以及包括基于学习，决策和其他过程的网络（包括作为新兴的脑电图）的网络，从而产生了基于行为的计算。他们将利用秀丽隐杆线虫，只有302个神经元，但能够在复杂的现实世界环境中学习和适应性行为。他们将优化和部署新颖的技术，包括针对秀丽隐杆线虫的新荧光电压指示器，以及通过物理扩展，通过物理扩张的体积高达10,000倍的整个神经系统3D可视化的方法。他们将记录神经元和行为动力学，对整个大脑中的神经元的活性进行成像，甚至整个神经元素的自由移动系统以及虚构行为的秀丽隐杆线虫从事复杂的决策任务或形成新的记忆。然后，他们将使用膨胀显微镜来绘制整个单个神经系统的结构和分子谱。他们将分析所得的网络结构，以确定这些特征中的个体变异如何连接到个人行为的细节，并制作能够预测神经系统在复杂环境中如何响应的相关神经元电路的数学模型。 The outcome of their work will yield radical new theories of how nervous systems operate, as well as a diversity of tools for the neuroscience and computational communities.This project is funded by Integrative Strategies for Understanding Neural and Cognitive Systems (NSF-NCS), a multidisciplinary program jointly supported by the Directorates for Computer and Information Science and Engineering (CISE), Education and Human Resources (EHR), Engineering (ENG), and Social,行为和经济科学（SBE）。