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).

大脑是如何进行计算的？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小组建议研究简单动物大脑中的细胞如何协同工作，产生行为基础的计算。研究小组将研究秀丽隐杆线虫，这是一种只有几百个神经元的小蠕虫，但却能够在复杂的现实环境中学习和适应行为。研究小组将应用新技术来测量和控制秀丽隐杆线虫的神经回路，以研究它们是如何工作的。该项目还将产生新的数学工具来分析收集到的数据，这些工具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是如何出错的。利用获得的数据，该项目将揭示大脑回路是如何计算的，这可能会激发机器学习和计算机信息处理的新算法。这些反过来又会对经济繁荣和提高人类生活质量产生广泛影响。Boyden, Flavell， Barabasi和Tegmark小组将发起一项全新的综合研究，揭示整个神经系统——从感觉输入神经元到运动输出神经元，包括作为学习、决策和其他过程基础的网络——如何作为一个突现的整体一起工作，产生作为行为基础的计算。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环境中学习和适应行为。他们将优化和部署新技术，包括一种用于秀丽隐杆线虫的新型荧光电压指示器，以及一种通过物理膨胀将整个神经系统的分子信息进行三维可视化的方法，该方法的体积可达10,000倍。他们将记录神经和行为动态，对整个大脑乃至整个自由运动的神经系统的神经元活动进行成像，以及对秀丽隐杆线虫进行复杂决策任务或形成新记忆的有效行为进行成像。然后，他们将使用扩展显微镜绘制整个个体神经系统的结构和分子图谱。他们将分析由此产生的网络结构，以确定这些特征的个体差异如何与个体行为的细节联系起来，并建立相关神经回路的数学模型，以预测神经系统在复杂环境下的反应。他们的工作成果将产生关于神经系统如何运作的激进的新理论，以及神经科学和计算界的各种工具。该项目由理解神经和认知系统的综合策略（NSF-NCS）资助，这是一个由计算机与信息科学与工程（CISE）、教育与人力资源（EHR）、工程（ENG）和社会、行为和经济科学（SBE）联合支持的多学科项目。