NSF EAGER: Initiative for Physics and Mathematics of Neural Systems

NSF EAGER：神经系统物理和数学倡议

• 批准号: 1444389
• 负责人: Michael Hasselmo
• 金额: $ 30万
• 依托单位: Trustees of Boston University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-09-01 至 2017-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1444389&HistoricalAwards=false
• 关键词: NSF; EAGER; Initiative; Physics; Mathematics

This project will foster collaborations between physicists, mathematicians and neuroscientists to generate theoretical frameworks and statistical tools to interpret genomic, anatomical and physiological data on brain function. A community of researchers will be built through development of a seminar series for discussions of problems in which the theoretical approaches of physics, mathematics and statistics can be brought to be bear on specific research questions regarding neural systems. In addition, a set of pilot projects will be funded to foster collaborations between mathematicians, physicists and neuroscientists. Specific pilot projects will use the techniques of theoretical physics to address problems of understanding large scale functional anatomical connectivity, with the objective of identifying constraints on the distance and pattern of inter-areal connectivity in the human brain. Pilot projects will also develop a theoretical framework for understanding neural activity on different time scales during behavior, with the objective of understanding the unifying neural principles underlying human memory behavior over time scales from seconds to minutes to hours. Pilot projects will also develop mathematical and statistical techniques to identify molecular networks underlying specific features of neural function, with the objective of identifying specific network modules in the prefrontal cortex. These pilot projects will provide example interactions that can be expanded to further build a community of interaction of physicists, mathematicians and neuroscientists. The maturation of scientific fields such as physics required the development of sophisticated theoretical frameworks to account for experimental phenomena at multiple different scales of analysis ranging from particle physics to condensed matter physics to astrophysics. The maturation of neuroscience as a field will require similarly sophisticated theoretical frameworks that effectively account for data at the different levels including the genomic, physiological and behavioral levels. Current theories of single neuron function have not yet been effectively extended to address physiological phenomena at the circuit and population level or the behavioral function of these network dynamics. The pilot projects in this grant will attempt to develop theoretical frameworks for addressing these multiple levels of analysis. The intellectual merit of the proposal will be the application of mathematical and statistical techniques to the interpretation of neuroscience data, including the development of theoretical models to account for existing data and to guide the design of future experiments. The field of neuroscience needs more extensive development of a theoretical framework for understanding the structure and function of neural systems at different levels, including genomic, physiological and behavioral. Successful interactions in the pilot projects could provide a model for further interaction of physicists, mathematicians, and neuroscientists throughout the field. More specifically, these pilot projects will provide a framework for development of new theories for analyzing the connectivity patterns of neural systems, the dynamics of brain function underlying behavior, and the molecular networks underlying these neural properties. The resources provided by this grant will serve to recruit additional mathematicians and physicists to address relevant questions concerning brain function.This project is being jointly supported by the Physics of Living Systems program in the Division of Physics and the Mathematical Biology program in the Division of Mathematical sciences.

该项目将促进物理学家、数学家和神经科学家之间的合作，以产生理论框架和统计工具，以解释大脑功能的基因组、解剖和生理数据。将通过发展一系列讨论问题的研讨会，建立一个研究人员社区，在这些问题中，物理学、数学和统计学的理论方法可以用于有关神经系统的具体研究问题。此外，还将资助一系列试点项目，以促进数学家、物理学家和神经科学家之间的合作。具体的试点项目将使用理论物理技术来解决理解大规模功能解剖连接的问题，目的是确定人类大脑区域间连接的距离和模式的限制。试点项目还将开发一个理论框架，用于理解行为过程中不同时间尺度上的神经活动，目的是理解从秒到分钟到小时的时间尺度上人类记忆行为的统一神经原理。试点项目还将开发数学和统计技术，以识别神经功能特定特征的分子网络，目标是识别前额皮质中的特定网络模块。这些试点项目将提供相互作用的例子，这些例子可以进一步扩大，以建立一个物理学家、数学家和神经科学家相互作用的社区。物理学等科学领域的成熟需要发展复杂的理论框架，以解释从粒子物理学到凝聚态物理学再到天体物理学等多个不同分析尺度的实验现象。神经科学作为一个领域的成熟将需要同样复杂的理论框架，以有效地解释不同层面的数据，包括基因组、生理和行为层面。目前的单神经元功能理论尚未有效地扩展到解决电路和群体水平的生理现象或这些网络动力学的行为功能。本基金的试点项目将尝试发展理论框架来处理这些多层次的分析。该提案的智力价值将是应用数学和统计技术来解释神经科学数据，包括发展理论模型来解释现有数据并指导未来实验的设计。神经科学领域需要更广泛的理论框架来理解不同层次的神经系统的结构和功能，包括基因组、生理和行为。试点项目的成功互动可以为物理学家、数学家和神经科学家在整个领域的进一步互动提供一个模型。更具体地说，这些试点项目将为新理论的发展提供一个框架，用于分析神经系统的连接模式、潜在行为的脑功能动力学以及这些神经特性背后的分子网络。本基金提供的资源将用于招募更多的数学家和物理学家来解决有关脑功能的相关问题。该项目由物理系的生命系统物理学项目和数学科学系的数学生物学项目共同支持。