NSF EAGER: Initiative for Physics and Mathematics of Neural Systems

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来解释大脑功能的基因组，解剖和生理数据。将通过一系列研讨会的发展建立一个研究人员的社区，讨论物理学，数学和统计学的理论方法可以对神经系统的具体研究问题产生影响的问题。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，目的是理解从几秒到几分钟到几小时的时间尺度上人类记忆行为背后的统一神经原则。试点项目还将开发数学和统计技术，以确定神经功能具体特征的分子网络，目的是确定前额叶皮层中的具体网络模块。这些试点项目将提供示例交互，可以扩展到进一步建立物理学家，数学家和神经科学家的交互社区。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种不同分析尺度上的实验现象。神经科学作为一个领域的成熟将需要类似复杂的理论框架，有效地解释不同层次的数据，包括基因组，生理和行为水平。目前单神经元功能的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态的行为功能。在这个赠款的试点项目将试图开发理论框架，以解决这些多层次的分析。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，包括开发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地发展一个理论框架，以便在不同水平上理解神经系统的结构和功能，包括基因组，生理和行为。试点项目中的成功互动可以为整个领域的物理学家，数学家和神经科学家的进一步互动提供一个模型。更具体地说，这些试点项目将提供一个框架，用于开发新的理论，分析神经系统的连接模式，行为背后的大脑功能动力学，以及这些神经特性背后的分子网络。该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大脑功能的问题。该项目由物理学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。

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.