US-French Collaboration: Mechanisms of emergent OscillaTIONs in the septo-hippocampal network-MOTION

美法合作：海马隔网络中突发振荡的机制-MOTION

• 批准号: 1614645
• 负责人: Ivan Soltesz
• 金额: $ 21.36万
• 依托单位: Stanford University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-07-22 至 2016-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1614645&HistoricalAwards=false
• 关键词: US; French; Collaboration; Mechanisms; emergent

The hippocampus in mammals is a brain area important for learning and memory that is also implicated in several major neurological and psychiatric disorders including epilepsy, autism, schizophrenia and Alzheimer's disease. Prior research revealed that learning and memory-related information processing in the hippocampus critically depends on clock-like, rhythmic electrical signals elicited by an adjacent brain structure called the septum. However, how the oscillatory neuronal activity emerges from the closely interconnected neuronal networks of the septum and the hippocampus is not understood. The current project will employ novel, uniquely high-throughput experimental approaches in mice integrated with innovative, biologically realistic, large-scale supercomputer-based theoretical modeling techniques to identify key mechanisms underlying rhythmic electrical signal generation in septo-hippocampal circuits. The project represents a potentially major milestone in the development of biologically based realistic computer models of the brain, as it would allow the generation and testing of hypotheses concerning network mechanisms of behaviorally relevant oscillatory neuronal activity with unparalleled biological realism, precision and speed. In addition, the experimental knowledge base and the large-scale computational brain models will be placed in open-source databases (including ModelDB for network models at http://senselab.med.yale.edu/modeldb/, and Neuromorpho for biological structural data at http://neuromorpho.org/) that are freely accessible for the unrestricted use by the scientific community. This project involves extensive postdoctoral training in neuroinformatics. This award is co-funded by NSF's Office of the Director, International Science and Engineering, and a companion project is being funded by the French National Research Agency (ANR).

哺乳动物中的海马是一个对学习和记忆重要的大脑区域，也涉及几种主要的神经和精神疾病，包括癫痫，自闭症，精神分裂症和阿尔茨海默氏病。先前的研究表明，海马中的学习和与记忆有关的信息处理严重取决于被称为隔膜的相邻大脑结构引起的时钟状的节奏电信号。然而，尚不清楚振荡性神经元活性如何从隔膜和海马的紧密相互联系的神经元网络中出现。当前的项目将采用与创新的，生物学上现实的，大规模超级计算机的理论建模技术相结合的小鼠中的新颖，独特的高通量实验方法，以识别Septo-Hippocampal Circuts中节律电信号产生的关键机制。该项目代表了基于生物学的逼真的大脑计算机模型发展的潜在主要里程碑，因为它可以通过无与伦比的生物学现实主义，精确性和速度来生成和测试有关行为相关的振动性神经元活动网络机制的假设。此外，实验知识库和大规模计算大脑模型将放置在开源数据库中（包括http://senselab.med.yale.edu/modeldb/上的网络模型的模型，以及通过http://neuromororpho.or.orcorcects for for for for forecteryselly intercterysection的生物结构数据的NeuroMorpho。该项目涉及神经信息学方面的广泛博士后培训。 该奖项由NSF国际科学与工程主任办公室共同资助，由法国国家研究局（ANR）资助了一个伴侣项目。