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

哺乳动物的海马体是一个对学习和记忆很重要的大脑区域，它也与几种主要的神经和精神疾病有关，包括癫痫、自闭症、精神分裂症和阿尔茨海默病。先前的研究表明，海马体中与学习和记忆相关的信息处理严重依赖于由相邻的被称为中隔的大脑结构引发的类似时钟的、有节奏的电信号。然而，振荡神经元活动是如何从中隔和海马体紧密相连的神经元网络中出现的尚不清楚。目前的项目将采用新颖的、独特的高通量实验方法，在小鼠身上结合创新的、生物逼真的、基于大型超级计算机的理论建模技术，以确定间隔-海马体回路中节律性电信号产生的关键机制。该项目代表了基于生物学的真实大脑计算机模型发展的一个潜在的重要里程碑，因为它将允许以无与伦比的生物学真实性，精度和速度生成和测试有关行为相关振荡神经元活动的网络机制的假设。此外，实验知识库和大规模计算脑模型将被放置在开源数据库中（包括网络模型的ModelDB （http://senselab.med.yale.edu/modeldb/）和生物结构数据的Neuromorpho (http://neuromorpho.org/)），这些数据库可供科学界自由访问，不受限制地使用。该项目涉及神经信息学方面的大量博士后培训。该奖项由美国国家科学基金会国际科学与工程主任办公室共同资助，一个伙伴项目由法国国家研究机构（ANR）资助。

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).