The Digital Fly Brain

数字苍蝇大脑

• 批准号: 1544383
• 负责人: Aurel Lazar
• 金额: $ 79.51万
• 依托单位: Columbia 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: 2015-08-01 至 2019-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1544383&HistoricalAwards=false
• 关键词: Digital; Fly; Brain

Several highly ambitious, large-scale, billion-pound research projects that aim to understand the human brain are currently under way. In Europe, The Human Brain Project is focused on accelerating brain research by integrating data available from a multitude of disparate research projects through the development of a multi-scale, multi-level model of the human brain - the 100 billion neurons modelling and simulation challenge. In the US, The Brain Initiative aims to reconstruct the full record of neural activity across complete neural circuits - the 100 billion neurons recording challenge. These are clearly huge, but worthy challenges that can benefit from an understanding of the principles of neural computation of much smaller yet sufficiently complex brains. The fruit fly brain has become one of the most popular model organisms to study neural computation and for relating brain structure to function. Many of the genes and proteins expressed in the mammalian brain are also conserved in the genome of the fruit fly. Remarkably, the fruit fly is capable of a host of complex nonreactive behaviors that are governed by a brain containing only ~100,000 neurons. The relationship between the fly's brain and its behaviors can be experimentally probed using a powerful toolkit of genetic techniques for manipulation of the fly's neural circuitry. Novel experimental methods for precise recordings of the fly's neuronal responses to stimuli and for mapping neurons and synapses in Drosophila nervous system have provided access to an immense amount of valuable data regarding the fly's neural connectivity map and its processing of sensory stimuli. These features coupled with the growing ethical and economic pressures to reduce the use of mammals in research, explain the growing interest in Drosophila-based brain models, not only to understand sensing, perception and neural computation, but also to gain mechanistic insights that may inform our efforts to address neurodegenerative diseases, such as Alzheimer's disease, in humans. This project aims to design, implement and experimentally evaluate a potentially transformative open-source fly brain simulation platform capable of simulating ~135,000 neurons that make up the adult Drosophila brain. This computational infrastructure will be based on the recently established Graphic Processor Units (GPU)-enabled Neurokernel software platform. The modular simulation platform will integrate all knowledge about the Drosophila brain as a set of interconnected simulation modules which describe the operation of about 41 Local Processing Units (LPUs), six hubs and their interconnections, partly elucidated by detailed EM imaging studies. The simulation platform will be used to develop and validate a first draft model that incorporates the most advanced biophysical and/or functional models of the neurons and the latest published synaptic connections maps. The main focus will be on developing detailed models of the early visual system (retina, lamina, medulla) and of the early olfactory system (OSNs, antennal lobe, mushroom body, lateral horn). These models will integrate complete models of the visual and olfactory systems. The brain simulation platform will enable for the first time the isolated and integrated emulation of fly brain model neural circuits and their connectivity patterns (e.g., sensory and locomotion systems) and other parts of the fly's nervous system on clusters of GPUs. Using the Neurokernel simulation platform it will be possible to generate data sufficiently fast to enable researchers to compare and tune the input-output characteristics of virtual neurons on-line, while the experiment is running.

几个雄心勃勃、规模巨大、耗资数十亿英镑的研究项目目前正在进行中，这些项目旨在了解人类的大脑。在欧洲，人脑项目的重点是通过开发多尺度、多层次的人脑模型来整合大量不同研究项目的数据，从而加速大脑研究--1000亿个神经元建模和模拟的挑战。在美国，大脑倡议旨在重建完整神经回路中神经活动的完整记录-1000亿神经元记录挑战。这些显然是巨大的，但值得的挑战，可以受益于对小得多但足够复杂的大脑的神经计算原理的理解。果蝇脑已成为研究神经计算和将脑结构与功能联系起来的最受欢迎的模式生物之一。在哺乳动物大脑中表达的许多基因和蛋白质在果蝇的基因组中也是保守的。值得注意的是，果蝇能够做出一系列复杂的非反应性行为，这些行为是由只有10万个神经元的大脑控制的。苍蝇的大脑及其行为之间的关系可以用一个强大的遗传技术工具包来实验探索，该工具包用于操纵苍蝇的神经电路。精确记录果蝇对刺激的神经元反应以及绘制果蝇神经系统神经元和突触的新的实验方法，为了解果蝇的神经连接图及其对感觉刺激的处理提供了大量有价值的数据。这些特点，再加上在研究中减少使用哺乳动物的日益增长的伦理和经济压力，解释了人们对以果蝇为基础的大脑模型越来越感兴趣，不仅是为了理解感知、感知和神经计算，也是为了获得机械性见解，这些见解可能会为我们解决人类神经退行性疾病的努力提供信息，例如阿尔茨海默氏症。该项目旨在设计、实现并实验评估一个具有潜在变革性的开源苍蝇脑模拟平台，该平台能够模拟组成成年果蝇大脑的约135,000个神经元。这一计算基础设施将基于最近建立的支持图形处理器单元(GPU)的Neurocore软件平台。模块化模拟平台将把有关果蝇大脑的所有知识整合为一套相互连接的模拟模块，描述大约41个局部处理单元(LPU)、6个中枢及其相互连接的操作，部分原因是详细的电磁成像研究。该模拟平台将用于开发和验证第一稿模型，该模型包含最先进的神经元生物物理和/或功能模型以及最新发布的突触连接图。主要的重点将是建立早期视觉系统(视网膜、板层、髓质)和早期嗅觉系统(嗅觉神经元、触角、蘑菇体、侧角)的详细模型。这些模型将整合视觉和嗅觉系统的完整模型。大脑模拟平台将首次在图形处理器集群上实现苍蝇大脑模型神经电路及其连接模式(例如，感觉和运动系统)以及苍蝇神经系统其他部分的隔离和集成仿真。使用Neurocore模拟平台，可以足够快地生成数据，使研究人员能够在实验运行期间在线比较和调整虚拟神经元的输入输出特性。