NIH Director's Pioneer Award

NIH 院长先锋奖

• 批准号: 7667955
• 负责人: KWABENA BOAHEN
• 金额: $ 79万
• 依托单位: STANFORD UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2006
• 资助国家: 美国
• 起止时间: 2006-09-28 至 2011-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7667955
• 关键词: American; Arts; Award; Benchmarking; Biological; Brain; Brain Mapping; Cochlea; Cochlear nucleus; Collaborations; Computer software; Development; Doctor of Philosophy; Hippocampus (Brain); Laboratory Animals; Modeling; Neurons; Neurosciences; Retina; Simulate; Societies; System; Testing; Thalamic structure; Time; United States National Institutes of Health; Visual Cortex; Work; analog; design; digital; flexibility; relating to nervous system; research study; retinotectal

I propose to build Neurogrid, a specialized hardware platform that will perform cortex-scale emulations while offering software-like flexibility. Recent breakthroughs in brain mapping present an unprecedented opportunity to understand how the brain works, with profound implications for society. To understand the brain, we have to interpret these richly growing observations by modeling the brain, the only way to test our understanding? since building a real brain out of biological parts is currently infeasible. Neurogrid will emulate (simulate in real-time) one million neurons connected by six billion synapses?making it possible to model vertical, horizontal and top-down cortical interactions in biophysical detail. My ability to bring this endeavor to fruition and my commitment to biomedicine is evident in my past accomplishments. Over the past eight years, my lab has designed seven neuromorphic chips that model seven neural systems?retina, cochlea, cochlear nucleus, thalamus, hippocampus, visual cortex, and retinotectal development. To pursue such diverse projects, I established productive collaborations with six colleagues in Penn?s Neuroscience Department; our work was a Scientific American cover story (May 2005). The visual cortex chip illustrates the potential of Analog VLSI: Emulating 9,216 neurons, it is 2,765 times faster than the state-of-the-art. However, neither this chip nor the other six is programmable. Neurogrid will provide programmability by augmenting Analog VLSI with Digital VLSI, a mixed-mode approach that combines the best of both worlds. While including biophysical detail in a model provides contact with experiment, programmability supports replicating manipulations, performing controls, benchmarking models, and exploring mechanism. Realizing these two critical functions without sacrificing scale will make it possible to replicate tasks laboratory animals perform in biologically realistic models for the first time, which I will do in close collaboration with two neurophysiologists (Matthew Dalva Ph.D. and William Newsome Ph.D.).

我建议构建 Neurogrid，这是一个专门的硬件平台，它将执行皮层规模的仿真，同时提供 软件般的灵活性。脑图谱的最新突破为理解大脑提供了前所未有的机会 大脑如何工作，对社会具有深远的影响。要了解大脑，我们必须 通过大脑建模来解释这些丰富的观察结果，这是测试我们理解力的唯一方法吗？ 因为用生物部件构建真正的大脑目前是不可行的。 Neurogrid 将模拟（模拟 实时）一百万个神经元由六十亿个突触连接？使得建模垂直、 生物物理细节中的水平和自上而下的皮质相互作用。 我实现这一努力的能力以及我对生物医学的承诺在我过去的成就中显而易见。 在过去的八年里，我的实验室设计了七种神经形态芯片，可以模拟七种神经形态芯片。 神经系统？视网膜、耳蜗、耳蜗核、丘脑、海马、视觉皮层和视网膜顶盖 发展。为了追求如此多样化的项目，我与六位同事建立了富有成效的合作 宾夕法尼亚大学神经科学系；我们的作品登上了《科学美国人》的封面故事（2005 年 5 月）。视觉皮层 芯片展示了模拟 VLSI 的潜力：模拟 9,216 个神经元，它比普通芯片快 2,765 倍 最先进的。然而，这个芯片和其他六个芯片都不是可编程的。 Neurogrid 将通过使用数字 VLSI（一种混合模式方法）增强模拟 VLSI 来提供可编程性 结合了两个世界的优点。虽然在模型中包含生物物理细节可以提供联系 通过实验，可编程性支持复制操作、执行控制、基准测试 模式、探索机制。在不牺牲规模的情况下实现这两个关键功能将使 首次可以复制实验动物在生物学真实模型中执行的任务， 我将与两位神经生理学家（Matthew Dalva 博士和 William 纽瑟姆博士）。