Dynamic multi-scale modelling of primate visuo-motor systems

灵长类动物视觉运动系统的动态多尺度建模

• 批准号: 418331-2012
• 负责人: Tripp, Bryan
• 金额: $ 1.6万
• 依托单位: University of Waterloo
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2016
• 资助国家: 加拿大
• 起止时间: 2016-01-01 至 2017-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=596301
• 关键词: Dynamic; multi; scale; modelling; primate

The human brain is the most complex system known to science. It contains tens of billions of neurons, which communicate through an intricate network of trillions of connections. Neuroscience is a very active field of basic research, and information about how the brain works is being amassed so quickly that is has become important to invest separate research effort to quantitatively integrate diverse research results into a coherent picture. For this purpose, computational models are needed that are both large in scale and fine in detail, and which contain layers of abstraction that provide insight without sacrificing realism. This project advances this goal by developing new computer simulation technology that will allow very large scale, accurate simulations of brain tissue. The degree of detail and realism in these simulations will vary across different parts of the brain, and over time, to focus computational power on the key areas at each instant. To ensure that computer simulations that use this technology will provide insight into brain function, a hierarchy of abstractions will be developed, which constantly link fine detail of simulations to large-scale information processing functions of many cells. This technology will provide a foundation on which we can build computer models of the brain that have realistic anatomy, realistic patterns of neural activity, and realistic information processing capabilities. This will ultimately advance our understanding of brain function and facilitate development of artificial systems that understand the world as we do.

人类的大脑是科学界已知的最复杂的系统。它包含数百亿神经元，这些神经元通过一个由数万亿连接组成的复杂网络进行交流。神经科学是一个非常活跃的基础研究领域，关于大脑如何工作的信息积累得如此之快，以至于投入单独的研究努力，将不同的研究结果定量地整合成一个连贯的画面变得非常重要。为此，计算模型需要规模大，细节精细，并且包含抽象层，在不牺牲现实性的情况下提供洞察力。该项目通过开发新的计算机模拟技术来推进这一目标，该技术将允许对脑组织进行大规模、精确的模拟。随着时间的推移，这些模拟的细节和现实程度会因大脑的不同部分而异，以便将计算能力集中在每个时刻的关键区域。为了确保使用这种技术的计算机模拟将提供对大脑功能的深入了解，将开发一个抽象层次，将模拟的精细细节与许多细胞的大规模信息处理功能不断联系起来。这项技术将为我们建立具有真实解剖结构、真实神经活动模式和真实信息处理能力的大脑计算机模型提供基础。这将最终推进我们对大脑功能的理解，并促进像我们一样理解世界的人工系统的发展。