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: 2015
• 资助国家: 加拿大
• 起止时间: 2015-01-01 至 2016-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=573595
• 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.

人脑是科学已知的最复杂的系统。它包含数以万计的神经元，这些神经元通过数万亿个连接的复杂网络进行通信。神经科学是一个非常活跃的基础研究领域，并且有关大脑工作原理的积累的信息如此之快，以至于投资单独的研究工作以定量将多样化的研究结果整合到一致的情况下变得很重要。为此，需要计算模型，既规模又详细，并且包含抽象层，这些层次可以提供洞察力而不会牺牲现实主义。该项目通过开发新的计算机仿真技术来推动这一目标，该技术将允许对脑组织进行非常大规模，准确的模拟。这些模拟中的细节和现实主义程度将在大脑的不同部位以及随着时间的流逝而有所不同，以将计算能力集中在每个瞬间的关键领域。为了确保使用此技术的计算机模拟将提供有关大脑功能的洞察力，将开发出抽象的层次结构，该层次结构不断将模拟细节连接到许多细胞的大规模信息处理功能。这项技术将为我们建立具有现实解剖结构，神经活动现实模式以及现实信息处理能力的大脑计算机模型的基础。这最终将提高我们对大脑功能的理解，并促进像我们一样理解世界的人造系统的发展。