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通过超级计算机进行人体尺度的大脑模拟:以小脑为例的案例研究

Human-scale Brain Simulation via Supercomputer: A Case Study on the Cerebellum.

作者信息

Yamazaki Tadashi, Igarashi Jun, Yamaura Hiroshi

机构信息

Graduate School of Informatics and Engineering, The University of Electro-Communications, Japan.

Center for Computational Science, RIKEN, Japan.

出版信息

Neuroscience. 2021 May 10;462:235-246. doi: 10.1016/j.neuroscience.2021.01.014. Epub 2021 Jan 20.

DOI:10.1016/j.neuroscience.2021.01.014
PMID:33482329
Abstract

Performance of supercomputers has been steadily and exponentially increasing for the past 20 years, and is expected to increase further. This unprecedented computational power enables us to build and simulate large-scale neural network models composed of tens of billions of neurons and tens of trillions of synapses with detailed anatomical connections and realistic physiological parameters. Such "human-scale" brain simulation could be considered a milestone in computational neuroscience and even in general neuroscience. Towards this milestone, it is mandatory to introduce modern high-performance computing technology into neuroscience research. In this article, we provide an introductory landscape about large-scale brain simulation on supercomputers from the viewpoints of computational neuroscience and modern high-performance computing technology for specialists in experimental as well as computational neurosciences. This introduction to modeling and simulation methods is followed by a review of various representative large-scale simulation studies conducted to date. Then, we direct our attention to the cerebellum, with a review of more simulation studies specific to that region. Furthermore, we present recent simulation results of a human-scale cerebellar network model composed of 86 billion neurons on the Japanese flagship supercomputer K (now retired). Finally, we discuss the necessity and importance of human-scale brain simulation, and suggest future directions of such large-scale brain simulation research.

摘要

在过去20年里,超级计算机的性能一直在稳步且呈指数级增长,并且预计还会进一步提升。这种前所未有的计算能力使我们能够构建和模拟由数百亿个神经元和数万亿个突触组成的大规模神经网络模型,这些模型具有详细的解剖连接和现实的生理参数。这样的“人类规模”大脑模拟可被视为计算神经科学乃至整个神经科学领域的一个里程碑。为了实现这一里程碑,必须将现代高性能计算技术引入神经科学研究。在本文中,我们从计算神经科学和现代高性能计算技术的角度,为实验神经科学和计算神经科学领域的专家提供有关超级计算机上大规模大脑模拟的入门概述。在介绍建模和模拟方法之后,我们回顾了迄今为止进行的各种代表性大规模模拟研究。然后,我们将注意力转向小脑,回顾更多针对该区域的模拟研究。此外,我们展示了在日本旗舰超级计算机“京”(现已退役)上构建的由860亿个神经元组成的人类规模小脑网络模型的最新模拟结果。最后,我们讨论人类规模大脑模拟的必要性和重要性,并提出此类大规模大脑模拟研究的未来方向。

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Human-scale Brain Simulation via Supercomputer: A Case Study on the Cerebellum.通过超级计算机进行人体尺度的大脑模拟:以小脑为例的案例研究
Neuroscience. 2021 May 10;462:235-246. doi: 10.1016/j.neuroscience.2021.01.014. Epub 2021 Jan 20.
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Simulation of a Human-Scale Cerebellar Network Model on the K Computer.在“京”计算机上对人体尺度小脑网络模型进行模拟。
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