Real-time million-synapse simulation of rat barrel cortex.

Real-time million-synapse simulation of rat barrel cortex.
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DOI:
10.3389/fnins.2014.00131
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发表时间:
2014
影响因子:
4.3
通讯作者:
Furber S
Furber S
中科院分区:
医学2区
文献类型:
--
作者:
Sharp T;Petersen R;Furber S

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神经回路的模拟在规模和速度上受到可用计算资源的限制,特别是受到大脑和高性能计算机在并行性和通信模式上的差异的限制。SpiNNaker是一种计算机架构,通过模拟神经组织的结构和功能来解决这个问题,它使用了许多低功耗处理器和受轴突轴突启发的处理器间通信机制。在这里,我们证明了千处理器SpiNNaker原型可以模拟由50,000个神经元和5000万个突触组成的啮齿动物桶系统模型。我们使用PyNN库来指定模型,并使用Python的固有特性来控制实验过程和分析。这些模型再现了已知的丘脑皮质反应转化,展示了已知的、平衡的兴奋和抑制动力学,并显示了通过皮层表层的活动的时空分布。这些演示是在开发中的具有百万处理器的SpiNNaker机器上对整个皮质区域进行可处理模拟的重要一步。
Simulations of neural circuits are bounded in scale and speed by available computing resources, and particularly by the differences in parallelism and communication patterns between the brain and high-performance computers. SpiNNaker is a computer architecture designed to address this problem by emulating the structure and function of neural tissue, using very many low-power processors and an interprocessor communication mechanism inspired by axonal arbors. Here we demonstrate that thousand-processor SpiNNaker prototypes can simulate models of the rodent barrel system comprising 50,000 neurons and 50 million synapses. We use the PyNN library to specify models, and the intrinsic features of Python to control experimental procedures and analysis. The models reproduce known thalamocortical response transformations, exhibit known, balanced dynamics of excitation and inhibition, and show a spatiotemporal spread of activity though the superficial cortical layers. These demonstrations are a significant step toward tractable simulations of entire cortical areas on the million-processor SpiNNaker machines in development.
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