大规模皮质网络的神经形态建模抽象与模拟

J. Krichmar, N. Dutt, J. Nageswaran, Micah Richert
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引用次数: 7

摘要

生物神经系统以其在高噪声环境下的鲁棒性和高能效而闻名。我们概述了大脑的关键建模抽象,并重点介绍了尖峰神经网络模型。我们讨论了神经元处理的各个方面以及与这些过程建模相关的计算问题。虽然这些算法中的许多可以在专门的硬件上有效地实现,但我们提出了一个使用基于GPU的模拟环境模拟视觉皮层的案例研究,该环境易于被神经科学家和计算机科学家使用,并且足够有效地构建与大脑网络相当的非常大的网络。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Neuromorphic modeling abstractions and simulation of large-scale cortical networks
Biological neural systems are well known for their robust and power-efficient operation in highly noisy environments. We outline key modeling abstractions for the brain and focus on spiking neural network models. We discuss aspects of neuronal processing and computational issues related to modeling these processes. Although many of these algorithms can be efficiently realized in specialized hardware, we present a case study of simulation of the visual cortex using a GPU based simulation environment that is readily usable by neuroscientists and computer scientists and efficient enough to construct very large networks comparable to brain networks.
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