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神经科学模拟编程语言的发展趋势。

Trends in programming languages for neuroscience simulations.

作者信息

Davison Andrew P, Hines Michael L, Muller Eilif

机构信息

Unité de Neurosciences Intégratives et Computationnelles, Centre National de la Recherche Scientifique Gif sur Yvette, France.

出版信息

Front Neurosci. 2009 Dec 15;3(3):374-80. doi: 10.3389/neuro.01.036.2009. eCollection 2009.

Abstract

Neuroscience simulators allow scientists to express models in terms of biological concepts, without having to concern themselves with low-level computational details of their implementation. The expressiveness, power and ease-of-use of the simulator interface is critical in efficiently and accurately translating ideas into a working simulation. We review long-term trends in the development of programmable simulator interfaces, and examine the benefits of moving from proprietary, domain-specific languages to modern dynamic general-purpose languages, in particular Python, which provide neuroscientists with an interactive and expressive simulation development environment and easy access to state-of-the-art general-purpose tools for scientific computing.

摘要

神经科学模拟器使科学家能够依据生物学概念来表达模型,而无需操心模型实现的底层计算细节。模拟器接口的表达能力、功能以及易用性对于将想法高效且准确地转化为可行的模拟至关重要。我们回顾了可编程模拟器接口开发的长期趋势,并探讨了从专有的、特定领域语言转向现代动态通用语言(尤其是Python)的益处,Python为神经科学家提供了一个交互式且富有表现力的模拟开发环境,还能让他们轻松使用最先进的科学计算通用工具。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/297d/2796921/817350110799/fnins-03-374-g001.jpg

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