Center for Neuroscience, Department of Neurobiology, Physiology, and Behavior, and Department of Ophthalmology and Vision Science, University of California - Davis, Davis, CA 95618, USA.
McGovern Institute and Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA.
Curr Opin Neurobiol. 2017 Oct;46:25-30. doi: 10.1016/j.conb.2017.06.007. Epub 2017 Jul 22.
Neuroscience research has become increasingly reliant upon quantitative and computational data analysis and modeling techniques. However, the vast majority of neuroscientists are still trained within the traditional biology curriculum, in which computational and quantitative approaches beyond elementary statistics may be given little emphasis. Here we provide the results of an informal poll of computational and other neuroscientists that sought to identify critical needs, areas for improvement, and educational resources for computational neuroscience training. Motivated by this survey, we suggest steps to facilitate quantitative and computational training for future neuroscientists.
神经科学研究越来越依赖于定量和计算数据分析以及建模技术。然而，绝大多数神经科学家仍然在传统的生物学课程中接受培训，在这种课程中，除了基础统计学之外的计算和定量方法可能没有得到足够的重视。在这里，我们提供了一份对计算神经科学家和其他神经科学家的非正式调查结果，该调查旨在确定计算神经科学培训的关键需求、改进领域和教育资源。受这项调查的启发，我们提出了一些步骤，以促进未来神经科学家的定量和计算培训。
