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Curr Opin Neurobiol. 2017 Oct;46:25-30. doi: 10.1016/j.conb.2017.06.007. Epub 2017 Jul 22.

Computational training for the next generation of neuroscientists.

Author information

1
Center for Neuroscience, Department of Neurobiology, Physiology, and Behavior, and Department of Ophthalmology and Vision Science, University of California - Davis, Davis, CA 95618, USA. Electronic address: msgoldman@ucdavis.edu.
2
McGovern Institute and Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA.

Abstract

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.

PMID:
28738240
DOI:
10.1016/j.conb.2017.06.007
[Indexed for MEDLINE]

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