Computational training for the next generation of neuroscientists
Author(s)
Goldman, Mark S; Fee, Michale Sean
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Alternative title
Computational training for the next generation of neuroscientists
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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.
Date issued
2017-07Department
Massachusetts Institute of Technology. Department of Brain and Cognitive Sciences; McGovern Institute for Brain Research at MITJournal
Current Opinion in Neurobiology
Publisher
Elsevier
Citation
Goldman, Mark S, and Michale S Fee. “Computational Training for the Next Generation of Neuroscientists.” Current Opinion in Neurobiology 46 (October 2017): 25–30 © 2017 Elsevier Ltd
Version: Author's final manuscript
ISSN
0959-4388