Neuromatch Academy: a 3-week, online summer school in computational neuroscience

B. M. ’t Hart, T. Achakulvisut, A. Akrami, Bradly Alicea, Ulrik R Beierholm, Gunnar Blohm, Kathryn Bonnen, John S Butler, Brandon Caie, You Cheng, H. Chow, Isaac David, Eric E. J. DeWitt, Jan Drugowitsch, Kshitij Dwivedi, P. Fiquet, Jeremy Forest, Byron Galbraith, Qingling Gu, Pankaj Gupta, Alexandre Hyafil, K. Kording, Arvind Kumar, Patrick Mineault, John D. Murray, Megan A. K. Peters, P. Schrater, C. Stringer, P. Wallisch, B. Wyble
{"title":"Neuromatch Academy: a 3-week, online summer school in computational neuroscience","authors":"B. M. ’t Hart, T. Achakulvisut, A. Akrami, Bradly Alicea, Ulrik R Beierholm, Gunnar Blohm, Kathryn Bonnen, John S Butler, Brandon Caie, You Cheng, H. Chow, Isaac David, Eric E. J. DeWitt, Jan Drugowitsch, Kshitij Dwivedi, P. Fiquet, Jeremy Forest, Byron Galbraith, Qingling Gu, Pankaj Gupta, Alexandre Hyafil, K. Kording, Arvind Kumar, Patrick Mineault, John D. Murray, Megan A. K. Peters, P. Schrater, C. Stringer, P. Wallisch, B. Wyble","doi":"10.31219/osf.io/9fp4v","DOIUrl":null,"url":null,"abstract":"Neuromatch Academy (https://neuromatch.io/academy) was designed as an online summer school to cover the basics of computational neuroscience in three weeks. The materials cover dominant and emerging computational neuroscience tools, how they complement one another, and specifically focus on how they can help us to better understand how the brain functions. An original component of the materials is its focus on modeling choices, i.e. how do we choose the right approach, how do we build models, and how can we evaluate models to determine if they provide real (meaningful) insight. This meta-modeling component of the instructional materials asks what questions can be answered by different techniques, and how to apply them meaningfully to get insight about brain function.","PeriodicalId":75094,"journal":{"name":"The Journal of open source education","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2021-02-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"The Journal of open source education","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.31219/osf.io/9fp4v","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

Abstract

Neuromatch Academy (https://neuromatch.io/academy) was designed as an online summer school to cover the basics of computational neuroscience in three weeks. The materials cover dominant and emerging computational neuroscience tools, how they complement one another, and specifically focus on how they can help us to better understand how the brain functions. An original component of the materials is its focus on modeling choices, i.e. how do we choose the right approach, how do we build models, and how can we evaluate models to determine if they provide real (meaningful) insight. This meta-modeling component of the instructional materials asks what questions can be answered by different techniques, and how to apply them meaningfully to get insight about brain function.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Neuromatch Academy:一个为期三周的计算神经科学在线暑期学校
Neuromatch Academy (https://neuromatch.io/academy)被设计为一个在线暑期学校,在三周内涵盖计算神经科学的基础知识。这些材料涵盖了主流和新兴的计算神经科学工具,它们如何相互补充,并特别关注它们如何帮助我们更好地理解大脑的功能。材料的一个原始组成部分是其对建模选择的关注,即我们如何选择正确的方法,我们如何构建模型,以及我们如何评估模型以确定它们是否提供真正的(有意义的)洞察力。教学材料的元模型组件询问了哪些问题可以通过不同的技术来回答,以及如何有意义地应用它们来深入了解大脑功能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Ecological Forecasting and Dynamics: A graduate course on the fundamentals of time series and forecasting in ecology From Maps to Models - Tutorials for structural geological modeling using GemPy and GemGIS Planet_LB: Lattice-Boltzmann solutions for planetary geodynamics problems Manim Slides: A Python package for presenting Manim content anywhere Course Materials for an Introduction to Data-Driven Chemistry
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1