Teaching	Research	Outreach
Undergraduate and Graduate Course Materials	Tools for Computational Neuroscience Research	K-12 Content, RET, and Media

Information

This website contains a collection of web-based tutorials and Jupyter notebooks discussing the various topics of Computational Neuroscience. These notebooks provide an introduction to basic neuroscience, differential equations, single cell analysis, large scale neural networks, and signal processing. Many pages are available in an interactive manner and should be run this way to take full advantage of the content. Some of these pages are loosely based on lectures in the undergradute/graduate course “Computational Neuroscience” developed by Satish Nair, Neural Engineering Lab, Department of Electrical Engineering and Computer Science, University of Missouri.

Literature

The contents are based on the following literature:

• Eugene M. Izhikevich, The Dynamical Systems in Neuroscience: Geometry of Excitability and Bursting, MIT Press, 2007

Contributors (About link)

• Satish Nair
• Prasad Calyam
• Dong Xu
• Trupti Joshi
• Tyler Banks
• Ben Latimer
• Ziao Chen
• Feng Feng
• Wei
• Zhenru Chen

Contributing to this project

• Using Git
• Website Structure

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This page is part of a collection of pages on various topics of Computational Neuroscience. Please direct questions and suggestions to the author Tyler Banks at tbanks@mail.missouri.edu.