Michigan Neuroimaging Initiative

Software information

Matlab student license

UM students can sign up for a free Matlab license for their personal computer. For information about this program, please see the ITS Licensing, Matlab for students web page at https://www.itcs.umich.edu/sw-info/math/MATLABStudents.html This license is good for one calendar year and must be renewed annually.

Python distributions

People talk about the Python programming language quite a bit. It can be daunting getting started because so much functionality is in libraries that have to be separately installed. There are two companies that have created installers for Python and many of its most useful libraries. If you wish to work on Python on your own computer, we recommend that you pick one of them to use.


The Anaconda Python distribution provides precompiled Python and several hundred of the most popular libraries. This is probably the easiest way to get started with Python because you probably won't have to spend a lot of time figuring out how to install the next library dependency. It has recently expanded to also provide a management environment for R. Go to Anaconda to download it.

Python tutorials

Nipype Beginner’s Guide

Michael Notter created a very nice web site to introduce people to using the Nipype Python library to write automated, programmatic neuroimaging pipelines. The site contains a short introduction to neuroimaging, a nice diagram of typical processing steps in a neuroimaging analysis, as well covering Nipype itself.

functional MRI methods

The materials from the Psych 214 course at UC Berkeley is online at Psych 214 — functional MRI methods. The course aims to teach you about the structure of brain data, how to work with it, analytic concepts and how to code them in Python, as well as inculcating the instructors' ideas about programming practices including version control, reproducibility, etc.


Much of the reason Python has become popular is because it is now possible to program quite a lot of the mathematics that was previously only well-handled by Matlab. That is possible because of NumPy, a library of mathematical and matrix functions, that is used by virtually all Python libraries that do a lot of mathematics. These are some of the guides to NumPy on the internet.