This lesson is in the early stages of development (Alpha version)

Introduction to Working with MRI Data in Python

The goal of this lesson is to provide an introduction to the core concepts involved in working with magnetic resonance imaging (MRI) data. It is intended for learners with no prior experience.

The lesson will introduce different types of MRI modalities and how they can be easily organized and shared. This lesson is also a pre-requisite for the Structural, Functional and Diffusion MRI Data Analysis lessons, which go more in-depth into their respective MRI modalities.

Over the past decade, the neuroimaging field has produced (and continues to produce) incredible amounts of data. As a result, the scientific community has developed a diverse set of tools to facilitate the access, analysis and visualization of this data. This lesson will start you on a path towards using these tools effectively in your own work.


This lesson assumes that you have some working knowledge of the Unix shell and Python. These requirements can be fulfilled by:

  • completing the Software Carpentry Unix and/or Python lessons
  • previous exposure to these tools

Getting Started

To get started, follow the directions on the Setup page to install the necessary software packages and download the data.


Setup Download files required for the lesson
00:00 1. Before we start What is Python and why should I learn it?
00:30 2. From the scanner to our computer What are the main MRI modalities?
What’s the first step necessary to start working with MRI data?
01:00 3. Anatomy of a NIfTI How are MRI data represented digitally?
01:25 4. Data organization with BIDS
02:10 5. Exploring open MRI datasets How does standardizing neuroimaging data ease the data exploration process
02:55 6. BIDS derivatives
03:40 Finish

The actual schedule may vary slightly depending on the topics and exercises chosen by the instructor.