Brainstorm Tutorials

The following pages will take you through a typical workflow of data analyses that will feature most of the tools and applications of Brainstorm. We are updating these pages constantly, keeping up with new developments and features in the software: you are therefore welcome to suggest improvements and additions but also to contribute by becoming an editor of this wiki. Please email us if you would like to contribute.

These tutorial pages suppose you are comfortable with the basic concepts of MEG and EEG source imaging. If you're not, we engage you to read some background information, which will quickly help you getting up to speed with this field:

• A non-technical overview of MEG and EEG, with an emphasis on source modeling and imaging: here,

• Slides from a selection of educational courses at megcommunity.org,

• Reference books:
  • Peter Hansen, Morten Kringelbach, and Riitta Salmelin (Eds)

    MEG: An Introduction to Methods, Oxford University Press; (29 July 2010); 448 pages; ISBN-13: 978-0195307238

  • The following book features an extensive introduction to MEG:

    • The Oxford Handbook of Social Neuroscience (Oxford Library of Psychology), Oxford University Press, (Sept 2011) Jean Decety & John T. Cacioppo (Eds), ISBN-10: 019534216X, 1128 pages.

    • A draft version of the MEG chapter by Sylvain Baillet can be found here.

• You can also ask us to come and organize a training session at your institution, or visit us to obtain training (McGill's Montreal Neurological Institute).

Now you are well equipped to go through the software tutorial. Enjoy!

Tutorial Guidelines

1. Go through the following 12 steps to get started with Brainstorm. In just a few hours, you will be introduced to the essential features of the application.

2. Read more tutorials (see Advanced Tutorials below), that may be more specific to your personal interests/needs.

3. If you need a printed version of a page, click on the "print" link at the top-right corner of the page.

Get started: 12 easy steps through Brainstorm

• ?0. Brainstorm architecture

• ?1. First steps

• ?2. Importing individual anatomy

• ?3. Importing MEG recordings

• ?4. Exploring the recordings

• ?5. Computing a head model

• ?6. Computing a noise covariance matrix

• ?7. Source estimation

• ?8. Scouts: Cortical regions of interest

• ?9. Processes: Graphical batching interface

• ?10. Statistics

• ?11. Time-frequency

Advanced tutorials

Exploring Continuous Recordings

1. ?Review raw recordings and edit markers

2. Import and process raw recordings

Anatomy and registration

1. Brainstorm coordinate systems

2. MRI segmentation with BrainVISA

3. MRI segmentation with BrainSuite

4. Warping default anatomy

Source modeling

1. Boundary Element Modeling (BEM)

2. Source estimation not constrained to cortical surface

3. ?Import and visualize dipole models from another software (Neuromag's Xfit)

4. ?BrainEntropy MEM (Maximum Entropy on the Mean)

Other useful how-to's

1. How to cite Brainstorm in your publications

2. ?How to use Brainstorm without the GUI

3. ?How to compile Brainstorm

4. Known bugs

Getting started (details)

• ?0. Brainstorm architecture

  • Brainstorm folders

  • Brainstorm database (concept)

  • Brainstorm database (files)

• ?1. First steps

  • Create first protocol

  • Fiducials selection (MRI Viewer)

  • Protocol exploration

  • MRI visualization

  • Surfaces visualization

  • Coordinates tab

• ?2. Importing individual anatomy

  • Dataset description

  • Import MRI

  • Import surfaces

  • Downsample and merge surfaces

  • Check registration with MRI

  • Fix registration with MRI

  • What happened on the hard drive

• ?3. Importing MEG recordings

  • Import recordings

  • Channel file

  • MEG recordings

  • Managing conditions

• ?4. Exploring the recordings

  • Display recordings

  • Time exploration

  • Sensors selection

  • Time series in columns

  • Time selection

  • Good / bad channels

  • Colormap configuration

  • Toolbar / Manipulating multiple windows

  • Database navigator

  • Snapshots

  • Keyboard shortcuts

• ?5. Computing a head model

  • Forward problem

  • Single sphere model

  • Overlapping spheres model

  • Selection of a head model

  • Batching head model computation

• ?6. Computing a noise covariance matrix

  • Compute from recordings

  • Noise covariance from another dataset

• ?7. Source estimation

  • Computing sources for a single data file

  • Sources visualization

  • Computing sources for multiple data files

  • Minimum norm options

  • Project sources on default anatomy

• ?8. Scouts: Cortical regions of interest

  • Creating a scout

  • Scout function

  • Multiple scouts

  • Load/save scouts

  • Display scouts time series from the database tree

  • Scout toolbar and menus

• ?9. Processes: Graphical batching interface

  • Selecting files to process

  • Creating a pipeline

  • Another example: z-score and scouts

• ?10. Statistics

  • Binary processes

  • Mixing recordings from different runs

  • Tests

• ?11. Time-frequency

  • Introduction to complex Morlet wavelets

  • Edge effects

  • TF: Recordings

  • Description of the options

  • Display time-frequency maps

  • Contents of the "timefreq" files

  • Time and frequency bands

  • TF: Clusters time series

  • TF: Cortical sources

  • TF: Scouts time series

  • Processing time-frequency files