Tutorials

These tutorial pages suppose you are comfortable with the basic concepts of MEG/EEG analysis and source imaging. If you're not, we encourage you to read some background literature.
To get a quick overview of the software interface, you can watch this introduction video.

Get started

The easiest way to get started with Brainstorm is to read and follow carefully these introduction tutorials. They can be separately consulted (links below), or all in one page.

Starting a new study     1. Create a new protocol     2. Import the subject anatomy     3. Explore the anatomy Reviewing     4. Channel file / MRI registration     5. Continuous recordings     6. Multiple windows     7. Event markers Pre-processing     8. Stimulation delays     9. Select files / Run processes     10. Power spectrum / Frequency filters     11. Bad channels     12. Artifact detection     13. Artifact cleaning with SSP     14. Additional bad segments

Epoching and averaging     15. Import epochs     16. Average response     17. Visual exploration     18. Colormaps     19. Clusters of sensors Source modeling     20. Head model     21. Noise/data covariance     22. Source estimation     23. Scouts Advanced processes     24. Time-frequency     25. Difference     26. Statistics     27. Workflows     28. Scripting

Other analysis scenarios

EEG and epilepsy iEEG Contact Localization (UNDER CONSTRUCTION) SEEG epileptogenicity maps ECoG+sEEG epilepsy (BIDS) MEG visual: single subject (Elekta/BIDS) MEG visual: group study (Elekta/BIDS) MEG current phantom (CTF) MEG current phantom (Elekta)

MEG resting state & OMEGA database (CTF) MEG corticomuscular coherence (CTF) MEG Human Connectome Project (4D) MEG median nerve (Elekta) MEG median nerve (Yokogawa) MEG median nerve (CTF) NIRS finger tapping

Advanced tutorials

Anatomy and registration Brainstorm coordinate systems MRI segmentation: CAT12, FreeSurfer, BrainSuite, BrainVISA, FastSurfer, CIVET Using the anatomy templates Warping the anatomy templates Group analysis: Subjects coregistration Digitize EEG electrodes and head shape Real-time head positioning (CTF MEG) Head motion detection (MEG) Recordings Montage editor ICA analysis SSP cookbook Detect subject movements Synchronization with eye tracker Scripting How to write your own process Export volume sources to SPM8/SPM12 Export surface sources to SPM12 Export raw data to BIDS format Software Plugins MNE-Python How to cite Brainstorm Known bugs Export figures to Plotly

Source modeling Volume source estimation Deep cerebral structures Realistic head model: BEM with OpenMEEG Dipoles: Scanning and displaying Dipoles: FieldTrip dipole fitting Maximum entropy on the mean (MEM) Other beamforming methods Simulations Finite Element Modeling Realistic head model: FEM with DUNEuro FEM mesh generation FEM tensors estimation FEM median nerve example Signal processing Machine learning: Decoding / MVPA Phase-amplitude coupling: Method Phase-amplitude coupling: Example Partial Least Squares (PLS) Epileptogenic Zone Fingerprint FOOOF: Fitting Oscillations & One-Over-F SPRiNT: Spectral Param. Resolved in Time Connectivity Functional connectivity Corticomuscular coherence Connectivity graphs Virtual fibers for connectivity Granger causality

Single/Multi-Unit Electrophysiology

Learn how to use Brainstorm for analyzing single/multi-unit electrophysiological data in a variety of preparations:

Importing raw e-phys data Spike-sorting Using external spike-sorters Converting raw data to LFP

Tuning curves Noise correlation Spike field coherence Raster plots Spike triggered average

Background readings

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

• MEG for Human Electrophysiology and Imaging (Baillet S, Nature Neuroscience, 2017)

• Connectomics of Human Electrophysiology (Sadaghiani S, Brookes M, Baillet S, Neuroimage, 2022)

• Introduction to MEG (Medical College of Wisconsin)
  A non-technical overview of MEG and EEG, with an emphasis on source modeling.

• MEG: An Introduction to Methods
  Editors: P Hansen, M Kringelbach, R Salmelin, Oxford University Press, 2010, 448 pages.

• The Oxford Handbook of Social Neuroscience
  Editors: J Decety, JT Cacioppo, Oxford University Press, 2011, 1128 pages
  A draft version of the MEG chapter by Sylvain Baillet can be found here.

• Good practice for conducting and reporting MEG research, Gross et al, Neuroimage, 2013.

• MATLAB for Brain and Cognitive Scientists, Mike X Cohen, MIT press, 2017

• Slides from a selection of educational courses: megcommunity.org

• We can also come and organize a training session at your institution, or visit us at the MNI.

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