britta-wstnr / mne_pratical_meeg_2022

Materials for MNE-Python sessions at Practical MEEG 2022

Material for the MNE-Python workshop of Practical MEEG 2022

More info on the workshop: http://practicalmeeg2022.org/

Authors of the material:

- Britta Westner, Radboud University Nijmegen, Donders Institute
- Alexandre Gramfort, Inria, CEA Neurospin
- Denis A. Engemann, Inria, CEA Neurospin

Before you arrive

Please make sure you do the following steps before the first hands-on session:

0. You will need to download this directory of scripts.
1. You will need to download the data.
2. You will need to download the extra data that we will use in some tutorials.
3. You will need to have an up-to-date version of MNE-Python installed on your machine (you need a full install with all dependencies, not "MNE-Python with core functionalities only"). See instructions at: https://mne.tools/stable/install/index.html
4. To check your installation, please look at the (very short!) notebook Check your installation. See below if you need a reminder how to start it.
5. If you are not familiar with Python, we invite you to take the time to work on these tutorials: Intro to Python, Intro to Numpy.

Start a Jupyter notebook

To start a Jupyter notebook, open your terminal and navigate to the directory where you saved this directory of scripts. Then type the command jupyter notebook and Jupyter should open in your internet browser. Click on the notebook you want to run!

Program

Day 1 (Wednesday December 14, 2022)

• 08:30 – 09:00 Registration, with coffee/tea + Welcome & intro

• 09:00 – 09:45 Lecture: Good scientific Practice (Maxime, Anne-Sophie, François)

• 09:45 - 10:30 Lecture: Importing, cleaning, and preprocessing data (Johanna)

• 10:30 – 12:30 Hands-on: Preprocessing using MNE-Python

• 12:30 – 14:00 Lunch

• 14.00 – 18:00 Toolbox Bouquet (online)

Day 2 (Thursday December 15, 2022)

• 09:00 – 09:45 Panel discussion

• 09:00 – 09:45 Lecture: Time-domain analysis (Robert)

• 10:30 – 12:30 Hands-on: Sensor-level analysis using MNE-Python

• 12:30 – 14:00 Lunch

• 14:00 – 15:3 Lecture: Spectral / Time-frequency analysis (Natalie)

• 15:30 – 17:30 Hands-on: Time-frequency analysis using MNE-Python

• 17:30 – 18:00 Panel discussion

Day 3 (Friday December 16, 2022)

• 09:00 – 10:30 Lecture: Source estimation (Britta)

• 10:30 – 12:30 Hands-on: Forward modelling and Source estimation using MNE-Python

• 12:30 – 14:00 Lunch

• 14:00 – 15:30 Lecture: Group-level analysis (Robert)

• 15:30 – 17:30 Hands-on: Group level analysis using MNE-Python

• 17:30 – 18:00 Panel discussion

References and credit

The code from this tutorial is heavily inspired from this article:

Mainak Jas, Eric Larson, Denis Engemann, Jaakko Leppakangas, Samu Taulu, Matti Hamalainen,
and Alexandre Gramfort. 2018. A Reproducible MEG/EEG Group Study With the MNE Software:
Recommendations, Quality Assessments, and Good Practices.
Frontiers in Neuroscience. 12, doi: 10.3389/fnins.2018.00530

The MNE software when used in publications should be acknowledged using citations.

To cite MNE-C or the inverse imaging implementations provided by the MNE software, please use:

A. Gramfort, M. Luessi, E. Larson, D. Engemann, D. Strohmeier, C. Brodbeck, L. Parkkonen,
M. Hämäläinen, MNE software for processing MEG and EEG data, NeuroImage, Volume 86,
1 February 2014, Pages 446-460, ISSN 1053-8119.

To cite the MNE-Python package, please use:

A. Gramfort, M. Luessi, E. Larson, D. Engemann, D. Strohmeier, C. Brodbeck, R. Goj, M. Jas,
T. Brooks, L. Parkkonen, M. Hämäläinen, MEG and EEG data analysis with MNE-Python,
Frontiers in Neuroscience, Volume 7, 2013, ISSN 1662-453X.