workshop / practicalmeeg2025 /

PracticalMEEG workshop in Aix-en-Provence

PracticalMEEG offers an intensive three and a half day training program, featuring both plenary presentations of the theoretical concepts and immersive hands-on tutorials for four open-source packages: FieldTrip, EEGLAB, MNE-Python, and Brainstorm. Attendees will develop practical skills to create a complete MEEG analysis pipeline from preprocessing and source-level analysis to group-level statistics – based on exemplar or personal dataset using one or more of the four leading software packages.

Where

The entire meeting will take place at the building named Le Cube on the Aix-Marseille University – Schuman Campus. The address is 29 Av. Robert Schuman, 13100 Aix-en-Provence.

When

Oct 28-31, 2025.

Who

The FieldTrip tutorials will be presented and tutored by Robert Oostenveld and Songyun Bai from the Donders Institute for Brain, Cognition and Behaviour in Nijmegen, the Netherlands.

There will also be other experts from MNE-Python, Brainstorm and EEGLAB with their respective tutorials, and jointly we will organize the plenary lectures.

Hands-on program and training material

How to prepare

Get an overview of FieldTrip

Please take a quick look at the FieldTrip reference paper if you have not done so already. If you have an hour or so, you can watch this introductory lecture. Note that more recorded lectures are available as video.

Download and install a recent FieldTrip version

Please download the most recent version of the FieldTrip toolbox from here or from GitHub. As we did some last miniute bugfixes to make all tutorials run smoothly, you should have version 20250928 or later.

Please read this FAQ on how to set your path. After adding the FieldTrip main directory to your path, you should type ft_defaults which will add the required subdirectories (which depend on your MATLAB version). We recommend to put ft_defaults in your MATLAB startup.m file.

Download and organize the scripts and data

We will use a small datainfo_subject.m function that specifies the input and output data files for each participant. You can download that from the code folder on our download server. Please organize the workshop data and code as follows:

/Volumes/usbdisk/practicalmeeg2025/
├── README
├── code
│   ├── README.md
│   ├── atlas_subparc374_8k.mat
│   ├── datainfo_subject.m
│   └── ...
└── ds000117-pruned
│   ├── CHANGES
│   ├── README
│   ├── dataset_description.json
│   ├── derivatives
│   ├── participants.tsv
│   ├── stimuli
│   ├── sub-01
│   └── ...
└── derivatives
    ├── anatomy
    ├── groupanalysis
    ├── raw2erp
    ├── sensoranalysis
    └── sourceanalysis

The /Volumes/SamsungT7/practicalmeeg2025 directory is where I have the data on my laptop (actually on an external SSD), for you that would be somewhere else. There should be a code directory with (at least) the datainfo_subject.m function, there should be the ds000117-pruned directory with the raw data in subdirectories, and there should be a derivatives directory with one subdirectory per analysis step.

The derivatives directory contains (or will contain) the results of the analysis, you can download precomputed results as .mat files from our download server. For some steps that is not needed and you will compute them yourself, but for some lengthy analysis you will continue to work with the precomputed results of the previous step.

Download the raw data

You could download all data from OpenNeuro. However, that would be either a very large download, or you would have to install datalad to get the subset of the data used in this workshop. To make it easy for you, we provide a “pruned” version that only contains the subset of files needed.

You can download the pruned data as the ds000117-pruned folder on our download server. Note that this is a WebDav server and you should use a WebDav client like CyberDuck or FileZilla. On Windows you can also map it as a network drive. By using a WebDav client you can maintain the folder structure when downloading, which is important!

Besides the raw data, we will also use some already processed data (as some computations take too long). Specifically, we have prepared and shared the headmodel and sourcemodel for the selected subject. Furthermore, we have processed all subjects up to and including to the source level, as that is what we will use for the group analysis. This processed data is available from the derivatives folder on our download server. Please note that this is not the same as the derivatives that is contained within the BIDS ds000117-pruned data: that only contains the MaxFiltered data and the FreeSurfer output, not the FieldTrip-processed data.

 

Tags: practicalmeeg2025