Oct 27-31, 2025

Aix-Marseille Université

France

Three ways to join!

Regular participants



3.5 days analysis training in M/EEG with one toolbox

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Optional poster presentation



No prior experience in M/EEG analysis required

Fee 450€

TrainEErs

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Half day instructor training + 3.5 days as a teaching assitant with one toolbox



Optional poster presentation



Advanced experience with one toolbox required

Apply here by August 1st

Fee 650€

Toolbox bouquet florist

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1-3h teaching others to use your tool on Oct. 30 pm.



Online only satellite (no poster)



Know your tool and be ready to present it

Apply here by July 1st

FrEE

PracticalMEEG

Context

Analysing MEG or EEG data requires mastering complex mathematical concepts and software toolboxes with specific capabilities, balancing efficiency, ease of use, and the specific analytical methods needed for a specific study. Choose your toolbox, and join PracticalMEEG!

Content

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

New this year

A dedicated “Traineers” track for participants with strong expertise in one of these toolboxes who want to develop their training skills. Traineers will also serve as helpers in their respective software tutorials throughout the event. This hands-on experience will reinforce their own learning while providing valuable support to fellow attendees.

A poster session will allow participants to present their latest results and discuss their methodological approaches and implementation with pairs.

Keynote : AI use in M/EEG analyses: How to be a (good) practitioner in LLM era ?

Sylvain Chevallier, LISN-CNRS, France

AI-based models are ubiquitous in many scientific domains, with fast-evolving technologies and actors, and M/EEG research is no exception. On the one hand, transformers offer powerful models for brain time series encoding/decoding, even though foundation models have yet to be largely adopted by the community. On the other hand, AI tools are currently revolutionizing experimental practice, offering an impressive range of empowering agents for M/EEG practitioners. But a good MEEG practitioner should know the tricks of the trade for all the tasks required to complete a study: experimental design, bibliographical search, code writing, results interpretation, paper writing… and large language models (LLMs) — such as ChatGPT and other conversational agents — are available to assist you in all those tasks. Should you use them? Could you have confidence in the bibliographical references of LLMs? Is it possible to do vibe coding for your preferred MEEG toolbox? And what is vibe coding and could you do vibe research? During this lecture, we will investigate all these topics and more, like the environmental cost of using LLM, their legal implications and their ethical limits.