The meegBIDS project is funded by ANR and is a collaboration between the Inria Parietal team (Alexandre Gramfort, and Richard Höchenberger as research engineer), CEA Neurospin (Sophie Herbst and Virginie van Wassenhove), and the Paris Brain and Spine Institute ICM (Maximilien Chaumon).

An MEG helmet.

An MEG helmet.

What is it about?

Neuroimaging and neuroscience, like many other experimental disciplines, currently face important challenges such as data management, the so-called replication crisis, and the reuse or sharing of data and analysis software tools. To address these challenges, the neuroimaging community started an international effort to standardize the sharing of magnetic resonance imaging (MRI) data, and has recently extended the standard to cover  magnetoencephalography (MEG, in 2018) and electroencephalography (EEG, in 2019) data as well. We now need to ensure that this data format, known as the Brain Imaging Data Structure (BIDS),  will see a broader adoption among the scientific community, notably among French neuroimaging researchers.


Screenshot: The structure of a BIDS dataset.

The structure of a simple BIDS dataset.

We try to aid and incentivise BIDS adoption through the development of dedicated software tools that operate seamlessly on BIDS-formatted datasets. The project focuses on the less mature EEG and MEG BIDS ecosystem with three objectives:

  1. Accelerate research cycles by allowing analysis software tools to work with BIDS- formatted data.
  2. Simplify data sharing with high-quality standards thanks to automated validation tools.
  3. Train French neuroscientists to leverage existing public BIDS MEG/EEG datasets, and to share their own data with little effort.


To meet these aims, we strive to:

  • Consolidate the BIDS ​JavaScript validator for EEG/MEG. It allows simple validation of local files without any software installation besides a regular web browser.
  • Make the ​MNE-Python software – which is used by dozens of research groups around the globe – more BIDS compatible using the MNE-BIDS project.
  • Develop the first autonomous applications (a.k.a. BIDS apps) that can run a full MEG/EEG data analysis in a secured cloud.
  • Share datasets and advanced analysis pipelines from the research teams at CEA Neurospin and ICM with the neuroscience community to establish standardized and reproducible data processing across labs (and accessorily promote the French community)
  • Organize and disseminate tools and knowledge via a satellite workshop focusing on BIDS EEG/MEG software ecosystem during the CuttingEEG workshop happening in Marseille in 2020, as well as in other main neuroscience conferences worldwide (e.g. BIOMAG, HBM, FENS).
MNE Source Estimate.

Analysis of BIDS neuroimaging data using MNE-Python.

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