This site is dedicated to the statistical analysis of electro-encephalography (EEG) and magneto-encephalography (MEG) data using MNE-Python.

Particular emphasis is put on the statistical analysis of these data using LInear regression MOdels (i.e., LIMO).

For this purpose, we have started to replicate and extend the analysis and tools integrated in LIMO MEEG, a MATLAB toolbox originally designed to interface with EEGLAB.

Analyzing (M)EEG data with MNE-LIMO

Currently, we are implementing a series of examples to fit linear models on single subject data and derive inferential measures to evaluate the estimated effects. Please visit the single subject analysis gallery for more information on how to fit linear models to single subjects’ data.

In addition, we have started to develop methods to translate and extend these single subject analysis tools to allow group-level analyses, i.e., the estimation linear regression effects over a series of subjects. Please visit the group level analysis gallery for more information on how to carry out linear regression on data from multiple subjects.


This project is currently supported by a 2019 Google Summer of Code project grant issued to José C. García Alanis.

Special acknowledgements go to Denis A. Engemann, Jona Sassenhagen, and the MNE-Community for their support, guidance, and inputs for the project.