Graphical user interface (GUI) for MNE, a Python-based toolbox for EEG/MEG analysis.

MNELAB requires Python >= 3.6. In addition, the following Python packages are required:

• PyQt5 >= 5.6.0
• numpy >= 1.8.1
• scipy >= 0.17.1
• matplotlib >= 2.0.0
• mne >= 0.17

Optional dependencies provide additional features if installed:

• scikit-learn (ICA computation via FastICA)
• python-picard (ICA computation via PICARD)
• pyEDFlib (export raw to EDF/BDF)

In general, it is recommended to always use the latest package versions.

• Basic preprocessing (Filters, resampling, annotations of bads channels, importing of events and annotations, ICA processing, interpolation of bad channels, referencing...)
• Epoching of raw data with markers or events, Evoking of epoched data.
• Visualization tools (Raw data, Interactive epoch image plots, Interactive power spectrum density and Interactive Time-Frequency dialog)
• Batch processing: Does the same process on a batch of files, like filtering, resampling or computing time-frequency or power spectrum density of each file.

MNELAB comes with the following features that are not available in MNE:

• Export raw to EDF/BDF (requires pyEDFlib)
• Export raw to EEGLAB SET
• Import Cartool format (.sef )
• Import/Export to brainvision format (.vhdr)

A package on PyPI will be available soon. Meanwhile, to use MNELAB first install all dependencies (e.g. via pip or conda) and then download the source code. Unpack it into a folder of your choice and run python3 mnelab.py in this folder (if this does not work try python mnelab.py, just make sure to use Python 3).

• MNELAB is under the BSD 3-clause license (Copyright (c) 2017, Clemens Brunner) original work
• Philistine subfolder is under the BSD 3-clause license (Copyright (c) 2017--2018, Phillip Alday) original work
• Modifications of original works are under the BSD 3-clause license (Copyright (c) 2019, Victor Férat, Tanguy Vivier)