Before you install¶
Overview of the MNE tools suite¶
MNE-C was the initial stage of this project, providing a set of interrelated command-line and GUI programs focused on computing cortically constrained Minimum Norm Estimates from MEG and EEG data. These tools were written in C by Matti Hämäläinen.
MNE-Python reimplements the functionality of MNE-C, and extends considerably the analysis and visualization capabilities. MNE-Python is collaboratively developed and has more than 150 contributors.
The MNE-MATLAB toolbox provides a MATLAB interface to the .fif file format and other MNE data structures, and provides example MATLAB implementations of some of the core analysis functionality of MNE-C. It is distributed alongside MNE-C, and can also be downloaded from the MNE-MATLAB git repository.
MNE-CPP provides core MNE functionality implemented in C++ and is primarily intended for embedded and real-time applications.
There are also Python tools for easily importing MEG data from the Human Connectome Project for use with MNE-Python (MNE-HCP), and tools for managing MNE projects so that they comply with the Brain Imaging Data Structure specification (MNE-BIDS).
What should I install?¶
If you intend only to perform ERP, ERF, or other sensor-level analyses, MNE-Python is all you need. If you prefer MATLAB over Python, probably all you need is MNE-C — the MNE MATLAB toolbox is distributed with it — although note that the MATLAB toolbox is less actively developed than the MNE-Python module, and hence the MATLAB code is considerably less feature-complete.
If you want to transform sensor recordings into estimates of localized brain activity, you will most likely need:
FreeSurfer to convert structural MRI scans into models of the scalp, inner/outer skull, and cortical surfaces
MNE-C for constructing and solving a boundary-element model of tissue conductance, and for aligning coordinate frames between the structural MRI and the digitizations of M/EEG sensor locations
MNE-Python can be used for everything else
Getting help¶
There are three main channels for obtaining help with MNE software tools.
The MNE mailing list and MNE gitter channel are a good place to start for both troubleshooting and general questions. If you want to request new features or if you’re confident that you have found a bug, please create a new issue on the GitHub issues page. When reporting bugs, please try to replicate the bug with the MNE-Python sample data, and make every effort to simplify your example script to only the elements necessary to replicate the bug.
Next: Installing MNE-Python