MNE is a software package for processing magnetoencephalography (MEG) and electroencephalography (EEG) data.
The MNE software computes cortically-constrained L2 minimum-norm current estimates and associated dynamic statistical parametric maps from MEG and EEG data, optionally constrained by fMRI.
This software includes MEG and EEG preprocessing tools, interactive and batch-mode modules for the forward and inverse calculations, as well as various data conditioning and data conversion utilities. These tools are provided as compiled C code for the LINUX and Mac OSX operating systems.
In addition to the compiled C code tools, MNE Software includes a Matlab toolbox which facilitates access to the fif (functional image file) format data files employed in our software and enables development of custom analysis tools based on the intermediate results computed with the MNE tools.
The third and newest component of MNE is MNE-Python which implements all the functionality of the MNE Matlab tools in Python and extends the capabilities of the MNE Matlab tools to, e.g., frequency-domain and time-frequency analyses and non-parametric statistics. This component of MNE is presently evolving quickly and thanks to the adopted open development environment user contributions can be easily incorporated.
The MNE development is supported by National Institute of Biomedical Imaging and Bioengineering grants 5R01EB009048 and P41EB015896 (Center for Functional Neuroimaging Technologies) as well as NSF awards 0958669 and 1042134.
The Matlab and Python components of MNE are provided under the simplified BSD license.
- The Cookbook
- Processing raw data
- The forward solution
- The current estimates
- Interactive analysis
- Morphing and averaging
- Data conversion
- The Matlab toolbox
- Miscellaneous utilities
- The sample data set
- Related publications
- Creating the BEM meshes
- Setup at the Martinos Center
- Installation and configuration
- Release notes
- Licence agreement
- Getting started with MNE command line
- MNE with Python
- MNE with CPP
- Cite MNE and MNE-Python