User Manual
If you are new to MNE, consider first reading the Cookbook, as it
gives some simple steps for starting with analysis. The other sections provide
more in-depth information about how to use the software.
You can also jump to the Python API Reference for specific Python function
and class usage information.
Cookbook
A quick run-through of the basic steps involved in M/EEG source analysis.
Reading your data
How to get your raw data loaded in MNE.
Preprocessing
Dealing with artifacts and noise sources in data.
Source localization
Projecting raw data into source (brain) space.
Time-frequency analysis
Decomposing time-domain signals into time-frequency representations.
Statistics
Using parametric and non-parametric tests with M/EEG data.
Decoding
Datasets
How to use dataset fetchers for public data
Migrating
Pitfalls
C Tools
Additional information about various MNE-C tools.
MATLAB Tools
Information about the MATLAB toolbox.
Appendices
More details about our implementations and software.