User ManualΒΆ

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.