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 API Reference for specific Python function and class usage information.


A quick run-through of the basic steps involved in M/EEG source analysis.

Time frequency analysis

Decomposing time-domain signals into time-frequency representations.


Using parametric and non-parametric tests with M/EEG data.


To enable reproducibility of results, MNE-Python includes several dataset fetchers