Tutorials

Introductory tutorials to MNE.

Introductory tutorials

These tutorials cover the basic sensor-space processing pipeline (loading raw data, segmenting into epochs, and averaging epochs by condition), as well as introducing the mne.Info, events, and mne.Annotations data structures.

Working with continuous data

These tutorials cover the basics of loading EEG/MEG data into Python, querying and manipulating the raw data, some basic plotting, and how to save or export continuous data.

Segmenting continuous data into epochs

These tutorials cover epoched data, and how it differs from working with continuous data.

Estimating evoked responses

These tutorials cover estimates of evoked responses (i.e., averages across several repetitions of an experimental condition).

Time-frequency analysis

These tutorials cover frequency and time-frequency analysis of neural signals.

Machine learning models of neural activity

These tutorials cover some of the machine learning methods available in MNE-Python.

Simulation

These tutorials describe how to populate MNE-Python data structures with arbitrary data, using the array-based constructors and the simulation submodule.

Discussions

These tutorials offer longer, more nuanced discussions of key topics in the analysis of neural data.