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.
Preprocessing¶
These tutorials cover various preprocessing techniques for continuous data, as well as some diagnostic plotting methods.
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.
Statistical analysis of sensor data¶
These tutorials describe some approaches to statistical analysis of sensor-level data.
Statistical analysis of source estimates¶
These tutorials cover within-subject statistical analysis of source estimates.
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.
Sample datasets¶
These tutorials illustrate some of the sample datasets available through MNE-Python.
Discussions¶
These tutorials offer longer, more nuanced discussions of key topics in the analysis of neural data.
Miscellaneous tutorials¶
Assorted tutorials on configuring MNE-Python, working with eCOG data, and other topics.