Examples

General examples

General-purpose and introductory examples to MNE.

• Find events in a raw file
• Estimate covariance matrix from a raw FIF file
• Extract epochs, average and save evoked response to disk
• Reading and writing raw files
• Reading BEM surfaces from a forward solution
• Reading epochs from a raw FIF file
• Reading and writing an evoked file
• Reading a forward operator a.k.a. lead field matrix
• Reading/Writing a noise covariance matrix
• Plot topographies for MEG sensors
• Reading an event file

Inverse problem and source analysis

Estimate source activations, extract activations in labels, morph data between subjects etc.

• Compute MNE-dSPM inverse solution on evoked data
• Compute MNE-dSPM inverse solution on single epochs
• Compute MNE-dSPM inverse solution on raw data
• Compute MNE-dSPM inverse solution on evoked data in volume source space
• Extracting the time series of activations in a label
• Assemble inverse operator and compute MNE-dSPM inverse solution
• Morph source estimates from one subject to another subject
• Reading an inverse operator and view source space in 3D
• Reading a source space from a forward operator
• Reading an STC file

Preprocessing

Examples related to data preprocessing (artifact detection / rejection etc.)

• Find ECG artifacts
• Find EOG artifacts

Statistics Examples

Some examples of how to compute statistics on M/EEG data with MNE.

• Non-parametric 1 sample cluster statistic on single trial power
• Permutation F-test on sensor data with 1D cluster level
• Non-parametric between conditions cluster statistic on single trial power
• FDR correction on T-test on sensor data
• Permutation T-test on sensor data

Time-Frequency Examples

Some examples of how to explore time frequency content of M/EEG data with MNE.

• Compute the spectrum of raw data using multi-taper
• Compute power and phase lock in label of the source space
• Compute induced power in the source space with dSPM
• Time frequency : Induced power and inter-trial phase-lock