Examples Gallery¶

Contents

Connectivity Analysis Examples
Examples on open datasets
Machine Learning (Decoding, Encoding, and MVPA)
Forward modeling
Inverse problem and source analysis
Input/Output
Preprocessing
Real-time M/EEG Acquisition
Data Simulation
Statistics Examples
Time-Frequency Examples
Visualization

Connectivity Analysis Examples ¶

Examples demonstrating connectivity analysis in sensor and source space.

../_images/sphx_glr_plot_cwt_sensor_connectivity_thumb.png

Compute seed-based time-frequency connectivity in sensor space

../_images/sphx_glr_plot_mixed_source_space_connectivity_thumb.png

Compute mixed source space connectivity and visualize it using a circular graph

../_images/sphx_glr_plot_mne_inverse_coherence_epochs_thumb.png

Compute coherence in source space using a MNE inverse solution

../_images/sphx_glr_plot_mne_inverse_connectivity_spectrum_thumb.png

Compute full spectrum source space connectivity between labels

../_images/sphx_glr_plot_mne_inverse_label_connectivity_thumb.png

Compute source space connectivity and visualize it using a circular graph

../_images/sphx_glr_plot_mne_inverse_psi_visual_thumb.png

Compute Phase Slope Index (PSI) in source space for a visual stimulus

../_images/sphx_glr_plot_sensor_connectivity_thumb.png

Compute all-to-all connectivity in sensor space

Examples on open datasets ¶

Some demos on common/public datasets using MNE.

../_images/sphx_glr_plot_brainstorm_data_thumb.png

Brainstorm tutorial datasets

../_images/sphx_glr_plot_hf_sef_data_thumb.png

../_images/sphx_glr_plot_megsim_data_thumb.png

MEGSIM experimental and simulation datasets

../_images/sphx_glr_plot_megsim_data_single_trial_thumb.png

MEGSIM single trial simulation dataset

../_images/sphx_glr_plot_opm_data_thumb.png

Optically pumped magnetometer (OPM) data

../_images/sphx_glr_plot_opm_rest_data_thumb.png

VectorView and OPM resting state datasets

../_images/sphx_glr_spm_faces_dataset_thumb.png

From raw data to dSPM on SPM Faces dataset

Machine Learning (Decoding, Encoding, and MVPA)¶

Decoding, encoding, and general machine learning examples.

../_images/sphx_glr_decoding_rsa_thumb.png

Representational Similarity Analysis

../_images/sphx_glr_plot_decoding_csp_eeg_thumb.png

Motor imagery decoding from EEG data using the Common Spatial Pattern (CSP)

../_images/sphx_glr_plot_decoding_csp_timefreq_thumb.png

Decoding in time-frequency space data using the Common Spatial Pattern (CSP)

../_images/sphx_glr_plot_decoding_spatio_temporal_source_thumb.png

Decoding source space data

../_images/sphx_glr_plot_decoding_spoc_CMC_thumb.png

Continuous Target Decoding with SPoC

../_images/sphx_glr_plot_decoding_time_generalization_conditions_thumb.png

Decoding sensor space data with generalization across time and conditions

../_images/sphx_glr_plot_decoding_unsupervised_spatial_filter_thumb.png

Analysis of evoked response using ICA and PCA reduction techniques

../_images/sphx_glr_plot_decoding_xdawn_eeg_thumb.png

XDAWN Decoding From EEG data

../_images/sphx_glr_plot_ems_filtering_thumb.png

Compute effect-matched-spatial filtering (EMS)

../_images/sphx_glr_plot_linear_model_patterns_thumb.png

Linear classifier on sensor data with plot patterns and filters

../_images/sphx_glr_plot_receptive_field_mtrf_thumb.png

Receptive Field Estimation and Prediction

Forward modeling ¶

From BEM segmentation, coregistration, setting up source spaces to actual computation of forward solution.

../_images/sphx_glr_plot_decimate_head_surface_thumb.png

Decimating scalp surface

../_images/sphx_glr_plot_forward_sensitivity_maps_thumb.png

Display sensitivity maps for EEG and MEG sensors

../_images/sphx_glr_plot_left_cerebellum_volume_source_thumb.png

Generate a left cerebellum volume source space

../_images/sphx_glr_plot_source_space_morphing_thumb.png

Use source space morphing

Inverse problem and source analysis ¶

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

../_images/sphx_glr_plot_compute_mne_inverse_epochs_in_label_thumb.png

Compute MNE-dSPM inverse solution on single epochs

../_images/sphx_glr_plot_compute_mne_inverse_raw_in_label_thumb.png

Compute sLORETA inverse solution on raw data

../_images/sphx_glr_plot_compute_mne_inverse_volume_thumb.png

Compute MNE-dSPM inverse solution on evoked data in volume source space

../_images/sphx_glr_plot_covariance_whitening_dspm_thumb.png

Demonstrate impact of whitening on source estimates

../_images/sphx_glr_plot_custom_inverse_solver_thumb.png

Source localization with a custom inverse solver

../_images/sphx_glr_plot_dics_source_power_thumb.png

Compute source power using DICS beamfomer

../_images/sphx_glr_plot_gamma_map_inverse_thumb.png

Compute a sparse inverse solution using the Gamma-Map empirical Bayesian method

../_images/sphx_glr_plot_label_activation_from_stc_thumb.png

Extracting time course from source_estimate object

../_images/sphx_glr_plot_label_from_stc_thumb.png

Generate a functional label from source estimates

../_images/sphx_glr_plot_label_source_activations_thumb.png

Extracting the time series of activations in a label

../_images/sphx_glr_plot_lcmv_beamformer_thumb.png

Compute LCMV beamformer on evoked data

../_images/sphx_glr_plot_lcmv_beamformer_volume_thumb.png

Compute LCMV inverse solution in volume source space

../_images/sphx_glr_plot_mixed_norm_inverse_thumb.png

Compute sparse inverse solution with mixed norm: MxNE and irMxNE

../_images/sphx_glr_plot_mixed_source_space_inverse_thumb.png

Compute MNE inverse solution on evoked data in a mixed source space

../_images/sphx_glr_plot_mne_crosstalk_function_thumb.png

Compute cross-talk functions (CTFs) for labels for MNE/dSPM/sLORETA

../_images/sphx_glr_plot_mne_point_spread_function_thumb.png

Compute point-spread functions (PSFs) for MNE/dSPM/sLORETA

../_images/sphx_glr_plot_morph_surface_stc_thumb.png

Morph surface source estimate

../_images/sphx_glr_plot_morph_volume_stc_thumb.png

Morph volumetric source estimate

../_images/sphx_glr_plot_rap_music_thumb.png

Compute Rap-Music on evoked data

../_images/sphx_glr_plot_read_inverse_thumb.png

Reading an inverse operator

../_images/sphx_glr_plot_read_source_space_thumb.png

Reading a source space from a forward operator

../_images/sphx_glr_plot_read_stc_thumb.png

Reading an STC file

../_images/sphx_glr_plot_snr_estimate_thumb.png

Plot an estimate of data SNR

../_images/sphx_glr_plot_tf_dics_thumb.png

Time-frequency beamforming using DICS

../_images/sphx_glr_plot_tf_lcmv_thumb.png

Time-frequency beamforming using LCMV

../_images/sphx_glr_plot_time_frequency_mixed_norm_inverse_thumb.png

Compute MxNE with time-frequency sparse prior

../_images/sphx_glr_plot_vector_mne_solution_thumb.png

Plotting the full MNE solution

Input/Output ¶

Reading and writing files. See also our Documentation on manipulating data structures.

../_images/sphx_glr_plot_elekta_epochs_thumb.png

Getting averaging info from .fif files

../_images/sphx_glr_plot_objects_from_arrays_thumb.png

Creating MNE objects from data arrays

../_images/sphx_glr_plot_read_and_write_raw_data_thumb.png

Reading and writing raw files

../_images/sphx_glr_plot_read_epochs_thumb.png

Reading epochs from a raw FIF file

../_images/sphx_glr_plot_read_events_thumb.png

Reading an event file

../_images/sphx_glr_plot_read_evoked_thumb.png

Reading and writing an evoked file

../_images/sphx_glr_plot_read_noise_covariance_matrix_thumb.png

Reading/Writing a noise covariance matrix

../_images/sphx_glr_plot_read_proj_thumb.png

Read and visualize projections (SSP and other)

Preprocessing ¶

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

../_images/sphx_glr_plot_define_target_events_thumb.png

Define target events based on time lag, plot evoked response

../_images/sphx_glr_plot_eog_artifact_histogram_thumb.png

Show EOG artifact timing

../_images/sphx_glr_plot_find_ecg_artifacts_thumb.png

Find ECG artifacts

../_images/sphx_glr_plot_find_eog_artifacts_thumb.png

Find EOG artifacts

../_images/sphx_glr_plot_head_positions_thumb.png

Visualize subject head movement

../_images/sphx_glr_plot_ica_comparison_thumb.png

Compare the different ICA algorithms in MNE

../_images/sphx_glr_plot_interpolate_bad_channels_thumb.png

Interpolate bad channels for MEG/EEG channels

../_images/sphx_glr_plot_metadata_query_thumb.png

Querying epochs with rich metadata

../_images/sphx_glr_plot_movement_compensation_thumb.png

Maxwell filter data with movement compensation

../_images/sphx_glr_plot_otp_thumb.png

Plot sensor denoising using oversampled temporal projection

../_images/sphx_glr_plot_rereference_eeg_thumb.png

Re-referencing the EEG signal

../_images/sphx_glr_plot_resample_thumb.png

Resampling data

../_images/sphx_glr_plot_run_ica_thumb.png

Compute ICA components on epochs

../_images/sphx_glr_plot_shift_evoked_thumb.png

Shifting time-scale in evoked data

../_images/sphx_glr_plot_virtual_evoked_thumb.png

Remap MEG channel types

../_images/sphx_glr_plot_xdawn_denoising_thumb.png

XDAWN Denoising

Real-time M/EEG Acquisition ¶

Receive data from an MNE Real-time server (mne_rt_server, part of MNE-CPP), compute real-time moving averages, etc.

../_images/sphx_glr_ftclient_rt_average_thumb.png

Compute real-time evoked responses with FieldTrip client

../_images/sphx_glr_ftclient_rt_compute_psd_thumb.png

Compute real-time power spectrum density with FieldTrip client

../_images/sphx_glr_plot_compute_rt_average_thumb.png

Compute real-time evoked responses using moving averages

../_images/sphx_glr_plot_compute_rt_decoder_thumb.png

Decoding real-time data

../_images/sphx_glr_rt_feedback_client_thumb.png

Real-time feedback for decoding :: Client Side

../_images/sphx_glr_rt_feedback_server_thumb.png

Real-time feedback for decoding :: Server Side

Data Simulation ¶

Tools to generate simulation data.

../_images/sphx_glr_plot_simulate_evoked_data_thumb.png

Generate simulated evoked data

../_images/sphx_glr_plot_simulate_raw_data_thumb.png

Generate simulated raw data

Statistics Examples ¶

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

../_images/sphx_glr_plot_cluster_stats_evoked_thumb.png

Permutation F-test on sensor data with 1D cluster level

../_images/sphx_glr_plot_fdr_stats_evoked_thumb.png

FDR correction on T-test on sensor data

../_images/sphx_glr_plot_linear_regression_raw_thumb.png

Regression on continuous data (rER[P/F])

../_images/sphx_glr_plot_sensor_permutation_test_thumb.png

Permutation T-test on sensor data

../_images/sphx_glr_plot_sensor_regression_thumb.png

Analysing continuous features with binning and regression in sensor space

Time-Frequency Examples ¶

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

../_images/sphx_glr_plot_compute_csd_thumb.png

Compute a cross-spectral density (CSD) matrix

../_images/sphx_glr_plot_compute_raw_data_spectrum_thumb.png

Compute the power spectral density of raw data

../_images/sphx_glr_plot_compute_source_psd_epochs_thumb.png

Compute Power Spectral Density of inverse solution from single epochs

../_images/sphx_glr_plot_source_label_time_frequency_thumb.png

Compute power and phase lock in label of the source space

../_images/sphx_glr_plot_source_power_spectrum_thumb.png

Compute power spectrum densities of the sources with dSPM

../_images/sphx_glr_plot_source_space_time_frequency_thumb.png

Compute induced power in the source space with dSPM

../_images/sphx_glr_plot_temporal_whitening_thumb.png

Temporal whitening with AR model

../_images/sphx_glr_plot_time_frequency_erds_thumb.png

Compute and visualize ERDS maps

../_images/sphx_glr_plot_time_frequency_global_field_power_thumb.png

Explore event-related dynamics for specific frequency bands

../_images/sphx_glr_plot_time_frequency_simulated_thumb.png

Time-frequency on simulated data (Multitaper vs. Morlet vs. Stockwell)

Visualization ¶

Looking at data and processing output.

../_images/sphx_glr_make_report_thumb.png

Make an MNE-Report with a Slider

../_images/sphx_glr_plot_3d_to_2d_thumb.png

How to convert 3D electrode positions to a 2D image.

../_images/sphx_glr_plot_channel_epochs_image_thumb.png

Visualize channel over epochs as an image

../_images/sphx_glr_plot_eeg_on_scalp_thumb.png

Plotting EEG sensors on the scalp

../_images/sphx_glr_plot_evoked_arrowmap_thumb.png

Plotting topographic arrowmaps of evoked data

../_images/sphx_glr_plot_evoked_topomap_thumb.png

Plotting topographic maps of evoked data

../_images/sphx_glr_plot_evoked_whitening_thumb.png

Whitening evoked data with a noise covariance

../_images/sphx_glr_plot_meg_sensors_thumb.png

Plotting sensor layouts of MEG systems

../_images/sphx_glr_plot_parcellation_thumb.png

Plot a cortical parcellation

../_images/sphx_glr_plot_roi_erpimage_by_rt_thumb.png

Plot single trial activity, grouped by ROI and sorted by RT

../_images/sphx_glr_plot_sensor_noise_level_thumb.png

Show noise levels from empty room data

../_images/sphx_glr_plot_ssp_projs_sensitivity_map_thumb.png

Sensitivity map of SSP projections

../_images/sphx_glr_plot_topo_compare_conditions_thumb.png

Compare evoked responses for different conditions

../_images/sphx_glr_plot_topo_customized_thumb.png

Plot custom topographies for MEG sensors

../_images/sphx_glr_plot_xhemi_thumb.png

Cross-hemisphere comparison

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