Removing muscle ICA components (muscle_ica.py) |
00:28.076 |
0.0 |
Find MEG reference channel artifacts (find_ref_artifacts.py) |
00:27.176 |
0.0 |
Plot sensor denoising using oversampled temporal projection (otp.py) |
00:25.036 |
0.0 |
Transform EEG data using current source density (CSD) (eeg_csd.py) |
00:24.754 |
0.0 |
Compare the different ICA algorithms in MNE (ica_comparison.py) |
00:23.547 |
0.0 |
Identify EEG Electrodes Bridged by too much Gel (eeg_bridging.py) |
00:22.315 |
0.0 |
Interpolate bad channels for MEG/EEG channels (interpolate_bad_channels.py) |
00:13.863 |
0.0 |
Annotate movement artifacts and reestimate dev_head_t (movement_detection.py) |
00:11.791 |
0.0 |
Reduce EOG artifacts through regression (eog_regression.py) |
00:10.806 |
0.0 |
Remap MEG channel types (virtual_evoked.py) |
00:09.869 |
0.0 |
Maxwell filter data with movement compensation (movement_compensation.py) |
00:09.751 |
0.0 |
Visualise NIRS artifact correction methods (fnirs_artifact_removal.py) |
00:05.885 |
0.0 |
XDAWN Denoising (xdawn_denoising.py) |
00:04.681 |
0.0 |
Annotate muscle artifacts (muscle_detection.py) |
00:04.003 |
0.0 |
Define target events based on time lag, plot evoked response (define_target_events.py) |
00:02.155 |
0.0 |
Automated epochs metadata generation with variable time windows (epochs_metadata.py) |
00:01.712 |
0.0 |
Cortical Signal Suppression (CSS) for removal of cortical signals (css.py) |
00:01.544 |
0.0 |
Using contralateral referencing for EEG (contralateral_referencing.py) |
00:01.109 |
0.0 |
Shifting time-scale in evoked data (shift_evoked.py) |
00:00.776 |
0.0 |
Show EOG artifact timing (eog_artifact_histogram.py) |
00:00.590 |
0.0 |
