Find MEG reference channel artifacts (find_ref_artifacts.py) |
00:29.300 |
0.0 |
Removing muscle ICA components (muscle_ica.py) |
00:29.002 |
0.0 |
Plot sensor denoising using oversampled temporal projection (otp.py) |
00:25.581 |
0.0 |
Transform EEG data using current source density (CSD) (eeg_csd.py) |
00:24.679 |
0.0 |
Compare the different ICA algorithms in MNE (ica_comparison.py) |
00:22.083 |
0.0 |
Identify EEG Electrodes Bridged by too much Gel (eeg_bridging.py) |
00:21.231 |
0.0 |
Interpolate bad channels for MEG/EEG channels (interpolate_bad_channels.py) |
00:14.107 |
0.0 |
Reduce EOG artifacts through regression (eog_regression.py) |
00:12.124 |
0.0 |
Annotate movement artifacts and reestimate dev_head_t (movement_detection.py) |
00:11.151 |
0.0 |
Remap MEG channel types (virtual_evoked.py) |
00:09.810 |
0.0 |
Maxwell filter data with movement compensation (movement_compensation.py) |
00:09.683 |
0.0 |
Visualise NIRS artifact correction methods (fnirs_artifact_removal.py) |
00:06.343 |
0.0 |
XDAWN Denoising (xdawn_denoising.py) |
00:04.879 |
0.0 |
Annotate muscle artifacts (muscle_detection.py) |
00:03.851 |
0.0 |
Automated epochs metadata generation with variable time windows (epochs_metadata.py) |
00:01.760 |
0.0 |
Define target events based on time lag, plot evoked response (define_target_events.py) |
00:01.603 |
0.0 |
Cortical Signal Suppression (CSS) for removal of cortical signals (css.py) |
00:01.553 |
0.0 |
Using contralateral referencing for EEG (contralateral_referencing.py) |
00:01.147 |
0.0 |
Show EOG artifact timing (eog_artifact_histogram.py) |
00:00.817 |
0.0 |
Shifting time-scale in evoked data (shift_evoked.py) |
00:00.780 |
0.0 |
