Bad channel detection

Warning

This functionality will soon be removed from the pipeline, and will be integrated into MNE-BIDS.

"Bad", i.e. flat and overly noisy channels, can be automatically detected using a procedure inspired by the commercial MaxFilter by Elekta. First, a copy of the data is low-pass filtered at 40 Hz. Then, channels with unusually low variability are flagged as "flat", while channels with excessively high variability are flagged as "noisy". Flat and noisy channels are marked as "bad" and excluded from subsequent analysis. See :func:mne.preprocssessing.find_bad_channels_maxwell for more information on this procedure. The list of bad channels detected through this procedure will be merged with the list of bad channels already present in the dataset, if any.

find_flat_channels_meg module-attribute

Python

find_flat_channels_meg: bool = False

Auto-detect "flat" channels (i.e. those with unusually low variability) and mark them as bad.

Pipeline steps using this setting

The following steps are directly affected by changes to find_flat_channels_meg:

• preprocessing/_01_data_quality
• preprocessing/_02_head_pos
• preprocessing/_03_maxfilter
• preprocessing/_04_frequency_filter
• preprocessing/_05_regress_artifact
• preprocessing/_08a_apply_ica
• preprocessing/_08b_apply_ssp

find_noisy_channels_meg module-attribute

Python

find_noisy_channels_meg: bool = False

Auto-detect "noisy" channels and mark them as bad.

Pipeline steps using this setting

The following steps are directly affected by changes to find_noisy_channels_meg:

• preprocessing/_01_data_quality
• preprocessing/_02_head_pos
• preprocessing/_03_maxfilter
• preprocessing/_04_frequency_filter
• preprocessing/_05_regress_artifact
• preprocessing/_08a_apply_ica
• preprocessing/_08b_apply_ssp