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app-bad-channels
- Aurore Bussalb (Unlicensed)
App under development Private app on bl
It’s critical to mark bad channels as ‘bad’ before applying Maxwell Filter in order to prevent bad channel noise from spreading. This app allows to automatically detect bad channels using the MNE Python function mne.preprocessing.find_bad_channels_maxwell. Nevertheless, this algorithm is not perfect so a visual inspection of the signals before and after running this App is recommended.
GitHub repository:
GitHub - brainlife/app-bad-channels: Detect bad channels in MEG signals.
Brainlife datatype used:
For input: neuro/meg/fif and neuro/meg/fif-override
For outputs: neuro/meg/fif-override and report/html
Inputs of the App
Files | Format | Datatype | Description | Optional |
|---|---|---|---|---|
MEG signals | .fif | meg/fif | Data to process | No |
Head position file | .pos | meg/fif-override or meg/fif | Compensates for head movements | Yes |
Fine calibration file | .dat | meg/fif | Encodes site-specific information about sensors orientation and calibration | Yes |
Cross talk compensation file | .fif | meg/fif | Reduces interference between Elekta’s co-located magnetometer and paired gradiometer sensor units | Yes |
The head position file can be obtained thanks to the app-head-pos.
This headpos file can be obtained thanks to the app-head-pos (if so, the file will be linked to the meg/fif-override datatype) or can be directly available with the meg.fif in the meg/fif datatype. If there are two head.pos (one from meg/fif datatype and the other from meg/fif-override datatype, only the file from the meg/fif-override will be used (see How to use the meg/fif-override datatype).
Outputs of the App:
Files | Format | Datatype | Description |
|---|---|---|---|
Channels | .tsv | meg/fif-override | BIDS compliant tsv file in which bad channels are marked as bad |
Report | .html | html | List of the automated detected bad channels and visualizations in time and frequency domains |
Besides, in the output directory, there are the optional files that can be used in a next App. This is mandatory, because the App that will be run after app-bad-channels can take as input all the files in app-bad-channels’s output directory corresponding to the datatype of the input of the next App (see How to run Apps one after another).
Parameters of the App
The parameters of the App correspond to the parameters passed to the Python functions used in the App. Their default values proposed in Brainlife or in config.json.example correspond to the default values of MNE Python 0.23 (except for return_scores, which here is set to True because we need this info to create the html report).
Next improvements
Rename it into “app-find-bad-channels-maxwell-filter”?
Allow user to change the plot parameters for the plots in the HTML report?