The BeMoBIL Pipeline is an open-source MATLAB toolbox for fully synchronized, automatic, transparent, and replicable import, processing and visualization of mobile brain/body imaging and other EEG data. It includes wrappers for EEGLAB functions, the use of various EEGLAB plugins, and comes with additional new functionalities.
All parameters are configurable in central scripts and everything is stored in the EEG.etc struct. Additionally, analytics plots are generated for each step.
A comprehensive guide to installing, using, and understanding the pipeline can be found in our wiki on github!
For a quick start, we recommend you to have a look at the following scripts in the root directory of the pipeline.
example_bemobil_config.m
example_bemobil_import_xdf2bids.m
example_bemobil_import_bids2set.m
example_bemobil_process_all_EEG_data.m
example_bemobil_process_all_motion_data.m
The importing scripts are complete on their own. If the data is already in BIDS format, one can start with example_bemobil_import_bids2set.m and skip xdf2bids.m.
The scripts example_bemobil_process_all_EEG_data.m and example_bemobil_process_all_motion_data.m will all load example_bemobil_config.m. So the configuration file serves as the summary of settings used throughout the pipeline. Comments within the files explain the parameters. These scripts are the only scripts that need to be run. They contain all steps from the source xdf data over the raw imported data to the processed and cleaned data, and allow batch processing of all subjects.
The example_bemobil_import.m script contains an exemplary import process from xdf over BIDS to EEGLAB structure. If you already have your data in EEGLAB set files you may skip this step entirely, if you have your data already in BIDS, you can just run the bottom part that loads from BIDS to EEGLAB set. Specific instruction is given as comments.
Here is an example of the final BeMoBIL pipeline output :
In the single subject EEG analysis folder there are two final data sets after the complete processing is done (xxx_preprocessed_and_ICA.set and xxx_cleaned_with_ICA.set). Both sets have basic preprocessing done (line noise removal, channel locations, channel interpolation, removal of very slow trends), and contain ICA information. The xxx_cleaned_with_ICA.set file additionally has ICs removed as determined by the settings for ICLabel in the pipeline config. If ICA was only meant to be used for cleaning, any kind of sensor-level analysis (like ERPs at Pz electrode) can now be performed on the cleaned data. If the end goal is source analysis, and potentially analysis of muscle or eye activity in conjunction with other MoBI modalities, this data is still available in xxx_preprocessed_and_ICA.set. Consider our repeated clustering approach in that case.
The pipeline has more functionalities than this, so don't forget to check out our wiki on github with details on the parameters and usage, as well as more info on event creation and other additional options the pipeline has to offer!
If you have any comments, questions, or suggestions, please open issues on git, join our discord server, or write an email to [email protected]!