Basic usage
Prepare your dataset¶
MNE-BIDS-Pipeline only works with BIDS-formatted raw data. To find out more about BIDS and how to convert your data to the BIDS format, please see the documentation of MNE-BIDS.
We recommend that
-
faulty channels are marked as "bad".
Why?
While we do run automated bad channel detection in the pipeline, it is considered good practice to flag obviously problematic channels as such in the BIDS dataset.
How?
MNE-BIDS provides a convenient way to visually inspect raw data and interactively mark problematic channels as bad by using the command
Run in your terminalPlease see the MNE-BIDS documentation for more information.mne-bids inspect
-
the data is anonymized before running the pipeline if you require anonymization, as the pipeline itself does not allow for anonymization.
Why?
This was a conscious design decision, not a technical limitation per se. If you think this decision should be reconsidered, please get in touch with the developers.
How?
If you already have BIDS formatted data you can use
mne_bids.anonymize_dataset
. Otherwise you can use themne_bids.write_raw_bids
function of MNE-BIDS that accepts ananonymize
parameter and can be used to anonymize your data by removing subject-identifying information and shifting the measurement date by a given number of days. For example, you could usePythonto shift the recording date 1000 days into the past. By default, information like participant handedness etc. will be removed as well.from mne_bids import write_raw_bids write_raw_bids(..., anonymize=dict(daysback=1000))
You can also deface your MRIs with
mne_bids.write_anat
:PythonPlease see the tutorials offrom mne_bids import write_anat write_anat(..., landmarks=landmarks, deface=True)
mne_bids
for more information.
Create a configuration file¶
All parameters of the pipeline are controlled via a configuration file. You can create a template configuration file by running the following command:
Create a template configuration file
mne_bids_pipeline --create-config=/path/to/your/custom_config.py
You can then edit the file and adjust all parameters that are relevant to your data processing and analysis.
Run the pipeline¶
Run the full pipeline
To run the full pipeline, execute the following command in your terminal:
mne_bids_pipeline --config=/path/to/your/custom_config.py
Run only parts of the pipeline
Run only the preprocessing steps:
mne_bids_pipeline --config=/path/to/your/custom_config.py --steps=preprocessing
Run only the sensor-level processing steps:
mne_bids_pipeline --config=/path/to/your/custom_config.py --steps=sensor
Run only the source-level (inverse solution) processing steps:
mne_bids_pipeline --config=/path/to/your/custom_config.py --steps=source
(Re-)run ICA:
mne_bids_pipeline --config=/path/to/your/custom_config.py --steps=preprocessing/ica
You can also run multiple steps with one command by separating different steps by a comma. For example, to run preprocessing and sensor-level processing steps using a single command, do:
mne_bids_pipeline --config=/path/to/your/custom_config.py --steps=preprocessing,sensor
You can directly visit our examples page to see some configuration files and the corresponding results.