Mne bids pipeline

From MEG Core
Jump to navigation Jump to search

Skip Background

Use on Biowulf

Intro

BIDS is a standard specification for neuroimaging/physiology data. This currently includes at least: MRI, fMRI, DTI, EEG, MEG, fNIRS (and possibly ECOG/sEEG). BIDS typically describes how RAW data is organized - and processed data is located in the bids_dir/derivatives/{AnalysisPackage}/{SUBJECT}/... The main advantage is that common code can be generated to process data organized in a standard format. Therefore, you should be able to import the bids data into any number of neurophysiological packages (MNE, Brainstorm, SPM, Fieldtrip, ...). Additionally, standardized processing packages known as BIDS apps can be used to process the data in the same way as long as the data is organized in BIDS.

 BIDS (formal specs) >> MNE_BIDS (python neurophysiological BIDS) >> MNE_BIDS_PIPELINE (structured processing in MNE python according to BIDS definition)

BIDS website

 https://bids-specification.readthedocs.io/en/stable/

MNE Bids

MNE bids is a python tool to make and access neurophysiological data. This tool is a branch of the MNE tools for neurophysiological analysis.

MNE Bids website

 https://mne.tools/mne-bids/stable/index.html

MNE bids pipeline background

Mne bids pipeline website:

 https://mne.tools/mne-bids-pipeline/

Full example:

 https://mne.tools/mne-bids-pipeline/examples/ds000248.html

Processing

All processing is defined in the config.py file. This has hundreds of options to define the processing.

 Here are some of the typical options:  https://mne.tools/mne-bids-pipeline/settings/general.html

Here is the full list of options:

 https://github.com/mne-tools/mne-bids-pipeline/blob/main/config.py

Example Config (copy into a config.py text file and use)

Modify for use with your data - at a minimum: bids_root, conditions

 study_name = 'TESTSTudy'
 bids_root = 'YOUR_BIDS_DIR' #<< Modify
 l_freq = 1.0
 h_freq = 100.
 epochs_tmin = -0.1
 epochs_tmax = 0.2
 baseline = (-0.1, 0.0)
 resample_sfreq = 300.0
 ch_types = ['meg']
 conditions = ['stim']  #<< list of conditions
 N_JOBS=4
 
 #crop_runs = [0, 900] #Can be useful for long tasks that are ended early

Use on biowulf

!!If you run into any issues - please let Jeff Stout know so that the code can be updated!!

Start interactive session with scratch to render visualization offscreen

 sinteractive --mem=6G --cpus-per-task=4 --gres=lscratch:50  #adjust mem and cpus accordingly - subjects will run in parrallel

Create BIDS data from data off the scanner

 module load mne_scripts
 
 #Afni coregistered mri data  
 make_meg_bids.py -meg_input_dir ${MEGFOLDER} -mri_brik AFNI_COREGED+orig.BRIK
       ## OR ##
 #Brainsight coregistered mri data
 make_meg_bids.py -meg_input_dir ${MEGFOLDER} -mri_bsight ${MRI_BSIGHT} -mri_bsight_elec ${MRI_BSIGHT_ELEC}

Freesurfer Processing

Already Processed

 mkdir -p ${bids_dir}/derivatives/freesurfer/subjects  #If this folder doesn't already exists
 #Copy your subject from the freesurfer directory to the bids DERIVATIVES freesurfer directory
 cp -R ${SUBJECTS_DIR}/${SUBJID}  ${bids_dir}/derivatives/freesurfer/subjects

Process Using MNE-BIDS-Pipeline

 #add the following step to your processing
 #your sinteractive session must include 
 --steps=freesurfer

Process data using MNE Bids Pipeline

First make a config file [Example Config (copy into a config.py text file and use) | ExampleConfig]

 module purge 
 module load mne_bids_pipeline
 mne-bids-pipeline-run.py --config=CONFIG.py
       #Optional Flags
       #--steps=preprocessing,sensor,source,report  or all (default) - Can be a list of steps or a single step
       #--subject=SUBJECTID(without the sub- prefix)

TEST DATA for biowulf

This section provides some test data to analyze using mne-bids-pipeline. Feel free to adjust parameters in the config.py after you run through the analysis the first time. All of the analysis parameters are defined in the config.py provided. Additional config.py parameters can be found above in Processing.

Start Interactive Session

 sinteractive --mem=6G --cpus-per-task=4 --gres=lscratch:50

Copy and untar the data into your folder

 cp -R /vf/users/MEGmodules/modules/bids_example_data_airpuff.tar ./
 tar -xvf bids_example_data_airpuff.tar
 
 #Add the bids_root to your config file
 echo bids_root=\'$(pwd)/bids_example_data_airpuff\' >> $(pwd)/bids_example_data_airpuff/config.py

Load module and process the data

 module load mne_bids_pipeline
 mne-bids-pipeline-run.py --config=$(pwd)/bids_example_data_airpuff/config.py
 #Copy this path for the next step
 echo $(pwd)/bids_example_data_airpuff/derivatives/mne-bids-pipeline/sub-ON02747/ses-01/meg/sub-ON02747_ses-01_task-airpuff_report.html
 #In another terminal download your results from biowulf
 scp ${USERNAME}@helix.nih.gov:${PathFromAbove} ./
 Open sub-ON02747_ses-01_task-airpuff_report.html in an internet browser to view the report