This is still under construction. Once finished it should become a software pipeline to create and maintain a BIDS dataset of clinical MEG resting state measurements and for electromagnetic source imaging in python with free software.
Under the hood it mainly uses
- mne-python
- mne-bids
- nipype
- nilearn
- clone the git repository (git clone https://github.com/RuKrei/SourceLoc.git)
- install mne (https://mne.tools/dev/install/index.html)
- Activate mne-environment (conda activate name_of_your_mne_environment)
- pip install -r requirements.txt
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freesurfer (https://surfer.nmr.mgh.harvard.edu/fswiki/DownloadAndInstall) should be installed on your system for use of anatomical processing steps. The pipeline checks, if SUBJECTS_DIR is set.
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BIDSROOT (root directory for output of the pipeline) and INPUTFOLDER (where MRI and MEEG-data are stored) need to be set. This can be done either when launching a process as arguments, or in form of environment variables.
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OPENMP (the number of processes to use) defaults to 1 and should be set to meet your needs.
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SRCSPACING (https://mne.tools/dev/overview/cookbook.html#setting-up-source-space) should be set on your system, it defaults to "oct6".
- put MEEG-data in INPUT_FOLDER, filenames MUST contain the name of the subject
- put MRI-data in a folder named with subjects name in INPUT_FOLDER
- cd to directory of pipeline on harddisk
- python run_pipeline.py
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- if no arguments are given you will be prompted for subject name to process
-
- specify INPUT_FOLDER and BIDS_ROOT via one of the options below
- export BIDS_ROOT=/path/to/store/results/in
- export INPUT_FOLDER=/path/to/input/folder
- python run_pipeline.py --bidsroot /path/to/store/results/in --inputfolder /path/to/input/folder --openmp 8 --srcspacing ico4