MNE Python Tutorial 2021: Difference between revisions
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cd <NEW PATH>/nimh_tutorial_data |
cd <NEW PATH>/nimh_tutorial_data |
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jupyter notebook mne_tutorial_10_01_21.ipynb |
jupyter notebook mne_tutorial_10_01_21.ipynb |
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=Prep Non-tutorial Data= |
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Run Freesurfer on Dataset: recon-all -all -i <MRI Used w/ MEG> -s <SUBJECT> |
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Run mne.bem.make_watershed_bem() on your subject |
Revision as of 11:38, 24 September 2021
Steps to prepare prior to tutorial
Prepare python environment
!!IF YOU DO NOT HAVE MINICONDA/ANACONDA INSTALLED - have IT install miniconda under your user account!! !!If you already have an mne environment, you can use another name for the environment and adjust accordingly!! conda activate base conda install -n base mamba -c conda-forge -y mamba create -n mne conda-forge::mne main::pip main:jupyter -y
conda activate mne
Download the sample data
NIMH Users: Download here
scp <USERNAME>@helix.nih.gov:/data/NIMH_scratch/mne_tutorial/mne_tutorial.tar.gz <NEW PATH> cd <NEW PATH> tar -xvf mne_tutorial.tar.gz
NON-NIH MEG Users: Download from MEG Data server
The data is located on the MEG data server and is accessible by all users with accounts An email will be sent with the path to the data
Start Jupyter Notebook
cd <NEW PATH>/nimh_tutorial_data jupyter notebook mne_tutorial_10_01_21.ipynb
Prep Non-tutorial Data
Run Freesurfer on Dataset: recon-all -all -i <MRI Used w/ MEG> -s <SUBJECT> Run mne.bem.make_watershed_bem() on your subject