Difference between revisions of "MNE Python Tutorial 2021"

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tar -xvf mne_tutorial.tar.gz
 
tar -xvf mne_tutorial.tar.gz
   
=== NON-NIH MEG Users: Download from MEG Data server ===
+
=== NON-NIMH MEG Users: Download from MEG Data server ===
 
The data is located on the MEG data server and is accessible by all users with accounts
 
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
 
An email will be sent with the path to the data

Revision as of 13:24, 24 September 2021

Steps to prepare prior to tutorial

Prepare python environment - For 3D rendering and interactive plots, this should be installed on your local computer

 !!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

Wait until 09/30/21 and then 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-NIMH 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