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Setting Up MNE Python

Purpose

Install MNE Python on ARC for neurophysiological data analysis (MEG, EEG, and related signals). This is a one-time setup that creates a dedicated Python environment and Jupyter kernel for use across your ARC projects.

Prerequisites

  • A SSO (Single Sign-On) account at the University of Oxford
  • VPN access to the University of Oxford network (required for off-site access)
  • An account on the project psyc-neuosc at ARC
  • Neuronal Oscillations Group (NOG) initialisation files installed; see Initialise Settings and Folders

Steps

1. Connect to ARC

Connect to the VPN, then access ARC via remote desktop or SSH. You will land on a gateway node.

SSH into the login node:

ssh -X htc-login

2. Run the MNE Installation Script

Navigate to the group handbook and run the setup script:

cd $DATA/git-repos
bash group-handbook/code/hpc/setup_mne.sh

This script performs the following: - Downloads and configures FLUX (a compute scheduler) - Creates a new MNE Python environment in $DATA/environments - Installs the MNE Python package and dependencies - Registers a Jupyter kernel for this environment (allows use in Jupyter notebooks on ARC)

The installation may take several minutes. Wait for the script to complete.

3. Verify Installation

Check that MNE is installed correctly (making sure to use the right Python version):

source activate $DATA/environments/mne_env
$DATA/environments/mne_env/bin/python -c "import mne; print(mne.__version__)"

If successful, you will see the MNE version number printed.

Next Steps

Once installed, you can:

  • Use MNE in scripts: Activate the environment and run Python scripts that import MNE
  • Use Jupyter notebooks: The registered kernel allows you to select the MNE environment in Jupyter on ARC
  • Submit batch jobs: Use MNE scripts within HPC job submissions for large-scale analysis

For usage examples and documentation, see the MNE Python documentation.