MEGaNorm
MEGaNorm is a Python package for normative modeling on MEG and EEG data.
Install / Use
/learn @ML4PNP/MEGaNormREADME
MEGaNorm
MEGaNorm is a Python package that wraps MNE-Python and PCNToolkit functionalities for extracting functional imaging-derived phenotypes (f-IDPs) from large-scale EEG and MEG datasets, and then deriving their normative ranges. It allows researchers to analyze large MEG and EEG dataset using high-performance computing facilities, and then build, visualize, and analyze normative models of brain dynamics across individuals.
🚀 Features
- Compatibility with MNE-Python, PCNToolkit, SpecParam libraries
- Normative modeling of oscillatory brain activity
- Using high performance capabilities on SLURM clusters
- EEG and MEG support with BIDS integration
- Ready for reproducible deployment with Docker
📦 Installation
Option 1: From PyPI (recommended)
This is the easiest way to get started if you just want to use the toolbox.
conda create --channel=conda-forge --strict-channel-priority --name mne python=3.12 mne
conda activate mne
pip install meganorm
Option 2: Installl from the source files
# 1. Create and activate environment
conda create --channel=conda-forge --strict-channel-priority --name mne python=3.12 mne
conda activate mne
# 2. Clone and install MEGaNorm
git clone https://github.com/ML4PNP/MEGaNorm.git
cd MEGaNorm/
pip install .
Option 3: Using Docker
We provide a pre-configured Docker environment with Jupyter Lab. You can either build the image locally or pull the latest version from Docker Hub.
Option A: Build the image locally
make build
make run
Option B: Pull the latest image from Docker Hub
make pull
make run
This mounts:
notebooks/→ for saving Jupyter notebooksresults/→ for analysis outputsdata/→ for raw/processed EEG/MEG data
Jupyter will open in your browser on http://localhost:8888
📒 Getting Started (under construction)
👉 documentation Early helpers are available at: https://meganorm.readthedocs.io. We are working hard to add more thorough documentations and tutorials and they will be available soon.
import meganorm
Explore examples in the notebooks/ folder.
🧚♂️ Testing (under construction)
Run unit tests using:
pytest tests/
🧠 Citing MEGaNorm
If you use MEGaNorm in your work, please cite:
You can download BibTeX and other citation formats directly from the Zenodo page.
🤝 Contributing
Contributions, issues and feature requests are welcome!
See CONTRIBUTING.md for more info.
📜 License
This project is licensed under the terms of the GNU General Public License v3.0 – see the LICENSE file for details.
