Welcome to the ANT documentation! ANT is a open-source package which provides a comprehensive framework for real-time M/EEG analysis and visualization, including:

• Real-time feature extraction from M/EEG signals.

• Processing at multiple levels: sensor-space to source-space.

• 3D visualization of brain activation on a rendered brain reconstructed from the subject’s MRI.

• Integration with visualization modules to monitor neurofeedback responses in real time.

• Real-time artifact correction methods, including: - ORICA (Online Recursive ICA) for source separation. - Adaptive regression (LMS) for removing blink artifacts from EEG. - Real-time SSP (Signal Space Projection) for MEG artifact correction. - HFC correction for MEG high-frequency artifacts.

• Lightweight management of experimental projects, enabling organized and efficient experimentation.

• Flexible and extensible tools for real-time neuroimaging, visualization, and neurofeedback applications.

Installation

You can install ANT via PyPI, Conda, or directly from Source.

💻 PyPI

$ pip install ant

🌟 Conda

$ conda install -c conda-forge ant

📦 From Source (GitHub)

$ pip install git+https://github.com/payamsash/ANT

Cite

If you use ANT, please consider citing our paper [1].

[1]

Payam S Shabestari, Delphine Ribes, Lara Défayes, Danpeng Cai, Emily Groves, Harry H Behjat, Dimitri Van de Ville, Tobias Kleinjung, Adrian Naas, Nicolas Henchoz, and others. Advances on real time m/eeg neural feature extraction. In 2025 IEEE 38th International Symposium on Computer-Based Medical Systems (CBMS), 337–338. IEEE, 2025.

Supporting institutions

The development of ANT was supported by the Swiss National Science Foundation.

For more information, see:

• GitHub repository: payamsash/ANT

• Tutorials and guides in the examples section.