Meet Cedalion: an open-source Python toolkit for wearable fNIRS/DOT
What if lab-grade brain imaging could go wearable—and be analyzed with the same, reproducible playbook? Meet Cedalion, an open-source Python framework for making sense of light-based brain data: fNIRS and DOT (they use harmless light to track brain activity).
Cedalion unifies the whole pipeline in one place: forward modeling and optode co-registration, signal cleaning and quality checks, GLM analysis, DOT image reconstruction, and modern ML. It speaks community standards (SNIRF, BIDS), runs in cloud-friendly Jupyter notebooks, and ships containerized workflows you can share alongside your paper.
- Plug into scikit-learn and PyTorch for data-driven insights and multimodal fusion with EEG/MEG/physiology.
- Use validated tools for motion correction, QC, simulation, and data augmentation.
- Seven fully executable tutorial notebooks get you from raw data to results fast.
Built for reproducibility, scalability, and collaboration, so you can move from lab benches to real-world neurotech with confidence.
Read the tutorial and try the notebooks: https://arxiv.org/abs/2601.05923v1
Paper: https://arxiv.org/abs/2601.05923v1
Register: https://www.AiFeta.com
Neuroimaging fNIRS DOT OpenSource Python MachineLearning Reproducibility BIDS SNIRF EEG MEG PyTorch scikitLearn Jupyter
