Citing MOABB and related publications

If you use MOABB in your experiments, please cite this library when publishing a paper to increase the visibility of open science initiatives:

• Aristimunha, B., Carrara, I., Guetschel, P., Sedlar, S., Rodrigues, P., Sosulski, J., Narayanan, D., Bjareholt, E., Barthelemy, Q., Schirrmeister, R. T., Kobler, R., Kalunga, E., Darmet, L., Gregoire, C., Abdul Hussain, A., Gatti, R., Goncharenko, V., Andreev, A., Tates, A., Kojima, S., Thielen, J., Hajhassani, D., Graignic, P.-A., Begany, K., Leto, B., Davis, E., Munro, Z., Romani, M., Talar, B., Schrag, E., Kowshik, B., Badang, R. A., Xu, G., Polychroniadou, D., Lefundes da Silva, H., Bano, A., Singh, A., Rahimipour, M., Moreau, T., Roy, Y., Jayaram, V., Barachant, A., & Chevallier, S. (2026). Mother of all BCI Benchmarks (Version 1.6.1). Zenodo. 10.5281/zenodo.10034223

and here is the Bibtex version:

@misc{Aristimunha_Mother_of_all,
  author       = {Aristimunha, Bruno and
                          Carrara, Igor and
                          Guetschel, Pierre and
                          Sedlar, Sara and
                          Rodrigues, Pedro and
                          Sosulski, Jan and
                          Narayanan, Divyesh and
                          Bjareholt, Erik and
                          Barthelemy, Quentin and
                          Schirrmeister, Robin Tibor and
                          Kobler, Reinmar and
                          Kalunga, Emmanuel and
                          Darmet, Ludovic and
                          Gregoire, Cattan and
                          Abdul Hussain, Ali and
                          Gatti, Ramiro and
                          Goncharenko, Vladislav and
                          Andreev, Anton and
                          Tates, Alberto and
                          Kojima, Simon and
                          Thielen, Jordy and
                          Hajhassani, Davoud and
                          Graignic, Paul-Adrien and
                          Begany, Katelyn and
                          Leto, Benedetto and
                          Davis, Ethan and
                          Munro, Zachary and
                          Romani, Michele and
                          Talar, Baris and
                          Schrag, Emily and
                          Kowshik, Bhargav and
                          Badang, Ralph Angelo and
                          Xu, Grace and
                          Polychroniadou, Danae and
                          Lefundes da Silva, Henrique and
                          Bano, Azra and
                          Singh, Aditya and
                          Rahimipour, Meysam and
                          Moreau, Thomas and
                          Roy, Yannick and
                          Jayaram, Vinay and
                          Barachant, Alexandre and
                          Chevallier, Sylvain},
        title        = {Mother of all BCI Benchmarks},
        year         = 2026,
        publisher    = {Zenodo},
        version      = {1.6.1},
        url = {https://github.com/NeuroTechX/moabb},
        doi = {10.5281/zenodo.10034223},
}

If you want to cite the scientific contributions of MOABB, you could use the following paper:

• Sylvain Chevallier, Igor Carrara, Bruno Aristimunha, Pierre Guetschel, Bruna Junqueira Lopes, Sébastien Velut, Salim Khazem, Thomas Moreau. The largest EEG-based BCI reproducibility study for open science: the MOABB benchmark, 2023. HAL: hal-04537061.

• Vinay Jayaram and Alexandre Barachant. MOABB: trustworthy algorithm benchmarking for BCIs. Journal of neural engineering 15.6 (2018): 066011. DOI:10.1088/1741-2552

Here is the BibTeX entry for the above paper:

@article{moabb2018,
  title={MOABB: trustworthy algorithm benchmarking for BCIs},
  author={Jayaram, Vinay and Barachant, Alexandre},
  journal={Journal of neural engineering},
  volume={15},
  number={6},
  pages={066011},
  year={2018},
  publisher={IOP Publishing}
}

If you publish a paper using MOABB, please contact us on [gitter][link_gitter] or open an issue! We would love to hear about your work and help you promote it.