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., Thielen, J., Moreau, T., Roy, Y., Jayaram, V., Barachant, A., & Chevallier, S. (2025). Mother of all BCI Benchmarks (v1.2.0). Zenodo. 10.5281/zenodo.10034223

and here is the Bibtex version:

@software{Aristimunha_Mother_of_all_2023,
  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
                  Thielen, Jordy and
                  Moreau, Thomas and
                  Roy, Yannick and
                  Jayaram, Vinay and
                  Barachant, Alexandre and
                  Chevallier, Sylvain},
        title        = {Mother of all BCI Benchmarks},
        year         = 2025,
        publisher    = {Zenodo},
        version      = {v1.2.0},
        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.