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<h1>Mother of all BCI Benchmarks (MOABB)</h1>
<p>
Build a comprehensive benchmark of popular Brain-Computer Interface (BCI) algorithms applied on an extensive list
of freely available EEG datasets.
</p>
<p>
<a href="https://moabb.neurotechx.com/">Docs</a> •
<a href="https://moabb.neurotechx.com/docs/install/install.html">Install</a> •
<a href="https://moabb.neurotechx.com/docs/auto_examples/index.html">Examples</a> •
<a href="https://moabb.neurotechx.com/docs/paper_results.html">Benchmark</a> •
<a href="https://moabb.neurotechx.com/docs/dataset_summary.html">Datasets</a>
</p>
<p>
<a href="https://doi.org/10.5281/zenodo.10034223"><img src="https://zenodo.org/badge/DOI/10.5281/zenodo.10034223.svg" alt="DOI"></a>
<a href="https://github.com/NeuroTechX/moabb/actions/workflows/test.yml?query=branch%3Adevelop"><img src="https://github.com/NeuroTechX/moabb/actions/workflows/test.yml/badge.svg?branch=develop" alt="Build Status"></a>
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<section id="quickstart">
<h1>Quickstart<a class="headerlink" href="#quickstart" title="Link to this heading">#</a></h1>
<div class="highlight-shell notranslate"><div class="highlight"><pre><span></span>pip<span class="w"> </span>install<span class="w"> </span>moabb
</pre></div>
</div>
<div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="kn">import</span><span class="w"> </span><span class="nn">moabb</span>
<span class="kn">from</span><span class="w"> </span><span class="nn">moabb.datasets</span><span class="w"> </span><span class="kn">import</span> <span class="n">BNCI2014_001</span>
<span class="kn">from</span><span class="w"> </span><span class="nn">moabb.evaluations</span><span class="w"> </span><span class="kn">import</span> <span class="n">CrossSessionEvaluation</span>
<span class="kn">from</span><span class="w"> </span><span class="nn">moabb.paradigms</span><span class="w"> </span><span class="kn">import</span> <span class="n">LeftRightImagery</span>
<span class="kn">from</span><span class="w"> </span><span class="nn">moabb.pipelines.features</span><span class="w"> </span><span class="kn">import</span> <span class="n">LogVariance</span>
<span class="kn">from</span><span class="w"> </span><span class="nn">sklearn.discriminant_analysis</span><span class="w"> </span><span class="kn">import</span> <span class="n">LinearDiscriminantAnalysis</span> <span class="k">as</span> <span class="n">LDA</span>
<span class="kn">from</span><span class="w"> </span><span class="nn">sklearn.pipeline</span><span class="w"> </span><span class="kn">import</span> <span class="n">make_pipeline</span>
<span class="n">moabb</span><span class="o">.</span><span class="n">set_log_level</span><span class="p">(</span><span class="s2">"info"</span><span class="p">)</span>
<span class="n">pipelines</span> <span class="o">=</span> <span class="p">{</span><span class="s2">"LogVar+LDA"</span><span class="p">:</span> <span class="n">make_pipeline</span><span class="p">(</span><span class="n">LogVariance</span><span class="p">(),</span> <span class="n">LDA</span><span class="p">())}</span>
<span class="n">dataset</span> <span class="o">=</span> <span class="n">BNCI2014_001</span><span class="p">()</span>
<span class="n">dataset</span><span class="o">.</span><span class="n">subject_list</span> <span class="o">=</span> <span class="n">dataset</span><span class="o">.</span><span class="n">subject_list</span><span class="p">[:</span><span class="mi">2</span><span class="p">]</span>
<span class="n">paradigm</span> <span class="o">=</span> <span class="n">LeftRightImagery</span><span class="p">(</span><span class="n">fmin</span><span class="o">=</span><span class="mi">8</span><span class="p">,</span> <span class="n">fmax</span><span class="o">=</span><span class="mi">35</span><span class="p">)</span>
<span class="n">evaluation</span> <span class="o">=</span> <span class="n">CrossSessionEvaluation</span><span class="p">(</span><span class="n">paradigm</span><span class="o">=</span><span class="n">paradigm</span><span class="p">,</span> <span class="n">datasets</span><span class="o">=</span><span class="p">[</span><span class="n">dataset</span><span class="p">])</span>
<span class="n">results</span> <span class="o">=</span> <span class="n">evaluation</span><span class="o">.</span><span class="n">process</span><span class="p">(</span><span class="n">pipelines</span><span class="p">)</span>
<span class="nb">print</span><span class="p">(</span><span class="n">results</span><span class="o">.</span><span class="n">head</span><span class="p">())</span>
</pre></div>
</div>
<p>For full installation options and troubleshooting, see the <a class="reference external" href="https://moabb.neurotechx.com/docs/install/install.html">documentation</a>.</p>
</section>
<section id="disclaimer">
<h1>Disclaimer<a class="headerlink" href="#disclaimer" title="Link to this heading">#</a></h1>
<p><strong>This is an open science project that may evolve depending on the need of the community.</strong></p>
</section>
<section id="the-problem">
<h1>The problem<a class="headerlink" href="#the-problem" title="Link to this heading">#</a></h1>
<p><a class="reference external" href="https://en.wikipedia.org/wiki/Brain%E2%80%93computer_interface">Brain-Computer Interfaces</a>
allow to interact with a computer using brain signals. In this project, we focus mostly on
electroencephalographic signals
(<a class="reference external" href="https://en.wikipedia.org/wiki/Electroencephalography">EEG</a>), that is a very active
research domain, with worldwide scientific contributions. Still:</p>
<ul class="simple">
<li><p>Reproducible Research in BCI has a long way to go.</p></li>
<li><p>While many BCI datasets are made freely available, researchers do not publish code, and
reproducing results required to benchmark new algorithms turns out to be trickier than
it should be.</p></li>
<li><p>Performances can be significantly impacted by parameters of the preprocessing steps,
toolboxes used and implementation “tricks” that are almost never reported in the
literature.</p></li>
</ul>
<p>As a result, there is no comprehensive benchmark of BCI algorithms, and newcomers are
spending a tremendous amount of time browsing literature to find out what algorithm works
best and on which dataset.</p>
</section>
<section id="the-solution">
<h1>The solution<a class="headerlink" href="#the-solution" title="Link to this heading">#</a></h1>
<p>The Mother of all BCI Benchmarks allows to:</p>
<ul class="simple">
<li><p>Build a comprehensive benchmark of popular BCI algorithms applied on an extensive list
of freely available EEG datasets.</p></li>
<li><p>The code is available on GitHub, serving as a reference point for the future algorithmic
developments.</p></li>
<li><p>Algorithms can be ranked and promoted on a website, providing a clear picture of the
different solutions available in the field.</p></li>
</ul>
<p>This project will be successful when we read in an abstract “ … the proposed method
obtained a score of 89% on the MOABB (Mother of All BCI Benchmarks), outperforming the
state of the art by 5% …”.</p>
</section>
<section id="core-team">
<h1>Core Team<a class="headerlink" href="#core-team" title="Link to this heading">#</a></h1>
<p>This project is under the umbrella of <a class="reference external" href="http://neurotechx.com/">NeuroTechX</a>, the international
community for NeuroTech enthusiasts.</p>
<p>The Mother of all BCI Benchmarks was founded by <a class="reference external" href="http://alexandre.barachant.org/">Alexander Barachant</a> and <a class="reference external" href="https://www.linkedin.com/in/vinay-jayaram-8635aa25">Vinay Jayaram</a>.</p>
<p>It is currently maintained by:</p>
<ul class="simple">
<li><p><a class="reference external" href="https://sylvchev.github.io/">Sylvain Chevallier</a></p></li>
<li><p><a class="reference external" href="https://bruaristimunha.github.io/">Bruno Aristimunha</a></p></li>
<li><p><a class="reference external" href="https://github.com/PierreGtch">Pierre Guetschel</a></p></li>
<li><p><a class="reference external" href="https://github.com/gcattan">Grégoire Cattan</a></p></li>
<li><p><a class="reference external" href="https://github.com/toncho11">Anton Andreev</a></p></li>
</ul>
</section>
<section id="contributors">
<h1>Contributors<a class="headerlink" href="#contributors" title="Link to this heading">#</a></h1>
<p>The MOABB is a community project, and we are always thankful to all the contributors!</p>
<div align="center" class="moabb-contributors">
<a href="https://github.com/NeuroTechX/moabb/graphs/contributors">
<img src="https://contrib.rocks/image?repo=NeuroTechX/moabb" alt="MOABB contributors" width="1100" />
</a>
</div>
</section>
<section id="acknowledgements">
<h1>Acknowledgements<a class="headerlink" href="#acknowledgements" title="Link to this heading">#</a></h1>
<p>MOABB has benefited from the support of the following organizations:</p>
<p><a href="https://www.dataia.eu/en"><img src="https://www.dataia.eu/themes/dataia/css/images/DATAIA-h-sansfond.png" alt="DATAIA" style="height:60px; background-color:#2e4a7d; padding:10px; border-radius:5px;"/></a></p>
<section id="what-do-we-need">
<h2>What do we need?<a class="headerlink" href="#what-do-we-need" title="Link to this heading">#</a></h2>
<p><strong>You</strong>! In whatever way you can help.</p>
<p>We need expertise in programming, user experience, software sustainability, documentation
and technical writing and project management.</p>
<p>We’d love your feedback along the way.</p>
<p>Our primary goal is to build a comprehensive benchmark of popular BCI algorithms applied
on an extensive list of freely available EEG datasets, and we’re excited to support the
professional development of any and all of our contributors. If you’re looking to learn to
code, try out working collaboratively, or translate your skills to the digital domain,
we’re here to help.</p>
</section>
</section>
<section id="cite-moabb">
<h1>Cite MOABB<a class="headerlink" href="#cite-moabb" title="Link to this heading">#</a></h1>
<p>If you use MOABB in your experiments, please cite MOABB and the related publications:</p>
<p>📚 <a class="reference external" href="https://moabb.neurotechx.com/docs/cite.html">Full citation guide</a></p>
<section id="software-citation">
<h2>Software Citation<a class="headerlink" href="#software-citation" title="Link to this heading">#</a></h2>
<section id="apa-format">
<h3>APA Format<a class="headerlink" href="#apa-format" title="Link to this heading">#</a></h3>
<div class="highlight-text notranslate"><div class="highlight"><pre><span></span>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., Thielen, J., Hajhassani, D., Begany, K., Moreau, T., Roy, Y., Jayaram, V.,
Barachant, A., & Chevallier, S. (2026). Mother of all BCI Benchmarks (MOABB) (Version 1.5.0).
Zenodo. https://doi.org/10.5281/zenodo.10034223
</pre></div>
</div>
</section>
<section id="bibtex-format">
<h3>BibTeX Format<a class="headerlink" href="#bibtex-format" title="Link to this heading">#</a></h3>
<div class="highlight-bibtex notranslate"><div class="highlight"><pre><span></span><span class="nc">@software</span><span class="p">{</span><span class="nl">Aristimunha_Mother_of_all</span><span class="p">,</span>
<span class="w"> </span><span class="na">author</span><span class="w"> </span><span class="p">=</span><span class="w"> </span><span class="s">{Aristimunha, Bruno and</span>
<span class="s"> Carrara, Igor and</span>
<span class="s"> Guetschel, Pierre and</span>
<span class="s"> Sedlar, Sara and</span>
<span class="s"> Rodrigues, Pedro and</span>
<span class="s"> Sosulski, Jan and</span>
<span class="s"> Narayanan, Divyesh and</span>
<span class="s"> Bjareholt, Erik and</span>
<span class="s"> Barthelemy, Quentin and</span>
<span class="s"> Schirrmeister, Robin Tibor and</span>
<span class="s"> Kobler, Reinmar and</span>
<span class="s"> Kalunga, Emmanuel and</span>
<span class="s"> Darmet, Ludovic and</span>
<span class="s"> Gregoire, Cattan and</span>
<span class="s"> Abdul Hussain, Ali and</span>
<span class="s"> Gatti, Ramiro and</span>
<span class="s"> Goncharenko, Vladislav and</span>
<span class="s"> Andreev, Anton and</span>
<span class="s"> Thielen, Jordy and</span>
<span class="s"> Hajhassani, Davoud and</span>
<span class="s"> Begany, Katelyn and</span>
<span class="s"> Moreau, Thomas and</span>
<span class="s"> Roy, Yannick and</span>
<span class="s"> Jayaram, Vinay and</span>
<span class="s"> Barachant, Alexandre and</span>
<span class="s"> Chevallier, Sylvain}</span><span class="p">,</span>
<span class="w"> </span><span class="na">title</span><span class="w"> </span><span class="p">=</span><span class="w"> </span><span class="s">{Mother of all BCI Benchmarks}</span><span class="p">,</span>
<span class="w"> </span><span class="na">year</span><span class="w"> </span><span class="p">=</span><span class="w"> </span><span class="m">2026</span><span class="p">,</span>
<span class="w"> </span><span class="na">publisher</span><span class="w"> </span><span class="p">=</span><span class="w"> </span><span class="s">{Zenodo}</span><span class="p">,</span>
<span class="w"> </span><span class="na">version</span><span class="w"> </span><span class="p">=</span><span class="w"> </span><span class="s">{1.5.0}</span><span class="p">,</span>
<span class="w"> </span><span class="na">url</span><span class="w"> </span><span class="p">=</span><span class="w"> </span><span class="s">{https://github.com/NeuroTechX/moabb}</span><span class="p">,</span>
<span class="w"> </span><span class="na">doi</span><span class="w"> </span><span class="p">=</span><span class="w"> </span><span class="s">{10.5281/zenodo.10034223}</span><span class="p">,</span>
<span class="p">}</span>
</pre></div>
</div>
</section>
</section>
<section id="scientific-publications">
<h2>Scientific Publications<a class="headerlink" href="#scientific-publications" title="Link to this heading">#</a></h2>
<p>If you want to cite the scientific contributions of MOABB, please use the following papers:</p>
<section id="moabb-benchmark-paper">
<h3>MOABB Benchmark Paper<a class="headerlink" href="#moabb-benchmark-paper" title="Link to this heading">#</a></h3>
<blockquote>
<div><p>Sylvain Chevallier, Igor Carrara, Bruno Aristimunha, Pierre Guetschel, Sara Sedlar,
Bruna Junqueira Lopes, Sébastien Velut, Salim Khazem, Thomas Moreau</p>
<p><strong><a class="reference external" href="https://cnrs.hal.science/hal-04537061/">“The largest EEG-based BCI reproducibility study for open science: the MOABB benchmark”</a></strong></p>
<p>HAL: hal-04537061</p>
</div></blockquote>
</section>
<section id="original-moabb-paper">
<h3>Original MOABB Paper<a class="headerlink" href="#original-moabb-paper" title="Link to this heading">#</a></h3>
<blockquote>
<div><p>Vinay Jayaram and Alexandre Barachant</p>
<p><strong><a class="reference external" href="https://doi.org/10.1088/1741-2552/aadea0">“MOABB: trustworthy algorithm benchmarking for BCIs”</a></strong></p>
<p>Journal of Neural Engineering 15.6 (2018): 066011</p>
<p><a class="reference external" href="https://doi.org/10.1088/1741-2552/aadea0">DOI: 10.1088/1741-2552/aadea0</a></p>
</div></blockquote>
<hr class="docutils" />
<p>📣 <strong>If you publish a paper using MOABB, please <a class="reference external" href="https://github.com/NeuroTechX/moabb/issues">open an issue</a> to let us know!</strong>
We would love to hear about your work and help you promote it.</p>
</section>
</section>
</section>
<section id="contact-us">
<h1>Contact us<a class="headerlink" href="#contact-us" title="Link to this heading">#</a></h1>
<p>If you want to report a problem or suggest an enhancement, we’d love for you to
<a class="reference external" href="https://github.com/NeuroTechX/moabb/issues">open an issue</a> at this GitHub repository
because then we can get right on it.</p>
</section>
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