References#
The bibliography below is the single source of truth for citations
across the EEGDash documentation. Tutorials and concept pages reference
entries with :cite:`<key>` (e.g. :cite:`alexander2017hbn`);
add or amend an entry once in docs/source/refs.bib and every
referenced page picks it up automatically on the next build.
Obada Al Zoubi, Chung Ki Wong, Rayus T. Kuplicki, Hung-wen Yeh, Ahmad Mayeli, Hazem Refai, Martin Paulus, and Jerzy Bodurka. Predicting age from brain EEG signals — a machine learning approach. Frontiers in Aging Neuroscience, 2018. doi:10.3389/fnagi.2018.00184.
Lindsay M. Alexander, Jasmine Escalera, Lei Ai, Charissa Andreotti, Karina Febre, Alexander Mangone, Natan Vega-Potler, Nicolas Langer, Alexis Alexander, Meagan Kovacs, Shannon Litke, Bridget O'Hagan, Jennifer Andersen, Batya Bronstein, Anastasia Bui, Marijayne Bushey, Henry Butler, Victoria Castagna, Nicolas Camacho, Elisha Chan, Danielle Citera, Jon Clucas, Samantha Cohen, Sarah Dufek, Megan Eaves, Brian Fradera, Judith Gardner, Natalie Grant-Villegas, Gabriella Green, Camille Gregory, Emily Hart, Shana Harris, Megan Horton, Danielle Kahn, Katherine Kabotyanski, Bernard Karmel, Simon P. Kelly, Kayla Kleinman, Bonhwang Koo, Eliza Kramer, Elizabeth Lennon, Catherine Lord, Ginny Mantello, Amy Margolis, Kathleen R. Merikangas, Judith Milham, Giuseppe Minniti, Rebecca Neuhaus, Alexandra Levine, Yael Osman, Lucas C. Parra, Ken R. Pugh, Amy Racanello, Anita Restrepo, Tian Saltzman, Batya Septimus, Russell Tobe, Rachel Waltz, Anna Williams, Anna Yeo, Francisco X. Castellanos, Arno Klein, Tomas Paus, Bennett L. Leventhal, R. Cameron Craddock, Harold S. Koplewicz, and Michael P. Milham. An open resource for transdiagnostic research in pediatric mental health and learning disorders. Scientific Data, 2017. doi:10.1038/sdata.2017.181.
Bruno Aristimunha, Igor Carrara, Pierre Guetschel, Sara Sedlar, Pedro Rodrigues, Jan Sosulski, Divyesh Narayanan, Erik Bjareholt, Quentin Barthelemy, Robin Tibor Schirrmeister, Reinmar Kobler, Emmanuel Kalunga, Ludovic Darmet, Cattan Gregoire, Ali Abdul Hussain, Ramiro Gatti, Vladislav Goncharenko, Anton Andreev, Alberto Tates, Simon Kojima, Jordy Thielen, Davoud Hajhassani, Katelyn Begany, Thomas Moreau, Yannick Roy, Vinay Jayaram, Alexandre Barachant, and Sylvain Chevallier. Mother of all BCI benchmarks. 2026. URL: NeuroTechX/moabb, doi:10.5281/zenodo.10034223.
Bruno Aristimunha, Raphael Y. de Camargo, Walter H. Lopez Pinaya, Sylvain Chevallier, Alexandre Gramfort, and Cedric Rommel. Evaluating the structure of cognitive tasks with transfer learning. 2023. arXiv preprint. doi:10.48550/arXiv.2308.02408.
Bruno Aristimunha, Dung Truong, Pierre Guetschel, Seyed Yahya Shirazi, Isabelle Guyon, Alexandre R. Franco, Michael P. Milham, Aviv Dotan, Scott Makeig, Alexandre Gramfort, Jean-Remi King, Marie-Constance Corsi, Pedro A. Valdés-Sosa, Amit Majumdar, Alan Evans, Terrence J. Sejnowski, Oren Shriki, Sylvain Chevallier, and Arnaud Delorme. EEG foundation challenge: from cross-task to cross-subject EEG decoding. 2025. arXiv preprint, NeurIPS 2025 Competition track. doi:10.48550/arXiv.2506.19141.
Hubert Banville, Omar Chehab, Aapo Hyvärinen, Denis-Alexander Engemann, and Alexandre Gramfort. Uncovering the structure of clinical eeg signals with self-supervised learning. Journal of Neural Engineering, 18(4):046020, 2021. doi:10.1088/1741-2552/abca18.
Hans Berger. Über das elektrenkephalogramm des menschen. Archiv für Psychiatrie und Nervenkrankheiten, 87(1):527–570, 1929. doi:10.1007/BF01797193.
Geoffrey Brookshire, Jake Kasper, Nicholas M. Blauch, Yunan Charles Wu, Ryan Glatt, David A. Merrill, Spencer Gerrol, Keith J. Yoder, Colin Quirk, and Ché Lucero. Data leakage in deep learning studies of translational eeg. Frontiers in Neuroscience, 2024. doi:10.3389/fnins.2024.1373515.
Avshalom Caspi, Renate M. Houts, Daniel W. Belsky, Sidra J. Goldman-Mellor, HonaLee Harrington, Salomon Israel, Madeline H. Meier, Sandhya Ramrakha, Idan Shalev, Richie Poulton, and Terrie E. Moffitt. The p factor. Clinical Psychological Science, 2(2):119–137, 2013. doi:10.1177/2167702613497473.
Stanislas Chambon, Mathieu N. Galtier, Pierrick J. Arnal, Gilles Wainrib, and Alexandre Gramfort. A deep learning architecture for temporal sleep stage classification using multivariate and multimodal time series. IEEE Transactions on Neural Systems and Rehabilitation Engineering, 26(4):758–769, 2018. doi:10.1109/TNSRE.2018.2813138.
Sylvain Chevallier, Igor Carrara, Bruno Aristimunha, Pierre Guetschel, Bruna Junqueira Lopes, Sébastien Velut, Salim Khazem, and Thomas Moreau. The largest EEG-based BCI reproducibility study for open science: the MOABB benchmark. 2024. HAL preprint hal-04537061. URL: https://cnrs.hal.science/hal-04537061/, doi:10.48550/arXiv.2404.15319.
Giulia Cisotto and Davide Chicco. Ten quick tips for clinical electroencephalographic (eeg) data acquisition and signal processing. PeerJ Computer Science, 10:e2256, 2024. doi:10.7717/peerj-cs.2256.
Etienne Combrisson and Karim Jerbi. Exceeding chance level by chance: the caveat of theoretical chance levels in brain signal classification and statistical assessment of decoding accuracy. Journal of Neuroscience Methods, 250:126–136, 2015. doi:10.1016/j.jneumeth.2015.01.010.
Arnaud Delorme and Scott Makeig. Eeglab: an open source toolbox for analysis of single-trial eeg dynamics including independent component analysis. Journal of Neuroscience Methods, 134(1):9–21, 2004. doi:10.1016/j.jneumeth.2003.10.009.
Arnaud Delorme, Dung Truong, Choonhan Youn, Subhashini Sivagnanam, Claire Stirm, Kenneth Yoshimoto, Russell A Poldrack, Amitava Majumdar, and Scott Makeig. Nemar: an open access data, tools and compute resource operating on neuroelectromagnetic data. Database, 2022. doi:10.1093/database/baac096.
Charmaine Demanuele, Christopher J James, and Edmund JS Sonuga-Barke. Distinguishing low frequency oscillations within the 1/f spectral behaviour of electromagnetic brain signals. Behavioral and Brain Functions, 3(1):62, 2007. doi:10.1186/1744-9081-3-62.
Thomas Donoghue, Matar Haller, Erik J. Peterson, Paroma Varma, Priyadarshini Sebastian, Richard Gao, Torben Noto, Antonio H. Lara, Joni D. Wallis, Robert T. Knight, Avgusta Shestyuk, and Bradley Voytek. Parameterizing neural power spectra into periodic and aperiodic components. Nature Neuroscience, 23(12):1655–1665, 2020. doi:10.1038/s41593-020-00744-x.
Alexandre Défossez, Charlotte Caucheteux, Jérémy Rapin, Ori Kabeli, and Jean-Rémi King. Decoding speech perception from non-invasive brain recordings. Nature Machine Intelligence, 5(10):1097–1107, 2023. doi:10.1038/s42256-023-00714-5.
Alexandre Gramfort, Martin Luessi, Eric Larson, Denis A. Engemann, Daniel Strohmeier, Christian Brodbeck, Roman Goj, Mainak Jas, Teon Brooks, Lauri Parkkonen, and Matti Hämäläinen. Meg and eeg data analysis with mne-python. Frontiers in Neuroscience, 2013. doi:10.3389/fnins.2013.00267.
Vinay Jayaram and Alexandre Barachant. Moabb: trustworthy algorithm benchmarking for bcis. Journal of Neural Engineering, 15(6):066011, 2018. doi:10.1088/1741-2552/aadea0.
Wolfgang Klimesch. Alpha-band oscillations, attention, and controlled access to stored information. Trends in Cognitive Sciences, 16(12):606–617, 2012. doi:10.1016/j.tics.2012.10.007.
Andreas Miltiadous, Katerina D. Tzimourta, Theodora Afrantou, Panagiotis Ioannidis, Nikolaos Grigoriadis, Dimitrios G. Tsalikakis, Pantelis Angelidis, Markos G. Tsipouras, Euripidis Glavas, Nikolaos Giannakeas, and Alexandros T. Tzallas. A dataset of scalp eeg recordings of alzheimer’s disease, frontotemporal dementia and healthy subjects from routine eeg. Data, 8(6):95, 2023. doi:10.3390/data8060095.
Alexander Nederbragt, Rayna Michelle Harris, Alison Presmanes Hill, and Greg Wilson. Ten quick tips for teaching with participatory live coding. PLOS Computational Biology, 2020. doi:10.1371/journal.pcbi.1008090.
R. Näätänen, P. Paavilainen, T. Rinne, and K. Alho. The mismatch negativity (mmn) in basic research of central auditory processing: a review. Clinical Neurophysiology, 2007. doi:10.1016/j.clinph.2007.04.026.
Adam Paszke, Sam Gross, Francisco Massa, Adam Lerer, James Bradbury, Gregory Chanan, Trevor Killeen, Zeming Lin, Natalia Gimelshein, Luca Antiga, Alban Desmaison, Andreas Köpf, Edward Yang, Zachary DeVito, Martin Raison, Alykhan Tejani, Sasank Chilamkurthy, Benoit Steiner, Lu Fang, Junjie Bai, and Soumith Chintala. PyTorch: an imperative style, high-performance deep learning library. In Advances in Neural Information Processing Systems 32, 8024–8035. 2019. doi:10.48550/arXiv.1912.01703.
F. Pedregosa, G. Varoquaux, A. Gramfort, V. Michel, B. Thirion, O. Grisel, M. Blondel, P. Prettenhofer, R. Weiss, V. Dubourg, J. Vanderplas, A. Passos, D. Cournapeau, M. Brucher, M. Perrot, and E. Duchesnay. Scikit-learn: machine learning in Python. Journal of Machine Learning Research, 12:2825–2830, 2011.
Cyril R. Pernet, Stefan Appelhoff, Krzysztof J. Gorgolewski, Guillaume Flandin, Christophe Phillips, Arnaud Delorme, and Robert Oostenveld. Eeg-bids, an extension to the brain imaging data structure for electroencephalography. Scientific Data, 2019. doi:10.1038/s41597-019-0104-8.
John Polich. Updating p300: an integrative theory of p3a and p3b. Clinical Neurophysiology, 2007. doi:10.1016/j.clinph.2007.04.019.
Robin Tibor Schirrmeister, Jost Tobias Springenberg, Lukas Dominique Josef Fiederer, Martin Glasstetter, Katharina Eggensperger, Michael Tangermann, Frank Hutter, Wolfram Burgard, and Tonio Ball. Deep learning with convolutional neural networks for eeg decoding and visualization. Human Brain Mapping, 38(11):5391–5420, 2017. doi:10.1002/hbm.23730.
Nancy K. Squires, Kenneth C. Squires, and Steven A. Hillyard. Two varieties of long-latency positive waves evoked by unpredictable auditory stimuli in man. Electroencephalography and Clinical Neurophysiology, 1975. doi:10.1016/0013-4694(75)90263-1.
Michael Tangermann, Klaus-Robert Müller, Ad Aertsen, Niels Birbaumer, Christoph Braun, Clemens Brunner, Robert Leeb, Carsten Mehring, Kai J. Miller, Gernot R. Müller-Putz, Guido Nolte, Gert Pfurtscheller, Hubert Preissl, Gerwin Schalk, Alois Schlögl, Carmen Vidaurre, Stephan Waldert, and Benjamin Blankertz. Review of the bci competition iv. Frontiers in Neuroscience, 2012. doi:10.3389/fnins.2012.00055.
Daniel G Wakeman and Richard N Henson. A multi-subject, multi-modal human neuroimaging dataset. Scientific Data, 2015. doi:10.1038/sdata.2015.1.
P. Welch. The use of fast fourier transform for the estimation of power spectra: a method based on time averaging over short, modified periodograms. IEEE Transactions on Audio and Electroacoustics, 15(2):70–73, 1967. doi:10.1109/TAU.1967.1161901.
Mark D. Wilkinson, Michel Dumontier, IJsbrand Jan Aalbersberg, Gabrielle Appleton, Myles Axton, Arie Baak, Niklas Blomberg, Jan-Willem Boiten, Luiz Bonino da Silva Santos, Philip E. Bourne, Jildau Bouwman, Anthony J. Brookes, Tim Clark, Mercè Crosas, Ingrid Dillo, Olivier Dumon, Scott Edmunds, Chris T. Evelo, Richard Finkers, Alejandra Gonzalez-Beltran, Alasdair J. G. Gray, Paul Groth, Carole Goble, Jeffrey S. Grethe, Jaap Heringa, Peter A. C. 't Hoen, Rob Hooft, Tobias Kuhn, Ruben Kok, Joost Kok, Scott J. Lusher, Maryann E. Martone, Albert Mons, Abel L. Packer, Bengt Persson, Philippe Rocca-Serra, Marco Roos, Rene van Schaik, Susanna-Assunta Sansone, Erik Schultes, Thierry Sengstag, Ted Slater, George Strawn, Morris A. Swertz, Mark Thompson, Johan van der Lei, Erik van Mulligen, Jan Velterop, Andra Waagmeester, Peter Wittenburg, Katherine Wolstencroft, Jun Zhao, and Barend Mons. The FAIR guiding principles for scientific data management and stewardship. Scientific Data, 2016. doi:10.1038/sdata.2016.18.
EEG 2025 Foundation Challenge. EEG 2025 Foundation Challenge. https://eeg2025.github.io, 2025.