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The american soldier, vol. 1: Adjustment during army life, 1949
S. RMJ · 1949
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Talking off the top of your head: toward a mental prosthesis utilizing event-related brain potentials
L. A. Farwell and E. Donchin · 1988
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Spatial patterns underlying population differences in the background EEG
Z. J. Koles, M. S. Lazar, and S. Z. Zhou · 1990
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Individual comparisons by ranking methods
F. Wilcoxon · 1992
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Designing optimal spatial filters for single-trial EEG classification in a movement task
J. Müller-Gerking, G. Pfurtscheller, and H. Flyvbjerg · 1999
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Optimal spatial filtering of single trial EEG during imagined hand movement
H. Ramoser, J. Muller-Gerking, and G. Pfurtscheller · 2000
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Efficient backprop
Y. LeCun, L. Bottou, G. B. Orr, and K.-R. Müller · 2002
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BCI2000: a general-purpose brain-computer interface (BCI) system
G. Schalk, D. J. McFarland, T. Hinterberger, N. Birbaumer, and J. R. Wolpaw · 2004
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A differential geometric approach to the geometric mean of symmetric positive-definite matrices
M. Moakher · 2005
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Frequency recognition based on canonical correlation analysis for SSVEP-based BCIs
Z. Lin, C. Zhang, W. Wu, and X. Gao · 2006
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Optimizing spatial filters for robust EEG single-trial analysis
B. Blankertz, R. Tomioka, S. Lemm, M. Kawanabe, and K.-R. Muller · 2007
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Brain–computer communication: motivation, aim, and impact of exploring a virtual apartment
R. Leeb, F. Lee, C. Keinrath, R. Scherer, H. Bischof, and G. Pfurtscheller · 2007
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A review of classification algorithms for EEG-based brain–computer interfaces
F. Lotte, M. Congedo, A. Lécuyer, F. Lamarche, and B. Arnaldi · 2007
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The influence of cognitive tasks on different frequencies steady-state visual evoked potentials
Z. Wu and D. Yao · 2007
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Filter bank common spatial pattern (FBCSP) in brain-computer interface
K. K. Ang, Z. Y. Chin, H. Zhang, and C. Guan · 2008
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An efficient P300-based brain–computer interface for disabled subjects
U. Hoffmann, J.-M. Vesin, T. Ebrahimi, and K. Diserens · 2008
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Beamforming in noninvasive brain–computer interfaces
M. Grosse-Wentrup, C. Liefhold, K. Gramann, and M. Buss · 2009
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How many people are able to control a P300-based brain–computer interface (BCI)?
C. Guger, S. Daban, E. Sellers, C. Holzner, G. Krausz, R. Carabalona, F. Gramatica, and G. Edlinger · 2009
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xDAWN algorithm to enhance evoked potentials: application to brain–computer interface
B. Rivet, A. Souloumiac, V. Attina, and G. Gibert · 2009
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Common spatial pattern revisited by riemannian geometry
A. Barachant, S. Bonnet, M. Congedo, and C. Jutten · 2010
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On over-fitting in model selection and subsequent selection bias in performance evaluation
G. C. Cawley and N. L. Talbot · 2010
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Regularizing common spatial patterns to improve BCI designs: unified theory and new algorithms
F. Lotte and C. Guan · 2010
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Openvibe: An open-source software platform to design, test, and use brain–computer interfaces in real and virtual environments
Y. Renard, F. Lotte, G. Gibert, M. Congedo, E. Maby, V. Delannoy, O. Bertrand, and A. Lécuyer · 2010
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Multiclass brain–computer interface classification by Riemannian geometry
A. Barachant, S. Bonnet, M. Congedo, and C. Jutten · 2011
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Brain invaders: a prototype of an open-source P300-based video game working with the OpenViBE platform
M. Congedo, M. Goyat, N. Tarrin, G. Ionescu, L. Varnet, B. Rivet, R. Phlypo, N. Jrad, M. Acquadro, and C. Jutten · 2011
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Scikit-learn: Machine learning in Python
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 · 2011
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Commande robuste d’un effecteur par une interface cerveau machine EEG asynchrone
A. Barachant · 2012
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Autocalibration and recurrent adaptation: Towards a plug and play online ERD-BCI
J. Faller, C. Vidaurre, T. Solis-Escalante, C. Neuper, and R. Scherer · 2012
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A P300 BCI for the masses: Prior information enables instant unsupervised spelling
P.-J. Kindermans, H. Verschore, D. Verstraeten, and B. Schrauwen · 2012
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Review of the BCI competition IV
M. Tangermann, K.-R. Müller, A. Aertsen, N. Birbaumer, C. Braun, C. Brunner, R. Leeb, C. Mehring, K. J. Miller, G. Mueller-Putz, et al · 2012
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MEG and EEG data analysis with MNE-Python
A. Gramfort, M. Luessi, E. Larson, D. A. Engemann, D. Strohmeier, C. Brodbeck, R. Goj, M. Jas, T. Brooks, L. Parkkonen, and M. S. Hämäläinen · 2013
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Attention and P300-based BCI performance in people with amyotrophic lateral sclerosis
A. Riccio, L. Simione, F. Schettini, A. Pizzimenti, M. Inghilleri, M. O. Belardinelli, D. Mattia, and F. Cincotti · 2013
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Influence of P300 latency jitter on event related potential-based brain–computer interface performance
P. Aricò, F. Aloise, F. Schettini, S. Salinari, D. Mattia, and F. Cincotti · 2014
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MEG decoding using Riemannian geometry and unsupervised classification
A. Barachant · 2014
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A plug&play P300 BCI using information geometry
A. Barachant and M. Congedo · 2014
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Visual and auditory brain–computer interfaces
S. Gao, Y. Wang, X. Gao, and B. Hong · 2014
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Statistical methods for meta-analysis
L. V. Hedges and I. Olkin · 2014
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Adam: A method for stochastic optimization
D. P. Kingma and J. Ba · 2014
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An introduction to the event-related potential technique
S. J. Luck · 2014
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Enhancing unsupervised canonical correlation analysis-based frequency detection of SSVEPs by incorporating background EEG
M. Nakanishi, Y. Wang, Y.-T. Wang, Y. Mitsukura, and T.-P. Jung · 2014
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Evaluation of EEG oscillatory patterns and cognitive process during simple and compound limb motor imagery
W. Yi, S. Qiu, K. Wang, H. Qi, L. Zhang, P. Zhou, F. He, and D. Ming · 2014
Cited alongside, same era.
Frequency recognition in SSVEP-based BCI using multiset canonical correlation analysis
Y. Zhang, G. Zhou, J. Jin, X. Wang, and A. Cichocki · 2014
Cited alongside, same era.
TensorFlow: Large-scale machine learning on heterogeneous systems, 2015
M. Abadi, A. Agarwal, P. Barham, E. Brevdo, Z. Chen, C. Citro, G. S. Corrado, A. Davis, J. Dean, M. Devin, S. Ghemawat, I. Goodfellow, A. Harp, G. Irving, M. Isard, Y. Jia, R. Jozefowicz, L. Kaiser, M. Kudlur, J. Levenberg, D. Mané, R. Monga, S. Moore, D. Murray, C. Olah, M. Schuster, J. Shlens, B. Steiner, I. Sutskever, K. Talwar, P. Tucker, V. Vanhoucke, V. Vasudevan, F. Viégas, O. Vinyals, P. Warden, M. Wattenberg, M. Wicke, Y. Yu, and X. Zheng · 2015
Cited alongside, same era.
A comparison study of canonical correlation analysis based methods for detecting steady-state visual evoked potentials
M. Nakanishi, Y. Wang, Y.-T. Wang, and T.-P. Jung · 2015
Cited alongside, same era.
Individually adapted imagery improves brain-computer interface performance in end-users with disability
wav2vec: Unsupervised pre-training for speech recognition
S. Schneider, A. Baevski, R. Collobert, and M. Auli · 2019
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Spatial filters for auditory evoked potentials transfer between different experimental conditions
J. Sosulski and M. Tangermann · 2019
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Brain invaders adaptive versus non-adaptive P300 brain-computer interface dataset
E. Vaineau, A. Barachant, A. Andreev, P. C. Rodrigues, G. Cattan, and M. Congedo · 2019
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Building brain invaders: EEG data of an experimental validation
G. Van Veen, A. Barachant, A. Andreev, G. Cattan, P. C. Rodrigues, and M. Congedo · 2019
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A simple framework for contrastive learning of visual representations
T. Chen, S. Kornblith, M. Norouzi, and G. Hinton · 2020
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R. Scherer, J. Faller, E. V. Friedrich, E. Opisso, U. Costa, A. Kübler, and G. R. Müller-Putz · 2015
Cited alongside, same era.
Broad-band visually evoked potentials: re (con) volution in brain-computer interfacing
J. Thielen, P. van den Broek, J. Farquhar, and P. Desain · 2015
Cited alongside, same era.
1,500 scientists lift the lid on reproducibility
M. Baker · 2016
Cited alongside, same era.
Comparison of an open-hardware electroencephalography amplifier with medical grade device in brain-computer interface applications
J. Frey · 2016
Cited alongside, same era.
Transfer learning in brain-computer interfaces
V. Jayaram, M. Alamgir, Y. Altun, B. Scholkopf, and M. Grosse-Wentrup · 2016
Cited alongside, same era.
Online SSVEP-based BCI using Riemannian geometry
E. K. Kalunga, S. Chevallier, Q. Barthélemy, K. Djouani, E. Monacelli, and Y. Hamam · 2016
Cited alongside, same era.
Comparative evaluation of state-of-the-art algorithms for SSVEP-based BCIs
V. P. Oikonomou, G. Liaros, K. Georgiadis, E. Chatzilari, K. Adam, S. Nikolopoulos, and I. Kompatsiaris · 2016
Cited alongside, same era.
Open access dataset for EEG+ NIRS single-trial classification
J. Shin, A. von Lühmann, B. Blankertz, D.-W. Kim, J. Jeong, H.-J. Hwang, and K.-R. Müller · 2016
Cited alongside, same era.
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SciKeras , 2020
A. Garcia Badaracco · 2020
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Array programming with NumPy
C. R. Harris, K. J. Millman, S. J. van der Walt, R. Gommers, P. Virtanen, D. Cournapeau, E. Wieser, J. Taylor, S. Berg, N. J. Smith, R. Kern, M. Picus, S. Hoyer, M. H. van Kerkwijk, M. Brett, A. Haldane, J. F. del Río, M. Wiebe, P. Peterson, P. Gérard-Marchant, K. Sheppard, T. Reddy, W. Weckesser, H. Abbasi, C. Gohlke, and T. E. Oliphant · 2020
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EEG-TCNet: An accurate temporal convolutional network for embedded motor-imagery brain–machine interfaces
T. M. Ingolfsson, M. Hersche, X. Wang, N. Kobayashi, L. Cavigelli, and L. Benini · 2020
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SciPy 1.0: Fundamental algorithms for scientific computing in python
P. Virtanen, R. Gommers, T. E. Oliphant, M. Haberland, T. Reddy, D. Cournapeau, E. Burovski, P. Peterson, W. Weckesser, J. Bright, S. J. van der Walt, M. Brett, J. Wilson, K. J. Millman, N. Mayorov, A. R. J. Nelson, E. Jones, R. Kern, E. Larson, C. J. Carey, İ. Polat, Y. Feng, E. W. Moore, J. VanderPlas, D. Laxalde, J. Perktold, R. Cimrman, I. Henriksen, E. A. Quintero, C. R. Harris, A. M. Archibald, A. H. Ribeiro, F. Pedregosa, P. van Mulbregt, and SciPy 1.0 Contributors · 2020
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Uncovering the structure of clinical EEG signals with self-supervised learning
H. Banville, O. Chehab, A. Hyvärinen, D.-A. Engemann, and A. Gramfort · 2021
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Improving P300 speller performance by means of optimization and machine learning
L. Bianchi, C. Liti, G. Liuzzi, V. Piccialli, and C. Salvatore · 2021
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Minimizing subject-dependent calibration for BCI with Riemannian transfer learning
S. Khazem, S. Chevallier, Q. Barthélemy, K. Haroun, and C. Noûs · 2021
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Brain-computer interfaces based on code-modulated visual evoked potentials (c-VEP): A literature review
V. Martínez-Cagigal, J. Thielen, E. Santamaria-Vazquez, S. Pérez-Velasco, P. Desain, and R. Hornero · 2021
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J. Sosulski, D. Hübner, A. Klein, and M. Tangermann · 2021
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From full calibration to zero training for a code-modulated visual evoked potentials for brain–computer interface
J. Thielen, P. Marsman, J. Farquhar, and P. Desain · 2021
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A review on transfer learning in EEG signal analysis
Z. Wan, R. Yang, M. Huang, N. Zeng, and X. Liu · 2021
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Toward reliable signals decoding for electroencephalogram: A benchmark study to EEGNeX
X. Chen, X. Teng, H. Chen, Y. Pan, and P. Geyer · 2022
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Functional connectivity ensemble method to enhance BCI performance (FUCONE)
M.-C. Corsi, S. Chevallier, F. D. V. Fallani, and F. Yger · 2022
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Unraveling the hidden environmental impacts of AI solutions for environment life cycle assessment of AI solutions
A.-L. Ligozat, J. Lefevre, A. Bugeau, and J. Combaz · 2022
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Benchopt: Reproducible, efficient and collaborative optimization benchmarks
T. Moreau, M. Massias, A. Gramfort, P. Ablin, P.-A. Bannier, B. Charlier, M. Dagréou, T. D. la Tour, G. Durif, C. F. Dantas, Q. Klopfenstein, J. Larsson, E. Lai, T. Lefort, B. Malézieux, B. Moufad, B. T. Nguyen, A. Rakotomamonjy, Z. Ramzi, J. Salmon, and S. Vaiter · 2022
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Building experiments in PsychoPy
J. Peirce, R. Hirst, and M. MacAskill · 2022
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Data augmentation for learning predictive models on EEG: a systematic comparison
C. Rommel, J. Paillard, T. Moreau, and A. Gramfort · 2022
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Neuroergonomics and physiological computing contributions to human-machine interaction
R. N. Roy · 2022
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EEG-ITNet: An explainable inception temporal convolutional network for motor imagery classification
A. Salami, J. Andreu-Perez, and H. Gillmeister · 2022
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A 120-target brain-computer interface based on code-modulated visual evoked potentials
Q. Sun, L. Zheng, W. Pei, X. Gao, and Y. Wang · 2022
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2021 BEETL competition: Advancing transfer learning for subject independence & heterogenous EEG data sets
X. Wei, A. A. Faisal, M. Grosse-Wentrup, A. Gramfort, S. Chevallier, V. Jayaram, C. Jeunet, S. Bakas, S. Ludwig, K. Barmpas, et al · 2022
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pyriemann, June 2023
A. Barachant, Q. Barthélemy, J.-R. King, A. Gramfort, S. Chevallier, P. L. C. Rodrigues, E. Olivetti, V. Goncharenko, G. W. vom Berg, G. Reguig, A. Lebeurrier, E. Bjäreholt, M. S. Yamamoto, P. Clisson, and M.-C. Corsi · 2023
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End-to-end P300 BCI using Bayesian accumulation of riemannian probabilities
Q. Barthélemy, S. Chevallier, R. Bertrand-Lalo, and P. Clisson · 2023
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An introduction to optimization on smooth manifolds
N. Boumal · 2023
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A novel OpenBCI framework for EEG-based neurophysiological experiments
Y. N. Cardona-Álvarez, A. M. Álvarez-Meza, D. A. Cárdenas-Peña, G. A. Castaño-Duque, and G. Castellanos-Dominguez · 2023
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Classification of BCI-EEG based on augmented covariance matrix
I. Carrara and T. Papadopoulo · 2023
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EEG is better left alone
A. Delorme · 2023
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Transfer learning between motor imagery datasets using deep learning - validation of framework and comparison of datasets, Nov. 2023
P. Guetschel and M. Tangermann · 2023
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An experimental comparison of software-based power meters: focus on CPU and GPU
M. Jay, V. Ostapenco, L. Lefèvre, D. Trystram, A.-C. Orgerie, and B. Fichel · 2023
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Estimating the carbon footprint of bloom, a 176b parameter language model
A. S. Luccioni, S. Viguier, and A.-L. Ligozat · 2023
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UMM: Unsupervised mean-difference maximization
J. Sosulski and M. Tangermann · 2023
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Pseudo-online framework for BCI evaluation: a MOABB perspective using various MI and SSVEP datasets
I. Carrara and T. Papadopoulo · 2024
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