Distinct cortical networks for hand movement initiation and directional processing: An EEG study von Kobler, Reinmar J., Kolesnichenko, Elizaveta, Sburlea, Andreea I., Müller-Putz, Gernot R.

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Tuning characteristics of low-frequency EEG to positions and velocities in visuomotor and oculomotor tracking tasks von Kobler, Reinmar J., Sburlea, Andreea I., Müller-Putz, Gernot R.

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Corneo-retinal-dipole and eyelid-related eye artifacts can be corrected offline and online in electroencephalographic and magnetoencephalographic signals von Kobler, Reinmar J., Sburlea, Andreea I., Lopes-Dias, Catarina, Schwarz, Andreas, Hirata, Masayuki, Müller-Putz, Gernot R.

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Editorial: Towards dependable brain computer/machine interfaces for movement control von Müller-Putz, Gernot R, Collinger, Jennifer L, Kobler, Reinmar J

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Distance- and speed-informed kinematics decoding improves M/EEG based upper-limb movement decoder accuracy von Kobler, Reinmar J, Sburlea, Andreea I, Mondini, Valeria, Hirata, Masayuki, Müller-Putz, Gernot R

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Feel Your Reach: An EEG-Based Framework to Continuously Detect Goal-Directed Movements and Error Processing to Gate Kinesthetic Feedback Informed Artificial Arm Control von Müller-Putz, Gernot R, Kobler, Reinmar J, Pereira, Joana, Lopes-Dias, Catarina, Hehenberger, Lea, Mondini, Valeria, Martínez-Cagigal, Víctor, Srisrisawang, Nitikorn, Pulferer, Hannah, Batistić, Luka, Sburlea, Andreea I

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Long-Term Mutual Training for the CYBATHLON BCI Race With a Tetraplegic Pilot: A Case Study on Inter-Session Transfer and Intra-Session Adaptation von Hehenberger, Lea, Kobler, Reinmar J, Lopes-Dias, Catarina, Srisrisawang, Nitikorn, Tumfart, Peter, Uroko, John B, Torke, Paul R, Müller-Putz, Gernot R

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Continuous low-frequency EEG decoding of arm movement for closed-loop, natural control of a robotic arm von Mondini, Valeria, Kobler, Reinmar J, Sburlea, Andreea I, Müller-Putz, Gernot R

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Using machine learning to reveal the population vector from EEG signals von Kobler, Reinmar J, Almeida, Inês, Sburlea, Andreea I, Müller-Putz, Gernot R

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Test-retest reliability of EEG microstate metrics for evaluating noise reductions in simultaneous EEG-fMRI von Kuroda, Toshikazu, Kobler, Reinmar J., Ogawa, Takeshi, Tsutsumi, Mizuki, Kishi, Tomohiko, Kawanabe, Motoaki

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SPDIM: Source-Free Unsupervised Conditional and Label Shift Adaptation in EEG von Li, Shanglin, Kawanabe, Motoaki, Kobler, Reinmar J

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On Similarities and Differences of Invasive and Non-Invasive Electrical Brain Signals in Brain-Computer Interfacing von Steyrl, David, Kobler, Reinmar J., Müller-Putz, Gernot R.

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SPDIM: Source-Free Unsupervised Conditional and Label Shift Adaptation in EEG von Li, Shanglin, Kawanabe, Motoaki, Kobler, Reinmar J

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SPD domain-specific batch normalization to crack interpretable unsupervised domain adaptation in EEG von Kobler, Reinmar J, Hirayama, Jun-ichiro, Zhao, Qibin, Kawanabe, Motoaki

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On the interpretation of linear Riemannian tangent space model parameters in M/EEG von Kobler, Reinmar J, Hirayama, Jun-Ichiro, Lopes-Dias, Lea Hehenberger Catarina, Müller-Putz, Gernot R, Kawanabe, Motoaki

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SPD domain-specific batch normalization to crack interpretable unsupervised domain adaptation in EEG von Kobler, Reinmar J, Hirayama, Jun-ichiro, Zhao, Qibin, Kawanabe, Motoaki

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HEAR to remove pops and drifts: the high-variance electrode artifact removal (HEAR) algorithm von Kobler, Reinmar J, Sburlea, Andreea I, Mondini, Valeria, Müller-Putz, Gernot R

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On the interpretation of linear Riemannian tangent space model parameters in M/EEG von Kobler, Reinmar J, Hirayama, Jun-Ichiro, Lea Hehenberger Catarina Lopes-Dias, Müller-Putz, Gernot R, Kawanabe, Motoaki

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HEAR to remove pops and drifts: the high-variance electrode artifact removal (HEAR) algorithm von Kobler, Reinmar J, Sburlea, Andreea I, Mondini, Valeria, Müller-Putz, Gernot R

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