PubMed Mentions
The links below are to publications on PubMed referring to BCI2000. This list is gathered weekly from PubMed automatically.
| Publication/References | |
| Cortical alpha activity predicts the confidence in an impending action. Description: Kubanek, Jan, et al. Cortical alpha activity predicts the confidence in an impending action. ''Front Neurosci''. 2015; '''9''': 243 | |
| Unilateral, 3D Arm Movement Kinematics Are Encoded in Ipsilateral Human Cortex. Description: Bundy, David T, et al. Unilateral, 3D Arm Movement Kinematics Are Encoded in Ipsilateral Human Cortex. ''J Neurosci''. 2018 Nov 21; '''38''' (47):10042-10056 | |
| Different oscillatory entrainment of cortical networks during motor imagery and neurofeedback in right and left handers. Description: Vukelic, Mathias, et al. Different oscillatory entrainment of cortical networks during motor imagery and neurofeedback in right and left handers. ''Neuroimage''. 2019 Jul 15; '''195''': 190-202 | |
| Denoising EEG Signals for Real-World BCI Applications Using GANs. Description: Brophy, Eoin, et al. Denoising EEG Signals for Real-World BCI Applications Using GANs. ''Front Neuroergon''. 2021; '''2''': 805573 | |
| Dynamic causal modelling shows a prominent role of local inhibition in alpha power modulation in higher visual cortex. Description: Van de Steen, Frederik, et al. Dynamic causal modelling shows a prominent role of local inhibition in alpha power modulation in higher visual cortex. ''PLoS Comput Biol''. 2022 Dec; '''18''' (12):e1009988 | |
| Electroencephalogram-Based Subject Matching Learning (ESML): A Deep Learning Framework on Electroencephalogram-Based Biometrics and Task Identification. Description: Xu, Jin, et al. Electroencephalogram-Based Subject Matching Learning (ESML): A Deep Learning Framework on Electroencephalogram-Based Biometrics and Task Identification. ''Behav Sci (Basel)''. 2023 Sep 14; '''13''' (9): | |
| EEG-based identification system using deep neural networks with frequency features. Description: Akbarnia, Yasaman, et al. EEG-based identification system using deep neural networks with frequency features. ''Heliyon''. 2024 Feb 29; '''10''' (4):e25999 |