Klaus-Robert Müller

TL;DR: This work uses a large database of EEG recordings from 45 subjects, who took part in movement imagination task experiments, to construct an ensemble of classifiers derived from subject-specific temporal and spatial filters.

TL;DR: This Letter proposes a novel technique, stationary subspace analysis (SSA), that decomposes a multivariate time series into its stationary and nonstationary part and succeeds in finding stationary components that lead to a significantly improved prediction accuracy and meaningful topographic maps which contribute to a better understanding of the underlyingnonstationary brain processes.

TL;DR: Psychological parameters as measured in this study play a moderate role for one-session performance in a BCI controlled by modulation of SMR.

TL;DR: This work applies a specific propagation rule applicable to multiplicative connections as they arise in recurrent network architectures such as LSTMs and GRUs to a word-based bi-directional LSTM model on a five-class sentiment prediction task and evaluates the resulting LRP relevances both qualitatively and quantitatively.

TL;DR: The present variant of the Berlin BCI is designed to achieve fast classifications in normally behaving subjects and opens a new perspective for assistance of action control in time-critical behavioral contexts; the potential transfer to paralyzed patients will require further study.