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Context Left-hemispheric stroke can lead to different language deficits, which are a heavy burden both, for the individual and his/her social interaction, as well as for society. While spontaneous recovery in the first weeks after the stroke may reduce this so-called aphasia, many patients remain with different language problems also in the chronic phase.

Context Left-hemispheric stroke can lead to different language deficits, which are a heavy burden both, for the individual and his/her social interaction, as well as for society. While spontaneous recovery in the first weeks after the stroke may reduce this so-called aphasia, many patients remain with different language problems also in the chronic phase.

Brain-computer interface (BCI) protocols, which make use of an event-related potential protocol typically provide different external stimuli to users and record, if one of these stimuli was perceived as an attended target stimulus, while the other stimuli should have been ignored as so-called non-target stimuli.

Context Left-hemispheric stroke can lead to different language deficits, which are a heavy burden both, for the individual and his/her social interaction, as well as for society. While spontaneous recovery in the first weeks after the stroke may reduce this so-called aphasia, many patients remain with different language problems also in the chronic phase.

Our group developed a fast assessment of motor performance for Parkinson patients, the CopyDraw task. This paradigm enables us to record multiple repetitions of Parkinson patients performing the task with and without deep brain stimulation.

Context For the rehabilitation training after stroke, simple repetitive hand motor tasks have been developed. One of them, the Sequential Visual Isometric Pinch Task (SVIPT) has been performed in studies with healthy users and stroke patients while the user’s brain activity (electroencephalogram, EEG) has been recorded.

Context Simple repetitive hand motor tasks, such as those used for rehabilitation training after stroke, are known to show strong trial-by-trial performance variations even though a trial typically lasts a few seconds only.

Context Reinforcement learning (RL) methods interact with a system in closed loop in order to learn suitable action strategies. The goal of this interaction is to control the system, e.g., to bring it into a desired state.