EEG based Brain Computer Interfaces have matured considerably since their first appearance. However, one central aspect, their online character, still seems underexploited. This aspect allows for a more optimal stimulus selection and we will explain how this can be used for well-known (speller) BCI's and can increase their performance. When the stimulus and response space is very large, as it is in less common (word-probing) BCI's this approach becomes essential. Another domain in which our knowledge on reliable detection of EEG markers still needs be applied more thorough is plasticity and training. While general neuro-feedback on features of the mental state still seems unable to demonstrate lasting cognitive or behavioral changes, feedback on the processing of stimuli may allow for more efficient training of a whole range of perceptual skills. We will explain how we are investigating this approach for second language learning.