Neurofeedback is based on a brain-computer interface (BCI) and is implemented by a software system and a processing pipeline, altogether consisting of five elements (Fig. 1) [12•]. Neurofeedback measures the participant’s own brain activity, which is pre-processed (steps 1 and 2). Pre-selected brain parameters (a specific frequency band or a brain potential) are calculated online (step 3) and translated to signals that are fed back to the user in real time (step 4). Thus, selected features of brain activity are made perceivable for the participant. Through this feedback, the participant (step 5) can learn to self-regulate his own brain activity to directly alter the underlying neural mechanism of cognition and behavior.

Nowadays, neurofeedback is used in three ways: (i) as a therapeutic tool to normalize deviating brain activity and treat neurocognitive disorders, (ii) as a so-called peak performance training to enhance cognitive performance in healthy participants, and (iii) as an experimental method to investigate the causal role of neural oscillations in cognition and behavior.