A crucial challenge for BCIs is the so called “non-learner” problem, the observation that a large proportion of users have difficulty in learning to self-regulate the neural activity that is reflected in the feedback. In other words, these “non-learner” users have difficulty in controlling the feedback provided by the BCI (i.e. neurofeedback, NFB). This has profound consequences for BCIs and NFB systems since only a limited portion of users can benefit from the technology.

In this line of research, we want to understand why some users have difficulty in learning to self-regulate their own brain activity. In our recent study, we set out to explore how the ability to self-regulate EEG power activity vary between different frequency bands and electrode locations. Twenty participants performed 4 sessions of EEG-based NFB training. Participants were instructed to make an arrow-head point upwards as much as possible without providing them with any specific strategy. The direction and pointiness of the arrow-head was determined by the EEG power in a specific frequency band and averaged across specified electrode locations. For each session, the arrow-head reflected a different frequency-electrode set of features, namely frontomidline theta, occipital alpha, centrotemporal SMR, and cenral beta.

We observed that all participants could learn to control at least 2 features. These results challenges the universal “non-learner” phenotype commonly portrayed in the literature.