The Unlock Project: a Python-based framework for practical brain-computer interface communication "app" development.
Detection of error related neuronal responses recorded by electrocorticography in humans during continuous movements.
Volitional control of neural activity relies on the natural motor repertoire.
Improving brain-machine interface performance by decoding intended future movements.
Collaborative filtering for brain-computer interaction using transfer learning and active class selection.
Estimating the intended sound direction of the user: toward an auditory brain-computer interface using out-of-head sound localization.
Assisted closed-loop optimization of SSVEP-BCI efficiency.
Prediction of auditory and visual p300 brain-computer interface aptitude.