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