Learning to operate an imagined speech Brain-Computer Interface involves the spatial and frequency tuning of neural activity.

ABSTRACT: Brain-Computer Interfaces (BCI) will revolutionize the way people with severe impairment of speech production can communicate. While current efforts focus on training classifiers on vast amounts of neurophysiological signals to decode imagined speech, much less attention has been given to users' ability to adapt their neural activity to improve BCI-control. To address whether BCI-control improves with training and characterize the underlying neural dynamics, we trained 15 healthy participants to operate a binary BCI system based on electroencephalography (EEG) signals through syllable imagery for five consecutive days. Despite considerable interindividual variability in performance and learning, a significant improvement in BCI-control was globally observed. Using a control experiment, we

SUBMITTER: Bhadra K 

PROVIDER: S-EPMC11842755 | biostudies-literature | 2025 Feb

REPOSITORIES: biostudies-literature