This work aims at corroborating the importance and efficacy of mutual learning in motor
imagery (MI) brain–computer interface (BCI) by leveraging the insights obtained through our …

Research in brain-computer interfaces has achieved impressive progress towards
implementing assistive technologies for restoration or substitution of lost motor capabilities …

We adopted a fusion approach that combines features from simultaneously recorded
electroencephalogram (EEG) and magnetoencephalogram (MEG) signals to improve …

Advances in neural interfaces have demonstrated remarkable results in the direction of
replacing and restoring lost sensorimotor function in human patients. Noninvasive brain …

Brain-computer interfaces (BCIs) have been largely developed to allow communication,
control, and neurofeedback in human beings. Despite their great potential, BCIs perform …

Objective. This work presents a first motor imagery-based, adaptive brain–computer
interface (BCI) speller, which is able to exploit application-derived context for improved …

Online coadaptive training has been successfully employed to enable people to control
motor imagery (MI)-based brain-computer interfaces (BCIs), allowing to completely skip the …

ABSTRACT Introduction Restorative Brain–Computer Interfaces (BCIs) provide an
alternative non-muscular channel for stroke patients lacking volitional movement by …

Objective. Brain–computer interfaces (BCIs) constitute a promising tool for communication
and control. However, mastering non-invasive closed-loop systems remains a learned skill …

Large-scale interactions among multiple brain regions manifest as bursts of activations
called neuronal avalanches, which reconfigure according to the task at hand and, hence …