Brain–computer interfaces have revolutionized the field of neuroscience by providing a
solution for paralyzed patients to control external devices and improve the quality of daily …

Brain–machine interfaces (BMIs) promise to restore movement and communication in
people with paralysis and ultimately allow the human brain to interact seamlessly with …

Objective. Decoding language representations directly from the brain can enable new brain–
computer interfaces (BCIs) for high bandwidth human–human and human–machine …

Objective. Brain–machine interfaces (BMIs) seek to restore lost motor functions in individuals
with neurological disorders by enabling them to control external devices directly with their …

The fault safety monitoring of hydrogen sensors is very important for their practical
application. The precondition of traditional machine learning methods for sensor fault …

The electroencephalography (EEG) signals are easily contaminated by various artifacts and
noise, which induces a domain shift in each subject and significant pattern variability among …

Objective. For intracortical neurophysiological studies, spike sorting is an important
procedure to isolate single units for analyzing specific functions. However, whether spike …

A brain-computer interface (BCI) facilitates direct interaction between the brain and external
devices. To concurrently achieve high decoding accuracy and low energy consumption in …

The brain, recognized as one of the most intricate systems globally, has been a focal point
for scientific exploration. Researchers have made efforts to construct models of the brain …

The time spent in collecting current samples for decoder calibration and the computational
burden brought by high-dimensional neural recordings remain two challenging problems in …