Implanted brain–computer interfaces (iBCIs) translate brain activity recorded intracranially
into commands for virtual or physical machines to restore or rehabilitate motor, sensory or …

Invasive brain-computer interfaces hold promise to alleviate disabilities in individuals with
neurologic injury, with fully implantable brain-computer interface systems expected to reach …

The efficacy of wireless intracortical brain–computer interfaces (iBCIs) is limited in part by
the number of recording channels, which is constrained by the power budget of the …

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

Fully-implantable wireless intracortical Brain Machine Interfaces (iBMI) is one of the most
promising next frontiers in the nascent field of neurotechnology. However, scaling the …

Intracortical brain-computer interfaces (iBCIs) enable people with tetraplegia to gain intuitive
cursor control from movement intentions. To translate to practical use, iBCIs should provide …

We present practical solutions to applying Gaussian‐process (GP) methods to calculate
spatial statistics for grid cells in large environments. GPs are a data efficient approach to …

The Kalman filter provides a simple and efficient algorithm to compute the posterior
distribution for state-space models where both the latent state and measurement models are …

Objective. The goal of this work is to identify the spatio-temporal facets of state-of-the-art
electroencephalography (EEG)-based continuous neurorobotics that need to be addressed …

Brain machine interfaces (BMI) connect brains directly to the outside world, bypassing
natural neural systems and actuators. Neuronal-activity-to-motion transformation algorithms …