Intracortical brain-computer interface for navigation in virtual reality in macaque monkeys

We present an innovative intracortical Brain-Computer Interface (BCI) to
bridge the gap between laboratory settings and real-world applications.
This BCI approach introduces three key advancements. First, we utilized
neural signals from three macaque brain regions – primary motor, dorsal
and ventral premotor cortex – enabling precise and flexible decoding of
real-time three-dimensional (3D) sphere/avatar velocities. Second, we
developed a realistic, immersive 3D virtual reality setup with dynamic
camera tracking, allowing continuous navigation and obstacle avoidance
that closely mimic real-world scenarios. Finally, our BCI approach is very
well suited for use by paralyzed patients, featuring a brief passive
fixation without overt movements and closed-loop operation without
retraining of the decoder during online decoding, relying on the user’s
neural plasticity and the decoder’s robust generalization across tasks.
Our BCI adapted to different environments, targets, and obstacles,
illustrating its potential to substantially enhance the quality of life
for paralyzed patients by enabling natural, reliable and flexible control
in complex settings.