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 3D sphere/avatar velocities. Second, we developed a realistic, immersive three-dimensional virtual reality setup with dynamic camera tracking, allowing continuous navigation and obstacle avoidance that closely mimic real-world scenarios. Finally, our BCI approach is optimized for use by paralyzed patients, featuring a brief training phase without overt movements and closed-loop operation without retraining of the decoder, 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 significantly enhance the quality of life for paralyzed patients by enabling natural, reliable and flexible control in complex settings.