Review: Human Intracortical Recording and Neural Decoding for Brain-Computer Interfaces

Abstract

Brain-computer interfaces (BCIs) use neural information recorded from the brain for the voluntary control of external devices. The development of BCI systems has largely focused on improving functional independence for individuals with severe motor impairments, including providing tools for communication and mobility. In this review, we describe recent advances in intracortical BCI technology and provide potential directions for further research.

Trial registration: ClinicalTrials.gov NCT00912041.

Figures

Fig. 1

Illustration of a closed-loop intracortical BCI setup. The user has an intracortical electrode (Utah array) inserted into the motor cortex acting as the sensor, which then sends real-time voltage signals to the external processing system, converting raw voltages into spikes. The decoder then maps the high-dimensional spike data to low-dimensional output that is fed to the effector as computer cursor control. The real-time cursor control is then provided as feedback to the user, who is then able to modulate further neural activity accordingly.

Fig. 2

BCI control of a prosthetic limb. Enrolled in the BrainGate2 pilot clinical trial (https://www.clinicaltrials.gov/ct2/show/NCT00912041), Participant S3 reached out using a prosthetic arm and drank coffee for the first time in over a decade.