Brain-computer interfaces have been used in the past to control prosthetic devices. They have focused on reading signals from the motor cortex, the part of the brain responsible for movement. The signals arising there, though, are meant to control the movement of muscles, not the motors of prosthetic devices. The result is jerky motion that’t not very natural or effective. That’s why researchers at Caltech decided to instead use signals coming from the posterior parietal cortex, the part of the brain involved in movement planning, as the source of control for a robotic arm.
In a study on one paralyzed patient, two implants, each having 96 electrodes, each of which sample one neuron, were implanted in the posterior parietal cortex. The researchers created software that processed and decoded the signals, which then were converted into control signals to move the robotic arm. The investigators showed that sensing electric signals from the posterior parietal cortex can significantly improve the quality of the motion of robotic prostheses.
The next step the researchers are hoping to take is to gather data coming from both the motor cortex as well as the posterior parietal cortex in order to improve the overall function prostheses controlled by brain computer interfaces.
Here’s an example of the patient using the new robotic arm system controlled via the posterior parietal cortex :
Caltech video explaining the workings of the new technology: