Brain-computer interfaces have been utilized in the past to control artificial devices that replace missing body parts. They have focused on reading signals from the motor cortex, the part responsible for movement in the brain.
The signals arising in this part of the brain are meant to control the movement of muscles, not the motors of prosthetic devices. The result is jerky motion that's not very natural or effective.
With this in mind, scientists at the California Institute of Technology (Caltech) have used these signals coming from the posterior parietal cortex as the source of control for a robotic arm. The posterior parietal cortex is the part of the brain involved in movement planning.
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 researchers 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.