Brain-machine interface helps move paralyzed hand
New tech out of Northwestern bypasses the spinal cord to deliver messages directly from the brain to muscles.
After "eavesdropping" on the electrical signals of monkeys' brains that tell their arms and hands how to move, researchers at Northwestern University are reporting this week in the journal Nature that they've devised new tech that could some day help paralyzed patients move their limbs in spite of their spinal cord injuries.
To analyze the monkeys' natural neuroelectrical activity, the researchers implanted tiny multi-electrode arrays that detected the activity of about 100 neurons in the brain to decipher the signals that generate hand movements.
They then recorded the electrical activity that occurred when the monkeys grasped, lifted, and dropped a ball, and developed an algorithm to help predict the patterns of muscle activity this required.
"We can extract a remarkable amount of information from only 100 neurons, even though there are literally a million neurons involved in making that movement," lead investigator and neuroscience professor Lee Miller said in a school news report. "These are output neurons that normally send signals to the muscles. Behind these neurons are many others that are making the calculations the brain needs in order to control movement. We are looking at the end result from all those calculations."
To simulate paralysis, researchers gave the monkeys a local anesthetic that blocked nerve activity at the elbow to cause temporary hand paralysis. With the help of the neuroprosthesis in the monkeys' brains and arms, their brain signals alone were able to deliver the electrical instructions to their muscles, without the use of their spinal cords.
It turns out that in less than 40 milliseconds, this directing of current caused the monkeys' hands to contract and pick up the ball almost as well as they did prior to paralysis.
This is not the first time this kind of tech has been tested. Back in 2008, researchers at the University of Washington developed an algorithm based on the activity of a dozen neurons, and were able to get monkeys to directly control otherwise paralyzed muscles by creating artificial connections that bypassed the injury.
Miller tells New Scientist that the Northwestern experiment further advances these findings by building an algorithm based on 100 (as opposed to 12) neurons. Presumably, studying more neurons down the road will help researchers further fine-tune brain-machine interfaces to help people with spinal cord injuries essentially circumvent the resulting paralysis.