Ian Burkhart has been a cyborg for two years now. In 2014, scientists at Ohio State’s Neurological Institute implanted a pea-sized microchip into the 24-year-old quadriplegic’s motor cortex. Its goal: to bypass his damaged spinal cord and, with the help of a signal decoder and electrode-packed sleeve, control his right arm with his thoughts. Cue the transhumanist cheers!
Neuroengineers have been developing these so-called brain-computer interfaces for more than a decade. They've used readings from brain implants to help paralyzed patients play Pong on computer screens and control robotic arms. But Burkhart is the first patient who's been able to use his implant to control his *actual *arm.
Over the past 15 months, researchers at the Ohio State University Wexner Medical Center and engineers from Battelle, the medical group that developed the decoder software and electrode sleeve, have helped Burkhart relearn fine motor skills with weekly training sessions. In a paper in *Nature, *they describe hooking a cable from the port screwed into Burkhart’s skull (where the chip is) to a computer that translates the brain signals into instructions for the sleeve, which stimulates his muscles into moving his wrist and fingers.
When Burkhart thinks “clench fist,” for example, the implanted electrodes record the activity in his motor cortex. Those signals are decoded in real-time, jolting his arm muscles in all the right places so that his fingers curl inwards. But he can do more than make a fist: Using the one-of-a-kind system, he's learned to shred a video game guitar, pour objects from a bottle, and pick up a phone. “Card swiping is the most impressive movement right now,” says Herb Bresler, a senior researcher at Battelle. “It demonstrates fine grip as well as coarse hand movements.”
If Burkhart can swipe credit cards after a year, he might play the piano after five—that’s how long similar chips have lasted—because he and the computer have been learning from each other. But the implant will stop collecting signals in July when it's removed, even if the chip is still providing good data, because the clinical trial was structured for a two-year period. In those two years, the computer trained itself on Burkhart’s thoughts, learning which signals translate to what movements, while he figured out how to make commands more clearly (often with the help of visual cues). “That’s the real achievement here. We’ve shown we know how to process the data,” says Bresler. “The chip is a limiting factor. We need to work on new ways of collecting brain signals.”
Though similar neuroprosthetics have been helpful in reducing tremors in Parkinson’s patients, they still have a ways to go. Besides the serious, invasive surgery, there’s always a chance the body will reject an array, blocking any attempts to record and transmit brain signals while ensuring you get patted down at every airport security scanner, forever. “Something will replace this array,” says Bresler. “Future signal collection devices will cover a larger area of the brain and be less invasive.”
Drawbacks aside, the electrode sleeve and decoding software wouldn’t be where they are today without the array driving them. With improved collection devices, these products could eventually help stroke victims recover by reteaching their brain to use their limbs, while quadriplegics could mount similar systems on their wheelchairs. At the very least, the neuroprosthetic experiment suggests that in the future, paralysis might not mean dependence—and that deserves a fist bump.
