A technology currently used to monitor epilepsy is being adapted into a neural interface for people who are paralyzed or have motor impairments from neurodegenerative disease. Neurolutions, a startup based in St. Louis, is developing a small, implanted device that translates signals recorded from the surface of the brain into computer commands.
The device is based on electrocorticography (ECoG), in which a grid of electrodes is surgically placed directly on the surface of the brain to monitor electrical activity. This technology is currently used for surgical planning in patients with uncontrolled epilepsy in order to find the origin of their seizures. But Eric Leuthardt and Dan Moran at Washington University School of Medicine, in St. Louis, and Gerwin Schalk at the Wadsworth Center, in Albany, NY, are developing a much smaller version that would be implanted long term to allow paralyzed patients to control a computer and perhaps prosthetic limbs and other devices.
“We’re extremely excited about these signals because they are really opening a whole new avenue for extracting information from the brain in humans,” says Schalk. “The nice thing about ECoG is that it targets a space that no other sensor technology has been in before.”
Most efforts to build neural interfaces have focused on either electroencephalography (EEG), a noninvasive technology that records electrical activity from the scalp, or electrodes implanted into the brain. ECoG represents an intermediate between the two: because it records directly from the brain, it can provide a higher level of control than EEG, which is susceptible to distortion as the signal travels through the skull and as the patient moves. In addition, ECoG’s position on the surface of the brain may present fewer health issues than electrodes that penetrate brain tissue.
Because ECoG is used in epilepsy patients, researchers have already been able to conduct proof of principle experiments on a much wider scale than has been done using other invasive technologies. Tests of more than 20 patients have shown that people can quickly learn to move a cursor on a computer screen using their brain activity. Researchers first ask patients to imagine performing a certain action, such as moving a computer cursor to the left. They then identify changes in the frequency of electrical signals that correlate with that movement and use those to control the computer. The patient learns to more precisely control his or her brain activity and hence more reliably performs the task within half an hour.
“With minimal learning efforts, we have been able to tune and train the system to recognize simple commands, like ‘up,’ and ‘down,’ and ‘left’ and ‘right,’” says Shawn Lunney, Neurolutions’ chief executive officer. Lunney estimates that patients can control a computer cursor with approximately 80 percent accuracy.
“With the results from our studies, it made sense to develop the company and the intellectual property in parallel with a true next-generational implant,” says Leuthardt, a neurosurgeon and former TR100 winner who is continuing his studies in patients. He hopes to show that they can achieve three-dimensional control, which would be required for the most basic control of a prosthetic arm.