For years, researchers have been exploring how sensors can detect brain activity and use this data to give paralyzed patients control over their bodies. But that technical challenge is only half of the problem: People also need to receive tactile feedback from their environment in order to achieve desired tasks. Without this feedback, a task as simple as drinking from a cup can be impossible.
Chad Bouton, the vice president of advanced engineering at Feinstein Institutes for Medical Research in Manhasset, N.Y., leads a team of researchers that has been working on brain-computer interface technology for years. One of their early studies focused on sensing impulses from the brain, which were decoded to drive electrical impulses that enabled a paralyzed patient to move his arm just by thinking about it.
That 2015 study involved the creation of a “neural bypass” using a single chip that contained an array of electrodes, which was then implanted in the motor cortex of the patient’s brain. The neural activity of his brain was detected by this sensor, and an AI model interpreted the intended movements that these signals represented.
Bouton’s team has made great strides in the ensuing 10 years. Their most recent project is the creation of a “double neural bypass.” Instead of simply reading the brain signals of the intended movement, they added a second channel that stimulated the part of the brain that senses touch. To accomplish this, they implanted a total of five chips in the brain of Keith Thomas, a patient who was paralyzed from the chest down after a diving accident. Two electrode arrays were implanted into the motor cortex; the additional electrodes provide more data for the system to analyze about the subject’s intended movements. The team also implanted three additional chips into the patient’s somatosensory cortex—the part of the brain that processes touch. In total, 224 electrodes were implanted in Thomas’s brain.
The researchers then trained an AI model to process Thomas’s brain signals and control his hand. Information from the motor cortex is “decoded” by the AI and then used to stimulate an electrode array on the patient’s neck to modulate his spinal cord. He also was fitted with electrode patches on his forearm to stimulate muscles that control his hand movements.
Advances in Brain-Computer Interfaces
Initially, Thomas was able to lift his arm only about an inch off his wheelchair. After receiving spinal cord stimulation through the patch on his neck, he now has developed enough arm strength that he can lift his hand and wipe his face without assistance.
Keith Thomas, who has lived with paralysis since a diving accident in 2020, lifts and drinks from a cup on his own.Feinstein Institutes
Meanwhile, tiny sensors applied to Thomas’s fingers and palms send touch and pressure data back to the computer, which then stimulates appropriate parts of his somatosensory cortex, leading to the sensation of touch. This feedback has resulted in his ability to “feel” with his hand and use those sensations during his movements. Thomas “can now pick up an empty eggshell without cracking it,” says Bouton.
Thomas is also able to pick up a cup and drink from it, just by thinking about performing this task. What’s more, he can sense touch in his forearm and wrist, even when he is not connected to the neural bypass system. It’s not clear what physical mechanism is at work that made this happen—for example, it could be an instance of neuroplasticity forming new connections with nerves and the brain.
According to Bouton, “It is known from animal experiments electrical stimulation can promote neuronal growth, but here it is unclear whether it’s more about strengthening spared connections at the spinal cord injury site. Right now, we just know the results are significant and leading to functional and meaningful outcomes.”
With these promising results, double neural bypass systems could be a potential treatment to help other patients with spinal cord injuries, as well as other conditions such as stroke, Parkinson’s disease, or traumatic brain injury.
