When we do anything, our brain generates a specific pattern of electrical activity. For years, scientists have been connecting those brain impulses to machines, not only to learn about brain diseases but also to help people with disabilities. Brain-computer interfaces, or BCIs, can restore movement in people with paralysis. They also may help treat neurological and psychiatric diseases.
Now, a study published in Nature reports on a brain implant that will allow people with impaired limb movement to communicate with written text that they thought of in their minds – hands free.
The artificial intelligence software, which was developed by a team of researchers at Stanford University, used electrodes implanted in the brain to “read” the thoughts of a man with full-body paralysis as he was asked to imagine writing them in letters.
The BCI transformed his imagined letters and words into text on a computer screen.
Previous work by co-senior study author Krishna Shenoy was used to help analyze the neural patterns associated with speech. It also decoded imagined arm movements so that people with paralysis could move a cursor on a keyboard screen to type out letters. However, this technique only allowed the participants to type around 40 characters per minute, far lower than the average keyboard typing speed, which is around 190 characters per minute.
Shenoy’s team’s newest research focused on imagined handwriting as a way to improve the speed of communication. The researchers hope it will, at the least, reach smartphone texting rates.
The study subject, who was 65 years old at the time of the research, was able to mentally type 90 characters per minute. That rate is not far from average for most senior texters, who can typically type around 115 characters per minute on a phone.
“This line of work could help restore communication in people who are severely paralyzed, or ‘locked-in, ’” says Frank Willett, lead author of the paper and a research scientist at Stanford’s Neural Prosthetics Translational Laboratory. “It should help people express themselves and share their thoughts. It’s very exciting.”
The study participant suffered a spinal cord injury in 2007. He had lost most movement below his neck. In 2016, Stanford neurosurgeon Jaimie Henderson, co-senior author of the paper, implanted two small BCI chips into the patient’s brain. Each of the chips had 100 electrodes capable of sensing neuronal activity. They were implanted in a region of the motor cortex that controls movement of the arms and hands. This allowed the researchers to profile brain-activity patterns associated with written language.
“This study is an important and clear advance for intracortical brain-computer interfaces,” says Amy L. Orsborn, a member of the department of bioengineering at the University of Washington. “One obvious reason why is because they achieved a huge leap in performance on a challenging but important task like typing. It’s also the most significant demonstration to date of leveraging established tools in machine learning like predictive language models to improve BCIs.”
“I saw this research initially presented at a poster in 2019 and think it’s great!”, says Mijail D. Serruya, an assistant professor of neurology at Thomas Jefferson University, who studies BCIs in stroke recovery but was not involved in the research. “I think it clearly shows that fine motor trajectories can be decoded from neocortical activity.”
Serruya also said that his research could align with Willett’s to help treat people who have suffered brain trauma or a stroke. “We have shown that motor control signals can be decoded [following a stroke], implying that some of the decoding approaches developed by Willett might have applications beyond people with spinal cord injury,” he says.
As for when text-and-speech-decoding technology might be available to the public, Willett is optimistic. “It’s hard to predict when our method will be translated into a real device that anyone can buy,” he said. “Of course, we hope it will be soon, and there are companies working on implantable BCI devices now. But you never know when someone will succeed in translating it. We hope it’s within years and not decades!”