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Is John Doe's Brain-Machine Interface in Brilliant Minds Real? Explaining the True Tech
Everything you need to know about locked-in syndrome and brain-machine interfaces (BMIs).
Each episode of Brilliant Minds offers a new neurological mystery for Dr. Wolf (Zachary Quinto), his interns, and the viewers at home to solve. Along the way, however, we’ve also been following the story of John Doe, a patient with full-body paralysis and no way to communicate.
When Dr. Wolf first encountered John Doe, he had been passed from hospital to hospital, relocating every time he got a new infection. Wolf was the first person in years to take a real look at him — to treat him like a person and not just an empty shell needing to be kept alive. Soon, the team at Bronx General realized that John Doe wasn’t in a coma, but was in fact awake and aware but locked in, unable to move or communicate. His only method of interacting with the world was with eye movements, up or down. It’s a slow and binary form of communication, but it’s enough to crack open the door.
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They learn his name, Roman, and, in Episode 7, "The Man From Grozny," he enters a clinical study for a brain-machine interface (BMI) that will restore Roman’s ability to communicate with the rest of the world. The operation is relatively simple: They drill a hole and place a small sensor on the brain’s surface. After a little bit of training, the array can detect Roman’s thoughts, decode them, and present them as text or spoken audio.
It’s a modern-day medical miracle and it happens fast. The show takes some minor liberties with the state of real-world BMIs, but what we see on screen isn’t too far from the truth ...
What is Locked-in Syndrome?
Locked-in syndrome is sometimes called a "pseudocoma" because from the outside, they look the same. In a coma, a person is not conscious. They may or may not have some internal dream-like experience, but they aren’t conscious in the same way as you or I. When a person is locked in, they remain conscious but unable to interact with the outside world.
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Locked-in syndrome is usually caused by damage to the lower brain or brainstem, without damage to the upper brain. The injury causes a loss of muscle control, preventing patients from moving or speaking. Typically, the only remaining muscle control is of the eyes, allowing for vertical movement and blinking. Sometimes, however, even the eyes are paralyzed.
Locked-in syndrome is horrifyingly difficult to diagnose. Often, months pass between the beginning of symptoms and a diagnosis. In the interim, a patient experiences everything around them, but cannot respond or participate in any way. Once diagnosed, a form of communication can be built using blinks or vertical eye movements.
For most of human history, that was the best a locked-in patient could hope for. Today, brain-machine interfaces offer much more.
What are brain-machine interfaces?
The term brain-machine interface, sometimes also called a brain-computer interface, was coined in 1973 by Jacques Vidal at the University of California, Los Angeles. Vidal dreamed that in the future, the electrical signals from the brain might be captured, decoded, and used to control prosthetics and other devices. That dream is now a reality, but a fledgling one.
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BMIs are an emerging science that marries biology with technology. They’ve been around for a couple of decades and seem perpetually five years away from hitting the big time. In 2003, Duke University researchers demonstrated that monkeys with implanted electrodes could control robotic limbs with their thoughts.
Progress has been made since then, particularly in recent years, but BMIs still aren’t commonplace. That all might be poised to change, according to a recent report from Morgan Stanley. The report predicts the short-term financial landscape surrounding BMIs as guidance for potential investors and predicts the beginning of a boom in the next five years. It also estimates approximately 10 million potential patients who might benefit from a BMI in the United States alone.
There are a handful of companies in this space, each designing its own devices and platforms intended to bypass injury or physical deficit. Each device differs in its invasiveness, including how deeply it penetrates the brain tissue and how cleanly it records and interprets electrical signals from the brain. There’s also the question of how many electrodes are at work, as well as their data bandwidth. You have to have a pretty strong data stream from the brain to the device to do things like translate speech or move a cursor on a computer.
Of course, speech and movement aren’t the only applications of brain-machine interfaces. Recently, Motif Neurotech announced the first test of its device. It penetrates only the skull and sits atop the brain, much like the device seen in Brilliant Minds. Other devices are mounted on a stent and pass through an artery in the neck to sit atop the brain. In either case, these devices don’t get the high-bandwidth data of more invasive devices, but Motif Neurotech doesn’t need high bandwidth; they aren’t trying to control a prosthesis or move a cursor, and instead are trying to track emotions and treat mood disorders, which doesn’t require the same fidelity as translating speech.
Is Brilliant Minds’ brain-machine interface technology real?
Earlier this year, a team at UC Davis Health achieved 97% accuracy in translating speech in a clinical test of their own BMI. The patient has amyotrophic lateral sclerosis (ALS), which inhibits their ability to communicate. ALS affects nerves that control movement, including those used in speech. As the disease progresses, individuals often lose the ability to stand, walk, and communicate. The device used four electrode arrays to sense and translate thoughts into words.
“We’re really detecting their attempt to move their muscles and talk,” explained neuroscientist Sergey Stavisky, in a statement. “We are recording from the part of the brain that’s trying to send these commands to the muscles. And we are basically listening into that, and we’re translating those patterns of brain activity into a phoneme — like a syllable or the unit of speech — and then the words they’re trying to say.”
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It only took about 30 minutes of training for the device to achieve 99.6% translation accuracy from a vocabulary of 50 words. The second session took about an hour and a half and increased the vocabulary to 125,000 words with a translation accuracy of just over 90%. Additional data collection and training ultimately lifted the accuracy to above 97%.
The device translates the patient’s thoughts into spoken words, but the team went one step further. Instead of a default robotic voice, they were able to train the software on recordings of the patient’s actual speaking voice from before their diagnosis. When the patient thinks of a word or a sentence and the BMI interprets it, it’s his own voice he hears coming from the speakers.
Why aren’t brain-machine interfaces more common?
The remaining challenges are many-fold. Much of the science has been done, though improvements in the technology are sure to continue, but funding remains a major challenge. There are also the challenges of infection, device durability, wireless communication, and more. Not to mention the non-trivial question of brain privacy, particularly in a world where one of the major players in brain-machine interfaces (Elon Musk and Neuralink) is also the owner of a social media platform that makes money trading data and charging a subscription.
Once a person’s mind is connected to a computer, and that computer is facilitating the transmission of their thoughts and actions, we can’t help but consider the ethical implications. Who owns and has access to that data, which contains — at least in some cases — a person’s private thoughts, interests, and proclivities? Before BMIs become commonplace, we’re going to have to reckon with these challenges.
New episodes of Brilliant Minds premiere on Mondays on NBC at 10/9c and are available to stream on Peacock.