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Before a car crash in 2008 left her paralysed from the neck down, Nancy Smith enjoyed playing the piano. Years later, Smith started making music again, thanks to an implant that recorded and analysed her brain activity. When she imagined playing an on-screen keyboard, her brain–computer interface (BCI) translated her thoughts into keystrokes — and simple melodies, such as ‘Twinkle, Twinkle, Little Star’, rang out.
But there was a twist. For Smith, it seemed as if the piano played itself. “It felt like the keys just automatically hit themselves without me thinking about it,” she said at the time. “It just seemed like it knew the tune, and it just did it on its own.”
Smith’s BCI system, implanted as part of a clinical trial, trained on her brain signals as she imagined playing the keyboard. That learning enabled the system to detect her intention to play hundreds of milliseconds before she consciously attempted to do so, says trial leader Richard Andersen, a neuroscientist at the California Institute of Technology in Pasadena.
Smith is one of roughly 90 people who, over the past two decades, have had BCIs implanted to control assistive technologies, such as computers, robotic arms, or synthetic voice generators. These volunteers — paralysed by spinal-cord injuries, strokes or neuromuscular disorders, such as motor neuron disease (amyotrophic lateral sclerosis) — have demonstrated how command signals for the body’s muscles, recorded from the brain’s motor cortex as people imagine moving, can be decoded into commands for connected devices.
But Smith, who died of cancer in 2023, was among the first volunteers to have an extra interface implanted in her posterior parietal cortex, a brain region associated with reasoning, attention, and planning. Andersen and his team think that by also capturing users’ intentions and pre-motor planning, such ‘dual-implant’ BCIs will improve the performance of prosthetic devices.
Andersen’s research also illustrates the potential of BCIs that access areas outside the motor cortex. “The surprise was that when we go into the posterior parietal, we can get signals that are mixed together from a large number of areas,” says Andersen. “There’s a wide variety of things that we can decode.”
The ability of these devices to access aspects of a person’s innermost life, including preconscious thought, raises the stakes on concerns about how to keep neural data private. It also poses ethical questions about how neurotechnologies might shape people’s thoughts and actions — especially when paired with artificial intelligence.
Meanwhile, AI is enhancing the capabilities of wearable consumer products that record signals from outside the brain. Ethicists worry that, left unregulated, these devices could give technology companies access to new and more precise data about people’s internal reactions to online and other content.
Ethicists and BCI developers are now asking how previously inaccessible information should be handled and used. “Whole-brain interfacing is going to be the future,” says Tom Oxley, chief executive of Synchron, a BCI company in New York City. He predicts that the desire to treat psychiatric conditions and other brain disorders will lead to more brain regions being explored. Along the way, he says, AI will continue to improve decoding capabilities and change how these systems serve their users. “It leads you to the final question: how do we make that safe?”
Consumer concerns
Consumer neurotech products capture less-sophisticated data than implanted BCIs do. Unlike implanted BCIs, which rely on the firings of specific collections of neurons, most consumer products rely on electroencephalography (EEG). This measures ripples of electrical activity that arise from the averaged firing of huge neuronal populations and are detectable on the scalp. Rather than being created to capture the best recording possible, consumer devices are designed to be stylish (such as in sleek headbands) or unobtrusive (with electrodes hidden inside headphones or headsets for augmented or virtual reality).
Still, EEG can reveal overall brain states, such as alertness, focus, tiredness, and anxiety levels. Companies already offer headsets and software that give customers real-time scores relating to these states, with the intention of helping them to improve their sports performance, meditate more effectively, or become more productive, for example.
AI has helped to turn noisy signals from suboptimal recording systems into reliable data, explains Ramses Alcaide, chief executive of Neurable, a neurotech company in Boston, Massachusetts, that specializes in EEG signal processing and sells a headphone-based headset for this purpose. “We’ve made it so that EEG doesn’t suck as much as it used to,” Alcaide says. “Now, it can be used in real-life environments, essentially.”
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