Brain-Machine Interface
Miguel Nicolelis
Belle, a nocturnal owl monkey small enough to fit comfortably in a coat pocket, blinks her outsized eyes as a technician plugs four connectors into sockets installed in the top of her skull. In the next room, measurements of the electrical signals from some 90 neurons in Belle’s brain pulse across a computer screen. Recorded from four separate areas of Belle’s cerebral cortex, the signals provide a window into what her brain is doing as she reaches to touch one of four assigned buttons to earn her reward-a few drops of apple juice. Miguel Nicolelis, a Duke University neurobiologist who is pioneering the use of neural implants to study the brain, points proudly to the captured data on the computer monitor and says: “This readout is one of a kind in the world.”
The same might be said of Nicolelis, who is a leader in a competitive and highly significant field. Only about a half-dozen teams around the world are pursuing the same goals: gaining a better understanding of how the mind works and then using that knowledge to build implant systems that would make brain control of computers and other machines possible. Nicolelis terms such systems “hybrid brain-machine interfaces” or HBMIs. Recently, working with the Laboratory for Human and Machine Haptics at MIT, he scored an important first on the HBMI front, sending signals from individual neurons in Belle’s brain to a robot, which used the data to mimic the monkey’s arm movements in real time.
In the long run, Nicolelis predicts that HBMIs will allow human brains to control artificial devices designed to restore lost sensory and motor functions. Paralysis sufferers, for example, might gain control over a motorized wheelchair or a prosthetic arm-perhaps even regain control over their own limbs. “Imagine,” says Nicolelis, “if someone could do for the brain what the pacemaker did for the heart.” And, in much the same way that a musician grows to feel that her instrument is a part of her own body, Nicolelis believes the brain will prove capable of readily assimilating human-made devices.
Ongoing experiments in other labs are showing that this idea is credible. At Emory University, neurologist Phillip Kennedy has helped severely paralyzed people communicate via a brain implant that allows them to move a cursor on a computer screen (see “Mind Over Muscles,” TR March/April 2000). And implants may also shed light on some of the brain’s unresolved mysteries. Nicolelis and other neuroscientists still know relatively little about how the electrical and chemical signals emitted by the brain’s millions of neurons let us perceive color and smell, or give rise to the precise movements of Brazilian soccer players-whose photos adorn the walls of the So Paolo native’s office. “We don’t have a finished model of how the brain works,” says Nicolelis. “All we have are first impressions.”
Nicolelis’ latest experiments, however, show that by tapping into multiple neurons in different parts of the brain, it is possible to glean enough information to get a general idea of what the brain is up to. In Belle’s case, it’s enough information to detect the monkey’s intention of making a specific movement a few tenths of a second before it actually happens. And it was Nicolelis’ team’s success at reliably measuring tens of neurons simultaneously over many months-previously a key technological barrier-that enabled the remarkable demonstration with the robot arm.
Still, numerous stumbling blocks remain to be overcome before human brains can interface reliably and comfortably with artificial devices, making mind-controlled prosthetic limbs or computers more than just lab curiosities. Among the key challenges is developing electrode devices and surgical methods that will allow safe, long-term recording of neuronal activities. Nicolelis says he’s begun working with Duke’s biomedical engineering department to develop a telemetry chip that would collect and transmit data through the skull, without unwieldy sockets and cables. And this year Nicolelis will become co-director of Duke’s new Center of Neuroengineering and Neurocomputation, which will explore new combinations of computer science, chip design and neuroscience. Nicolelis sees the effort as part of an impending revolution that could eventually make HBMIs as commonplace as Palm Pilots and spawn a whole new industry-centered around the brain.
Others in Brain-Machine Interfaces
Organization | Project |
Andy Schwartz (Arizona State University) | Neural control of robotic arm |
John Donoghue (Brown University) | Brain representation of movement |
Richard Andersen (Caltech) | Improved neuroelectrode systems |
Phillip Kennedy, Roy Bakay (Emory University) | Communication systems for paralyzed patients |
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