Monkey Mind Control Could Lead to Treatment for Paralyzed Patients

Researchers trained monkeys to control virtual arms using only their brains.

A rhesus macaque monkey looks on as he drinks from a juice bottle in Hong Kong on April 30, 2011.
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It's an unusual path, but promising therapy for paralyzed patients may come from the work of monkeys.

Researchers at Duke University conducted a study in which monkeys learned to control the movement of virtual arms by using just their brains. These findings could prove particularly useful for people who have sensory and motor deficiencies caused by spinal cord injuries or for those who are severely paralyzed.

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"Bimanual movements in our daily activities – from typing on a keyboard to opening a can – are critically important," said Miguel Nicolelis, a professor of neurobiology at the Duke University School of Medicine and senior author of the study, in a statement. "Future brain-machine interfaces aimed at restoring mobility in humans will have to incorporate multiple limbs to greatly benefit severely paralyzed patients."

Brain-machine interfaces are systems that connect different regions of the brain to assistive devices that help restore patients' motor and sensory functions, the study said. Previous studies have developed brain-machine interfaces that control single prosthetic arms, but have not successfully used two at the same time.

According to the Christopher and Dana Reeve Foundation's Paralysis Resource Center, nearly 2 percent of the United States population, or about 5.6 million people, report currently living with some form of paralysis and 0.4 percent of the population, or about 1.3 million people, say they are paralyzed from a spinal cord injury.

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People can become paralyzed from a number of different sources, including cerebral palsy, multiple sclerosis, a traumatic brain injury, a spinal cord injury or stroke, which is the leading cause of paralysis, according to the Reeve Foundation.

Nicholelis' research is significant because the monkeys in the study successfully controlled two virtual arms at once and their performance improved over time.

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