NETANYA, Israel — A monkey has successfully fed itself with food and fluids using a robotic arm controlled by the power of its thought alone. The arm is controlled by signals picked up from its brain and the monkey learns how to feed using bio-feedback, researchers from the University of Pittsburgh School, of Medicine have reported in the journal Nature.

Such work has been done with human subjects with a view to improving pilot-aircraft interaction, the playing of electronics games and for helping paraplegics. According to the scientists, this recent study could improve the development of prosthetics for people with spinal cord injuries and those with "locked-in" conditions such as Lou Gehrig's disease, or amyotrophic lateral sclerosis.

"Our immediate goal is to make a prosthetic device for people with total paralysis," said Dr. Andrew Schwartz, the senior author and professor of neurobiology at the University of Pittsburgh, School of Medicine. "Ultimately, our goal is to better understand brain complexity."

Monkeys in the Schwartz lab had previously been trained to command cursor movements with the power of their thoughts.

"Now we are beginning to understand how the brain works using brain-machine interface technology," said Dr. Schwartz. "The more we understand about the brain, the better we'll be able to treat a wide range of brain disorders, everything from Parkinson's disease and paralysis to, eventually, Alzheimer's disease and perhaps even mental illness."

Using the technology, monkeys in the Schwartz lab are able to move a robotic arm to feed themselves marshmallows and chunks of fruit while their own arms are restrained.

Computer software interprets signals picked up by probes, inserted into neuronal pathways in the monkey's motor cortex. The neurons' collective activity is then translated in software into a control function and sent to the robot arm. Movements are fluid and natural, and evidence suggests the monkeys come to regard the robotic device as part of their own bodies.

The primary motor cortex, a part of the brain that controls movement, has thousands of nerve cells, called neurons, which fire together as they contribute to the generation of movement. Because of the massive number of neurons that fire at the same time to control even the simplest of actions, it would be impossible to create probes that capture the firing pattern of each. Pittsburg University researchers developed a special algorithm that uses limited information from about 100 neurons to fill in the missing signals.

"In our research, we've demonstrated a higher level of precision, skill and learning," said Dr. Schwartz. "The monkey learns by first observing the movement, which activates his brain cells as if he were doing it. It's a lot like sports training, where trainers have athletes first imagine that they are performing the movements they desire."

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