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Now a Neural Implant That Learns With the Brain

by Rajshri on Jun 25 2008 3:43 PM

A method to develop neural implants that not only translate brain signals into movement, but also evolve with the brain as it learns has been devised by University of Florida researchers.

The researchers say that instead of simply interpreting brain signals to help paralysed patients and amputees control prosthetic limbs with just their thoughts, the new brain-machine interface would adapt to a person's behaviour over time, and use the knowledge to help him/her complete a task more efficiently.

The researchers say that they have already tested a model system on rats.

To date, only one-way conversation has been possible between the brain and a computer, with the brain doing all the talking and the machine following commands.

However, the new system actually allows the computer to have a say during the communication process, according to the researchers.

"In the grand scheme of brain-machine interfaces, this is a complete paradigm change. This idea opens up all kinds of possibilities for how we interact with devices. It's not just about giving instructions but about those devices assisting us in a common goal. You know the goal, the computer knows the goal and you work together to solve the task," said Dr. Justin C. Sanchez, a UF assistant professor of pediatric neurology and the study's senior author.

The researcher revealed that the model system he and his colleagues had developed was based on setting goals and giving rewards.

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During a study, the researchers fitted tiny electrodes in the brains of three rats to capture signals for the computer to unravel. The rats were taught to move a robotic arm towards a target with just their thoughts.

The animals would be rewarded with a drop of water each time they succeeded, said Sanchez.

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He further said that the computer's goal was to earn as many points as possible.

The closer a rat moved the arm to the target, the more points the computer received, giving it incentive to determine which brain signals lead to the most rewards, making the process more efficient for the rat.

Many tests were conducted on rats, requiring them to hit targets that were farther and farther away.

Sanchez said that though the tasks became more and more difficult as the experiments advanced, the rats' efficiency in carrying them out improved over time.

"We think this dialogue with a goal is how we can make these systems evolve over time. We want these devices to grow with the user. (Also) we want users to be able to experience new scenarios and be able to control the device," he said.

A research article describing the study has been published online in the journal IEEE Transactions on Biomedical Engineering.

Source-ANI
RAS/S


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