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New Brain Machine Interfaces

A monkey controls a robotic arm with better precision than ever before.
November 8, 2007

In a stunning video demonstrating advances in the functionality of brain machine interfaces, a monkey used a robotic hand to reach for a piece of apple, grabbed it, brought it to his mouth, ate it, and then licked the hand for good measure; he did all this with the power of his mind. The research, presented by Andrew Schwartz and his colleagues at the Society for Neuroscience conference in San Diego this week, was just one of several new advancements in the rapidly advancing field of brain machine interfaces.

Schwartz’s monkey has a neural implant recording neural activity in the motor cortex, part of the brain that mediates movement. That activity is then translated into control signals for the robotic arm using a series of complex algorithms. While this isn’t the first time that a monkey–or, in fact, a human–has been able to move a prosthesis purely with its mind, the new advancements demonstrate the greatest level by far of fine-motor control. (See “Brain Chips Give Paralyzed Patients New Powers.”) The monkey could both reach with the arm and control a gripper at the end of it with relatively smooth, fast movements.

A similar device, developed by John Donoghue and his colleagues at Brown University, is currently in clinical trials. Patients can control computer cursors, move wheelchairs, and even make jerky movements to grab a piece of candy with a robotic arm, but not with the level of control shown by Schwartz’s monkey. Schwartz says that his device, currently being tested only in monkeys, is designed to better take advantage of the animal’s ability to adjust his brain activity as he learns to better control the device.

The brain machine interfaces being designed by Schwartz and Donoghue are meant for patients whose motor cortex is intact, such as those with paralysis linked to spinal cord injury or certain types of stroke. But in many other cases of stroke, large swaths of part of the cortex are damaged. Eric Leuthardt and his colleagues at Washington University School of Medicine are developing a neural prosthesis that could be used to help these patients.

People with massive stroke on one side of the brain are often left severely impaired on the other side of the body–evidence of the traditional neurological dogma that one side of the brain controls the other side of the body. But in recent years, brain-imaging studies have shown that the same side of the brain is also active during same-sided movement. Leuthardt, a neurosurgeon and a former TR100 winner, is taking advantage of that fact and building a brain machine interface that can help such patients move both sides of their body.

Leuthardt and his collaborators study epilepsy patients who have recording electrodes temporarily implanted into their brain for medical reasons. The researchers found that when patients were asked to move their right hand, the activity in the ipsilateral side of the brain occurred before activity on the contralateral side occurred, suggesting that the same-sided activity is involved in planning, while the contralateral side might be responsible for execution. In preliminary results presented at the conference, the researchers showed that those planning signals could be used to control a cursor: patients were able to play Space Invaders using their brain activity.

The findings could ultimately be used to develop a robotic orthotic to help with grip. “For patients with stroke, this is one of the most commonly lost functions after long-term stroke recovery,” says Leuthardt.

Caption: Here, a young epilepsy patient plays Space Invaders with his mind. The patient has a temporary implant on one side of his brain that records neural activity. (The implant is used to find the origin of his seizures, but scientists study such patients to take advantage of the rare direct access to the human brain.) Scientists used recorded brain activity to control the cursor in Space Invaders. The findings could ultimately enable brain machine interfaces for stroke patients.

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