The use of a grid atop the brain to record brain surface signals is a brain-machine interface technique that uses electrocorticographic (ECoG) activity-data taken invasively right from the brain surface. It is an alternative to the status quo, used frequently studying humans, called electroencephalographic activity (EEG) - data taken non-invasively by electrodes outside the brain on the skull.

The breakthrough is a step toward building biomedical devices that can control artificial limbs, some day, for instance, enabling the disabled to move a prosthetic arm or leg by thinking about it. The study was published in the June 8, 2004 issue of the Journal of Neural Engineering and was partially funded by the National Institutes of Health (NIH).

Eric C. Leuthardt, M.D., a physician in the Department of Neurological Surgery, Barnes Jewish Hospital, and Daniel Moran, Ph.D., assistant professor of biomedical engineering, performed their research on four adult epilepsy patients who had the grids implanted so that neurologists can find the area in the brain serving as the focus for an epileptic seizure, with hopes of removing it to avoid future seizures.

To do this, the patients and their doctors must wait for a seizure. With approval of the patients and the Washington University School of Medicine Institutional Review Board, Leuthardt and Moran connected the patients to a sophisticated computer running a special program known as BCI2000 (developed by their collaborators at the Wadsworth Center) which involves a video game that is linked to the EcoG grid.

They then asked the patients to do various motor and speech tasks, moving their hands various ways, talking, and imagining. The team could see from the data which parts of the brain correlate to these movements. They then asked the patients to play a simple, one-dimensional computer game involving moving a cursor up or down towards one of two targets.

They were asked to imagine various movements or imagine saying the word "move," but not to actually perform them with their hands or speak any words by mouth. When they saw the cursor in the video game, they then controlled it with their brains.

"We closed the loop," said Moran. "After a brief training session, the patients could play the game by using signals that come off the surface of the brain. They achieved between 74 and 100 percent accuracy, with one patient hitting 33 out of 33 targets correctly in a row."

The EcoG method is orders of magnitude faster to learn than EEG.

"It takes many months to train using EEG, whereas our approach was done basically in an hour or so," Moran said. "That's because we got the signals from the surface of the brain rather than having to go through the skull."

"To put this in perspective," Leuthardt said, " the previous EEG-based systems are equivalent to a 1908 Wright brothers airplane in regards to speed of learning to achieve control. Right now with our results we're flying around in an F-16 jet."

The two note that EcoG has higher spatial resolution, broader bandwidth and higher amplitude than the EEG approach, allowing the use of more electrodes and the gain of higher frequencies, which let the researchers go another step - they tried it out on a 2-D game and were able to predict where the patients would move by seeing which electrodes were active on the grid.

However, this group of patients did not control movement in the 2-D game with their brains, as they had with the 1-D game.

The researchers next want to try patients out with 2-D games to see if they can control the movements with their brains. They also will implant the EcoG grids into non-human primates - monkeys - to see how long they can get reliable data from them, the goal being eventually to develop a brain-machine interface device that will last years, say, up to 10, making the choice to have one implanted into a motor-impaired patient's brain practical.

"We are pretty confident that we can get signals from these for many years," Moran said. "There will have to be a rigorous study on monkeys for an indeterminate number of years before we can consider permanent implants in human subjects, but we're really excited about this advance. Brain-computer interface research is one of the hottest things going in biomedical engineering today."

"Our work," said Leuthardt, "has significant clinical relevance to potentially improve the lives of people with such disabilities as ALS and spinal cord injuries. Additionally, this type of research is producing some fundamental insights into a myriad of different fields ranging from neurophysiology to clinical medicine."

Collaborators on the study are Gerwin Schalk and Jonathan R. Wolpaw, M.D., of the Wadsworth Center, New York State Department of Health, Albany, N.Y., and Jeffrey G. Ojemann, M.D., University of Washington School of Medicine.

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