Subsequently analyzing the signals from these experiments, the team found that the signals contained enough information to be useful in predicting the hand motions. Such prediction is the necessary requisite for reliably using neural signals to control external devices.
"Despite the limitations on the experiments, we were surprised to find that our analytical model can predict the patients' motions quite well," said Nicolelis. "We only had five minutes of data on each patient, during which it took a minute or two to train them to the task. This suggests that as clinical testing progresses, and we use electrode arrays that are implanted for a long period of time, we could achieve a workable control system for external devices," he said.
While other researchers have demonstrated that individually implanted electrodes can be used to control a cursor on a computer screen, complex external devices would require data from large arrays of electrodes, said the Duke researchers.
According to Nicolelis, another major difference between the initial human studies and the monkey studies is that recording in the human patients were made from electrodes inserted deeper into the brain, in subcortical structures, rather than the cortical surface.
"This shows that one can extract information not only from cortical areas, but from subcortical ones, too," said Nicolelis. "This suggests that in the future, there will be more options for sampling neuronal information to control a prosthetic device," he said.
According to Turner, the progression to human clinical studies presents a number of challenges. For example, he said, the data with monkeys were obtained from electrodes attached to the
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Contact: Dennis Meredith
dennis.meredith@duke.edu
919-681-8054
Duke University Medical Center
23-Mar-2004