U.S. scientists have developed an algorithm to be used in prosthetic devices that help paralyzed people convert brain signals into action.

   "The work represents an important advance in our understanding of how to construct algorithms in neural prosthetic devices for people who cannot move to act or speak," said Lakshminarayan Srinivasan, a Harvard-Massachusetts Institute of Technology medical student who began working on the algorithm while an electrical engineering and computer science MIT graduate student.

   In neural prosthetic devices electronics are used to monitor neural signals that reflect an individual's intentions for the prosthesis or computer they are trying to use. 

   Algorithms form the link between neural signals that are recorded and the user's intentions that are decoded to drive the prosthetic device.

   Until now, researchers working on brain prosthetics have used different algorithms depending on what method they were using to measure brain activity. Srinivasan said the new model is applicable no matter what measurement technique is used. "We don't need to reinvent a new paradigm for each modality or brain region," he said.

   The study that included Assistant Professor Uri Eden and Professors Sanjoy Mitter and Emery Brown appears in the Journal of Neurophysiology.

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