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Hundreds of thousands of people worldwide suffer from neurological problems that disrupt the ability to move and communicate while leaving the cognitive faculties intact. Currently available assistive technology is limited, and many researchers are seeking to develop new neural prostheses to help paralyzed patients communicate and carry out simple tasks.
Most cutting-edge neural prostheses depend on brain-machine interfaces. A brain-machine interface detects neuronal activity in the brain and relays this information to other devices such as computers or robots. Decoding the neuronal activity in the brain is a complicated task, and the plasticity of the motor cortex has a major impact on the effectiveness of this decoding, causing the effectiveness of a brain-machine interface to fluctuate from day to day.
As researchers attempt to design better brain-machine interfaces, it is important for them to establish clear goals. Leigh Hochberg, MD, PhD, suggests that the ideal brain-machine interface should be safe, reliable, independent of any caregiver, easy to use, aesthetically acceptable, and affordable.
Dr. Hochberg is currently involved in a pilot trial designed to assess the effectiveness of the BrainGate neural prosthesis. This system allows some paralyzed patients to control a computer cursor. In future, the makers of the BrainGate system hope to eliminate day-to-day variation in the effectiveness of the prosthesis and to improve the algorithm decoding cortical activity.
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