Neural engineering refers to a new discipline that has emerged by combining engineering technologies and mathematical/computational methods with neuroscience techniques. The objective is to enhance our understanding of the functions of the human nervous system. Neural engineering also holds promise to improve human performance, especially after injury or disease. As befits such a broad definition, the field is multidisciplinary, in that it draws from neurological sciences (especially neurobiology and neurology) but also from a diverse range of engineering disciplines, including computer sciences, robotics, material sciences, neural networks, signal processing, and systems modeling and simulation.
While the potential applications of neural engineering are very broad, the discipline offers particular opportunities for improving motor and sensory function after major human central nervous system illnesses such as stroke, traumatic brain injury, or spinal cord injury. In these illnesses, the new technologies can be applied to help reroute neural signals around damaged areas of brain or spinal cord, or to substitute one type of neural signal for another type that is lost after the injury.
A particularly innovative example relating to the descending control of muscle actions in spinal cord injury relies on the application of multi-electrode recording techniques to enable long-term, simultaneous recordings from clusters of neurons in the motor cortex during the performance of skilled voluntary movement tasks. These cortical signals can be used to drive assistive devices, to program electrical stimulation of muscles (functional electrical stimulation or FES), or to interact directly with computers as communication systems.
Leading investigators in this area are Andrew Schwartz (2004) from the University of Pittsburgh, John Donoghue (2002) from Brown University in Rhode Island, and M. A. Nicolelis (Patil et al. 2004) at Duke in North Carolina. Each group has developed impressive animal models that involve recordings from various cortical areas during normal voluntary...