A key objective of neural engineering is
to incorporate fundamental structural and functional principles of the
nervous system, emerging rapidly in the field of neuroscience, into the
design of a new generation of adaptive neural-based computers, signal
processors, and robotic devices. A complementary objective is to apply
the advanced modeling methods, electronic/photonic technologies, and computing
and information systems tools being developed within the field of engineering
to study the dynamics and organizational complexity of neurobiological
systems.
The University of Southern California
Research of CNE faculty addresses several key facets of
neural and engineering sciences, including quantitative analysis of fundamental
properties of the brain, the development of novel electronic and photonic
devices and techniques for experimental probing of brain tissue, the simulation
and mathematical analysis of neural networks, and the development of nervous
system-inspired engineering devices and systems. Important practical applications
for neural engineering principles include advanced computers and computer
interfaces, adaptive communications systems, adaptive speech processors,
artificial vision sensors, smart cameras, and neural prostheses.
