Large-scale recording of neural signals is essential for gaining a better understanding of the elaborate, dynamic picture of the brain that emerges from interactions involving individual cells and complex neural circuits. Over the past few decades neural recording capabilities have progressed from single unit in vitro recordings to massively multichannel monitoring in vivo. Currently, microwire and microfabricated silicon neural probes are capable of sensing the simultaneous activity of hundreds of neurons. Miniaturized recording systems based on custom CMOS integrated circuits have been developed that can record from around 16-100 channels simultaneously, and these are no bigger than a postage stamp. Another wave of innovation is needed to enable next-generation neural interfaces that will provide high resolution access to 1,000-10,000 neurons and beyond.
Beyond understanding the brain, another "killer app" for neural interfaces is to directly connect prosthetic devices to a patient's nervous system. For example, cochlear implants today provide a sense of sound to over 100,000 patients in the US alone, including congenitally deaf children who now participate in music classes. Retinal prosthetics that provide artificial sight are currently being translated into medical products, with ongoing clinical trials inside and outside the US. Next on the horizon are motor prosthetics that allow paralyzed individuals to interact with the physical and cyber worlds. Bidirectional (read/write) motor prosthetics are being created at University of Utah that provide high degree of freedom control of mechanical prostheses while simultaneously invoking hundreds of different percepts generated by sensors and communicated to the patient through stimulation electrodes. Systems like these are comprised of many hardware and software components stretched to performance limits, offering a wealth opportunity for EE researchers.
Ross Walker is a graduate of Stanford University, and is now an Assistant Professor in the Department of Electrical and Computer Engineering, University of Utah. He received B.S. degrees in electrical engineering and computer science from the University of Arizona in 2005, the M.S. in electrical engineering from Stanford in 2007, and the Ph.D. in electrical engineering from Stanford in 2013. From 2003-2004 he held positions at IBM and National Semiconductor, both in Tucson, AZ. In 2006 he held a position at Linear Technology, Milpitas, CA. His research interests include mixed signal integrated circuit design with an emphasis on sensor interfacing, biomedical applications, and applied signal processing. Professor Walker has made contributions to biomedical imaging systems, direct neural interfaces, quantum biomolecular transducers, and other sensor applications.