High-Resolution Brain Machine Interfaces Using Flexible Silicon Electronics: Research and Clinical Applications
Speaker: Dr. Jonathan Viventi
Faculty Host: Professor Sundeep Rangan.
Abstract
Current implantable brain devices for clinical and research applications require that each electrode is individually wired to a separate electronic system. Establishing a high-resolution interface over broad regions of the brain is infeasible under this constraint, as an electrode array with thousands of passive contacts would require thousands of wires to be individually connected. To overcome this limitation, I have developed new implantable electrode array technology that incorporates active, flexible electronics. This technology has enabled extremely flexible arrays of 720 and, soon, thousands of multiplexed and amplified sensors spaced as closely as 250 µm apart, which are connected using just a few wires. These devices yield an unprecedented level of spatial and temporal micro-electrocorticographic (µECoG) resolution for recording and stimulating distributed neural networks. µECoG is one of the many possible applications of this technology, which also include cardiac, peripheral nerve and retinal prosthetic devices. I will present the development of this technology and examples of retinotopic and tonotopic maps produced from in vivo recordings. I will also present examples of finely detailed spatial and temporal patterns from feline neocortex that give rise to seizures and suggest new stimulation paradigms to treat epilepsy.
About the Speaker
Jonathan Viventi is a Kirschstein-NRSA Postdoctoral Fellow in the Institute for Medicine and Engineering at the University of Pennsylvania. He has also been selected as a Beckman Postdoctoral Fellow at the University of Illinois at Urbana-Champaign. He received his Ph.D. from the University of Pennsylvania in Bioengineering and M.Eng. and B.S.E. degrees in Electrical Engineering from Princeton University.
His publications include cover articles in Nature Materials and Science Translational Medicine. He has filed four patent applications, one of which has been licensed to industry. At the University of Pennsylvania, he has been selected for the 2009 Nano/Bio Interface Center Graduate Research Award for the best graduate research on nanotechnology applied to biology, the 2010 Solomon R. Pollack Award for best thesis in the department of bioengineering and the 2010 Mahoney Institute of Neurological Sciences Flexner Award for best neuroscience thesis