Princeton University

School of Engineering & Applied Science

Nanoelectronics Meeting Neuroengineering: Brain-inspired Systems and Neural Interfaces

Duygu Kuzum
E-Quad, B205
Thursday, March 12, 2015 - 4:30pm

Brain-inspired architectures and reconfigurable-adaptive systems are emerging research fields aiming to go beyond capabilities of digital logic and eventually to reach brain-like computational efficiency. In this first part of my talk, I will present a novel electronic device for brain-inspired computing, mimicking functionalities of biological synapses in the brain. I will discuss several aspects of brain computation including energy efficiency, robustness and parallelism and then explain how synaptic devices are used in hippocampus-inspired synaptic grids to demonstrate learning and robustness in hardware. I also will discuss how synaptic devices can help to understand brain computation. In the second part of my talk, I will introduce a new flexible transparent neural probe made of graphene for simultaneous electrophysiology and neuroimaging. Understanding dynamics of neural circuits requires probing them with high spatial and temporal resolution, simultaneously. To date, none of the available neural recording technologies has the ability to see individual neurons and their connections and simultaneously record their activity at the temporal resolution of single spikes. I will explain how the transparent probes made of graphene enable simultaneous functional optical imaging and electrophysiology to combine spatial and temporal resolution advantages of both techniques.   I will then demonstrate in vitro and in vivo recordings with transparent graphene electrodes and discuss electrochemical characteristics and noise performance of graphene neural electrodes.

Duygu Kuzum received her Ph.D in Electrical Engineering from Stanford University in 2010. She is currently a postdoctoral researcher at University of Pennsylvania, Bioengineering Department. Her research focuses on applying innovations in nanoelectronics to develop new technologies, which will help to better understand circuit-level computation in the brain. She developed nanoelectronic synaptic devices emulating the synaptic computation and plasticity in human brain. This technology could lead to portable and energy-efficient computers that can learn and process information in real time similar to human brain. Recently, she has been working on developing novel tools to probe brain circuits with high spatial and temporal precision. She is the author or coauthor of over 40 journal and conference papers. Her work on nanoelectronic devices was featured on the cover of Nano Letters, highlighted in Nature and covered by several media outlets (New Scientist, Stanford News Report, Nanowerk, EE Times). She was a recipient of a number of awards, including Texas Instruments Fellowship and Intel Foundation Fellowship, PopTech Science and Public Leaders Fellowship (2013) Award, Penn Neuroscience Pilot Innovative Research Award (2014), TASSA (Turkish-American Scientists and Scholars) Young Investigator Award (2014), and Innovators under 35 (TR35) by MIT Technology Review (2014).