Gold University of Minnesota M. Skip to main content. University of Minnesota.
Driven to Discover.
DMD

Neuroengineering 1

Wednesday, April 11, 2:00-3:30
Meridian Ballroom 1, Graduate Minneapolis

Organizers: Suhasa Kodandaramaiah, Benjamin Mayhugh Assistant Professor, University of Minnesota
Zhi Yang, Assistant Professor, Biomedical Engineering, University of Minnesota

"Neural Communication and Control"
Zhi Yang, Assistant Professor, Biomedical Engineering, University of Minnesota

"3D Printed Transparent Skulls for Pan Cortical Neural Interfacing"
Suhasa Kodandaramaiah, Benjamin Mayhugh Assistant Professor, University of Minnesota

"The Stentrode: Endovascular Electrodes for Brain-Computer Interfaces"
David Grayden, Professor, Department of Biomedical Engineering, The University of Melbourne


Session Organizer Bios:

Suhasa Kodandaramaiah, Benjamin Mayhugh Assistant Professor, University of Minnesota
Suhasa Kodandaramaiah is an Assistant Professor of Mechanical Engineering at the University of Minnesota. He received his Ph.D. degree from the Georgia Institute of Technology in 2013 after which he trained as a post-doctoral associate at Massachusetts Institute of Technology. His current research interests include developing robotic and optical neurotechnologies for large scale neural sensing.

Zhi Yang, Assistant Professor, Biomedical Engineering, University of Minnesota
Zhi Yang is an Assistant Professor of Biomedical Engineering at the University of Minnesota, Minneapolis campus. He is also with MnDrive robotics program and Systems Neuroengineering program at the University of Minnesota. His research is supported by DARPA, NIH, and industry partners. He received his Ph.D. degree from the University of California at Santa Cruz in 2010. He has published about 60 papers in peer-reviewed journals and conference proceedings. His current research interests include neural sensing and stimulation, neural information processing, and brain-machine interface.


Speaker Bios:

David Grayden, Professor, Department of Biomedical Engineering, The University of Melbourne
David Grayden is a Professor and Head of the Department of Biomedical Engineering at The University of Melbourne, Australia. He received his PhD degree from The University of Melbourne in 1999 and then completed a research fellowship at the Bionic Ear Institute, East Melbourne. His research interests are in understanding how the brain processes information, how best to present information to the brain using medical bionics, such as the bionic ear and bionic eye, and how to record information from the brain, such as for brain-machine interfaces. He is also conducting research in epileptic seizure prediction and electrical stimulation to prevent or stop epileptic seizures, and in electrical stimulation of the vagus nerve to control inflammatory bowel disease.


Presentation Abstracts:

"Neural Communication and Control"
In this talk, I will present a next-generation brain technology and testing results through a human clinical experiment. The brain technology includes a miniature sensor for acquiring neural signals and an artificial intelligent (AI) algorithm that analyzes neural signals for controlling a prosthetic hand and individual fingers. The sensor has a ten-fold improved sensitivity compared with current sensing systems in use. As a result, it can uniquely capture isolated neural waves traveling on nerves and harvest an unprecedented amount of information contents. The AI algorithm has 33 layers, which extracts and updates 100,000 features and refresh all joints’ positions every 0.02 second. In its first clinical testing on a transradial amputee, the technology has demonstrated a 15 degree-of-freedom in motor decoding. I will do a “Turing test” and invite the audience to differentiate normal subjects and amputees in videos. Our results suggest the recent development of neural sensor and AI could bridge human nervous system and machines, for example, making a new hand for amputees.

"3D Printed Transparent Skulls for Pan Cortical Neural Interfacing"
The brain mediates our interaction with the external world, by performing complex computations. Gaining a mechanistic understanding of how these computations are carried out will help to develop better treatments for neural diseases. These computations are undertaken by highly interconnected brain regions spread across several centimeters. To understand the brain computations, we need tools to measure and to manipulate the activities of these widespread brain regions at the single cell resolution, and at multiple timescales. Currently, appropriate tools to access to large brain regions and to sample information at high rates are not available. We are working on a suite of technologies that enable wide field-of- view cellular resolution neural interfacing in rodents. These include: (i) computer numerical controlled robots for precise skull excision; (ii) digitally designed and fabricated, optically clear skeletal prostheses (brain windows); and (iii) compatible head- mountable imaging modules for optically monitoring neural activity.

"The Stentrode: Endovascular Electrodes for Brain-Computer Interfaces"
Brain-machine interfaces enable control of prostheses for people with movement disorders such as spinal cord injury, loss of limb, and motor neurone disease. Robotic arms and exoskeletons have been developed with many degrees-of-freedom of operation. However, to provide adequate input to these systems has so far required direct implantation of electrodes into the brain via open craniotomy. We have developed a passive stent-electrode recording array, called the “Stentrode”, that is placed within a blood vessel in the brain where they can chronically record brain activity. We have completed pre-clinical trials and are now preparing for first-in-human trials.


Related Sessions:

Neuroengineering 2

Register Now


Stay connected with the DMD Conference through LinkedIn Twitter Facebook Icon G+ YouTube