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College of Science, Engineering, and Technology

Center for Materials Research

Faculty

Dr. Hargsoon Yoon

CMR Faculty-Dr. Hargsoon Yoon

Associate Professor of Engineering

Ph.D, Engineering Science, Pennsylvania State University


MCAR Suite #501F, Norfolk State University,
700 Park Ave., Norfolk, VA 23504,
Phone: (757) 823-0051
Fax: (757) 823-2698
Email: hyoon@nsu.edu

Biography

Dr. Hargsoon Yoon earned his Ph.D. degree in Engineering Science from Pennsylvania State University in 2003. Dr. Yoon also worked at Hynix Semiconductor Co. as a senior research engineer and a task force leader for system integrated circuit device development for seven years. After working as a post-doc at Pennsylvania State University and a research associate professor at University of Arkansas, he joined the Department of Engineering at the Norfolk State University in 2010 as an associate professor.

Dr. Yoon has developed several neural sensing devices using electrical and optical sensing principles and nanotechnology. His recent research interest is focused on the development of hybrid electronic and optical sensing systems for in-vivo neural sensing in the brain under grants from NSF, NIH, NASA and DoD.

Academic Service

  • Guest Editor of Journal, Biosensors (Special Issue: Neural Sensing and Interfacing Technology), 2015
  • Associate Editor of Journal, Smart Nanosystems in Engineering and Medicine, 2012-current
  • Program Committee of SPIE International Conference, 2012-current
  • Senior Member of IEEE Engineering in Medicine and Biology Society, current
  • Member of Society for Neuroscience, current
  • Steering Committee of Hampton Roads Neuro-Science Network, current

Research

  • Development of Mechanically Flexible Neural Sensing Devices
  • Functional Imaging of Neural Networks with Depth Nano-Electrodes
  • Optical Neural Sensing Based on Nano-Plasmonic Field Enhancement
  • Functional Near Infrared Sensing of Hemodynamic Neural Activity

PUBLICATIONS

Book Chapters

1. L. Chen, J. Xie, H. Yoon, M. Srivatsan, R. Harbaugh, V. Varadan, Biohybrid Systems: Nerves, Interfaces and Machines (Chapter 6 Biohybrid Circuits: Nanotransducers Linking Cells and Neural Electrodes), Wiley (2011).

Journal Publications

1. Michael Polanco, Hargsoon Yoon*, Sebastian Bawab, “Micromotion-induced dynamic effects from a neural probe and brain tissue interface” J. Micro/Nanolith. MEMS MOEMS., 13(2), 023009 (2014).
2. H. Yoon*, H.J. Kim, E. Song, K.D. Song, U. Lee, L.D. Sanford, S.H. Choi, “A hat-type wireless power transmission for a nano-neural sensing system, Smart Nanosys. Eng. Med., 1, 88 (2012).
3. R. Zhu, G.L. Huang, H. Yoon*, C.S. Smith, V.K. Varadan, “Biomechanical strain analysis at the interface of brain and nanowire electrodes on a neural probe”, J. Nanotech. Eng. Med., 2, 031001 (2011).
4. H. Yoon*, P. Hankins, S. Oh, R. E. Haubaugh, V. K. Varadan, “Heterostructured IrO2/Au nanowire electrodes and unit recordings from hippocampal rat brain” J. Nanotech. Engineering Medicine, 1(2), 021006 (2010).
5. H. Yoon*, D. C. Deshpande, V. K. Varadan, T. Kim, E. Jeong, and R. E. Harbaugh, “Development of titanium needle probes for neural recording” J. Nanotech. Engineering Medicine, 1(1), 011004 (2010).
6. T. C. Le, H. Yoon*, L. Chen, R. McCann, V. K. Varadan, “Fabrication of giant magneto resistance sensing devices with vertically grown Co/Cu nanowires on a substrate,” J. Micro/Nanolitho., MEMS, MOEMS, 8, 043055 (2009).
7. R. Dubey, T.C. Shami, K.U. Bhasker Rao, H. Yoon*, and V.K. Varadan, “Synthesis of polyamide microcapsules and effect of critical point drying on physical aspect,” Smart Mater. Struct, 18, 025021 (2009).
8. H. Yoon*, P. Hankins, V.K. Varadan, and R. E. Harbaugh, “Dual electrode ensembles with core and shell nanoelectrodes for dopamine sensing applications,” Electroanalysis, 20, 1147 (2008).
9. J. K. Abraham, H. Yoon, R. Reddy, M. Kavdia, and V.K. Varadan, “Design and development of nanowire integrated microelectrode arrays for lab-on-a-chip devices,” IET Nanobiotechnology, 2, 55 (2008).
10. D.C. Deshpande, H. Yoon*, A. M. Khaing, and V.K. Varadan, “Development of a Nanoscale heterostructured glucose sensor using modified microfabrication processes,” J. Micro/Nanolitho. MEMS. MOEMS, 7, 023005 (2008).
11. H. Yoon*, D. C. Deshpande, V. Ramachandran, and V. K. Varadan, “Aligned nanowire growth using lithography-assisted bonding of polycarbonate template for neural probe electrodes,” Nanotechnology, 19, 025304 (2007).
12. H. Yoon*, J. Xie, J. K. Abraham, V. K. Varadan, and P. B. Ruffin, “Passive wireless sensors using electrical transition of carbon nanotube junctions in polymer matrix,” Smart Mater. Struct., 15, s14 (2006).
13. T. Ji, H. Yoon, J. K. Abraham, and V. K. Varadan, “Ku-band antenna array feed distribution network with ferroelectric phase shifters on silicon,” IEEE Trans. Microw. Theo. Tech, 54, 1131 (2006).
14. T. Ji, H. Yoon, J. K. Abraham, and V. K. Varadan, “Design of a Ku-band wilkinson power divider on surface-stabilized high-resistivity Si substrates,” Microw. Opt. Lett., 44, 436 (2005).
15. H. Yoon, V. K. Varadan, “Design and performance of bilateral interdigital CPW phase shifter for RF communication applications,” J. Microlitho. Microfab. Microsys., 3, 459 (2004).
16. H. Yoon, J. K. Abraham and V. K. Varadan, “Design and experimental results of bilateral interdigital coplanar delay line for MMIC,” Microw. Opt. Lett., 40, 127 (2004).
17. H. Yoon, K. J. Vinoy and V. K. Varadan, “Design and development of micromachined bilateral interdigital coplanar waveguide RF phase shifter compatible with LDMOS voltage controller on Silicon,” Smart Mater. Struct., 12, 769 (2003).
18. V.K. Varadan, K.J. Vinoy, H. Yoon, K.A. Jose, and V.V. Varadan, “Application of MEMS in microwave and millimeter wave systems,” J. Wave-Material Interaction, 15, 101 (2000).

Non-Refereed Publication

1. J. R. Skuza, Y. Park, H. J. Kim, S. T. Seaman, G. C. King, S. H. Choi, K. D. Song, H. Yoon, and K. Lee, “Feasibility study of cargo airship transportation systems powered by new green energy technologies”NASA Technical Memorandum, NASA/TM-2014-218241 (2014).
2. V. K. Varadan, J. Xie, K. J. Vinoy, and H. Yoon, “Nano- and micro-devices for performance improvement of space solar power system,” URSI Radio Science Bulletin, No.310 (2004).

Selected Conference Proceedings and Presentation

1. Sang H. Choi; Min Hyuck Kim; Kyo D. Song; Hargsoon Yoon; Uhn Lee, “A wirelessly powered microspectrometer for neural probe-pin device,” Proc. SPIE Micro+Nano Materials, Devices, and Systems, 9668, 96683Z (2015).
2. Darryl Scott, Min H. Kim, Hargsoon Yoon, “Neural probe array for fast neural imaging of group cellular events using electrical impedance tomography” Cell Symposia: Engineering the Brain, Chicago, IL (Oct. 2015).
3. Min Hyuck Kim; Kyo D. Song; Hargsoon Yoon; Yeonjoon Park; Sang H. Choi; Dae-Sung Lee; Kyu-Sik Shin; Hak-In Hwang; Uhn Lee, “Probe-pin device for optical neurotransmitter sensing in the brain,” Proc. SPIE, Nanosensors, Biosensors, and Info-Tech Sensors and Systems, 9434, 943409 (2015).
4. Min Hyuck Kim; Ilho Nam; Youngki Ryu; Laurie W. Wellman; Larry D. Sanford; Hargsoon Yoon, “Miniaturized neural sensing and optogenetic stimulation system for behavioral studies in the rat,” Proc. SPIE Nanosensors, Biosensors, and Info-Tech Sensors and Systems, 9434,94340B (2015).
5. Demetris Geddis; Jaehwan Kim; Sang H. Choi; Hargsoon Yoon; Kyo D. Song, “Review of radio wave for power transmission in medical applications with safety,” Proc. SPIE Nanosensors, Biosensors, and Info-Tech Sensors and Systems. 9434, 94340T (2015).
6. Larry D. Sanford, Min Hyuck Kim, Laurie L. Wellman, Hargsoon Yoon, “ Real-time Sensing of Glutamate in the Basolateral Amygdala (BLA) in the Rat Brain across Sleep-wake States”, Society for Neuroscience Conf., Washington, DC (Nov. 2014).
7. Darryl W. Scott, Anish K. Kodeboyina, Min Hyuck Kim, Hargsoon Yoon, “Development of Nano-Electrode Array for Functional Electrical Impedance Tomography in the Brain” HRNN Conf., Norfolk, VA (Oct. 2014).
8. Nakyia Hinton, Anish K. Kodeboyina, Min H. Kim, Hargsoon Yoon, “Investigation of Hemodynamic Response on Occipital Lobe to Detect Distracted Driving” HRNN Conf. Norfolk, VA (Oct. 2014).
9. Michael Polanco, Hargsoon Yoon, Sebastian Bawab, “Finite Element Analysis for Time-Dependent Dynamic Effects from a Neural Probe and Brain Tissue Interface,” Neural Interface Conference, Dallas, TX (June 2014).
10. Min H. Kim, Darryl W. Scott, Alonzo Jenkins, Nakyia Hinton, Hargsoon Yoon, Laurie L. Wellman, Larry D. Sanford, “Amperometric Sensing of Glutamate in the Basolateral Amygdala (BLA) and Neuro-Potential Recordings across Sleep-wake States,” Neural Interface Conference, Dallas, TX (June 2014).
11. Camille Cooper; Keisharra Eldridge; Min Hyuck Kim; Hargsoon Yoon; Sang H. Choi; Kyo D. Song, “Parylene-C passivation and effects on rectennas' wireless power transfer performance,” Proc. SPIE, Nanosensors, Biosensors, and Info-Tech Sensors and Systems, 9060, 90601A (2014).
12. Min H. Kim, Young Kee Ryu, Hargsoon Yoon, Ilho Nam, Darryl W. Scott, Larry D. Sanford, “A dual-function electronic module for chronic neural sensing and optogenetic stimulation,” SPIE 2014 Nano-, Bio-, Info-Tech Sensors and Systems, San Diego, CA (2014).
13. Hargsoon Yoon, Min H. Kim, Hyunjung Kim, Kyo D. Song, Laurie L. Wellman, Larry D. Sanford, Hae S. Kim, Sang H. Choi, “Development of an electrical and optical neural probe for neurotransmitter sensing in the brain,” SPIE 2014 Nano-, Bio-, Info-Tech Sensors and Systems, San Diego, CA (2014).
14. Darryl W. Scott, Min H. Kim, Camille Cooper, Hargsoon Yoon, “Nano-electrode array for in-vivo action potential recording in the brain,” SPIE 2014 Nano-, Bio-, Info-Tech Sensors and Systems, San Diego, CA (2014).
15. Min H. Kim, Hargsoon Yoon, “Development of a flexible supercapacitor using iridium oxide nanowire and active carbon electrodes,” SPIE 2014 Nano-, Bio-, Info-Tech Sensors and Systems, San Diego, CA (2014).
16. Min Hyuck Kim, Hargsoon Yoon, Laurie L. Wellman, Larry D. Sanford, “In-vivo sensing of glutamate levels in the basolateral amygdala across sleep-wake states,” Proc. IEEE Sensors 348 (2013).
17. Courtney S. Smith, Darryl W. Scott, Min H. Kim, Larry D. Sanford, Kyo D. Song, Hargsoon Yoon, “Polyimide neural probe for chronic sensing of neural activity and micro-positioning,” SPIE Proceedings Nanosensors, Biosensors, and Info-Tech Sensors and Systems, 8691, 86910N (2013).
18. Michael Polanco, Hargsoon Yoon, Sebastian Bawab, “Micromotion-induced dynamic effects from a neuron probe and brain tissue interface,” SPIE Proceedings Nanosensors, Biosensors, and Info-Tech Sensors and Systems, 8691, 869109 (2013).
19. H. Yoon, “Nanotechnology: Development of devices and electrodes,” International Bioelectrics Workshop (2012).
20. Hargsoon Yoon, Kyo D. Song, Uhn Lee M.D., Sang H. Choi, “Microwave thermal radiation effects on skin tissues,” SPIE Proceedings Nanosystems in Engineering and Medicine, 8548, 85482R (2012).
21. M. Polanco, H. Yoon, K. Lee, S. Bawab, “Predicting brain tissue deformation around an implantable electrode due to dynamic micromotion,” SPIE Proceedings Nanosystems in Engineering and Medicine, 8344, 83441l (2012).
22. K.D. Song, H. Yoon, U. Lee, S.H. Choi, “Thermal effects of X-band microwaves on skin tissues,” SPIE Proc. Nanosystems in Engineering and Medicine, 8344, 834418 (2012)
23. Y. Park, H. Yoon, U. Lee, G.C. King, S. Choi, “Mathematical simulation for integrated linear Fresnel spectrometer chip,” SPIE Proc. Nanosensors, Biosensors, and Info-Tech Sensors and Systems, 8344, 83440D (2012).
24. H. Yoon, H. Kim, S.H. Choi, L.D. Sanford, D. Geddis, K. Lee, J. Kim, K.D. Song, “Wireless power using magnetic resonance coupling for neural sensing applications,” SPIE Proc. Nanosensors, Biosensors, and Info-Tech Sensors and Systems, 8344, 83440S (2012).
25. Sang Y. Yang; Kyo D. Song; Hargsoon Yoon; Jaehwan Kim, “Investigation of coplanar strip dipole rectenna elements for microwave power transmission: simulation and experiment,” SPIE Proc. Nanosensors, Biosensors, and Info-Tech Sensors and Systems, 8344, 83441H (2012).
26. C. S. Smith, C. M. Bowie, K. D. Song, V. K. Varadan, W. Kim, and H. Yoon*, Electrochemical Investigation of nano-electrodes for biomedical sensing applications in the brain,“ Proceedings of SPIE, 7980, 798011 (2011).
27. C. Smith, K.D. Song, H. Yoon, W. Kim, T. Zeng, L.D. Sanford, “Development and investigation of flexible polymer neural probe for chronic neural recording ,” SPIE Proc. Nanosensors, Biosensors, and Info-Tech Sensors and Systems, 8344, 834404 (2012).
28. H. Yoon, K. D. Song, K. Lee, J. Kim, and S. H. Choi, “Near field effects of millimeter-wave power transmission for medical applications,” SPIE Proc. Nano-, Bio-, Info-Tech Sensors and Systems, 7980, 798012 (2011).
29. H. Yoon*, C. Smith, C. Bowie, and K. Song, “Neural Electrodes with Sensing Core and Shielding Grid Nano-Structures for Chronic Neural,” UKC 2010 Symposium, Seattle WA (Aug. 2010).
30. C. Smith, K. Song, and H. Yoon*, “Design and Development of Heterostructured Nanoelectrodes to Shield Cell Adsorptions and Enhance Chronic Neural Recording,” Neural Interface Conference, Long Beach CA (June 2010).
31. H. Yoon, F. Williams, K. D. Song, S. Y. Yang, J. Kim; K. Lee; S. H. Choi, “Rectennas performance based on substrates for bio-medical applications,” SPIE Nanosensors, Biosensors, and Info-Tech Sensors and Systems, San Diego CA (Mar. 2010)
32. C. Smith, K. Song, and H. Yoon*, Development of Wireless Neural Probing System for Simultaneous Dopamine and Neural Impulse Sensing in Addictive Behaviors,” Society for Research on Nicotine and Tabacco, Baltimore MD, (Feb. 2010).
33. H. Yoon, P. Hankins, S. Oh, V. K. Varadan, C. Brantley, E. Edwards, P. B. Ruffin, Y. M. Kwon, “Nanowire gas sensors and wireless sensing network for electronic-nose development,” SPIE Nanosensors, Biosensors, and Info-Tech Sensors and Systems, San Diego CA (Mar. 2010).
34. S. Oh, H. Kwon; H. Yoon; V. K. Varadan “Application of wireless sensor system on security network,” SPIE Nanosensors, Biosensors, and Info-Tech Sensors and Systems, San Diego CA (Mar. 2010).
35. H. Kwon, S. Oh, H. Yoon, and V. K. Varadan, “Software structure for broadband wireless sensor network system,” SPIE Nanosensors, Biosensors, and Info-Tech Sensors and Systems, San Diego CA (Mar. 2010).
36. H. Yoon, P. T. Hankins, V. K. Varadan, “Neural Sensing and Stimulation with IrO2/Au Nanowires and Nanocavity Ensemble,” World Cong. Int. Neuromod. Soc. (2009).
37. H. Yoon, D. C. Deshpande, V. Ramachandran, P. T. Hankins, V. K. Varadan, “Nanodevices for biosensing applications,” SPIE Proc. Nanosensors, Biosensors, and Info-Tech Sensors and Systems, 7291, 729109 (2009).
38. V. Ramachandran, H. Yoon, V. K. Varadan, “Design and fabrication of nanowire electrodes on a flexible substrate for detection of myocardial ischemia,” SPIE Proc. Nanosensors, Biosensors, and Info-Tech Sensors and Systems, 7291, 729109 (2009).
39. S. Oh, H. Kwon, L. Kegley, H. Yoon, V. K. Varadan, “Wireless nanosensor network system”, SPIE Proc. Nanosensors, Biosensors, and Info-Tech Sensors and Systems, 7291, 729111 (2009).
40. V. Ramachandran, H. Yoon, and V. K. Varadan, “Development of potassium ion sensors using polypyrrole electrodes on a polyimide substrate,” SPIE Proc. Nanosensors, Microsensors, and Biosensors and Systems, 6931, 69310H (2008).
41. H. Yoon, V. Ramachandran, D. C. Deshpande, and V. K. Varadan, “Bio-inspired electric cilia development for biomedical applications: use of ionic electro active polymer, nanowire arrays, and micro-stereo-lithography” SPIE Proc. Nanosensors, Microsensors, and Biosensors and Systems, 6528, 652804 (2007).
42. P. T. Hankins, H. Yoon, and V. K. Varadan, “Cylindrical nanocavity and nanowire electrodes for redox cycle dopamine sensing: design, fabrication, and characterization,” SPIE Proc. Nanosensors, Microsensors, and Biosensors and Systems, 6528, 65281J (2007).
43. D. C. Deshpande, H. Yoon, A. M. Khaing and V. K. Varadan, “Development of amperometric glucose sensors with heterostructured nanowire arrays for continuous subcutaneous monitoring,” SPIE Proc. Nanosensors, Microsensors, and Biosensors and Systems, 6528, 652819 (2007).
44. J. K. Abraham, R. Chintakuntla, H. Yoon and V. K. Varadan, “Nanowire integrated microelectrode arrays for Lab-on-a-Chip applications,” SPIE Proc. Nanosensors, Microsensors, and Biosensors and Systems, 6528, 65280O (2007).
45. J. K. Abraham, H. Yoon and V. K. Varadan, “Nanowire integrated microelectrode arrays for neuroelectronic applications,” IEEE Regional conference, 20, 185 (2007).
46. H. Yoon, D. Devesh, V. K. Varadan, “Enzyme electrodes immobilized on hetero-structured metallic nanowire array for glucose sensing,” SPIE Proc. Biomedical Applications of Micro- and Nanoengineering, 6416, 641608 (2006).
47. H. Yoon, R. R. Chintakuntla, V. K. Varadan, P. B. Ruffin, “Aligned nanowire structures on silicon and flexible substrates and their applications,” SPIE Proc. Smart Electronics, MEMS, BioMEMS, and Nanotechnology, 6127, 128 (2006).
48. H. Yoon, B. Philip, J. K. Abraham, T. Ji, and V. K. Varadan, “Nanowire sensor array for wireless detection and identification of bio-hazards,” SPIE Proc. Smart Electronics, MEMS, BioMEMS, and Nanotechnology, 5763, 326 (2005).
49. H. Yoon, T. Ji, and V. K. Varadan, “Design and development of 3-bit polymer MEMS phase shifters,” SPIE Proc. Smart Electronics, MEMS, BioMEMS, and Nanotechnology, 5763, 61 (2005).
50. T. Ji , H. Yoon, J. K. Abraham, and V. K. Varadan, “Wilkinson power divider for antenna distribution networks,” Proc. of SPIE, 5763, 55 (2005).

Grants

National Aeronautics and Space Administration

  • Development of In-vivo Neural Sensing Systems based on Nano-Plasmonic Field Enhancement, 7/1/2013-6/30/2016, PI.
  • Optical Neural Sensing using a Micro-Spectrometer in the Rat Brain, 3/1/2012-2/28/2014, PI.
  • Optimization of X-band Rectennas and Development of Rectenna Circuit beyond k-band for Airship Application,” NASA, 11/1/2000-10/31/2013, co-PI.

National Science Foundation

  • Enhancement of Research Infrastructure for the Development (Electrochemical-Mechanical Coupling of 3-Dimensional Nano-Electrodes in Neural Sensing), PI, 3/1/2014-2/28/2017
  • Acquisition of an Integrated System of Instruments for Multichannel Biopotential Recording of In-vitro and In-vivo Experiments, PI, 9/1/2013-8/31/2015
  • Collaborative Research-Developing a Student Learning Strategy to Bridge Virtual Learning and Hands-on Activity in Organic Solar Energy Education, PI, 9/1/2013-8/31/2016
  • Acquisition of Time-Correlated Single Photon Collecting System for Multidisciplinary Research and Education, Co-PI, 9/1/2014-8/31/2017
  • Center for Renewable Energy and Advanced Materials, Co-PI, 9/1/2013-8/31/2016 (Recommended for Funding)
  • CREST: Center for Nano- and Bio-Inspired Materials and Devices, Senior Person, 10/1/2010-9/30/2015
  • Experimental Centric based Engineering Curriculum for HBCUs, Co-PI, 9/1/2013-8/31/2016

National Institute of Health

  • R01: Limbic Modulation of Stress-Induced Alterations in Sleep, 9/1/2013-8/31/2018, Collaborating Investigator.

Department of Defense

  • Center of Excellence for Advanced Nanomaterials & Devices, 6/1/2011-5/31/2016, Senior Investigator.

Awards and Honors

Awards

  • Outstanding Researcher of College, 2013, College of Science, Engineering and Technology
  • Employee of the Year, 1999, Hynix Semiconductor Co., South Korea

Neural Engineering and Nano-Electronics Laboratory

Group Members

Role and Mission:

We have been working on the development of electronic and optical devices and systems for neural sensing and functional imaging of neuronal activity and their functional network that are associated with behaviors. Major goals of this laboratory are to 1) Enable assessment of unit neuronal activity at specific anatomical location while preventing damages to the activity center, 2) Allow measurement of functional networks in real time with high spatiotemporal resolution, and 3) Allow monitoring of neural activity in real time and provide autonomous neuro-modulation for clinical neuro-stimulation or brain computer interface. As a long term goal, this laboratory intends on extending this research to both neuroscience and human clinical research (e.g. adaptive neuro-stimulation) and implementing outcomes to industrial applications (e.g. human computer interface).

Vision

Based on successful outcomes of our research developing neural sensing electrodes using nanotechnology from this laboratory for last five years, we are currently conducting research to extend the scope of functional imaging area into the deeper brain structures. Electrical Impedance Tomography (EIT) of fast neural activity will produce high spatial accuracy and image neuronal function of deep brain structures. This development will enable, for the first time in the world, imaging of fast neural activity in deep brain structures and produce a revolutionary advance in neuroscience technology. Moreover, it could enable quantitative mathematical analysis of the fast electrical activity in neural systems. This could lead to radical improvements in understanding the brain and in treatment of disorders like schizophrenia, depression and epilepsy, as well as advancing cognitive and computational neuroscience.

Major Research Activities

To accomplish the mission and specific aims, we developed numerous neural sensing devices and systems with research grant supports from NSF, NASA, NIH, and DoD programs and extensive research collaboration with Eastern Virginia Medical School, Old Dominion University, NASA Langley Research Center and Pennsylvania State University. Among many outstanding research outcomes, four major products are described below.

  • Development of mechanically flexible and nano-neural sensing devices and recording in the rat brain

To achieve better integration of the neural probes with brain tissue and enhance longevity of electrode function, we are investigating various materials and designs of neural probes. We perform computational analysis for the transient aspects of motion within the brain and analyzed various designs to reduce mechanical strains seen around neural sensing devices along the brain tissue interface. With analysis results, we design and fabricate polymer neural probes embedding vertically grown nanowire electrodes. By having a very soft polymer probe directly interfacing brain tissue, mechanical impact from the probing device can be reduced. This research is currently funded by NSF.

Neural sensing system
Neurotransmitter, Glutamate, sensing


Functional Imaging of Neural Networks with Depth Nano-Electrodes.

We are currently focusing on the development of neural sensing and functional imaging devices. By integration of nanotechnology, we can effectively monitor neural activities from neural cells. This research development will allow us to measure neuronal population activity and their functional link in the network regardless of the spatial arrangement of cells and irrespective of the source of excitatory or inhibitory inputs. This research will also aid the development of novel therapeutic treatments by observing details of neural activity in brain structures within functional networks. The application of the functional imaging with high spatiotemporal resolution is extended to human-computer interface. This research is currently funded by NSF and NIH.


Schematic diagram of optrode array for functional imaging.
Neural Recording from Locus Coeruleus

Optical Neural Sensing Based on Nano-Plasmonic Field Enhancement

We are developing an optical neural sensing module for in-vivo monitoring of neurotransmitter. In this optical sensing, laser light is delivered into the brain, and then, the optical spectrum of scattered lights by neurotransmitters in the brain is measured by a µ-spectrometer. To enhance sensitivity and selectivity, nano-features are embedded on optical sensing probes. The size of a proto-typed sensing module is 48mm × 22mm × 15 mm and is being reduced in a revised design. We are planning to integrate this module with a wireless electrophysiological sensing unit. This optical sensing technology has strong potential for clinical applications such as adaptive deep brain stimulation, because optical sensing can be free from the issues of electrical stimulation artifact and short lifetime of implanted neurotransmitter sensors. This research is currently funded by NASA.

Wireless Optical Dopamine Sensing

Finite element analysis of micromotion between neural sensing electrodes and brain tissue

Despite success in sensing the activity of the living brain, one of the important issues not overcome is how to relieve neural cell degeneration and losses caused by mechanical motion and impact around the sensing electrode interface. The mechanical motion is caused by breathing and vascular pulsation or external body motion such as rapid head movement or collision, which can hardly be avoided in normal behavior. We are performing a series of finite element analyses (FEA) with a viscoelastic model to study the extent of the strain induced within the brain in an area around a neural probe. FEM analysis for many years of my research showed that at least a 95% reduction in stress and strain can result when a 0.0002 GPa probe stiffness is utilized. With the analysis results, we have developed neural sensing probes with a multilayer soft polymer composite structure (e.g. Polydimethylsiloxane (PDMS)/Parylene-C/Polyimide layers embedding vertically grown nanowire electrodes). By having a very soft polymer material such as PDMS on the outer surface of the probe directly interfacing brain tissue, mechanical impact from the probing device can significantly be reduced.


FEM Analysis


f-NIR Sensing of Hemodynamic Neural Activity

Functional near-infrared (f-NIR) spectroscopy is a spectroscopic method that uses the near-infrared region of the light spectrum to measure hemodynamic activity in the brain. The functional state of hemoglobin in the blood can influence its optical properties. The brain undergoes a number of physiological changes as it responds to stimuli; these changes in blood levels and electro-potential activity, in turn affect its optical properties of neural tissues. Functional optical imaging capitalizes optical properties of these tissues by using light in the near-infrared range. This research is currently funded by NSF.

f-NIR

News

Awarded with NSF MRI grant

Dr. Hargsoon Yoon and his research team has received a two year $240k grant from NSF, entitled, "Acquisition of an Integrated System of Instruments for Multichannel Biopotential Recording of In-vitro and In-vivo Experiments." Drs. Sacharia Albin, Makarand Deo, Kyo Song, and Frances Williams are co-investigators on this grant from our Engineering Department. The project is also in collaboration with investigators at the Eastern Virginia Medical School and Old Dominion University. The aim of this research is to build an integrative research platform for neural recording and analysis and provide the resources for students, faculty and associated collaborators for their research activities from electronic and optical engineering, biology, computer science, nanotechnology, immunology, and neuroscience fields. Addition of this system to the existing research infrastructures will directly benefit and upgrade our research programs at NSU, as well as the collaborative network capabilities in the Hampton Roads area. The instrument will be applied for the study of neural mechanisms underlying the interactions under various behavioral, stimuli, and disease c onditions. In addition to the biopotential recording, the instrumentation will allow in-vivo a ssessment of neural sensing devices to be developed by engineering research. Furthermore, in-vivo and in-vitro real-time measurement and monitoring of sensing signal can be applied for the development of novel therapeutic treatment strategies of neurological disorders and degeneration.

Dr. Yoon awarded with NASA grant

Dr. Hargsoon Yoon and his research team was awarded a three-year grant from NASA, entitled, "Development of In-vivo Neural Sensing Systems based on Nano-Plasmonic Field Enhancement". The project is in collaboration with investigators at the Eastern Virginia Medical School (EVMS). Dr. Kyo Song, also from our Engineering Department, and Dr. Larry Sanford from EVMS are the other Co-principal investigators on the grant. The aim of this research is to develop an optical neural sensing system using nano-plasmonic optical sensing probes, a micro-spectrometer and miniaturized electronics which are targeted for in-vivo neural sensing in animals. The long term goal for this system is to read neural activity in real time and to provide autonomous control through a closed-loop feedback system for deep brain stimulation treatment. The impact of this technology will significantly enhance the accuracy of deep brain stimulation treatment for patients with neurological disease and disorders.

Neural Recording Systems Funded by NSF MRI


NSF MRI funded neural recording systems are available for neural engineering research.


  • 128 Channel Neural Recording and Stimulation System
  • Functional Near Infrared Neuro-Imaging System
128 channel
Commutator

Location: Marie V McDemmond Building, #210
555 Park Avenue, Norfolk, VA

User Fee: Based on the actual usage time on the system, usage fee will be charged (set by the steering committee). Consumables for specific research experiment which are not regularly used are required to be provided by the investigator performing the experiment.

Training: Requests should be made to Dr. Hargsoon Yoon (email: hyoon@nsu.edu, tel: 757-823-0051)

System Descriptions

Neuropotential recording and stimulation system (manufacturer: Plexon, TX)

This system is comprised of four different and integrative subunits: 1) A bio-potential data acquisition unit for 128-channel on-line data acquisition and stimulation which is a core of this sytem, 2) A 32-channel wireless data communication unit, 3) A digital interface unit for electrochemical workstation to be used for neurochemical sensing, and 3) A digital video recording and tracking unit for animal behavior study.

Schematic
DAQ setup

128 Channel On-Line Data Acquisition: This biopotential measurement and stimulation units provide a 16-bit, 40 kHz digitization unit, 32 digital inputs, digital programmable filtering, analog and digital referencing and work as the core and control unit of the proposed system. In this system, the control software sets flexible gain and filtering control for high quality neural sensing. The analog low-cut filter in the system has selectable cutoff frequencies, which allows us to try different values depending on the movement levels of the animal. Flexible digital filtering supports a wide variety of filter types (Bessel, Butterworth, Elliptic, 2-12 poles, plus notch filter) and cutoff frequencies, for extracting spikes and field potentials from the wide-band signal and for noise removal. For signal analysis, four manual and two automatic spike sorting methods are available, as well as automatic gain control and waveform thresholding. In addition, the system may be configured to acquire and sort waveforms from some electrode channels in single electrode mode while acquiring and sorting waveforms from other electrodes in stereotrode or tetrode mode. This mixed single/stereotrode/tetrode acquisition capability is particularly useful for recordings from multiple brain areas with different cell densities, such as combined basal ganglia recordings and prefrontal cortical recordings, which is an essential function for our research investigating functional network in the brain.

Omni Plex
DAQ setup

Neurostimulation: The stimulation unit can generate arbitrary waveform patterns initiated from either the software interface or from externally triggered digital inputs with an unprecedented 30 nA resolution and 1 µsec temporal resolution. With the unit, the intuitive graphical user interface makes it easy to generate bi-phasic rectangular pulses and bursts of pulses repeated at specific rates. More complicated rectangular waveforms and non-rectangular arbitrary waveforms may be defined in and loaded from a simple text file. In addition, an SDK is available for C/C++ and MATLAB® which may be used to create various stimulation waveforms or pulse patterns outside the GUI interface of the unit. Furthermore, the unit allows to trigger each of the 16 analog output channels independently. This stimulation patterns can be highly useful to our research requiring selective and coordinated stimulation of neurons.

Stimulator
Pulse

Wireless Recording and Digital Video Tracking System for Animal Behavior Study: The propose wireless neural headstage unit allows continuous and simultaneous monitoring of up to 128 neural electrodes collecting Local Field Potentials(LFPs) and single unit or spike data. Using this unit, neural recording experiments are free from the physical constraints required with recording systems that require cables attached to the animals. The unit is comprised of a proprietary RF headstage transmitter with integrated rechargeable battery, receiver/baseband demodulator, power supply and all required cables. With an effective range of four meters, the miniature light weight transmitter provides a wireless connection for rats and even primates. In addition, the proposed video tracking unit (CinePlex) synchronizes video capture with neural data files obtained by Omniplex. The synchronized video, tracking coordinates, and neural data can then be viewed offline, where behavioral event markers and time-interval variables can be inserted. The modified data file can be exported for further analysis. Detail features include 1) triggered video capture (50 microsecond accuracy), 2) low noise AVT Stingray cameras (640 x 480 resolution, up to 80 frames per second), and 3) removable infrared (IR) filter, for use of IR illuminator to visualize and track animals in dark environments.

Receiver
Transmitter

fNIR Recording System

f-NIR (functional near infrared) optical imaging system measures oxygen level changes in the prefrontal cortex of human subjects and provides information about ongoing brain activity similar to functional MRI studies. However, it eliminates many of the drawbacks of fMRI and provides a safe, affordable, noninvasive solution for cognitive function assessment. The optical neural sensing technology can access regions 1-2 cm deep inside the brain. During a cognitive activity, the change in concentration of these main absorbers provides information about brain functions. The optical sensing data can be combined with biopotential signals measured by the OmniPlex system, such as EEG and ECG, and provide important additional data which is also available in our laboratory.

fNIR100 Functional Brain Imaging System: This system includes a control device and 16-CH sensor for continuous fNIR spectroscopy (NIRS), plus COBI control device software and fNIRSOFT (fS) Standard Edition analysis software. fS is a stand-alone software package designed to process, analyze and visualize functional near infrared (fNIR) spectroscopy signals through a graphical user interface and/or scripting (for automation). For measurement, the subject wears a sensor on the forehead that includes four IR light sources and ten detectors that are mounted in a flexible band that is comfortable to wear for prolonged periods of time. The fNIR sensor detects the oxygen levels in the prefrontal cortex and provides values for oxy-hemoglobin and deoxygenated hemoglobin in real-time. It provides a continuous and real-time display of the oxygen changes as the subject performs different tasks.

fNIR
Brain measurement
fNIR Signals