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Rushi Acharya
Masters Student,
Louisiana Tech University

FRACTINATION OF REACTION TIME INTO CENTRAL AND PERIPHERAL COMPONENTS FOLLOWING AUDIO CUES
R.Acharya, W.Besio (Department of Biomedical Engineering, Louisiana Tech University-Ruston, LA, USA)

Rationale: To investigate fractionating reaction time into central and peripheral nervous system components. Methodology: Ten healthy volunteers sat relaxed with their eyes closed. Tripolar concentric ring electrodes were used to record auditory evoked potentials (AEP), motion related potentials (MRP) and electromyogram (EMG). Subjects pressed a micro-switch paced by audio cues. AEP was recorded from the mastoid process. EMG was recorded from the first dorsal interosseus muscle of the right hand. MRPs generated by index finger movements were recorded from the scalp at three locations, C3, 2.0 cm anterior and posterior to C3. The signals were preprocessed with a custom low-noise preamplifier and ensemble averaged. Results / Discussion: There was a latency of 250~300ms on average observed from the audio cue to the micro-switch pressing. A prominent negative peak in the AEP that is generated in the auditory thalamus and primary auditory cortex generally occurred 30 ms after the cue. The EMG activity initiated from 70~90 ms prior to the micro- switch pressing. With approximately 20 ms for motor conduction, this leads us to the conclusion that the CNS takes approximately 160~190 ms for processing the audio cues. The response took 130~160 ms.

Bio: Rushi Acharya graduated from Nirma University, Gujarat, India in June 2004 with a Bachelor of Engineering “First Class” with concentration in Instrumentation & Control. Since Fall 2004 he’s been engaged in his masters studies in the Biomedical Engineering Department of Louisiana Tech University under the guidance of Dr. Walter Besio. He is currently investigating latencies of the brain using Laplacian electroencephalography.

Walter G. Besio, Ph.D.
Assistant Professor,
Biomedical Engineering Dept.,
Louisiana Tech University

Bio
Walter G. Besio received the B.S.E.E. degree from the University of Central Florida, Orlando, in 1993, and the M.S. and Ph.D. degrees in biomedical engineering from the University of Miami, Coral Gables, FL, in 1997 and 2002, respectively. From fall 2002 to present, he has been an Assistant Professor in the Biomedical Engineering Department, Louisiana Tech University, Ruston, Louisiana. Prior to joining academia, he worked in the medical device and electronics industries for more than 12 years. His major research interests include neuro-stimulation, neuro-interfaces, Laplacian EEG and ECG, biosignal detection and processing, and source localization.

Feasibility Of Extending Life Of Rats With Pilocarpine Induced Status Epilepticus Via Non-invasive Transcutaneous Electrical Stimulation
W. Besio1, K. Koka1, and F. Zhu
Department of Biomedical Engineering, Louisiana Tech University-Ruston, LA

Rationale: The objective of this research was to determine the feasibility of transcutaneous electrical stimulation (TcES) via concentric ring electrodes for extending the life of rats with pilocarpine induced status epilepticus (SE). Methods: Male Sprague-Dawley rats weighing 290-330gms were briefly anesthetized, shaved and concentric ring electrodes were attached to their scalp one day before the experiment. Scopolamine (2 mg/kg i.p.) was given 30 minutes prior to pilocarpine. Pilocarpine (310mg/kg i.p) was given to cause long lasting SE. Laplacian EEG was recorded. TcES was applied 5 minutes after the onset of SE.
Results: In the control group (n=8), the rats followed the classic electrographic stages described by Treimen (1987) expiring on average 15 hours after the pilocarpine injection. The TcES treated rats (n=8) lived significantly longer (p=0.019, ANOVA) on average 48 hours.
Conclusions: The application of TcES extended the life of rats with pilocarpine induced SE. TcES treated rats were euthanized prematurely otherwise they could have lived much longer. All of the TcES treated rats recovered to baseline activity eating and drinking except two, who died prematurely from respiratory problems that they experienced prior to TcES. In contrast, none of the control group rats ate or drank after they entered SE.

Larry J. Cauller, Ph.D.
Associate Professor
School of Behavioral & Brain Sciences,
The University of Texas at Dallas

Work in our laboratory has concentrated upon the structure and function of the cerebral cortex and its role in the emergence of higher functions such as perception and interactive behavior. We have traced the circuits in cortex that interconnect the areas of cortex which are essential for conscious behavior and we have developed new ways to study the functions of these synaptic interconnections. We have integrated our findings in the form of large-scale computer models of cortical interactions so we may examine its development over long periods within nurturing environments. This work has culminated in a new theory of cortical 'neurointeractivity' which attempts to explain the emergence of higher cortical functions on the basis of the dynamical interaction between cortical neurons, between cortical areas, between the cortex and the environment, and ultimately between the cortical brains of interacting individuals. This new theory views perception as a pro-active behavior; subjective experience is created by the cortex; the senses are only used to test the validity of one's subjective model of reality.

http://bbs.utdallas.edu/staff_faculty/faculty/cauller.html

Title: Neuro-Micro-Transponders Can Solve a DARPA-Hard Problem: UTD is a Catalyst for NeuroEngineering Synergy with Industry and Medicine.
Larry Cauller (UTD)

Abstract: From its roots with Texas Instruments, growth at UTD has been intertwined with the growth of local high-tech industries, especially in Engineering where faculty commonly work side-by-side with corporate researchers.  Our neuro-micro-transponder (NeuT) is a synthesis of nano-material, micro-electronic, micro-fabrication and wireless technologies with a host of biomedical applications that illustrates the sort of far-reaching innovation made possible by this cross-fertilization at UTD. An award from UTD supported my direct collaboration with engineers at Zyvex, a local high-tech company, which has been instrumental for the development of the NeuT concept into a proposal for further funding and a patent, which we share. The NeuT is designed to wirelessly transmit neural signals out of the body without implanted batteries or other components that may fail or be a risk of toxicity or infection.  We believe the extreme simplicity of the NeuT design will permit micro-fabrication of devices as small as 0.1mm in diameter, small enough to pass through a hypodermic needle. Such ‘minimally invasive’ NeuTs will provide a medically superior alternative as a direct interface between the nervous system and machines that may assist, restore or enhance human abilities. We are developing NeuTs that can interface with the nerves in the shoulder to control the movements of artificial arms and hands as part of DARPA’s commitment to restore the natural abilities of our nation’s heroes who have sacrificed their arms in combat.

J.C. Chiao, Ph.D.
Associate Professor,
Electrical Engineering,
University of Texas at Arlington

Integrative wireless sensor and stimulator for neuronal activity study
T. Ativanichayaphong, J. He, Y.B. Peng, H. Stephanou and J.-C. Chiao
University of Texas at Arlington

Abstract: We have developed an integrative sensor and stimulator system (ISSS) consisting of miniature wireless neuronal signal sensor and neurostimulator to investigate the inhibitory effects of the spinal cord dorsal horn neuronal activity with the motor cortex stimulation. A wearable prototype with off-the-shelf circuit components was developed consisting of an amplifier and a 914-MHz transmitter module for sensing, and a 433-MHz receiver module with a microcontroller remotely controlled by a Labview program in a desktop computer to generate desired stimulating pulses. The wireless modules allow simultaneous recording and stimulating. In our study, lumbar spinal cord dorsal horn neurons were recorded in responses to peripheral mechanical stimulation on anesthetized rats, while stimulation at the motor cortex delivered at various combinations of electrical parameters. The results showed reduction of neuronal responses when electrical pulses were applied during mechanical stimuli. This project is supported by the NSF, ECS Division, IHCS Program, Grant #ECS-0601229.

Bio: J.C. Chiao received his Ph.D. degree at the California Institute of Technology in 1995. He served as a Research Scientist at Bell Communications Research, an Assistant Professor at the University of Hawaii - Manoa and a Product Line Manager and Senior Technology Advisor with the Chorum Technologies before joined the Department of Electrical Engineering, University of Texas at Arlington in 2002 as an Associate Professor. Dr. Chiao has published 99 technical journal and conference papers. He is the editor for the SPIE proceedings "Device and Process Technologies for MEMS and Microelectronics" and "Smart Sensors, Actuators, and MEMS". He holds 3 patents in RF MEMS, MEMS optical and liquid crystal technologies.

Jerry Chao
Graduate student,
Electrical Engineering Dept.,
University of Texas at Dallas

DESIGN AND APPLICATION OF THE MICROSCOPY IMAGE ANALYSIS TOOL – SOFTWARE FOR MEMORY-EFFICIENT PROCESSING AND SPACE-SAVING STORAGE OF LARGE SETS OF IMAGE DATA
Jerry Chao, Palmer Long, E. Sally Ward, Raimund J. Ober

Abstract: Advancements in microscopy instrumentation have resulted in larger volumes of acquired image data and, consequently, increased memory and space requirements for the processing and storage of the data. To address the issue in software, the Microscopy Image Analysis Tool (MIATool) was created to support processing of large image sets that makes efficient use of available resources. Implemented in MATLAB using object-oriented design, MIATool works with image pointer arrays to utilize RAM effectively and to support the analysis of different interpretations of data. Furthermore, the software provides image editing tools which operate on parameter objects that are saved in lieu of processed images to exploit the available disk space. MIATool also provides storage management of image data and processing results and is designed to be expandable such that new image processing and analysis capabilities can be incorporated with relative ease.

This work was supported in part by NIH grants RO1 GM071048, RO1 AI050747, and RO1 AI039167.

Bio: Jerry Chao received the B.S. and M.S. degrees in computer science from the University of Texas at Dallas in 2000 and 2002, respectively. From 2003 to 2005 he worked in the Center for Immunology at the University of Texas Southwestern Medical Center at Dallas where he was involved primarily in the design and development of software for data processing and analysis. He is currently a research assistant in the Department of Electrical Engineering at the University of Texas at Dallas.

Ovidiu Daescu, Ph.D.
Assistant Professor
Department of Computer Science
University of Texas at Dallas

Dr. Daescu's research interests are in computational geometry, algorithms, and bio-medical computing. One of the problems he Investigates is that of finding optimal trajectories to target regions In planar and spatial subdivisions, which could find applications in minimally-invasive neurosurgery. For example, in stereotactic brain surgery, probing problems arise in computer/robot-assisted minimally Invasive tumor biopsy and draining fluid from cysts, abscesses, and
cerebral hemorrhages. Together with the students in his lab he has developed theory and a prototype software for finding optimal paths In a general setup, known as the weighted-region model, which can be Instantiated for applications in stereotactic brain surgery, radiation therapy, etc.

http://www.utdallas.edu/~daescu/

Optimal Path Problems with Medical Applications

Abstract: The problem of finding optimal paths in 2-dimensional and 3-dimensional weighted subdivisions has been investigated in the past few years, with interesting theoretical results obtained recently. In medical settings, finding the best direction or path to probe a tumor while minimizing the damage to healthy tissues can be mapped to an optimal path problem in weighted subdivision. For example, in stereotactic brain surgery, probing problems arise in computer/robot-assisted minimally invasive tumor biopsy and draining fluid from cysts and cerebral hemorrhages. In radiation therapy, the regions may represent various organs within the human body. Different organs may have different characteristics. A region containing a tumor may correspond to the target region and should be treated by strong radiation, while healthy organs should suffer minimum exposure to radiation (various organs may have different degrees of tolerance to radiation, as indicated by their weight factors). This talk will address recent results on computing optimal paths in the 2-dimensional case, present the LinkSolver package for finding optimal paths, and outline main directions for addressing the 3-dimensional case.

Donald K. Eddington, Ph.D.
Principal Research Scientist,
Research Laboratory of Electronics,
Massachusetts Institute of Technology
Dept. of Otology and Laryngology,
Harvard Medical School

Dr. Eddington investigates and develops cochlear implants for use as auditory prostheses. Stimulating electrodes are implanted in or around the cochlea as a means to provide a measure of hearing to the profoundly deaf. The research aims to achieve an understanding of the mechanisms of neural activity provoked by electrical stimulation and to use this understanding to develop practically useful auditory prostheses.

http://www.rle.mit.edu/rleonline/people/DonaldK.Eddington.html

Changes in Brain Function Driven by Changes in Electrically-Elicited Patterns of Spike Activity
Donald K. Eddington1,2,3,  Becky Poon1 and Victor Noel2
1Massachusetts Institute of Technology, Cambridge, MA USA
2Massachusetts Eye and Ear Infirmary, Boston, MA,   USA
3Harvard Medical School, Boston, MA, USA

Whether one is engineering a neural prosthesis designed to transfer information into the brain (e.g., auditory, visual, vestibular or olfactory prostheses) or from the brain (e.g., limb or voice prostheses), the brain’s plasticity is a characteristic that should influence the design strategy, the approach to evaluating devices and the population in which they are introduced.

Two examples will be presented that illustrate changes in brain function in response to changes in the electrically-elicited spike activity on the auditory nerves of five deaf adult human subjects with cochlear implants who heard normally early in life and became deaf as adults.  Each subject used a monolateral implant for at least six months before implantation of their second ear.

Measures of fusion and of localization were made before and after the introduction of bilateral stimulation.  Results show substantial changes with bilateral experience that suggest alteration of brain function leading to fundamental changes in the perception of bilateral stimuli. This means it is possible that monolateral implantation of a very young child may constrain his/her brain’s ability to develop the machinery to take advantage of bilateral stimulation when introduced later in life.

Support provided by the NIH-NIDCD, the Keck Foundation and Advanced Bionics a Boston Scientific Corp.

Charles Finley, PhD
University of North Carolina at Chapel Hill
Depts. of Otolaryngology and Biomedical Engineering

Peripheral physio-anatomical factors influence cochlear implant outcomes

Charles Finley, University of North Carolina at Chapel Hill, USA Laura Holden, Tim Holden, Bruce Whiting and Margo Skinner, Washington University, St. Louis, USA

Because large variation in outcome is observed across patients with the same cochlear implant system, yet mean performance levels across different devices are highly similar, we hypothesize that patient-dependent factors play a significant role in determining outcome in individual cochlear implant patients. We further hypothesize that outcome performance may be improved by addressing such factors in processor fitting. Fourteen subjects implanted with the Clarion C-II or 90K implant systems have been examined using high-resolution CT imaging and recording of intracochlear evoked potentials (IEP) and electrical artifacts (EA). All subjects had “normal” insertions and spanned a wide range of CNC outcomes. Measures of loudness growth, tonotopic electrode discrimination, and CNC speech reception were also made. Based on the combined imaging, electrophysiological and psychophysical results ad hoc changes were made in processor maps to minimize perceptual errors in information representation based on a vocoder model of speech processing. Significant variation in electrode insertion depth, medio-lateral placement and scala tympani/vestibule placement were observed. In addition, wide variation in IEP magnitude and spatial distribution of IEP and EA were observed. Simple manipulations of removing electrodes from the map, adjusting individual channel maps, and reducing rate of stimulation resulted in significant improvement in lower- and mid-performing subjects. Work supported by R21 DC006665-01 (Finley) and R01 DC000581 (Skinner) from NIH-NIDCD.

Gregory J. Gerling
Department of Systems and Information Engineering
University of Virginia
 

Title: Fingertip skin microstructures impact the neural encoding of touch

Abstract
One vital way that we interact with our environment is through our sense of touch. People rely upon tactile sensation to estimate stimulus movement, slip, vibration, and surface form. The skin plays a role in conditioning mechanical indentation into distributions of stress and strain, which underlying mechanoreceptors convert into neural signals. Understanding the creation of these signals may be directly tied to the capabilities and limitations of our touch perception.  In this talk, we look at how fingertip skin microstructures affect tactile sensation. Solid mechanics models are used to analyze how particular skin microstructures, nearby the slowly adapting type I (SAI) tactile receptors, affect the conversion of edge indentation into coded, neural signals. Results help better explain the SA-I receptors’ neural response and physiological position and may inform the design of electro-mechanical sensors that could interface with the neural system. Emerging from this work is a speculative but intriguing new model of the interaction of skin microstructures with SAI receptors: the lens analogy. This analogy suggests that fingerpad skin microstructure may serve to focus stress/strain to the SA-I receptors just as a convex lens serves to focus light to a point.  

Bio
Greg Gerling joined the Department of Systems and Information Engineering in the fall of 2005. He received his PhD from the University of Iowa, Department of Mechanical and Industrial Engineering in the summer of 2005. Greg's major research interests include haptics, human factors/ergonomics, computational neuroscience, and human- & brain-machine interaction. The application of his research seeks to advance neural prosthetics/robotics, to aid people whose sense of touch is deteriorating, and to improve human-robot interfaces.

Maysam Ghovanloo, PhD
Assistant Professor,
Electrical and Computer Engineering,
NC Statue University

Development of a switched-capacitor based neurostimulating system for low-power head-mounted deep brain stimulators

Abstract: Deep Brain Stimulation (DBS) is a novel, highly effective therapy which has revolutionized the management of a number of neurological movement disorders. The therapy involves implantation of small electrodes in deep brain structures, connected to a pulse generator, which is currently so bulky that should to be implanted in the upper chest wall and wired subcutaneously to the electrode contacts emerging from the top of the head. According to several studies the subcutaneous extension wires and their connectors are a source of morbidity for patients and the primary cause of mechanical failure in DBS implants. In this talk we present the latest results of our research on developing a significantly smaller, more efficient, integrated microstimulator that can be practically attached to the head at the point of electrode entry to the brain. Existing DBS circuits, inherited from pre-existing cardiac pacing technology, only generate square-shaped pulses and control the stimulus pulse width, frequency, and either voltage or current amplitude. Voltage-controlled stimulation (VCS) provides great power-efficiency but it can only be used when the electrode and tissue impedances are well known. Current-controlled stimulation (CCS) is safer and provides more control over the stimulus parameters, but it consumes more power. We have designed a novel switched-capacitor based stimulation (SCS) circuitry that directly controls the amount of injected charge into the neural tissue. This is accomplished by generating charge-controlled, exponentially decaying bursts of stimulus pulses. The SCS circuit combines the power efficiency of the VCS circuits with the safety and stimulation parameter controllability of the CCS circuits. This innovative technique is expected to substantially simplify the pulse generator architecture and reduce its size and power requirements.

Bio: Maysam Ghovanloo received his B.Sc. in electrical engineering from the University of Tehran, Tehran, Iran in 1994. He received M.S. in biomedical engineering from Amirkabir Institute of Technology, Tehran, Iran in 1997. From 1994 to 1998 he worked at the Industrial Development for Electronic Application Inc., where he participated in the design and development of a modular patient care monitoring system. In December 1998 he founded Sabz Negar Rayaneh Co. Ltd., developing physiology and pharmacology lab equipments. During summer-2002 he was with the Advanced Bionics Inc. working on a spinal-cord stimulator. He received M.S. and Ph.D. from the University of Michigan in electrical engineering in 2003 and 2004, respectively. He joined the faculty of NC State University in August 2004, where he is currently an assistant professor at the department of Electrical and Computer Engineering. He is a member of Tau Beta Pi, Sigma Xi, and IEEE Solid-State Circuits, Circuits and Systems, and Engineering in Medicine and Biology societies.

http://www4.ncsu.edu/~mghovan
http://www.ncbionic.org

Stefanie J. Hallman
BS/MS student,
School of Biomedical Engineering Science & Health Systems,
Drexel University

Nanostructured Porous Silicon Scaffolds and Augmented Surface Coatings for Enhanced Biocompatibility of Multichannel Microelectrodes
Author(S) and affiliations: Stefanie J. Hallman, Kenneth Barbee, and Karen A. Moxon.

Abstract: Many different types of microelectrodes have been developed for use as a direct Brain-Machine Interface (BMI) to chronically record single neuron action potentials from ensembles of neurons. Unfortunately, the recordings from these microelectrode devices are not consistent and often last for only a few weeks. For most microelectrode types, the loss of these recordings is not due to failure of the electrodes but most likely due to damage to surrounding tissue that results in the formation of non-conductive glial-scar. In conjunction with developing nanostructured electrode surfaces to mimic the extracellular environment, we have also begun to study the effects of surface coatings such as laminin, Poloxamer and Neural Growth Factor (NGF) to understand how these compounds affect neural survival and glial cell proliferation around microelectrode. Preliminary data show that Poloxamer has a positive effect on neuronal survival and is successful in decreasing the proliferation of glial cells, as well as resulting in less hypertrophied astrocytic cell bodies. Further studies will include comparing the affects of Poloxamer and NGF to control coatings as well as the affects of laminin coating on the biocompatibility of the inserted electrode tip. In the long term, we hope that a combination of nanostructured electrode surfaces and surface coatings will lead to a sustainable chronically implantable electrode that can record from every recording site indefinitely. Acknowledgements: This work was supported in part by NIH SBIR grants (1R43MH071029-01 and 1R43 NS41690-01A1) and DARPA contract (N6600103C8035). Index Terms – porous silicon, chronic recording, rat, brain, single neuron action potential, multineuron recording, nanotechnology

Bio: Stefanie Hallman is a BS/MS student in the School of Biomedical Engineering Science and Health Systems, Drexel University. Dr. Barbee is an Associate Professor in the School of Biomedical Engineering Science and Health Systems, Drexel University and the Department of Mechanical Engineering, Drexel University. Dr. Moxon is an Associate Professor in the School of Biomedical Engineering Science and Health Systems, Drexel University, the Department of Electrical and Computer Engineering, Drexel University, and the Department of Neurobiology and Anatomy, Drexel University College of Medicine.

Gemunu S. Happawana, Ph.D.
Assistant Professor,
Southern Methodist University

Gemunu S. Happawana received a B.S. degree in mathematics (honors) from the University of Colombo, Colombo, Sri Lanka, in 1984, and an M.S. in mathematics and Ph.D in mechanical engineering from Purdue University, West Lafayette, IN, in 1988 and 1994, respectively. He is an Assistant Professor in the Department of Mechanical Engineering, Southern Methodist University (SMU), Dallas, TX. From 1989 to 1994 at Purdue University, his research focused on modeling, stability analysis, and control of gas turbine engines, including vibration effects in mistimed linear and cyclic propulsion systems, while working as a research assistant. Since 1995, he has been working in dynamical modeling, analysis, and design of multiwheel drive vehicle, and robust multivariable control of nonlinear systems. He is also working in the opto-electronic packaging area of thermal, mechanical, and optical design. He has published more than 40 journal and conference papers.

Development of high yielding therapeutic system for photodynamic therapy of esophageal carcinomas

Amaranath Premasiri, Graduate student
Department of Mechanical Engineering, Southern Methodist University, Dallas, TX

Gemunu Happawana, Assistant Professor
Department of Mechanical Engineering, Southern Methodist University, Dallas, TX

Abstract
Clinical details have shown that the efficient photodynamic therapeutic system can cure ~87% of the esophageal carcinomas which accounts for ~6% of cancer deaths in United States. Proper Combination of photosensitizing agent, oxygen, and a specific wavelength of light to activate the photosynthesizing agents is necessary for the cytotoxic destruction of cancerous cells by PDT. In this study it is shown that a semiconductor laser based light delivery system with direct de-ionized (DI) water cooling provides required quantity of light to the tumor. Further, a microwave antenna imprinted on the balloon catheter provides local heating of esophagus leading to an increase in oxygen availability to the tumor to generate effective levels of singlet oxygen for cellular death. Finite element modeling of different cooling methods for semiconductor lasers shows that the direct DI water cooling is more efficient compared to conventional cooling methods.  Microwave heating of esophagus is modeled with modified Penns bioheat equation. The Green Function is used to show the intensity of heating required to yield the blood flow and oxygen content to continue PDT without interruption. Based on these results, a microwave antenna system is designed to incorporate into the balloon catheter.

Jeffrey L. Hendricks
Ph.D. candidate,
Biomedical Engineering,
University of MIchigan

Soft conducting polymer electrode coatings for enhanced neural communication Jeffrey L. Hendricks, Sarah Richardson-Burns and David C. Martin
University of Michigan

Abstract
Interactions at the tissue-electrode interface plays a crucial role in the reliability, safety, and efficacy of implanted bio-electrical devices. Implanted devices in the human body including cardiac pacemakers, cochlear implants, cortical recording electrodes, deep brain stimulators, retinal prosthetics, and glucose sensors have varied performance due to the local reactive tissue response at the electrode sites. Cochlear implants operate unreliably and require frequent readjustments due to poor tissue-electrode integration. Improvements in the direct integration of cochlear stimulating electrodes and target neurons would improve device reliability, longevity, and tonal resolution. Polymeric coatings were developed to improve the performance and integration of metallic cochlear electrodes with spiral ganglion neurons. Conducting polymers and hydrogels form the bioactive electrode coatings. The fuzzy surface of the conducting polymer poly(3,4-ethylene dioxythiophene) (PEDOT) helps to reduce the impedance of the electrode, while alginate hydrogels serves as a non-fouling coating and as a scaffold for the delivery of neurotrophic factors and anti-inflammatory agents. The soft coatings can improve electrical performance and biological integration of cochlear electrodes and a wide range of other implanted devices.

Bio: Jeffrey L. Hendricks is a doctoral candidate in Biomedical Engineering at the University of Michigan in Ann Arbor .  He joined Dr. David C. Martin's lab in 2002 and received his MS in 2004.  His research interests include developing bioactive polymeric biomaterials and studying the tissue-electrode interface.  He has trained in materials science & engineering research at Lawrence Berkeley National Lab and at Cornell University ..  He has experience at a biomedical device startup in the materials and mechanical engineer group at NeuroPace, Inc.  In his free time he enjoys photography, snowboarding, and performing experiments in his kitchen.

Wenchuang (Walter) Hu, Ph.D.
Assistant Professor,
Dept. of Electrical Engineering,
University of Texas at Dallas

Title: 3D nanostructured testbeds for analysis and manipulation of cells and biospecies
Authors: Walter Hu, Li Tao, and Brandon Jarvis Department of Electrical Engineering The University of Texas at Dallas, Richardson, TX 75083

Abstract: Nanoimprint lithography and semiconductor manufacturing technologies are employed to build 3D nanostructures on tissue culture polystyrene plates to mimic natural collagen fibers. Compared to randomly distributed collagen, imprinted nanoscaffolds are highly ordered and show significant effects on the alignment/elongation and spreading behaviors of smooth muscle cells. Neurons will be studied on these biomimetic nanoscaffolds for the regeneration of nerve tissues. The platform is ideal for the study of basic science of cell-substratum interactions at the nanoscale, which is essential to design advanced devices or systems which interface cells. We are also developing a testbed with a computer addressable micro-electrode array to sense, analyze, and manipulate biospecies (protein, drugs, wrapped carbon nanotubes, nanoparticles, etc.) inside or outside cells via electric or magnetic field forces upon them and nanofluidic phenomena to guide these nanomaterials to specific cellular locations, where they can be used to unload drugs or monitor the cellular machinery using quantum-dots conjugated to these materials.

Bio: Walter (Wenchuang) Hu received the BS in electronics from the Peking University, Beijing, China, in 1999 and the MSEE from the University of Notre Dame, Indiana, in 2001. He received Ph.D. from the University of Notre Dame in 2004. Then Dr. Hu spent a year as a post-doctoral research fellow at the Solid State Electronics Laboratory, Department of Electrical Engineering and Computer Science, University of Michigan, Ann Arbor, Michigan. In September 2005, Dr. Hu joined the University of Texas at Dallas, Richardson, TX, as assistant professor in the Department of Electrical Engineering. His research interests include lithographic nanofabrication technologies and applications in biomedical devices, bio-MEMS, nanoelectronics, tissue engineering, molecular electronics, and photonic devices. Dr. Hu is an active member of Sigma Xi, IEEE, SPIE, American Vacuum Society.

Pedro P. Irazoqui, Ph.D.
Assistant Professor
Weldon School of Biomedical Engineering
Purdue University

Clinical Neural Prosthetic Devices for Epilepsy and Spinal-Cord Injury Repair

Abstract
Telemetry, power, and control modules, are designed with appropriate biological sensing and stimulating capabilities, on application-specific integrated circuits (ASICs). The ASICs are mounted on microstrip boards, with patch antennas, and neural electrodes. These assemblies are packaged using bio-compatible ceramics, to form miniature, wireless, implantable devices. The devices described, interface the brain with external real-time DSP computers, providing closed-loop clinical treatment of neural pathologies. Epilepsy, and spinal-cord injury are of particular interest. Current designs enable simultaneous telemetry with 256 devices, each with up to 64 recording or stimulating circuits. These circuits can be allocated to individual electrode sites on the fly. Each sensor has selectable gain and filtering. Each stimulator has an adjustable triphasic waveform with 19-bit amplitude, frequency, and duty-cycle resolution.We are using these designs, in conjunction with real-time seizure prediction capability, to elicit a carefully calibrated neural response leading to seizure suppression. Our other thrust builds on promising Phase I clinical trial results showing that implanted oscillating field stimulators lead to functional recovery following spinal-cord injury. We hypothesize that the continuous closed-loop monitoring and control of induced electrical fields provided by our devices, will improve the therapeutic efficacy of Oscillating Field Stimulators.

Bio
Dr. Irazoqui received his B.Sc. and M.Sc. degrees in Electrical Engineering from the University of New Hampshire, Durham in 1997 and 1999 respectively, and the Ph.D. in Neuroengineering from the University of California at Los Angeles in 2003 for work on the design, manufacture, and packaging, of implantable integrated-circuits for wireless neural recording. Together with three partners, he then helped found and was vice- president of IC development at Triangle Biosystems Inc., Research Triangle Park, NC. Currently he is an assistant professor in the Weldon School of Biomedical Engineering at Purdue University, where his lab is pursuing research into a modular approach to the design of biological implants in general and neural prosthetic devices in particular. These systems are being applied to the clinical treatment of neural disorders, using miniature, wireless, implantable devices. Specific research and clinical applications explored in his lab include: epilepsy and spinal-cord regeneration.

Vikram Jakkamsetti
Ph.D. Candidate,
University of Texas at Dallas

Bio: Vikram Jakkamsetti is a graduate student in the lab of Michael Kilgard at the University of Texas at Dallas. He received his M.D. (Internal Medicine) in April 2002 from South Gujarat University, Surat, India. He hopes to explore neuronal plasticity as a therapeutic tool for neuro-rehabilitation.

Rolipram causes frequency specific map plasticity : Potential method for neuro-rehabilitation
Author Block: V. Jakkamsetti, R. Jain, K.Q. Chang, R. J. Nance, J. G.
Kalangara, M. P. Kilgard.

Abstract: Input-specific reorganization of primary auditory cortex (A1) can occur with daily episodic activation of nucleus basalis paired with tonal stimuli (Kilgard & Merzenich, 1998). We are currently engaged in a series of experiments to identify pharmacological agents that effectively stimulate input-specific cortical plasticity.After just 20 days of exposure to a 4khz tone under the influence of Rolipram, a phosphodiesterase inhibitor, standard microelectrode mapping techniques were used to obtain responses from such animals and were subsequently compared to naive control animals. Our preliminary findings include: 1) Rolipram causes an increase in the percent of A1 neurons that respond to 2-4khz tones. 2) There is an increase in response strength of A1 neurons to the 2-4khz tones 3) Rolipram accelerates plasticity of A1 to long term tone exposure by increasing thresholds, increasing bandwidths, and increasing latencies for low frequency neurons. These findings provide support for the hypothesis that pharmacological manipulations combined with sensory exposure could be an effective tool in directing cortical plasticity for therapeutic benefit.

Danielle M. Kerkovich, Ph.D.
Assistant Director of VA Rehabilitation
Research and Development,
Department of Veteran Affairs
810 Vernon Ave. NW, MC-122P
Washington, DC 10402

Dr. Kerkovich oversees Veterans Administration research in Neuroengineering, especially as related to neuro prosthetics.  She has written extensively in the area of spinal core medicine.

http://www1.va.gov/RESDEV/news/features/prosthetics.cfm
http://www.prosthetics-research.info/prosthetic-center.htm

David B. Khatami
Ph.D. Candidate,
University of Illinois at Urbana-Champaign

Tools for Automated Stimulation and Connectivity Analysis of Neuronal Networks Grown on Multielectrode Arrays
David B. Khatami, Yoonkey Nam, Bruce C. Wheeler

Abstract: Although neural networks grown on top of microelectrode arrays appear to provide a great and powerful tool for the study of neuronal plasticity and mechanisms for learning and memory, the progress in this area has not been as rapid and earth shattering as one would have hoped. Apart from the profound complexity and huge variability whch is inherent in such network, the lack of proper technological capacities has proved to be a hinderance. One such shortcoming is a lack of automated and dynamic stimulation capability; another is lack of a visually appealing software interface for automatically processing the massive amounts of data generated thus providing quick feedback to the researcher. The aim of this paper is to propose a simple scheme which can be employed on top of exisiting commercially available devices in an effort to address both issues.

Bio: David Khatami received his B.S. in Electrical Engineering from Norwich University, Northfield, VT, in 2000. He then received an M.S. degree in Computer Science and another in Electrical Engineering from the University of Illinois at Urbana-Champaign, Urbana, IL, in 2002 and 2004 respectively. He subsequently joined the combined M.D./Ph.D. program at Illinois where he is currently working on his dissertation in Electrical Engineering while taking classes at the College of Medicine. David’s major research interests include Neuroscience and Neural Engineering. In particular, he is interested in neuronal modeling of learning and memory, cell-patterning, electrical stimulation and recording from dissociated cultures, neural prostheses, as well as, information processing within the CNS.

Daryl R. Kipke, PhD.
Associate Professor
Department of Biomedical Engineering
University of Michigan
Ann Arbor, MI

Bio
Daryl R. Kipke received the Ph.D. degree in Bioengineering in 1991 from the University of Michigan, Ann Arbor, Michigan.  From 1991 to 1992, he was a Research Associate in the Department of Bioengineering and the Institute for Sensory Research at Syracuse University, Syracuse, New York.  In 1992, he was appointed to the Bioengineering faculty at Arizona State University, Tempe, Arizona. In 2001, he returned to the University of Michigan where he is currently an Associate Professor in the Department of Biomedical Engineering and the Department of Electrical Engineering and Computer Science. 

Dr. Knipe’s research areas include:
Biomaterials and BioMEMS technologies for minimally-invasive neurosurgery; Biosensors for long-term brain implants;
Neural prostheses;
and Cerebral cortex function and plascicity. 

http://www-personal.engin.umich.edu/~dkipke/vitaes.htm
http://www.umich.edu/~neurosci/faculty/dkipke.htm

Advanced implantable microscale neural interface devices
Daryl R. Kipke (dkipke@umich.edu)

Abstract
Our group is developing microscale neural probes for combined electrical and chemical interfaces to selective areas of the brain, spinal cord, and peripheral nervous system.  Our long-term goal is to develop implantable devices for chronic sensing and actuation in both the electrical and chemical domains.  We have developed multi-channel implantable microelectrode arrays to reliably stimulate and/or record from populations of neurons for long periods of time.  While we have established baseline chronic performance benchmarks, long-term reliability and sensitivity remain issues as we work towards neural implants that remain functional for years.  We are developing methods to monitor and minimize the chronic tissue reactions to the implanted device.  We are also developing devices for precise chemical delivery and sensing.  These advances in microscale technologies enable translational research and development of innovative clinical neural interface devices directed at diagnostic and therapeutic applications in neuroprosthetics and neurosurgery.

Col. Geoffrey Ling, M.D., Ph.D.
Defense Advanced Research Projects Agency (DARPA)

Col. Ling is the Project Manager for the Human-Assisted Neural Devices (HAND) Program, which is developing the fundamental research basis to enable the use of brain activity to provide closed loop (motor commands out, sensor feedback in) for prosthetic devices. Additional technical challenges include methods for non-invasive sensors of brain activity and approaches for inputting sensory feedback into the nervous system. This program will also include new methods, processes, and instrumentation for accessing neural codes either through peripheral nerves or non-invasively at appropriate spatiotemporal resolution. Other aspects of the program examine memory storage as a means for improving learning and training. This fundamental research effort has formed the basis for establishing a new program in Revolutionizing Prosthetics that will incorporate advanced materials, actuation, and a power concept with neural control and sensory feedback to create a dramatically improved artificial limb for military amputees.

http://www.darpa.mil/DSO/personnel/ling.htm http://www.darpa.mil/DSO/thrust/biosci/hand.htm http://www.darpa.mil/DSO/thrust/biosci/revprost.htm

Philip Loizou, Ph.D.
Professor
Department of Electrical Engineering
University of Texas at Dallas

There has been a radical change in the way people communicate today. There exist many options for communicating or transmitting information over the wired network, including voice mail, beeper services, ISDN video, FAX, audio and video teleconferencing, etc. One of the main technologies that made this possible, is the speech processing technology, which includes speech compression (compression of the signal for transmission though limited-bandwidth channels), and speech recognition (recognition of voice input by the machine). Dr. Loizou has been involved in several projects related to speech compression, speech recognition, and speech enhancement.

Development of a PDA research platform for cochlear implants
Philip Loizou, Arthur Lobo, Nasser Kehtarnavaz, Murat Torlak, Hoi Lee, Anu Sharma and Phillip Gilley, University of Texas-Dallas

Abstract: Having access to a flexible research platform is critical for the advancement of cochlear implants or neural interface devices in general. While most implant manufacturers provide research speech processors which allow researchers to develop and test new signal processing algorithms, most research labs are unable to use them due to limited technical resources. In this talk, I will present our plans to develop a research processor that is portable, so that it allows for realistic assessment of new algorithms after long-term use, flexible so that it allows for quick development and evaluation of new research ideas, and easy to use so that it is accessible to all researchers interested in clinical and animal studies. More specifically, we propose the use of Personal Digital Assistants (PDAs) as research processors for cochlear implants. PDAs nowadays are not only used for managing appointments and contact lists, but are also used as cellphones, GPS devices with access to Internet. Furthermore, PDAs have sufficient computing power for real-time processing of speech signals, and are certainly portable and easy to use. This talk will also cover some of our ongoing efforts to develop noise reduction algorithms for cochlear implants.

For more information about our speech processing research visit our Speech Processing Lab

Jeff K. Longnion, MD.,
Ph.D. Candidate,
University of Washington

A Biophysical Auditory Nerve Model: Towards Improved Assessment of Cochlear Implant Signal Processing Strategies.
Jeff K. Longnion, Jay T. Rubinstein -- University of Washington Departments of Bioengineering and Otolaryngology; Virginia Merril Bloedel -- Hearing Research Center

Abstract:
Appreciation of music and discrimination of speech-in-noise are still limited among cochlear implant (CI) users. However, development of improved stimulation strategies is hindered by the need for a sophisticated understanding of the auditory system, time-consuming clinical trials, and the absence of tests for assessing encoding of temporal information. Previous work with a biophysical auditory nerve fiber model has already proven useful in predicting the probabilistic response to electrical stimuli. Current results reflect efforts to extend this neural model and address other barriers to strategy development. Single fiber and population fiber response characteristics have been matched to feline electrophysiologic data by tuning and updating existing model parameters and creating a population of model fibers according to literature-reported diameter distributions. The resultant population model has been used to simulate the response to speech encoded with existing and proposed strategies. In parallel, we have implemented a psychophysical test of phase sensitivity and measured performance of CI users as well as significant improvement in performance when switching from a pulsatile to analog strategy. Now, efforts are underway to develop predictions of psychophysical performance based on simulated neural output that, in conjunction with actual psychophysical test results, can be used to assess the model’s utility in assessing implant strategies.

Bio
Jeff Longnion received a B.S. in electrical engineering and a B.S. in neurobiology in 2002 from the University of Washington. He is currently in the Medical Scientist Training Program at the University of Washington and has been a Bioengineering PhD candidate in the lab of Dr. Jay T. Rubinstein since June 2005.

Hong Lu
Ph.D. candidate,
University of Texas at Dallas

Bio
Hong Lu has received his B.S. in Electrical Engineering from U.T.Dallas in year 2000. He has worked as a quality/reliability engineer at ST Microelectronics, Carrollton, Texas from 1999 – 2001. In 2001, he joined MiNDS (Micor-Nano Devices and Systems) laboratory at U.T.Dallas under the supervision of Professor J.B Lee. After he received M.S. EE in 2003, he continued his study under Professor J.B Lee and currently he is at the final stage in pursuing Ph.D. His research interests are concentrated in MEMS (Micro Electro Mechanical Systems) device design and fabrication process development, primarily for RF and bio-logical applications.

SU8-Based Micro Neural Probe for Spike Signals Detection from Regenerated Axons
Hong Lu, Sung-Hoon Cho, Lawrence Cauller, Mario Romero-Ortega, Gareth Hughes, and J-B. Lee: Department of Electrical Engineering, University of Texas at Dallas, Richardson, Texas, U.S.A; School of Behavioral and Brain Sciences, University of Texas at Dallas, Richardson, Texas, U.S.A; Texas Scottish Rite Hospital; University of Texas Southwestern Medical Center, Dallas, Texas, U.S.A.; Zyvex Corporation, Richardson, Texas, U.S.A.

Abstract
Neuro prosthesis using micro probes/electrodes has been intensively investigated for in the past three decades. Devices intended for recording or stimulation of the cerebral cortex have been primarily created based on the material of silicon1. Polyimide-based flexible electrodes have also been investigated2. In this work, we present development of a fully biocompatible micro neural probe based on SU8 photo sensitive material. The completed device have been assembled into a fully biodegradable biosynthetic nerve regeneration guide (BNRG) and long term (> 4 months) chronic in-vivo recording of spike signals from regenerated axons from amputated peripheral nerves has been successfully achieved. The probe consists of a pair of surface modified (conductive polymers and carbon nanotubes) gold microelectrodes embedded in SU8 photo sensitive polymer. The microelectrodes are placed in channels to capture a single axon and guide the axon growth to ensure sufficient contact between the axon and the electrodes. In-vitro cytotoxicity tests were carried out using fibroblasts and Schwann cells and the result showed that the probe is biocompatible. Dorsal root ganglion (DRG) was used to evaluate neuronal cell adhesion to the microelectrodes. Several peripheral nerves in a lab rat were amputated and probes were implanted near the amputated nerves in BNRG. Nerves have been regenerated and spike signals from the regenerated axons have been consistently recorded and analyzed for longer than 4 months.

David C. Martin, Ph.D.
Director, Macromolecular Science and Engineering Center
Professor of Materials Science and Engineering
Professor of Biomedical Engineering
The University of Michigan

Dr. Martin’s research interests include high resolution studies of the micromechanisms of deformation and failure in polymer solids, molecular engineering of high-strength polymer fibers, crystal structure and its evolution in polymers, grain boundaries and dislocations in polymer solids, the structure and properties of polymers near surfaces, cubic phases in block copolymers and amphiphilic systems, and the morphology of synthetic poly(peptides) produced by genetic engineering techniques.

Conference Presentation: Direct Integration of Electronic Biomedical Devices with Neurons using Conducting Polymers.

http://msewww.engin.umich.edu/research/groups/martin/
http://msewww.engin.umich.edu/people/faculty/martin

Lee E. Miller, Ph.D.
Associate Professor
Northwestern University

Research
The experiments in my laboratory involve recordings made directly from the brains of experimental animals during behavior. In these experiments, we are able to study not only the intricate circuits comprising real networks of nerves and neurons, but also the signals produced by individual neurons during movement. Much of this work is done in collaboration with students and faculty from the Biomedical Engineering Department, the Institute for Neuroscience (NUIN), and the IGERT funded program in the Dynamics of Complex Systems in Science and Engineering.  The three fundamental goals of my research are the following: 1) To understand the nature of the brain's own signals -- the "language" in which movement command signals are expressed by neurons in the central nervous system. 2) To understand the mechanisms by which these signals are produced -- the connections among networks of neurons, and the transformations that occur in the signals as they propagate throughout these networks. 3) To develop applications of these basic principles that could be of therapeutic value to human patients.

Conference Presentation: EMG prediction and the development of a primate model of cortically controlled FES for grasp.

http://www.physio.northwestern.edu/Secondlevel/Miller/hp.html

Title: EMG prediction and the development of a primate model of cortically controlled FES for grasp.
Eric A. Pohlmeyer, Kevin L. Kilgore, Robert F. Kirsch, Eric J. Perreault, Dawn Taylor, Lee E. Miller (University of Texas at Dallas, Northwestern University, Case Western Reserve University)

Abstract: Recently, our group has begun to test microelectrode recordings from the primary motor cortex (M1) and functional electrical stimulation (FES) of forelimb muscles as a means to restore grasp to paralyzed patients.  FES has great potential in a variety of applications, but controlling the many degrees of freedom of hand movements is well beyond the capability of current FES systems.  Cortical recordings could offer more dexterous and intuitive control.  We have shown that arm and hand muscle activity can be predicted using neuronal activity recorded from multi-electrode arrays chronically implanted in M1.  Predictions accounted for 50-80% of the variance of EMG during reaching and grasping movements. We have also developed a method of reproducibly inducing temporary grasp deficits by chemically blocking the median and ulnar nerves using a subdermal injection port and nerve cuff system.  We can cause the affected muscles to contract by stimulating electrically through percutaneous or chronically implanted muscle electrodes.  Together the EMG predictions, nerve block, and muscle stimulation provide the means to investigate whether cortical muscle predictions can be used to activate muscles in real-time and allow a monkey with a paralyzed arm to form a functional grasp.

Pedram Mohseni, Ph.D.
Assistant Professor
Electrical Engineering and Computer Science Department
Case Western Reserve University

Single-Chip Wireless Microsystems for Multichannel Neural Biopotential Recording

Abstract
Wireless single- and multi-channel telemetric systems have always been of great interest to researchers in the biology and neurophysiology communities due to their advantage of simultaneous recording and transmission of one or more physiological parameters. Although the emergence of high-quality surface-mount electrical components in the past has remarkably facilitated the implementation of such systems, the majority of the current recording devices still have either prohibitively large dimensions and weight, or high power consumption that makes them impractical for general-purpose low-power applications. Combining application-specific integrated circuit (ASIC) design techniques with micromachined biopotential recording electrode technology can significantly reduce the overall dimensions, weight, and power consumption of such systems, offering low-power multichannel radio-frequency recording devices that can be used in closed-loop neural prosthesis to study either the peripheral or central nervous system at the cellular level. This talk will focus on the design, implementation, testing, and performance characterization of wireless FM recording microsystems to remotely monitor input biopotentials recorded by micromachined penetrating silicon-based or nerve-regeneration polyimide-substrate microprobes. The functionality of the fabricated devices in an experimental procedure will be demonstrated via single-channel wireless in vivo recording of spontaneous neural activity in the auditory cortex of awake primates at different transmission ranges up to 0.5m. These devices serve as valuable test vehicles to obtain a fundamental knowledge of numerous limitations and trade-offs involved in the design of wireless integrated recording biomicrosystems.

Bio
Dr. Mohseni's research interests include analog/mixed-signal/RF integrated circuits and microsystems for neural engineering; low-power wireless sensing/actuating systems; biomedical microtelemetry; and assembly/packaging of biomicrosystems. He has authored eight papers in refereed IEEE journals and conferences, and has served as a technical reviewer for the IEEE JOURNAL OF SOLID-STATE CIRCUITS, IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING, IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS, and IEEE SENSORS JOURNAL since 2002. He is a member of the IEEE Solid-State Circuits, the IEEE Circuits & Systems, and the IEEE Engineering in Medicine and Biology societies. He currently serves on the Technical Program Committee (TPC) of the 3rd International Conference on Networked Sensing Systems (INSS’06).

Katherine Musick,
Ph.D. Candidate,
Dept. of Electrical Engineering
Univ. of Illinois at Urbana-Champaign

Bio
Katherine Musick received a B.S. degree in electrical and computer engineering from Valparaiso University, Valparaiso, Indiana, in May 2003, and an M.S. degree in electrical engineering from the University of Illinois at Urbana-Champaign in December 2005. She is presently a Ph.D. candidate in the Department of Electrical and Computer Engineering at the University of Illinois at Urbana-Champaign. Since 2004, she has been a member of Prof. Bruce Wheeler’s research group and has been involved in the fabrication of novel microelectrode arrays.

Three-Dimensional Microelectrode Array for Recording Dissociated Neuronal Cultures
Katherine Musick & Bruce C. Wheeler2 1Electrical and Computer Engineering Department, 2Bioengineering Department, University of Illinois at Urbana-Champaign, Urbana, IL Presently, in vitro studies of neural networks are done with two-dimensional monolayers of cells even though three-dimensional cultures survive longer and are more like in vivo correlates in both structure and response to stimuli than a monolayer. This device, a three-dimensional microelectrode array (3D MEA), aims to address this issue. The 3D MEA is created by fabricating, aligning, and stacking individually patterned thin films. Electrodes and microfluidic channels are created on these films prior to stacking to allow both electrical and fluidic access to the culture. The microfluidics provide an artificial vasculature for nutrient supply and aeration. Dissociated neurons are loaded into the structure via these microfluidics and allowed to extend processes to form intra- and inter-layer connections. The resulting system allows the collective properties of 3D neural networks to be observed and manipulated with unprecedented detail and precision at a level of control not possible in living animals. The poorly understood 3D organization of structures in the brain may be the key to the vast information storage and processing capabilities. This tool will allow further study of this organization.

Dr. Yoonkey Nam, Ph.D.
Post-doctoral research scientist,
The University of Illinois at Urbana-Champaign  

Title: Cellular lithography for the study of neural information processing in geometrically ordered Neuronal Networks in vitro
Yoonkey Nam, David Khatami, Gregory J. Brewer, Bruce C. Wheeler, Department of Bioengineering, University of Illinois, Urbana-Champaign, IL, USA; Department of Electrical and Computer Engineering, University of Illinois, Urbana-Champaign, IL, USA; School of Medicine, Southern Illinois University, Springfield, IL, USA

Abstract: Advances in photolithography, surface chemistry, cell culture techniques, and biosensors make it possible to consider the design of patterned neural networks in culture dishes. Our work demonstrates that we can create micro-patterns of neurons that are alive and functional on top of multielectrode arrays (MEAs). The bases for our advances include: (a) microcontact printing of proteins such that they survive cell culture conditions for up to a month; (b) the faithful compliance of the growing neurons to the underlying protein patterns; (c) microelectrode arrays suitable for stimulation and recording of neurons; (d) advanced cell culture media capable of supporting neurons in culture without use of serum containing media or other supporting cells. The results shows that we can confine neurons to desired patterns for extended periods of time and were able to stimulate and record from those neurons.

Bio: Yoonkey Nam received his BS degree in Electrical Engineering from Seoul National Univeristy, Seoul, Korea, in 1997 and the M.S. and Ph.D degrees in Electrical Engineering from the Univertisy of Illinois at Urbana-Champaign, Urbana, IL, in 2003 and 2005, respectively. From fall 2005 to present, he has been a postdoctoral research associate in the Bioengineering Department at University of Illinois at Urbana-Champaign. His major research interests include BioMEMS, surface micropatterning, cell patterning, neuron-on-a-chip, cell-electrode coupling, and electrical recording and stimulation of cultured neurons.

Aria Nosratinia
Associate Professor,
Department of Electrical Engineering
University of Texas at Dallas

Negar Bazargani
Ph.D.Student,
Department of Electrical Engineering,
University of Texas at Dallas

Richard Briggs
Professor,
Department of Radiology,
University of Texas Southwestern Medical Center at Dallas.

Title: A New Method for Drift Estimation in fMRI
Authors: Aria Nosratinia, Negar Bazargani, Richard Briggs

Abstract: Long term physiological pulsations and instrumental instability cause systematic decrease or increase in the fMRI signal with time. While the exact cause of the baseline drift is still unknown, because of inherently low signal to noise ratio of fMRI data, estimation and removing of the drift has a significant impact on the statistical image analysis and accurate detection of activation. Without removing the baseline drift, analysis methods based on the linear model may confuse large variation in the signal with the effects of the stimulus. Drift terms, if not accounted for, can also pose as additional noise and reduce detection sensitivity. We propose a new method for the estimation of the activation level and the baseline drift in the fMRI signal. Our method is based on the iterative estimation of the activation level and drift component. Using least square estimation and the concept of denoising. Our results show that the proposed algorithm can estimate the drift term without having any prior knowledge or assuming an overly restrictive model.

Bios: Aria Nosratinia is associate professor of Electrical Engineering at the University of Texas at Dallas. He received his Ph.D. in Electrical and Computer Engineering from the University of Illinois at Urbana-Champaign. He was with Princeton University during the academic year 95-96 and a visiting professor and faculty fellow at Rice University 1996-99. During the Spring and Summer of 2006 he is with the electrical engineering department at UCLA. Dr. Nosratinia's interests lie in the broad area of information theory, coding, and signal processing. He received the National Science Foundation career award in January 2000, serves as associate editor for the IEEE Transactions on Image Processing and IEEE Wireless Communications. He is a senior member of IEEE. http://www.utdallas.edu/~aria/

Negar Bazargani received her B.S. and M.S. degrees in biomedical engineering from Amir Kabir University (Tehran Polytechnic), Tehran, Iran, in 2001, and 2004, respectively. She is currently pursuing her Ph.D. degree in the department of electrical engineering at the University of Texas at Dallas. Since 2005, she has been a member of Prof. Nosratinia's research group. Her research interests are in the area of biomedical signal processing and statistical analysis of functional magnetic resonance images of the brain. -

Byron Olson, Ph.D.
Post-doc, Dept. of Electrical Engineering
Arizona State University

Decoding of High Level States for Asynchronous Brain Machine Interfaces    
Byron Olson, Jennie Si, Arizona State University, Dept. of Electrical Engineering

Abstract
Direct brain machine interfaces have developed from humble beginnings into impressive laboratory systems capable of generating elaborate robotic movements. However useful systems will require not only the ability to create such outputs, but also control between active use and non-use. Such asynchronous systems are being actively developed at ASU.  The current discrete directional control system continuously discriminates neural firing patterns into one of four classes (Left, Right, Start, and Idle) using a support vector machine (SVM). Neural signals classified as task related are output to real-world devices. Such a system is functional but results can be improved when the transitions between states are filtered using a state transition model. This hybrid method combines evidence from the SVM model and the probability of a state transition from the current to the next to produce useful, asynchronous outputs.

Bio
Byron Olson received his B.S. in mathematics with honors and distinction from Iowa State in 1999. He received his Ph.D. in bioengineering from Arizona State in 2004. He is currently a post-doc in the department of electrical engineering at ASU.

Kevin J. Otto, Ph.D.
Assistant Professor,
Biological Sciences and Biomedical Engineering
Purdue University

Rejuvenation and Neural Interface Improvement in Bidirectional Neural Prostheses
Kevin J. Otto, Department of Biological Sciences and Biomedical Engineering, Purdue University, West Lafayette, IN

Abstract
One goal of utilizing chronically implanted neural interfaces probes is to record electrical activity in the nervous system in order to enable an output-type neural prosthesis. Another chronic neural interface goal is to electrically stimulate neural tissue in order to provide information to a user of an input-type neural prosthesis. However, the quality of the interface of the chronically implanted probes often degrades over the lifetime of the device, putatively limiting the bandwidth of the information transfer in either direction. We have previously reported a procedure for extending the lifetime of chronically implanted iridium-plated silicon-substrate probes in terms of recording performance. This procedure, hereafter termed ‘rejuvenation’, involves applying a direct-current bias between an electrode site and a distant ground. Here we report current findings on the long-term effect of rejuvenation on the performance of bidirectional neural prostheses.

Bio
Kevin Otto received the B.S. degree in chemical engineering from Colorado State University in 1997, the M.S. degree in bioengineering in 2002 and the Ph.D. Degree in bioengineering in 2003 from Arizona State University, Tempe.
From 1997 to 2003 he was a Research Assistant in the Bioengineering Department, Arizona State University, where his work was in the areas of neural engineering and sensory neuroprostheses.  From 2003 to 2004 he was a Research Fellow in the Department of Biomedical Engineering, University of Michigan, Ann Arbor where his work focused on brain-machine interface systems and implantable devices.  From 2004 to 2006 he was a Post-Doctoral Fellow in the Central Systems Laboratory in the Kresge Hearing Research Institute within the Department of Otolaryngology at the University of Michigan, Ann Arbor.  He is currently at Purdue University as an Assistant Professor of Biological Sciences and Biomedical Engineering.  His research interests include neuroprostheses, systems neuroscience, and neurotechnologies.

Joseph J. Pancrazio, Ph.D.
Program Director,
Extramural Research Program
NIH/NINDS

As Principal Investigator at the US Navel Research Lab (NRL) Center for Bio/Molecular Science and Engineering, Dr. Pancrazio was Head of Code 6920, the Laboratory of Biomolecular Dynamics.  At the NRL, Dr. Pancrazio led an extramurally supported project including biologists and engineers for the development and demonstration of a biosensor system based cultured neuronal networks for environmental threat detection. In addition, he initiated programs in high-performance computational modeling of neuronal networks, microarray-based toxicogenomics, and cellular microarrays for biodetection. Dr. Pancrazio joined the Repair and Plasticity Cluster of NINDS in January of 2004, where his research interests include: 1) neural engineering and neuroprosthesis; 2) novel neural repair technologies and biomaterials, and 3) neural information processing and control.

http://www.ninds.nih.gov/find_people/ninds/pdbio_joseph_pancrazio.htm

Connecting to the Nervous System to Restore Function – NINDS Support

Abstract: The National Institute for Neurological Disorders and Stroke has the mission to relieve the burden of neurological disease. Neural prosthetic devices, which are artificial extensions to the body that restore or supplement function of the nervous system lost during disease or injury, have been a vital and productive component of the NINDS mission. For over 30 years, the NINDS has supported grants and contracts on a number of areas within the neural prosthesis field including: functional neuromuscular stimulation, deep brain stimulation, multielectrode cuffs for nerve interfaces, cortical microelectrode arrays, biocompatibility of neural interfaces, implantable neural stimulators, and brain/computer interfaces. NINDS is particularly interested in seeing the resulting technologies reach translation to the clinical. To this end, the NINDS supports not only academic efforts, but those of the private sector as well. Of particular interest to the mission of the NINDS is the restoration of motor and communicative functions for individuals with spinal cord injuries, Amyotrophic Lateral Sclerosis, and stroke. Among the goals of the NINDS effort is the development of totally implantable systems for restoring the motor control and sensory feedback for a paralyzed individual. Significant progress is being made towards the development of motor prostheses for disabled individuals, particularly for upper limb control. It is anticipated that future efforts will combine subsystems for functional neuromuscular stimulation with neural interfaces that can detect signals in the brain associated with movement, such as implanted microelectrodes regions of the brain essential for mediating motor function. Potential emergent areas that are likely to impact the future of neural prosthetics and deep brain stimulation include nanotechnologies, novel bioactive materials, adaptive computational methods for multi-neuron analysis, and technologies that capture sensory information for more effective control of paralyzed limbs.

Chi-Sang Poon, Ph.D.
Principal Research Scientist
Division of Health Sciences and Technology
Massachusetts Institute of Technology

Presentaton Title
Chaotic brain rhythms: from neuronal bursting to cardiorespiratory variability

Research in Computational and Systems Biology
Research in the Poon lab takes a multidisciplinary approach that combines biology with engineering and computational science to investigate the mechanisms of neural control at both the cellular and systems levels.
Respiratory rhythm
Our work on respiration focuses on mechanisms of control in neural and neuronal plasticity, in which physiological changes during development and in response to environmental stimuli produce adaptive behavior.  This process is sometimes called “brain calculus” because it uses computing blocks that can perform integrated and differentiated processes on a neuronal level to perform high-order calculations.
Cardiovascular rhythm
Another project in the Poon lab studies control mechanisms that are used by the brain to regulate cardiovascular rhythms and maintain blood pressure. We have developed mathematical methods for separating chaos from additive noise, and we are using them to study the chaotic dynamics of the heartbeat.  We hope to apply this approach to develop diagnostic and predictive tools for cardiac malfunction.  

Dr. Curtis W. Ponton, Ph.D.
Chief Scientist, Compumedics Neuroscan
Vice President Compumedics USA

Bio
Dr. Curtis W. Ponton received a Master’s Degree in Clinical Neuropsychology from the University of Western Ontario, in London Canada, and a Ph.D. specializing in Physiological Psychology from the University of Calgary in Calgary, Canada. After completing his graduate work in 1989, Dr. Ponton accepted a post-doctoral fellowship at the House Ear Institute in Los Angeles, California. The post-doc fellowship evolved into a fulltime appointment as a research scientist which he held at House Ear Institute until 2000. At that time, Dr. Ponton accepted a position as Senior Scientist with Neuroscan, a world-wide leader of both hardware and software products for brain imaging research based on EEG and evoked potentials. His primary responsibilities have been to direct R&D activities for both hardware and software groups. In 2005, Dr. Ponton accepted appointments as Chief Scientist for Compumedics Neuroscan and Vice President for Compumedics. Dr. Ponton also holds an adjunct appointment at the University of Texas at El Paso. Dr. Ponton’s research activities have focused on cortical plasticity related to cochlear implant use, simultaneous brain imaging technologies, and most recently brain computer interface systems. Simultaneous EEG/fMRI Acquisition - Imaging Electrical Brain Activity In Hostile Environments

http://www.neuroscan.com

Abstract
Over the past decade, there has been an explosion of studies investigating the neural origins of cognitive behavior using techniques that rely on changes in neural activity, metabolic activity, and blood flow. While electrophysiological measures of cortical function continue to be employed and have added much to our knowledge of cortical function, there is a tendency to view this approach as inferior due to the higher spatial resolution of PET and fMRI. However, compared to electrophysiological measures of brain activity, both PET and fMRI lack sufficient temporal resolution to determine when specific cognitive processes such as language, memory, and attention occur. The timing of such events may be critically important to the successful execution of a particular cognitive activity. Thus, there is now an increased interest, in particular, in simultaneously obtaining fMRI with EEG measures of brain activity. The purpose of this presentation is to review the rationale for simultaneous fMRI / EEG acquisition and to describe, from the EEG point of view, some of the specialized technologies and methods that have been developed to obtain these data. Investigations of spontaneous EEG activity (alpha rhythms), evoked EEG activity (visual evoked potentials) and pathological EEG activity (epileptic spikes) will be summarized.

Prashant Prabhat
Ph.D. Candidate,
Dept. of Electrical Engineering
University of Texas at Dallas

Novel simultaneous multi-focal plane imaging technique for the study of the cellular trafficking of immunoglobulin G and its receptor FcRn in three dimensions
Prashant Prabhat, Zhuo Gan, Yen-Ching Chao, Sripad Ram,E. Sally Ward, Raimund J. Ober

Abstract: The study of protein trafficking pathways in three dimensions is important for understanding cellular processes. Wide-field fluorescence microscopy is extensively used to study intracellular trafficking events. On the other hand, total internal reflection fluorescence (TIRF) microscopy can be used to image events such as exocytosis that occur on the cellular membrane. However, the imaging of three-dimensional trafficking pathways from the cell interior to the cellular membrane requires that the focus of the objective be changed since the events occur at different focal planes. However, the typical devices used to change the focal plane are relatively slow. Thus, for example, when the cell interior is being imaged, important events on the cell membrane can be missed.

To overcome these limitations, we have developed a novel microscopy technique that enables the simultaneous imaging of multiple focal planes within a cell (1). This technique uses multiple detectors, each of which simultaneously images a distinct plane within the sample. We have made use of this technique to study the trafficking pathways of quantum dot immunoglobulin G (IgG) conjugate and its salvage receptor, FcRn, in human endothelial cells.

1. P. Prabhat, S. Ram, E.S. Ward and R.J. Ober, IEEE Transaction on Nanobioscience, 3(4), 237-242, (2004).

This research was supported in part by the National Institutes of Health (grant: R01 AI50747).

Bio: Prashant Prabhat received his B.E. degree in mechanical engineering from the Manipal Institute of Technology, India in 1998, and the M.S. degree in mechanical engineering from the University of Missouri, Rolla in 2002. He worked at the automotive research and development division of Mahindra and Mahindra Ltd., India, during 1998–1999. In his masters program, he worked in the area of model development of distributed parameter thermal system and neural networks based control. He is currently a PhD student and a research assistant in the Department of Electrical Engineering at the University of Texas at Dallas and a fellow at the University of Texas Southwestern Medical Center at Dallas. His current research work is focused on the development of a new fluorescence microscopy imaging technique and its application to cell biology. This technique enables simultaneous imaging of multiple focal planes in live cells for the study of the cellular trafficking pathways in three-dimensions. Trafficking pathways of immunoglobulin G (IgG) and its salvage receptor, FcRn, in human endothelial cells are being studied using this technique. Prashant is a student member of the American Society for Cell Biology.

Bio: Zhuo Gan was born in Guizhou, China, in 1973. He received the B.E. degree in electrical engineering in 1995 and the M.S. degree in biomedical engineering in 2004, from Huazhong University of Science and Technology, Wuhan, China. He is currently working toward the Ph.D. degree at University of Texas Southwestern Medical Center at Dallas. He is currently a Research Assistant at the University of Texas Southwestern Medical Center at Dallas. His research is protein trafficking and fluorescence microscopy.

Amaranath Premasiri
Ph.D. Student,
Southern Methodist University

Amaranath Premasiri graduated in B.Sc. Eng (Materials Engineering-honors) in 1999 and in M.Eng (Mechanical Engineering) in 2003 from the University of Moratuwa, Moratuwa, Sri Lanka. From 1999-2000 he worked as a consultant engineer for the Brown Group Corrosion Consultancy Service, in Colombo, Sri Lanka. In the year 2000 he joined the Department of Mechanical Engineering at the Faculty of Engineering, University of Ruhuna, Sri Lanka as a laboratory instructor and continued the carrier as a Lecturer since 2003. Currently He is a Ph.D. student at the Department of Mechanical Engineering under Dr.Gemunu Happawana at the Southern Methodist University (SMU), Dallas, TX. His research area is focused on opto-electronic packaging and currently working on a therapeutic device for the use in photodynamic therapy for esophageal carcinoma.

Development of high yielding therapeutic system for photodynamic therapy of esophageal carcinomas

Amaranath Premasiri, Graduate student
Department of Mechanical Engineering, Southern Methodist University, Dallas, TX

Gemunu Happawana, Assistant Professor
Department of Mechanical Engineering, Southern Methodist University, Dallas, TX

Abstract
Clinical details have shown that the efficient photodynamic therapeutic system can cure ~87% of the esophageal carcinomas which accounts for ~6% of cancer deaths in United States. Proper Combination of photosensitizing agent, oxygen, and a specific wavelength of light to activate the photosynthesizing agents is necessary for the cytotoxic destruction of cancerous cells by PDT. In this study it is shown that a semiconductor laser based light delivery system with direct de-ionized (DI) water cooling provides required quantity of light to the tumor. Further, a microwave antenna imprinted on the balloon catheter provides local heating of esophagus leading to an increase in oxygen availability to the tumor to generate effective levels of singlet oxygen for cellular death. Finite element modeling of different cooling methods for semiconductor lasers shows that the direct DI water cooling is more efficient compared to conventional cooling methods.  Microwave heating of esophagus is modeled with modified Penns bioheat equation. The Green Function is used to show the intensity of heating required to yield the blood flow and oxygen content to continue PDT without interruption. Based on these results, a microwave antenna system is designed to incorporate into the balloon catheter.

Richard D. Rabbitt, Ph.D.
Professor and Chairman
Dept. of Bioengineering
University of Utah
Adjunct Professor of Surgery,
Division of Otolaryngology

Dr. Rabbitt’s research interests include:
Micro-electric impedance spectroscopy of auditory and vestibular hair cells.
 Biomechanics, biophysics and neurophysiology of the inner ear including the cochlea, semicircular canals and otolith organs.
Chemoanatomic bases for perepheral vestibular function.
Micro-domain voltage clamp using MEMS.
The role of prestin in outer hair cell piezoelectricy.  and
MEMS biosensors.

http://www.bioen.utah.edu/faculty/RDR
http://www.bioen.utah.edu/directory/profile.php?userID=78

Electrophysiology on a chip:  Micro-domain voltage clamp, dielectric cytometry and micro-electric impedance tomography.
Richard D. Rabbitt, H.E. Ted Ayliffe, Sameera Dharia, Greg Dittami, Curtis King, Jeff Wyrick

Department of Bioengineering, Department of Surgery Division of Otolaryngology, University of Utah, Salt Lake City, UT  84112.

Abstract
Our laboratory has been developing microfabricated systems to measure electrophysiological properties of isolated cells.  Three new techniques will be described for spatially-resolved and time-resolved interrogation of cell membranes.   First, “micro-domain voltage clamp” is a technique where arrays of electrodes located in the extracellular space around the outside of an isolated cell are used to stimulate excitable membranes and to interrogate electrical properties at subcellular resolution.  Second, “micro-electric impedance tomography” extends this concept to estimate the spatial distribution and to generate images of the electrical properties of the cell with specific attention to the plasma membrane.  Third, “time-resolved dielectric flow cytometry” is a method to record excitable changes in membrane conductance and gating charge as cells flow along a micro channel.  Unlike previous approaches, these methods do not require direct electrical access to the intracellular space.  Measurements are made by:  i) controlling the local membrane potential of isolated cells by patterning of the extracellular electric field and ii) using an array electrodes passing radio-frequency interrogation signals to probe the passive electrical properties and excitable electrical responses of local regions of the cell membrane.  Specific novel results obtained using these systems will be presented for outer hair cells of the inner ear.  (Supported by NIDCD DC R01-04928)

Guy Rachmuth, Ph.D.
Postdoctoral Fellow, MIT

Bio: Guy Rachmuth is a biomedical engineer by training, and his research interests are focused on miniaturizing medical devices for the healthcare industry. Guy’s doctoral thesis centered on developing realistic brain signal models in a microchip environment. He is presently a postdoctoral fellow at MIT working on connecting these devices to biological tissue for close-loop interactions. Guy interned in Hadassah Hospital in Jerusalem, Israel where he developed micro-sensors for infants, as well as at Beth Israel Deaconess Hospital in Boston where he worked on contrast agents for MRIs. Guy earned his Ph.D in Biomedical Engineering from Harvard University in December 2005, and performed his work at Harvard-MIT Division of Health Sciences and Technology. He has a B.S. in Biomedical Engineering from Boston University (1999; Suma Cum Laude), and an M.S. from Harvard University in Engineering Sciences (2000).

High-Speed in-silico Simulation of Neuronal Ion Channel Dynamics
G. Rachmuth; C-S. Poon
Health Sciences and Technology, MIT, Cambridge, MA, USA

Abstract: Computational modeling of neuronal dynamics requires detailed simulation of varying membrane ion channels and intracellular processes. Software-based simulation environments such as GENESIS and NEURON have streamlined this complex process by providing a flexible platform to model at many different levels. However, the reliance on general-purpose computers limits their utility for large-scale neuronal modeling due to the prohibitively long computation times. Here we propose an in-silico neuronal simulation approach, using MOS subthreshold analog circuits, which is orders of magnitude faster than digital simulation. The circuits are configured to model various ligand- and/or voltage-gated ion channels that regulate neuronal excitability, synaptic signaling or dendritic signal propagation. We present equivalent circuit modules of ligand-gated excitatory (AMPA, NMDA) and inhibitory (GABAA, GABAB) synaptic channels and demonstrate their ability to reproduce certain spatiotemporal synaptic computations such as feedforward inhibition of excitatory transmission. We further show circuit modules of persistent Na+and Ca+2 dependent K+ channels that underlie complex bursting or tonic firing behaviors seen in certain pacemaker neurons. The results show the potential use of highly integrated, small, and power efficient MOS circuits in high-speed computational modeling of large-scale neural networks with complex neuronal characteristics.

Sripad Ram
Ph.D. Candidate,
University of Texas at Arlington,
UT Southwestern Medical Center

Bio: Sripad Ram received the B.Sc. degree in applied sciences from PSG College of Technology, Coimbatore, India, in 1999 and the M.Sc. degree in physics from Indian Institute of Technology, Chennai, in 2001. He is currently working toward the Ph.D. degree in the joint Biomedical Engineering graduate program at the University of Texas, Arlington, and the University of Texas Southwestern Medical Center, Dallas. His research interests include statistical image processing and fluorescence microscopy. He is a Student Member of the IEEE, the SPIE and the Biophysical Society.

HOW FAR CAN WE GO BEYOND RAYLEIGH’S LIMIT?
A NEW RESOLUTION MEASURE WITH APPLICATION TO SINGLE MOLECULE STUDIES
Sripad Ram, E. Sally Ward, Raimund J. Ober

Abstract: Optical microscopes are an invaluable imaging tool in life sciences research. The recent past has witnessed an increased use of optical microscopes in quantitative studies such as single molecule microscopy. To carry out such studies, it is important to have a methodology available to be able to assess the performance limit of a microscope setup for a given experimental configuration. Here, by adopting an information-theoretic stochastic framework, we present expressions to calculate performance limits that quantify the capabilities of optical microscopes. We consider two problems that are of current interest in single molecule studies, i.e., the resolution problem and the localization accuracy problem. For the resolution problem, we derive a novel resolution measure that predicts the accuracy with which the distance between two single molecules can be determined for a given imaging condition. Our new resolution measure shows that the resolution of an optical microscope is not limited, but that the resolvability of single molecules depends on the collected photon count. For the localization accuracy problem, we present analytical formulae for the fundamental limit to the 2D/3D localization accuracy of a single molecule. In both problems, we investigate the effects of deteriorating experimental factors such as pixelation of the detector and additive noise sources.

This research was supported in part by the National Institutes of Health (grant RO1 GM071048).

Christy L. Rogers
Ph.D. Candidate
Department of Electrical and Computer Engineering,
University of Floriday, Gainesville

Title: Analog VLSI Hardware For Amplifying and Compressing Extracellular Neural Recordings
Christy L. Rogers, John G. Harris, Du Chen, Yuan Li, Dongming Xu, Jose C. Principe, Justin C. Sanchez (Department of Electrical and Computer Engineering, Department of Pediatrics Division of Neurology: University of Florida, Gainesville, FL)

Abstract: An implantable extracellular neural recording system, such as that required for Brain Machine Interfaces (BMIs), must satisfy strict power, size and wireless transmission bandwidth constraints. Currently hundreds of channels are recorded with the desire to increase to thousands in the near future. Transmitting the raw signal for this many channels with the current desired sampling rate of at least 25kHz and at least 8 bits of resolution is impossible given the challenging power, size and bandwidth constraints. While compact lowpower subthreshold CMOS circuitry can be employed to reduce the size and power of a neural implant, the transmission bandwidth remains a problem. The Computational NeuroEngineering Laboratory at the University of Florida is exploring three different approaches for compressing the neural signals. The first uses a novel encoding scheme with asynchronous biphasic pulses to transmit the raw voltages. The second extracts and transmits features from the spikes. The third and most drastic data reduction method performs multi-scale spike detection and transmits only the timing of the spikes.

Bios: Christy Rogers received a B.S. degree in electrical engineering from the University of North Florida, Jacksonville, FL, in May of 2002. She received a M.S. degree in Electrical and Computer Engineering from the University of Florida, Gainesville, FL in December 2004. Currently, Christy is a PhD candidate at the University of Florida under the supervision of Dr. John Harris. She works in the Computational NeuroEnginering Laboratory on the brain machine interface project. Her role is to design and implement low-power analog VLSI hardware to perform spike feature extraction and/or detection in extracellular neural recordings.

Will Rosellini
President & CEO,
WMR Group, LLC

Will Rosellini is President and CEO of the WMR Group, LLC, a consulting group with expertise in insurance reimbursement strategies for innovative technologies under Medicare and Medicaid. There most recent engagement includes coordinating the 9 step Medicaid Applied Income process for dental services performed onsite at nursing homes and assisted living centers. Mr. Rosellini completed his Master’s of Accounting and Master’s of Business Administration in 2003 at the University of Texas Dallas. He completed his Juris Doctor at Hofstra Law School in 2006 and will complete a dual Master’s of Biotechnology and Master’s of Applied Cognition and Neuroscience at UTDallas in 2006-2007. He holds a Real Estate Broker’s License and is a CPA candidate.

Abstract:
My research centers on policy recommendations for the Medicare/Medicaid program for cost benefit analysis of the reimbursement of certain medical and dental services. The Texas Dental Journal recently published my article analyzing Senate Bill 34 and its failure to cut Medicaid costs by not funding preventative periodontal maintenance for nursing home residents. It also comprehensively analyzes changes in the Medicaid system to keep annual costs of nursing home residents down, by linking poor oral health with an increase in the number of heart, lung and other general health problems. My current interest surrounds the problems associated with technically sufficient neuro-prosthetic solutions that aren’t being adequately funded by Medicare or Medicaid.

Jay Rubinstein, M.D., Ph.D.
Professor
University of Washington

Dr Rubinstein's research focuses on understanding how spike timing characteristics in the auditory nerve influence clinical outcomes with these devices.  Using biophysical computational models, psychophysical measures in human subjects and measures of speech and music perception, his laboratory focuses on attempts to improve encoding of temporal information by cochlear implant signal processing strategies.  Dr Rubinstein received the MD and PhD degree in Bioengineering from the University of Washington.  He completed an Otolaryngology residency and postdoctoral research fellowship at the Massachusetts Eye and Ear Infirmary.  He completed an Otology/Neurotology fellowship at the University of Iowa.  He was an Assistant and Associate Professor of Otolaryngology and Bioengineering at Iowa from 1995-2004 as well as the Boerhaave Professor at Leiden University in the Netherlands in 2003-2004.  He is currently Director of the Virginia Merrill Bloedel Hearing Research Center and Professor of Otolaryngology & Bioengineering at the University of Washington.

Justin C. Sanchez, Ph.D.
Assistant Professor,
Pediatrics and Neuroscience,
University of Florida College of Medicine
and McKnight Brain Institute,
Gainesville, Florida

 

 

Bio
Dr. Sanchez’s research interests are in Neural Engineering and neural assistive technologies. Topics include the analysis of neural ensemble recordings, adaptive signal processing, brain-machine Interfaces, motor system electrophysiology, treatment of movement disorders, and the neurophysiology of epilepsy. He is an Assistant Professor of pediatrics and neuroscience at the University of Florida College of Medicine and McKnight Brain Institute in Gainesville, Florida. He received his Ph.D. (2004) and M.E. degrees in Biomedical Engineering and B.S. degree in Engineering Science (Highest Honors - 2000) with a minor in Biomechanics from the University of Florida. The goal of his research is to develop state-of-the-art novel medical treatments by operating at the interface between basic neural engineering research and clinical care. This direction of research is motivated by the potential of direct neural interfaces for delivering therapy and restoring functionality to disabled individuals using engineering principles. In 2005, he won two prestigious awards for his work including Excellence in Neuroengineering and more recently an American Epilepsy Society Young Investigator Award. In 2006 he founded the Gainesville Section of the IEEE Engineering in Medicine and Biology Society and serves as the IEEE Gainesville Section Director for membership development. His neural engineering electrophysiology laboratory is currently developing direct neural interfaces for use in the research and clinical settings and has published over 35 peer review papers and holds 3 patents in neuroprosthetic design. He is the founding member of the Neuroprosthetics Group (NRG) at the University of Florida

http://nrg.mbi.ufl.edu

Title: Selecting State Variables for ECoG Neuroprosthetics

Abstract
The ability to employ human electrocorticographic neuroprosthetics in the clinical setting depends upon the extraction of relevant control signals. For adaptive filtering methodologies used in neuroprosthetics, extraction of spatio-control parameters remains a difficulty. Here we will explore how electrocorticogram recordings for neuroprosthetics provide an intermediate level of abstraction between EEG and microwire single neuron recordings. Since amplitude modulation in extracellular recordings plays a key role in both neuronal activation and rate coding, seeking spatial pattern classification and temporally intermittent population synchronization in terms of increased voltage may provide viable control signals. We will discuss preprocessing modalities that emphasize amplitude modulation in the ECoG above the level of noise and background fluctuations in order to derive the commands for complex control tasks. Results show that the decoding performance of the amplitude modulation across the recording spectra was found to be spatially specific in the cortex.

Krishna Shenoy, Ph.D.
Assistant Professor
Department of Electrical Engineering
& Neurosciences Program
Paul G. Allen Center for Integrated Systems
Stanford University

Our group conducts neuroscience and neuroengineering research. We Investigate the neural basis of sensorimotor integration and coordination using a combination of electrophysiological, behavioral, computational and theoretical techniques. For example, how do neurons in cerebral cortex plan and guide reaching arm movements? We also design neural prosthetic systems, that translate neural activity from the brain into control signals for prosthetic devices, to assist disabled patients. This work includes statistical signal processing, estimation and control algorithm design, low-power circuits and real-time system modeling and implementation. For example, how can we design neurally-controlled prosthetic arm systems with performance rivaling the natural arm, or communication systems rivaling the throughput of spoken English?

http://www.stanford.edu/~shenoy/ http://www.stanford.edu/~shenoy/Group.htm  

A High Performance Brain Computer Interface
Recent studies have demonstrated that monkeys and humans can use signals from the brain to guide computer cursors. Brain computer interfaces (BCIs) may someday assist patients suffering from neurological injury or disease, but relatively low system performance remains a major roadblock. In fact, the
speed and accuracy with which keys can be selected using BCIs is still far lower than for systems relying on simple eye movements. This is true whether BCIs employ recordings from populations of individual neurons using invasive electrode techniques or EEG recordings using less or non-invasive techniques. Here we present the design and demonstration, using electrode arrays implanted in monkey dorsal premotor cortex, of a four-fold higher performance
BCI than previously reported. These results indicate that a fast and accurate key selection system, capable of operating with a range of keyboard sizes, is possible (up to 6.5 bits/S, or ~15 words per minute, with 96 electrodes). The highest information throughput is achieved with unprecedentedly brief neural recordings, even as recording quality degrades over time. These performance results and their implications for system design should substantially increase the clinical viability of BCIs in humans.
 

 
Bio
Professor Shenoy received the B.S. degree in Electrical Engineering from
the University of California at Irvine in 1990 (Summa Cum Laude), the
S.M. degree in Electrical Engineering from MIT in 1992, and the Ph.D.
degree in Electrical Engineering from MIT in 1995. He was a postdoctoral
fellow in the Division of Biology at Caltech from 1995-2001. In 2001
Professor Shenoy joined the Department of Electrical Engineering at
Stanford University, where he is also a member of the Neurosciences
Program (School of Medicine) and is affiliated with Stanford's Bio-X
Program, Biodesign Program, and NIS (Neurosciences Institute at
Stanford). Honors and awards include NSF and Hertz Foundation graduate
fellowships, the 1996 Hertz Foundation Doctoral Thesis Prize, an NIH
postdoctoral fellowship, a Burroughs Wellcome Fund Career Award in the
Biomedical Sciences, the William George Hoover Faculty Scholar in
Electrical Engineering at Stanford University, the Robert N. Noyce
Family Scholar in the Stanford University School of Engineering, an
Alfred P. Sloan Research Fellowship, and Defense Sciences Research
Council (DSRC/DARPA) fellow and member. Dr. Shenoy is a Senior Member of
the IEEE (Engineering in Medicine and Biology Society, EMBS) and a
member of Eta Kappa Nu, Tau Beta Pi, American Physiological Society,
Society for Neuroscience and Neural Control of Movement Society.

 

Mario A. Svirsky, Ph.D.
Noel L. Cohen Professor, Vice-Chairman of Research,
Department of Otolaryngology,
New York University School of Medicine

A New Tool to Select Frequency Maps in an Acoustic Cochlear Implant Simulation
Mario A. Svirsky, Matthew Fitzgerald, Elad Sagi (Dept. of Otolaryngology, New York University, New York, NY); Tasnim Morbiwala (Currently at Advanced Bionics Corp., Sylmar, CA)

Abstract: Cochlear implants (CI’s) can restore hearing to deaf individuals by electrically stimulating the auditory nerve.   They do so by assigning different frequency bands to different stimulating electrodes via a frequency map.  The closer an electrode is to the base of the cochlea, the higher the frequency of the corresponding band.  This is done to mimic what happens in a normal hearing cochlea.  Almost all postlingually deaf CI users (those who lost their hearing after learning speech and language) can hold a fluent face-to- face conversation in a quiet environment, and a majority of patients can even understand speech without the help of lipreading.  However, this result is not always obtained immediately after implantation.  Instead, months of experience listening with the CI are required for most patients to reach asymptotic levels of speech perception.  This extensive perceptual learning may be required due to the ways in which CI’s distort auditory input, which include spectral degradation and frequency.  The former happens due to the limited number of stimulation channels; the latter is due to physical limitations in electrode insertion depth, which may cause a mismatch between the speech processor’s analysis filters and the characteristic frequency of the stimulated neurons.  A possible way to address frequency mismatch may be to allow CI users to select the preferred frequency-to-electrode map, under the assumption that they will select maps that minimize frequency mismatch.

We have developed a PC-based speech processing platform that enables us to change the frequency map in real time, and used this platform to study normal-hearing adults listening to an acoustic simulation of a cochlear implant.  In this study we investigated what frequency maps were initially preferred, and how the ability to understand speech with that preferred map compared with two other maps.   We show that naïve listeners prefer a map that balances the need for low-frequency information with the desire for a naturally-sounding stimulus, and that initial performance with this listener-selected map is better than that with a map that distorts the signal to provide low-frequency information.  Finally, we present results from a mathematical model of vowel perception by CI users that may help explain the speech perception data.

Bio: Dr. Svirsky’s B.S. and M.S. (From Universidad de la República, Uruguay) are in Electrical Engineering, and his Ph.D. in Biomedical Engineering is from Tulane University.  During his doctoral training (as well as his postdoctoral training, at MIT’s Reesearch Laboratory of Electronics) he focused on speech perception, speech production, speech processing, and hearing.  He has also published extensively on outcomes of pediatric and adult cochlear implantation.

Dawn Taylor, Ph.D.
Assistant Professor
Case Western Reserve University

The long term goal of Dr. Taylor’s research is to interface FES systems directly to the brain. Intended movement can be interpreted from the activity in the motor cortex, and she would like to use these signals to control FES systems. This would allow paralyzed individuals to move their limbs the same way everyone else does - just by thinking of doing so. She is investigating the use of both invasive and non-invasive brain recording techniques such as intracortical microelectrodes, brain surface recordings, and scalp surface recordings. These different types of brain signals are being applied to the control of a virtual arm representations of an arm as well as to the control of assistive robotics, and finally FES systems that restore arm and hand function to people with spinal cord injuries. One aspect of this work is to develop ways to utilize brain signals more effectively by retraining the brain to more accurately convey the desired action of the limb. This requires the development of appropriate training environments and adaptive decoding algorithms that can track changes in brain pattern generation over time. Direct brain control of both real and virtual arm and hand movements are being used to evaluate decoding algorithms and retraining methods. Her work includes the use of rodent models of spinal cord injury, healthy non human primate models, and human subjects both with and without movement deficits.

Making the Most of Cortical Signals for Command of High-Degree-Of-Freedom Devices

Abstract: We are currently developing brain-based command and control systems for assistive devices designed to restore reach and grasp function to individuals with high tetraplegia (e.g. upper limb neuroprostheses and wheelchair-mounted robotic arms). We are developing control systems that utilized neural signals recorded with both invasive and non-invasive electrodes in animal